DOCTORAL DEGREE IN APPLIED MATHEMATICS

• LAMAS RODRÍGUEZ, JOSÉ: Oscillatory motions, parabolic orbits and collision orbits in the planar circular restricted three-body problem.
  
  Author: LAMAS RODRÍGUEZ, JOSÉ
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 09/05/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: MARTINEZ-SEARA ALONSO, MARIA TERESA | GUARDIA MUNARRIZ, MARCEL
  Thesis abstract: The planar circular restricted three body problem (PCRTBP) models the motion of a massless body under the attraction of other two bodies, the primaries, which describe circular orbits around their common center of mass. In a suitable system of coordinates, this is a two degrees of freedom Hamiltonian system. The orbits of this system are either defined for all (future or past) time or eventually go to collision with one of the primaries. For orbits defined for all time, Chazy provided a classification of all possible asymptotic behaviors, usually called final motions.By considering a sufficiently small mass ratio between the primaries, we analyze the interplay between collision orbits and various final motions and construct several types of dynamics.We show that orbits corresponding to any combination of past and future final motions can be created to pass arbitrarily close to either one of the primaries. In particular, we also establish oscillatory motions accumulating to collisions. That is, oscillatory motions in both position and velocity, meaning that as time tends to infinity, the superior limit of the position and velocity is infinity while the inferior limit of the distance to one of the primaries is zero. Additionally, we construct arbitrarily large ejection-collision orbits (orbits which experience collision in both past and future times) and periodic orbits that are arbitrarily large and get arbitrarily close to either one of the primaries. Combining these results, we construct ejection-collision orbits connecting both primaries.
  

DOCTORAL DEGREE IN ARCHITECTURAL, CIVIL AND URBAN HERITAGE AND REFURBISHMENT OF EXISTING BUILDINGS

• GORDILLO BEL, DIDAC: De la caponera al búnquer. Evolució de la fortificació des de mitjans del segle XIX a mitjans del segle XX a Catalunya.
  
  Author: GORDILLO BEL, DIDAC
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, CIVIL AND URBAN HERITAGE AND REFURBISHMENT OF EXISTING BUILDINGS
  Department: Departamento de Representación Arquitectónica (RA)
  Mode: Normal
  Deposit date: 28/03/2025
  Reading date: 06/06/2025
  Reading time: 11:00
  Reading place: ETSAB (Escola Tècnica Superior d'Arquitectura de Barcelona) - Planta Baixa - Aula C-B4Av. Diagonal, 649-651 - 08028 - Barcelona
  Thesis director: ONECHA PEREZ, ANA BELEN | SÁNCHEZ RIERA, ALBERTO
  Thesis abstract: The thesis is composed, apart from the general introduction, of four interconnected chapters but which could be independent. The first is an overview of the evolution of fortification from antiquity to the middle of the 20th century. The second is the development of fortification in defensive enclosures since the middle of the 19th century, taking into account the curtains and bastions that gradually became low until they became covered caponiers, bastions that in principle are small forts that are part of a set but which could be independent in isolated forts, with crenellated galleries, embrasures with artillery pieces or plans protected only by parapets to place cannons to fire uncovered, and at the back of everything the tower divided into floors where the slingshots are located with the pieces to shoot at a long distance, both in slingshots under cover and pieces located on parapet at the highest point. Tortosa is taken as an excuse, because its case can be extrapolated to others in Catalonia. The fourth part is the realization of the bunker figure. There are enough cases here because unfortunately Catalonia, like the rest of the State, suffered a civil war. In this part, you can see how the bunkers were foreseen and how they gradually materialized with normalizing models that already came from before. Finally, the last part is the concrete explanation of the evolution of the bunker caponera and how it has become more and more camouflaged and more armored as the destructive power of the weaponry increases, how the traditional fortification has disappeared .
  

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

• GUTIÉRREZ MONDRAGÓN, MARIO ALBERTO: Exploring the Dynamics of the beta2-Adrenergic Receptor: Insights from Explainable AI in GPCR Research
  
  Author: GUTIÉRREZ MONDRAGÓN, MARIO ALBERTO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
  Department: Department of Computer Science (CS)
  Mode: Normal
  Deposit date: 12/05/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: VELLIDO ALCACENA, ALFREDO | KÖNIG, CAROLINE LEONORE
  Thesis abstract: G-protein coupled receptors are transmembrane proteins that serve as critical mediators between extracellular signals and intracellular responses. These highly dynamic entities orchestrate a wide array of cellular processes in response to various stimuli, including hormones, neurotransmitters, and environmental signals. Due to their versatility and central role in cellular communication, GPCRs are prime pharmacological targets for treating a wide spectrum of diseases, ranging from diabetes and Alzheimer's to various forms of cancer. Despite significant advances in understanding their dynamic conformational landscapes, the precise molecular mechanisms underlying their transient and intricate shifts, especially upon ligand binding, remain obscured by the complexity of their structures. This poses substantial challenges to the elucidation of the processes that govern their signaling mechanisms. In this thesis, we leverage the wealth of information generated by Molecular Dynamics simulations through advanced Machine Learning models to help decode the complex conformational landscape of GPCRs. A crucial step in our approach involves transforming the raw MD data into structured formats that are more suitable for analysis. Deep Neural Networks, known for their strength in capturing intricate relationships within large datasets, form the backbone of the thesis. When coupled with state-of-the-art explainability techniques, these models not only produce accurate classifications, but also reveal molecular mechanisms that drive the behavior of GPCRs.Our goal extends beyond building reliable models for classification. We aim to reveal critical patterns and insights that deepen our understanding of GPCR dynamics. By focusing on the beta2 -adrenergic receptor, our aim is to improve the interpretation of receptor behavior while creating a reliable framework for broader applications in proteomics.
  

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

• AGRELO LESTÓN, ASIER: Development of metal-enhanced TiO2-based photocatalysts for hydrogen production
  
  Author: AGRELO LESTÓN, ASIER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 02/04/2025
  Reading date: 02/06/2025
  Reading time: 11:00
  Reading place: Campus Diagonal Besòs, Edifici I (EEBE)Sala Polivalent, Edifici I - I.01Av. Eduard Maristany, 16 08019 Barcelonahttps://eebe.upc.edu/ca/lescola/com
  Thesis director: LLORCA PIQUE, JORDI | SOLER TURU, LLUIS
  Thesis abstract: Human activity has led to rising greenhouse gas levels, altering climate patterns and intensifying weather events. Therefore, a transition to a decarbonized energy system is needed, with hydrogen as a promising energy vector alongside solar and wind energy. However, current hydrogen production methods, such as steam methane reforming, generate significant CO2 emissions. Sunlight-driven water splitting offers a sustainable alternative, though efficiency improvements are required for industrial viability.This PhD thesis focuses on developing novel TiO₂-based catalysts for photocatalytic hydrogen production.Chapter 3 was conducted with the SYMAC team from Université Toulouse 3-Paul Sabatier. A TiO₂ catalyst was decorated with Cu nanoparticles stabilized by quinidine and compared to a sample prepared via incipient wetness impregnation (IWI) using L-ascorbic acid. The quinidine-stabilized sample exhibited 5 times superior activity under UV, as well as activity enhancement under Uv-visible irradiation. UV-vis spectroscopy revealed a plasmonic band relative to Cu, and a decrease in the bandgap was confirmed by Tauc plots. XRD confirmed Cu deposition and predominant anatase phase of the TiO2. TEM confirmed presence of Cu nanoparticles that XAS and XPS identified predominant metallic nature with minor oxide contributions.Chapter 4 was carried out with the Supra- and Nanostructured Systems group at Universitat de Barcelona (UB). Hybrid TiO₂ photocatalysts were prepared with Au(I) complexes and Au(0) systems were developed as co-catalysts. Three catalyst series incorporating coumarin-based ligands were evaluated under light and heat. Two (1 wt.% co-catalyst) were prepared via IWI and ball milling (BM), while a third (0.25 wt.% Au) was synthesized by IWI. IWI-prepared samples showed superior activity, achieving up to 2.7 times the H₂ production of conventional Au/TiO₂. UV-vis spectroscopy confirmed plasmonic bands relatives to Au and Tauc plots revealed bandgap narrowing. TEM, HAADF-STEM, and XPS confirmed the presence of Au nanoparticles with a predominant metallic nature.Chapter 5 focused on Pt/TiO₂ photocatalysts synthesized by BM, optimized through a design of experiments (DoE) approach. The most active sample was 1.4 times more efficient than an IWI-prepared Pt/TiO2 reference under UV light irradiation. HAADF-STEM-EDX revealed Pt atoms dispersed on TiO₂, with post-reaction growth into nanoparticles while there was presence of some Pt atoms dispersed. XPS confirmed partial Pt reduction during the reaction.Chapter 6 explored bimetallic PdCu photocatalysts with a total metal loading of 1 wt.%. A Pd:Cu atomic ratio of 1:2 was chosen after a screening from 3:1 to 1:3. The bimetallic sample outperformed theoretical activity of the combination of thus metals under UV light by 27%, and Cu incorporation enhanced H₂ production under UV-vis irradiation. BM-prepared samples were 1.2 times more active than IWI ones. Pd stability was improved with Cu incorporation, as seen in long-term tests, with less activity loss compared to monometallic Pd. Raman spectroscopy indicated strong metal-support interactions. UV-vis spectroscopy and Tauc plots showed enhanced visible absorption and bandgap narrowing, respectively. HAADF-STEM-EDX revealed bimetallic PdCu nanoparticles in BM samples, whereas IWI samples had separate Pd and Cu nanoparticles. BM also constrained Pd growth, as Pd nanoparticles in the monometallic sample grew 3.5 times during the reaction. XPS showed Pd reduction in both samples, with complete reduction in BM-prepared catalysts, further supported by H₂-TPR.
  
• BARBERO DEL RÍO, MANUEL: Estudio de los principales contaminantes en lavandería industrial y diseño de un sistema de reutilización de agua
  
  Author: BARBERO DEL RÍO, MANUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 24/04/2025
  Reading date: 27/06/2025
  Reading time: 11:00
  Reading place: Campus Diagonal Besòs, Edifici A (EEBE)Sala Polivalent, Edifici A,Av. Eduard Maristany, 16 08019 Barcelonahttps://eebe.upc.edu/ca/lescola/com
  Thesis director: DE PABLO RIBAS, JOAN | CASAS GARRIGA, SANDRA
  Thesis abstract: This doctoral thesis has enabled the development of a technological solution for water reuse in the industrial laundry sector. In addition, the emission of microplastics and emerging pollutants associated with this activity has been studied, focusing on strategies that minimise the problems associated with them.The reuse system, whose main technology is ceramic ultrafiltration, and uses foam fractionation and chemical oxidation as post-treatment, achieves a water reuse rate of 86% in unitary washing processes without affecting their final quality. The design process has been carried out in different phases, including analysis of the feasibility of the technologies, laboratory testing and validation at pilot and real scale.Foam fractionation was tested using an aeration column, which achieved surfactant separation rates of up to 70% from water and, as a result, a surfactant-concentrated stream whose reintroduction in subsequent washing processes improved the removal of certain pattern stains by up to 20%.Preliminary ultrafiltration membrane tests allowed the generation of explanatory models of permeate quality and transmembrane flux from a matrix of working pressure iterations for molecular cut-off sizes from 1 to 1400 kDa.For the pilot-scale validation of ceramic membrane ultrafiltration technology, a direct treatment-reuse process was combined and only 23L of mains water was used in each wash. This was implemented in a 13 kg capacity washing machine over 10 processes and demonstrated the greater efficiency of the 15 kDa membranes over the 50 kDa ones for the separation of anionic surfactants (+9%) and COD (+13%). The analysis of the rinsing efficiency showed more stable results with the use of 15 kDa membranes, which is associated with the greater removal of surfactants throughout the reuse cycles, so this pore size was chosen for the final validation of the system.Finally, ultrafiltration was combined with foam fractionation and chemical oxidation using ozone. These last two techniques coexisted in a cylindrical reactor built for this purpose and placed after ultrafiltration, which increased the removal efficiency of anionic surfactants to 91% after 15 minutes of treatment. In addition, a complete elimination of the colour released by the garments was confirmed, thus avoiding the transfer of this colour to subsequent washing processes.The emission of microplastics during the washing of garments throughout their useful life was estimated at 7,957,942 microfibres per kg of clothing washed. 44% of these microparticles are emitted during the first 5 washes and their emission can be substantially reduced with washing programmes with low mechanical action.The study of emerging contaminants in industrial laundry has shown the presence of this type of compounds in the wastewater generated. These would migrate from the fabrics where they are deposited or impregnated, to the water used in the washing process and would then be discharged into the sewage system. In total, 27 compounds of different types have been detected, such as disinfectants, medicines, antibiotics, drugs of abuse, pesticides and insect repellents. Hospital laundry has been found to be the sub-sector in whose water the highest concentrations and a greater variety of micropollutants have been detected, followed by hotel laundry and work clothes laundry. The elimination of this type of contaminant has been validated with a treatment system, achieving yields of over 98% for most of the compounds studied.
  
• PACHECO LÓPEZ, ADRIAN: Integrating modeling, synthesis, and knowledge management to support strategic decision-making toward the Circular Economy paradigm
  
  Author: PACHECO LÓPEZ, ADRIAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 16/04/2025
  Reading date: 16/06/2025
  Reading time: 11:00
  Reading place: EEBE - Sala Polivalent, edifici I, planta 0, espai I.0.1Campus Diagonal BesòsAv. Eduard Maristany, 16, 08019 BARCELONA
  Thesis director: GRAELLS SOBRE, MOISES | SOMOZA TORNOS, ANA
  Thesis abstract: This thesis tackles some of the most urgent global issues we face today: waste accumulation, resource scarcity, and climate change. The focus is on applying sustainable practices through models like Industrial Symbiosis (IS) and the Circular Economy (CE). Traditional linear economic models have hit a limit, and this research proposes a solution to optimize resource use and waste management. The central goal of this work is to develop a Decision Support System (DSS) to help identify and assess the most effective routes to convert waste into resources, particularly focusing on plastic waste, but with applications to other materials, too.Chapter 1 discusses how demographic and industrial trends are accelerating problems like waste accumulation, resource shortages, and climate crises. It emphasizes the urgent need to adopt models like CE and IS to reduce material consumption and waste generation. While implementing CE comes with challenges—such as figuring out the best ways to convert waste into valuable products—this chapter introduces the development of a DSS designed to support informed, rigorous decision-making for sustainable resource management.Chapter 2 dives into the methods and tools used to create the DSS. It introduces Process Systems Engineering (PSE), a crucial field for understanding and developing sustainable production processes. PSE uses tools like process modeling, simulation, and optimization to design more efficient and sustainable systems. This chapter explains how these tools can be applied to address the challenges of CE and help design sustainable processes.Chapter 3 presents a proof of concept for the application of CE, focusing on alternative fuels made from plastic waste. A techno-economic and environmental assessment compares plastic waste-derived fuels with traditional ones like diesel and gasoline. The results show that pyrolysis oil from plastic waste has a lower environmental impact and production cost compared to diesel. However, for gasoline substitutes, bioethanol and ethanol from plastic pyrolysis have mixed results. These findings highlight the potential of plastic waste conversion technologies, although more research is needed to improve fuel quality.Chapter 4 focuses on generating and evaluating new waste-to-resource routes, particularly for plastics. Using an ontological framework for more efficient knowledge management, this chapter creates a system to identify, generate, and classify processing alternatives for the upcycling of waste. The framework helps find the best ways to close material loops, and chemical recycling emerges as a promising option to reduce the environmental impact of plastic waste.Chapter 5 shows how an integrated set of tools was developed to design, model, and optimize waste conversion processes. Using methods like graph theory, network optimization, MCDM, and multi-objective optimization, the system helps identify and assess the best waste treatment routes. A case study on plastic waste highlights that chemical recycling for the recovery of raw materials could be a promising option from both an economic and environmental perspective.Chapter 6 concludes by summarizing the development and validation of the DSS. The thesis shows how the framework was successfully validated through case studies focused on plastic waste recovery, proving its effectiveness in closing material loops and supporting sustainable practices within the circular economy.
  
• ROA TORRES, ALEXANDRA: Acidic Mining Waters as Resource Recovery for Sustainable Supply of Raw and Critical Materials
  
  Author: ROA TORRES, ALEXANDRA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Article-based thesis
  Deposit date: 05/05/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: CORTINA PALLAS, JOSE LUIS | LÓPEZ RODRÍGUEZ, JULIO
  Thesis abstract: Over the past years, the treatment of Acidic Mine Waters (AMWs) has gained a new interest as they can be used as a secondary source for Critical and Strategic Raw Materials (CRMs and SRMs, respectively). This, along with the fact that the European Union (EU) is promoting circular approaches to move towards a green economy, has shifted the application of traditional treatments towards the development and implementation of a circular scheme for the valorisation of AMWs. The proposed treatment scheme consisted of four main stages. A first pre-treatment stage, consisting on the removal of transition metals is based on two steps, the first one focused on the removal of Fe and Al as hydroxides, followed by another one for the removal of metals as sulphides. Both steps attained metal removals >90% for Fe, Al, Zn, Cd and Cu. The second stage is focused on the recovery of Rare Earth Elements (REEs). To selectively extract and concentrate them, ion exchange (IX) was applied. In this step, two commercial IX resins such as the TP272 (impregnated resin) and the S930 (chelating resin) were evaluated for the fractionation of REEs into Heavy (HREEs) and Light (LREEs). After the regeneration, the REEs were recovered by crystallizing them as oxalates to avoid the precipitation of other transition and/or rare earth alkaline ions present in the eluate. For that, oxalic acid and NH3 were used, achieving recoveries >95% from the eluate and the solids were a mixture of REEs, with purities >90%. In addition, an optimisation of the solution used during the regeneration process of IX resins was carried out to improve the concentration factors (CF), and to reduce the chemical consumption during the crystallization.The third stage focused on the reclamation of water. For that, different polymeric nanofiltration (NF) membranes (dnF40 under hollow fibre configuration, and NF270, NFX, and PRO-XS2 under flat-sheet configuration) have been used to evaluate the recovery of water with different levels of hardness removal. This consisted of the removal of Mn and Mg as hydroxides, using NaOH, followed by the removal of Ca as carbonate, using NaHCO3. During the removal of Mg, efforts were made to optimize its crystallization by using different concentrations of NaOH. The NF experiments showed rejection values >96%, except for the dnF40. However, when working in concentration mode, the formation of scaling was observed during the tests, which was related to the precipitation of calcium sulphate mineral phases. An additional effort was performed to evaluate the use of NF membranes with different active layer chemistry (e.g. semi aromatic amides (Desal DL), sulphamide (Desal KH) and polysthersulphonated (e.g. AMS3012, AMS3014) for the recovery of CRMs from other acidic streams such as Lithium-Ion Batteries (LIB) lixiviates. For that, two key aspects were evaluated, the type of leaching acid (H2SO4 and HCl) and the alkali used to neutralize the excess of acidity (NaOH versus Mg(OH)2(s)). The tests showcased a high impact of the solution chemistry in NF processes for LIBs recycling, as when Mg(OH)2(s) was used in HCl media, Li rejections of -77% were achieved, while these rejections were of -14% under H2SO4 media. The last stage of the proposed scheme for AMWs treatment focused on the valorisation of waste brines to produce acidic and basic solutions by Electrodialysis with Bipolar Membranes (EDBM) that later could be used in the other stages of the treatment. From this stage, solutions of 0.5 mol/L of NaOH and 0.45 mol/L of H2SO4 were attained as well as a salinity reduction of 58%. These tests highlighted EBDM as a sustainable approach for AMWs valorisation, as it promotes resource recovery, reduces the discharge of sulphates and hazardous wastes, and provides that circular approach to mining and water treatment industries that the EU is promoting.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• BRAVO MARTÍNEZ, JOSÉ RAÚL: Development of Hyperreduced Order Models for Multiphysics Numerical Simulations: a Noninvasive Approach
  
  Author: BRAVO MARTÍNEZ, JOSÉ RAÚL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Article-based thesis
  Deposit date: 30/04/2025
  Reading date: 16/07/2025
  Reading time: 10:00
  Reading place: UPC Campus NordETSECCPBC/ Jordi Girona 1-3Edifici C1, Sala 002Barcelona
  Thesis director: ROSSI BERNECOLI, RICCARDO | HERNANDEZ ORTEGA, JOAQUIN ALBERTO
  Thesis abstract: Reduced Order Models (ROMs) are powerful tools for accelerating numerical simulations by identifying and exploiting underlying structures in complex systems. By approximating high-dimensional problems using low-dimensional representations, ROMs enable fast and accurate predictions while significantly reducing computational costs. This thesis focuses on projection-based ROMs, which are particularly attractive for their ability to deliver physics-based solutions that maintain consistency with the governing equations of the original high-dimensional solvers. However, their widespread adoption is hindered by a number of challenges. This work identifies and addresses these challenges by developing a ROM framework that bridges the gap between theoretical advancements and practical deployment. The proposed approach minimizes the modifications required to integrate ROMs into existing multiphysics solvers, making the technology more accessible to developers and users. This is complemented by a user-friendly interface that automates ROM construction and enables simulation professionals to leverage these tools for their specific applications.This work advances hyperreduction technology by introducing continuous formulations and methods tailored to multiple subspaces. Novel hyperreduction algorithms are presented, significantly enhancing the efficiency and accuracy of ROMs. These innovations expand the applicability of ROMs to complex, nonlinear, and multiphysics problems while laying the groundwork for future research.To address the computational challenges in the construction of ROMs, this work incorporates high-performance computing (HPC) capabilities, leveraging parallel computing techniques, efficient data management strategies, and optimized workflows. This ensures the feasibility of constructing ROMs for large-scale problems.The practical applicability of the proposed framework is demonstrated through its deployment in two European research projects: EdgeTwinsHPC and eFlows4HPC. These projects showcase the development of ROMs for practical applications, with demonstrators deployed on edge devices to validate the feasibility of ROM-based digital twins in real-world scenarios.In this way, this thesis advances the field of reduced order modeling by introducing a robust, scalable, and accessible framework that facilitates the adoption of ROMs in industrial and engineering applications while laying a solid foundation for future research.
  
• SETIEN UGALDE, IÑAKI: Enhanced Inherent Strain Modelling for Powder-Based Metal Additive Manufacturing
  
  Author: SETIEN UGALDE, IÑAKI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Article-based thesis
  Deposit date: 10/04/2025
  Reading date: 05/06/2025
  Reading time: 11:00
  Reading place: Campus Nord - UPCCIMNE - Edifici C1 C/ Gran Capità,s/nSala OCZ (Zienkiewicz)08034, Barcelona https://meet.google.com/nvd-fqgp-gsc
  Thesis director: CHIUMENTI, MICHELE | SAN SEBASTIÁN ORMAZABAL, MARÍA
  Thesis abstract: Metal additive manufacturing (MAM), particularly powder bed fusion using a laser beam (PBF-LB), has transformed manufacturing by enabling the production of intricate and optimised metal components directly from digital designs. This process offers major advantages such as material efficiency, high geometric flexibility, and the ability to produce lightweight, customised parts. However, its industrial adoption is hindered by challenges such as large residual stresses and distortions resulting from steep temperature gradients and rapid thermal cycles inherent in layer-by-layer manufacturing process. These issues compromise dimensional accuracy and structural integrity, posing barriers to the broader implementation of the technology.High-fidelity thermo-mechanical finite element (FE) simulations can predict these phenomena but their high computational cost makes them impractical for large-scale industrial applications. The inherent strain method (ISM) has emerged as an efficient alternative, condensing complex thermal and mechanical phenomena into an inherent strain tensor applied in simplified elastic simulations. While ISM significantly reduces computational time, conventional implementations often lack robustness, requiring extensive recalibration for different geometries and scanning strategies and failing to capture spatial and temporal variations in thermal histories.This thesis addresses these limitations by developing an enhanced inherent strain method (EISM) for powder bed fusion (PBF), improving ISM's predictive accuracy and extending its applicability to complex industrial geometries. By integrating a macro-scale thermal analysis into ISM, the method dynamically refines the precomputed inherent strain tensor based on part-scale temperature evolution. This enhancement better accounts for geometry- and boundary-specific thermal effects, improving distortion predictions compared to conventional ISM.Additionally, this work tackles the fundamental challenge of determining inherent strain tensors necessary for ISM-based methodologies. Two complementary approaches are proposed: (1) an empirical calibration strategy using twin-cantilever beam coupons, where distortions measured after partial cutting are used to determine best-fit inherent strain tensors via inverse engineering, and (2) a numerical approach employing a meso-scale thermo-mechanical model within a multi-scale framework, computing local inherent strains and homogenising them to obtain macro-scale inherent strain tensors.Comprehensive experimental calibration and validation were conducted using Ti-6Al-4V components manufactured via PBF-LB. Temperature histories were recorded with embedded thermocouples, while distortion and residual stress data were acquired using coordinate measuring machines (CMM), 3D scanning, and incremental hole-drilling, respectively. The empirical and numerical methodologies for inherent strain tensor determination, along with EISM, were validated across multiple geometries, including twin-cantilever beams, a non-symmetric bridge, and an industrial aerospace component (the Steady Blowing Actuator). The results demonstrated that EISM significantly improved distortion predictions while maintaining computational efficiency, reducing errors by more than half compared to conventional ISM.In conclusion, this thesis presents two methods for calculating the inherent strain tensor (empirical and numerical) and introduces the EISM methodology for distortion prediction, improving the accuracy of distortion prediction in PBF-LB. In this way, the dependence on trial-and-error-based experimental testing is reduced, moving towards an optimised simulation-based design and facilitating the industrial adoption of MAM.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• BERTRAN FERRER, MARTA: New approaches for resource management and job scheduling for HEP Grid computing
  
  Author: BERTRAN FERRER, MARTA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 08/05/2025
  Reading date: 25/06/2025
  Reading time: 10:00
  Reading place: Sala C6-E106
  Thesis director: BADIA SALA, ROSA MARIA | BETEV, LATCHEZAR
  Thesis abstract: The Large Hadron Collider (LHC) ALICE (A Large Ion Collider Experiment) experiment uses grid computing for its extensive data processing and analysis. The ALICE Grid is composed of 48 sites distributed globally, which provide access to over 300,000 CPU cores. This diverse environment presents unique challenges as the computing nodes are very heterogeneous in terms of hardware, resource availability and management policies. This thesis focuses on optimising resource utilisation and job execution within the ALICE Grid in the context of the evolving multicore computing paradigm. The transition from single to multicore slots, combined with the increasing prevalence of multiprocess and multithreaded workflows, requires new resource management approaches.The thesis presents a black-box analysis of the multicore experiment software framework, tracing resource usage and system calls. Multiple sources of overhead were identified, particularly concerning the large amount of short-lived processes spawned by some workflows. To address this, the JAliEn monitoring system was extended and improved to accurately account for the resource utilisation of these short-lived processes. The observations led to modifications on the internal job workflow, resulting in a 47% reduction in the number of deployed processes and a 35% decrease in overall job execution time.For tailoring job requests to the specific characteristics of the executing systems, a model is proposed to estimate job execution times. This model leverages proportionality factors from the execution times on different Grid CPU models and uses them to dynamically scale job requests.To ensure the coherent and controlled utilisation of CPU resources, two approaches are proposed. The first uses CPU pinning and adapts the core selection to the processor architecture, optimising resource allocation for specific workloads. The second uses cgroups v2 sub-partitioning features to set boundaries on job CPU utilisation. The thesis made significant contributions to popular grid batch systems by enabling support for cgroups v2. This integration allowed JAliEn to become the first grid middleware to make use of this powerful resource management technology.When a slot is sub-partitioned to run multiple jobs in parallel, careful resource orchestration is crucial. This thesis presents a module within JAliEn that ensures equitable memory resource distribution among co-executing jobs. This module implements a targeted preemption of resource-intensive jobs to prevent slot overconsumption and ensure that jobs remain within their allocated memory limits.The thesis explores whole-node slot allocations in which JAliEn manages all the resources of a node. This novel scheduling model offers great flexibility and adaptability. To maximise resource usage in whole-node slots, CPU oversubscription was introduced to allow the execution of additional jobs when the running workload does not fully use the available CPU resources. To exploit whole-node allocations and maximise resource utilisation, the thesis proposes the extension of job brokering to consider not only CPU availability but also memory and disk space. Furthermore, the job definition syntax was equipped with new parameters for users to have greater control over resource requests.To sum up, this thesis presents a set of contributions that have substantially improved the efficiency and performance of grid computing within the ALICE experiment. The thesis addresses the challenges emerging from the evolving multicore environment by optimising resource utilisation and improving middleware reliability and observability. All these contributions introduced significant advances to the capabilities of the ALICE Grid, effectively enabling a more efficient data analysis for the LHC experiment.
  
• LAUT TURÓN, SERGI: Architecture-aware Sparse Patterns to Accelerate Inverse Preconditioning
  
  Author: LAUT TURÓN, SERGI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 10/04/2025
  Reading date: 05/06/2025
  Reading time: 11:00
  Reading place: Sala C6-E101
  Thesis director: CASAS GUIX, MARC | BORRELL POL, RICARD
  Thesis abstract: This work focuses on improving the efficiency of iterative methods for solving large and sparse linear systems.These problems arise in many fields, including climate modeling, molecular and fluid dynamics, among others.To solve them, iterative methods such as the Conjugate Gradient (CG) and Generalized Minimal Residual (GMRES) methods are widely employed.Their efficiency heavily depends on the choice of preconditioners, which accelerate convergence by improving the numerical properties of the system.Sparse Approximate Inverse (SAI) preconditioners, and their factorized variant (FSAI) for symmetric positive definite systems, are particularly appealing due to their parallel-friendly nature and straightforward application via Sparse Matrix-Vector (SpMV) operations.State-of-the-art SAI and FSAI approaches define their sparsity patterns primarily based on numerical considerations.This work introduces novel architecture-aware preconditioners designed to enhance performance by optimizing the sparse pattern selection process.The first contribution presents the Factorized Sparse Approximate Inverse with Pattern Extension (FSAIE) preconditioner, an optimized version of FSAI tailored for shared memory CPU architectures.FSAIE introduces a cache-aware algorithm that extends sparsity patterns, improving both the numerical effectiveness of FSAI and its computational efficiency.Additionally, a filtering-out strategy is proposed to remove numerically insignificant entries, reducing computational cost without compromising convergence.These techniques enhance data locality in the SpMV kernel by ensuring that extended sparse patterns align with cache-line-sized memory access patterns.The second contribution extends FSAIE to distributed memory CPU environments, introducing the Communication-aware Factorized Sparse Approximate Inverse with Pattern Extension (FSAIE-Comm) preconditioner.FSAIE-Comm incorporates communication-awareness to ensure that the sparse pattern extension does not introduce unnecessary inter-process communication overhead.To prevent load imbalance, an innovative strategy is developed to distribute computational workload more evenly.The third contribution focuses on GPU execution by introducing the GPU-aware Factorized Sparse Approximate Inverse (GFSAI) preconditioner.By structuring the sparse pattern to enhance coalesced memory accesses and exploit GPU-specific architectural characteristics, GFSAI significantly accelerates FSAI computations on GPUs.The final contribution generalizes the architecture-aware preconditioning strategies beyond FSAI by introducing the Communication-aware Sparse Approximate Inverse with Pattern Extension (SAIE-Comm) preconditioner.This approach optimizes SAI for distributed memory environments, similar to FSAIE-Comm, but is adapted for general linear systems where the GMRES solver is preferable over CG.SAIE-Comm highlights the versatility and flexibility of the proposed optimizations, demonstrating that architecture- and communication-aware pattern extensions can be effectively integrated into different preconditioning strategies and solver frameworks.By integrating hardware-aware considerations into preconditioner design, this research advances the state of the art in iterative solvers and contributes to the development of scalable and high-performance numerical methods.The proposed methods achieve substantial improvements in time-to-solution across diverse High-Performance Computing (HPC) architectures, with reductions ranging from 12.94% to 26.43% on five different CPU architectures—Intel Skylake, Power9, Zen 2, A64FX, and Intel Sapphire Rapids—and from 23.83% to 26.07% on two GPU architectures—Volta and Vega20—when applied to representative sparse matrix benchmarks.These results underscore the impact of architecture-aware preconditioning strategies in modern HPC applications, paving the way for more efficient and scalable iterative solvers.
  
• SEYGHALY, RASOOL: A Federated Learning Approach to Smart Advertising
  
  Author: SEYGHALY, RASOOL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 17/03/2025
  Reading date: 12/06/2025
  Reading time: 10:00
  Reading place: Sala VGE205 - NEÀPOLIS Building
  Thesis director: GARCÍA ALMIÑANA, JORDI | MASIP BRUIN, XAVIER
  Thesis abstract: This thesis presents a Federated Learning-based Smart Advertising System designed to enhance user engagement, optimize network efficiency, and ensure data privacy in digital advertising. Traditional advertising systems face significant challenges in balancing personalization with privacy, managing network overhead, and scaling efficiently. This study addresses these issues by integrating Edge Computing and Federated Learning (FL) to enable real-time, decentralized ad targeting while keeping user data secure.The proposed system consists of a decentralized recommendation engine, where local models are trained on users’ devices and aggregated using meta-heuristic optimization techniques, particularly the Whale Optimization Algorithm (WOA). Experimental results demonstrate that WOA outperforms other aggregation techniques, such as the Firefly Algorithm (FA) and Bat Algorithm (BA), in terms of convergence speed and overall efficiency. The system also leverages formal verification techniques, including model checking, to ensure correctness, security, and compliance with privacy regulations.Comprehensive evaluation through both simulated and real-world case studies (such as the AROUND system) shows that the proposed architecture reduces network traffic, minimizes computational overhead, and significantly improves Click-Through Rates (CTR) and user engagement compared to traditional centralized models. The system is particularly beneficial for applications in museums, shopping malls, and retail chains, providing real-time tracking, indoor mapping, and personalized content delivery.The findings underscore the potential of Federated Learning and Edge Computing in privacy-preserving smart advertising, offering a scalable, cost-efficient, and user-centric solution for the future of digital marketing.
  

DOCTORAL DEGREE IN COMPUTING

• FLORES HERRERA, JAVIER DE JESÚS: A Framework to Operationalize and Automate the Data Integration Lifecycle
  
  Author: FLORES HERRERA, JAVIER DE JESÚS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTING
  Department: Department of Computer Science (CS)
  Mode: Normal
  Deposit date: 14/04/2025
  Reading date: 16/06/2025
  Reading time: 10:00
  Reading place: Sala d'Actes Martí Recober FIB
  Thesis director: ROMERO MORAL, OSCAR | NADAL FRANCESCH, SERGI
  Thesis abstract: Data plays a key role in today’s world. Many organizations collect and store massive amounts of data from many different data sources. As a result, these data collections show a diversity in structure and semantics that grows as the data sources expand and evolve. These factors challenge traditional data management methods, which depend on fixed structures and stable conditions. There is a mismatch between old assumptions and new realities, where it is not enough to just collect data and run conventional tools. Instead, we must rethink how we integrate data to support high variety, handle large-scale collections, and accommodate new available data. This PhD thesis proposes innovative and advanced techniques to support and automate the data integration lifecycle. First, we describe how to represent and standardize data sources using graph-based schemas. These schemas provide a solid foundation for all steps of the data integration lifecycle. Next, we introduce an integration method that leverages graph-based schemas to add new data incrementally without disrupting existing integration structures. This approach ensures that data integration remains flexible and scalable as organizations grow. We also help users find the right datasets to integrate. By focusing on data discovery, we reduce the time spent exploring irrelevant data sources and suggest relevant ones for integration. To this end, we focus first on facilitating the discovery of joinable attributes among datasets. We propose a new qualitative metric and use data profiles and learning models to decide which attributes are worth joining. To further enhance data discovery, we introduce contextual pre-filtering. Using data profiles and graph-based schemas, we can focus on promising datasets before applying data discovery tools. This pre-filtering step not only boosts the accuracy of existing data discovery tools but also optimizes their performance by narrowing the search space. In summary, this thesis helps bridge the gap between conventional data methods and modern, diverse data ecosystems. The results contribute to the field of data integration by offering scalable and automated solutions that match the changing needs of data integration today.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• GADELHA TEIXEIRA FILHO, VINICIUS: Conceptualization, Design and Optimal Operation of Hybrid AC-DC Power Router Grids
  
  Author: GADELHA TEIXEIRA FILHO, VINICIUS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 10/04/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: SUMPER, ANDREAS | BULLICH MASSAGUÉ, EDUARD
  Thesis abstract: Driven by increasingly strict climate goals, the need for modernization of the electric power system has intensified in recent years. The transition towards a distributed and decarbonized smart energy system requires modernizing power grids to accommodate the widespread adoption of renewable energy sources (RES), electric vehicles (EVs), and distributed energy resources (DERs). One key factor to enable this is the advancements in power electronics and their widespread deployment. The Power Router (PR) technology is crucial for this transition, as it facilitates flexible and efficient management of electricity as well as integration between AC and DC grids. It is a device composed of multiple ports that provides a seamless interface of different elements of a power grid by controlling the power between ports.In the first half of this thesis, different kinds of PR concepts are investigated and a novel grid concept based on PRs has been defined, named Power Router Grid (PRG). The PR concept adopted consists of coupling a set of voltage source converters to a common DC bus, in which each converter functions as a different input or output port. The converter model design used is the Modular-Multilevel-Converter (MMC) and is adaptable for PRs with any number of ports and any power level. Then, the theory behind the PRG is presented. First, a set of rules is proposed to ensure the correct configuration and operation of the PRG. Secondly, each PR role is defined based on their tasks within the PRG. Finally, in combination with graph theory methods, a new concept is introduced called Slack Tree (ST). The ST is the backbone that regulates and ensures power balance and the feasibility of the PRG operation, and is a connection path between all ports operating as a slack element.In the second half, all of these novelty concepts behind the PRG are combined with optimal power flow (OPF) models, convexity techniques and converter loss modelling. The goal is to create a Python-based convex OPF formulation suitable for any hybrid AC-DC network Based on PRs. The mathematical formulation is based on a second-order cone relaxation of the traditional power flows equations applied to radial networks. The developed PRG-OPF however, due to the decoupling characteristics of the PRs, is demonstrated to be suitable for any network meshed through PRs. In the last part of thesis, this formulation is further expanded to include the effects of converter losses. The loss model developed is defined as a set of linear constraints that are scalable and easy to implement inside an OPF. Additionally, other constraints regarding DC lines and AC grid integration are developed and integrated. The proposed OPF formulation is loss-aware and utilizes the full potential of PRs to integrate different systems.Throughout this doctoral thesis, seven case studies are presented in order to demonstrate the validity of the proposed concepts. Specifically, the power flow analysis show the viability of the highly-flexible PRG design. Different sensitivity analysis are conducted in order to assess the impact of converter losses and also the ST selection in the optimal operation of the PRG. Among the key remarks, the results demonstrate that the choice of ST does not significantly affect line losses. It is also shown that, despite the added converter losses, the PRG is more efficient than a traditional network in most scenarios, particularly in the presence of loads with low power factor.
  
• SALDAÑA GONZÁLEZ, ANTONIO EMMANUEL: Supervised Learning for Optimal Investment Planning in Active Distribution Networks
  
  Author: SALDAÑA GONZÁLEZ, ANTONIO EMMANUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 28/03/2025
  Reading date: 16/06/2025
  Reading time: 11:00
  Reading place: Aula Capella - ETSEIB
  Thesis director: SUMPER, ANDREAS | ARAGÜÉS PEÑALBA, MÒNICA
  Thesis abstract: Due to the exponential growth of electric vehicles and distributed generation in distribution networks, potential congestion in power lines, transformers, and voltage deviations is expected to increase in the coming years. For this reason, the development of modern distribution planning strategies to strengthen grid infrastructure needs to be studied, considering its dynamics and impacts.This thesis proposes a simulation-based optimization model for active distribution network expansion, capturing nonlinear complexities through AC power flows, voltage stability, and operational constraints. The formulation includes an objective function, constraints, and both traditional and flexible planning actions, focusing on determining the optimal battery power and capacity over projected horizons to defer infrastructure investments.Additionally, this thesis reviews and compares smart grid measurement devices based on their technical specifications and potential applications in distribution network operation and planning. A recurrent neural network model is also presented for medium- and long-term load forecasting using historical consumption data from medium-voltage (MV) transformer stations. This forecasting model was later integrated with an investment planning model to compare passive and flexible reinforcement actions in a real case study in Spain.Finally, supervised learning models (Random Forest, XGBoost, LSTM, and SVM) were trained using the proposed optimization model to predict and minimize investment costs, thereby identifying the most effective approach for DSO planning applications. This methodology was tested on a CINELDI network under various electric vehicle charging expansion scenarios and is intended for use in connection request applications.
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• PASTOR LÓPEZ, EDWARD JAIR: Nature-based solutions to reduce the spread of antibiotics and antimicrobial resistance genes in aquatic ecosystem
  
  Author: PASTOR LÓPEZ, EDWARD JAIR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 14/04/2025
  Reading date: 05/06/2025
  Reading time: 11:00
  Reading place: Place: ETSECCPBUPC, Campus NordBuilding C2. Classroom: 212C/Jordi Girona, 1-308034 Barcelona
  Thesis director: MATAMOROS MERCADAL, VÍCTOR | ESCOLÀ CASAS, MÒNICA
  Thesis abstract: Antibiotics (ABs) are antimicrobial agents whose production and consumption have increased exponentially since the discovery of penicillin in 1929. The overuse of ABs has driven the emergence of antibiotic resistance, leading the frequent detection of ABs and antimicrobial resistance genes (ARG) in aquatic environments, primarily due to wastewater treatment plants (WWTP) effluent discharge despite regulatory efforts. Additionally, prolonged extreme weather conditions, such as droughts, intensify this issue by reducing water availability, threatening aquatic ecosystems and human health. Although advanced water treatment technologies, such as ozonation or membrane-based systems, can remove these pollutants from wastewater, their high cost of construction and maintenance, limited their widespread implementation. Alternatively, Nature-Based Solutions (NBS) have emerged as a potential option due to their cost-effectiveness and their potential capacity to remove a wide range of pollutants. However, studies on the reduction of ABs and ARGs in full-scale on NBS applied to wastewater treatment or river streams remain limited.This PhD dissertation is presented as a compendium of publications and evaluates the effectiveness of NBS in reducing ABs and ARGs in wastewater. First, a review study explored the capacity of NBS to reduce the presence of ABs, ARGs and pathogens across diverse aquatic environments spanning secondary wastewater treatment to estuarine areas and saltmarshes (Chapter II – DOI: 10.1016/j.scitotenv.2024.174273). Second, the performance of two full-scale configurations of constructed wetlands (CW) as tertiary wastewater treatment systems were monitored during the summer and the winter seasons to assess the reduction of ABs and ARGs (Chapter III – DOI: 10.1016/j.watres.2024.122038). Their effectiveness were compared with a conventional tertiary wastewater treatment technology system. Third, the impact of wastewater effluent-dominated stream renaturalization on the reduction of ABs and ARGs across seasonal variations was assessed by monitoring a vegetated and less vegetated stream during both warm and cold periods (Chapter IV – DOI: 10.1016/j.envres.2025.120910).The findings presented in this doctoral research project demonstrate that NBSs are potential alternatives for water treatment management in river basins. CWs as tertiary wastewater-treatment systems have shown the capacity to improve the general water quality parameters and remove ABs and ARGs. In addition, unlike conventional systems, those systems promote a shift in microbial composition towards a more natural profile and reduce the ecotoxicological and resistance selection risks more than a conventional tertiary WWTP. Furthermore, vegetated streams with meanders have shown to increase the degradation kinetics of ABs and the attenuation of ARGs, foster gradual changes in bacterial community structures and decrease the ecotoxicological and resistance selection risks, especially during the warm period. Further research should keep focusing on evaluating novel full-scale NBS configurations, identification of the transformation products (TPs) as well as other aquatic micropollutants, quantification of diverse ARGs and assessing the ecological status of the water.
  

DOCTORAL DEGREE IN MARINE SCIENCES

• SÁNCHEZ ARTÚS, XAVIER: Morphodynamic modelling for coastal hazard mitigation
  
  Author: SÁNCHEZ ARTÚS, XAVIER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 30/04/2025
  Reading date: 17/06/2025
  Reading time: 11:00
  Reading place: Place: ETSECCPBUPC, Campus NordBuilding C2. Classroom: 212C/Jordi Girona, 1-308034 Barcelona
  Thesis director: GRACIA GARCIA, VICENTE | ESPINO INFANTES, MANUEL
  Thesis abstract: Mediterranean sandy beaches are facing increasing hazard, a situation that will be exacerbated due to climate change. This thesis focuses on the analysis of flooding and erosion along Catalan beaches under present and future conditions. The analysis is performed using the hydromorphodynamic model XBeach. A user-friendly and high-resolution operational service is developed to forecast these impacts, enabling authorities to take preemptive measures to minimise their effects. A nature-based mitigation approach is tested in a thoroughly validated area to assess their efficacy in reducing coastal hazards. Finally, the modelling strategy is used to simulate different coastal archetypes for both present and future conditions, including sea level rise scenarios due to climate change. Through the study of these three fields, a complete review of the capacities of the hydromorphodynamic modelling is presented. Thus, the analysis sheds light on the knowledge of beach responses across different time scales and demonstrates the necessity of implementing nature-based solutions (NbS) and Early Warning Systems (EWS) to mitigate coastal hazards during storm events.
  

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

• RIU PERDRIX, GUIOMAR: Dry-electropolishing of WC-Co cemented carbides: Chemical, microstructural and mechanical characterization
  
  Author: RIU PERDRIX, GUIOMAR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Article-based thesis
  Deposit date: 06/05/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: ROA ROVIRA, JOAN JOSEP | LLANES PITARCH, LUIS MIGUEL
  Thesis abstract: WC-Co cemented carbides are widely used in industry, particularly for cutting tools, due to its exceptional combination of mechanical properties. They are composites consisting of tungsten carbide (WC) particles embedded within a cobalt (Co) metallic binder. This microstructural assemblage provides a unique combination of hardness, wear resistance, and fracture toughness. However, these properties can degrade at high temperatures (>500 ºC) due to corrosion sensitivity. To address this limitation, protective coatings, such as titanium aluminium nitride (TiAlN) or titanium silicon nitride (TiSiN) are frequently applied, enhancing performance under high-temperature loading.Grinding is the most conventional post-processing technique used to achieve the final geometry and dimensional tolerances of WC-Co components. However, this method impacts surface integrity, inducing defects like voids, cracks, high roughness (0.2 - 0.6 µm), phase transformations in the metallic Co binder, and compressive residual stresses, extending up to 10-20 µm in depth. Accordingly, removal of the damaged layer though polishing is commonly advised.In recent years, a new dry-electropolishing technology has emerged for metallic alloys, allowing precise defect reduction and surface improvement. Unlike conventional electropolishing, which uses liquid electrolytes, dry-electropolishing uses solid porous polymeric particles (ion exchange resins) filled with an electrolytic medium. This method selectively removes material layer-by-layer from surface irregularities, reducing roughness and improving surface quality.This industrial Ph.D. thesis focus on the development of a novel dry-electrolyte specifically tailored for electropolishing WC-Co composites using DryLyte® Technology. The research explores the underlying polishing mechanisms, optimizes electrical parameters, and identifies key chemical reactions involved in the process. Results demonstrate that this process effectively eliminates surface defects, reduces roughness, and preserves the WC-Co microstructure, avoiding Co leaching and WC embrittlement.A comparative microstructural and mechanical analysis was conducted, evaluating various shaping and finishing methods, including grinding, electrical discharge machining (EDM), conventional polishing, and dry-electropolishing. The findings reveal that, while grinding and EDM are widely used, they generate surface defects such as micro-cracks, porosity, and harmful oxides. Conventional polishing improves surface roughness but removes hundreds of microns of material and fails to preserve compressive residual stresses, thereby diminishing the mechanical performance of the system. Conversely, dry-electropolishing precisely eliminates deformed layers, achieves smooth surfaces between phases, and retains beneficial compressive residual stresses.The thesis further explores the industrial applications of this technology, such as cutting edge preparation for WC-Co end-mill tools. Previous studies have demonstrated that an optimal edge preparation increases tool life. The results of this research confirm that dry-electropolishing can fine-tune the cutting edge radius, refine micro-geometric parameters, reduce roughness, and eliminate manufacturing-induced defects. A direct correlation between polishing time and micro-geometric parameters is established, showing rapid changes within the first three minutes, followed by stabilization.Additionally, the research investigates the stripping of worn TiAlN/TiSiN coating on WC-Co substrates to extend their operational lifespan and reduce costs. This process removes the films precisely, leaving an oxide surface layer without compromising the substrate microstructure. The process demonstrates a linear relationship between polishing time and remaining coating thickness, ensuring a controllable, efficient, and homogeneous method.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• SENDER, PIOTR GRZEGORZ: Surveillance and prediction of machining results in honing and grinding processes using sound signal analysis method
  
  Author: SENDER, PIOTR GRZEGORZ
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 04/04/2025
  Reading date: 03/07/2025
  Reading time: 10:30
  Reading place: aula I-28.8 ETSEIB
  Thesis director: BUJ CORRAL, IRENE
  Thesis abstract: Abrasive machining processes are usually applied after turning or milling processes in order to improve dimensional accuracy and to reduce surface roughness of the machined parts. The sound signal contains information about machining processes, and it is possible to use it to monitor and control them, by analysis of received data directly from sound signal during ongoing machining. In this thesis, honing and tangential grinding tests were performed, and the acoustic emission signal was measured and examined. Experimental tests were carried out in order to verify the correlation of the selected machining parameters with the obtained results, regarding surface roughness parameters and shape errors of machined workpiece. In the tests, the acoustic emission signal was recorded, in order to check the possibility to implement to supervising of conducting of abrasive machining in workshop practice. To collect acoustic signals, a unidirectional condenser microphone was employed, and Matlab and Audacity software was used.In honing processes, different experiments were carried out. Rotation speed of the workpiece and feed speed values of the honing head were varied, together with the grain size and density of the honing stones, as well as the pressure value of the whetstones to the honed surface. Selected responses were surface roughness, cylindricity error and material removal rate. As for tangential grinding, three parameters were varied: depth of cut, feed rate and transverse infeed. Responses of the grinding process were surface roughness and material removal rate.In both cases, honing and grinding tests, linear regression models were searched for roughness and for material removal rate, and multiobjective optimization was carried out by means of the Derringer-Suich desirability function.It is possible to supervise the abrasive machining process, both grinding and honing, while the machining is in progress and without interrupting it. The proposed method consists of carrying out machining tests, measuring several responses such as roughness or material removal rate and supervising the received acoustic signals. Afterward, it will be possible to carry out comparative analysis of the acoustic signal on an ongoing basis registered.It was confirmed that it is possible to predict the result parameters of the conducted abrasive machining (including surface roughness profile parameters) by analyzing the recorded acoustic signal.
  

DOCTORAL DEGREE IN NUCLEAR AND IONISING RADIATION ENGINEERING

• MARTÍN GIL, KEVIN: Thermal-hydraulic Scaling Distortions in Pressurized Water Reactors
  
  Author: MARTÍN GIL, KEVIN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NUCLEAR AND IONISING RADIATION ENGINEERING
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 10/04/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: FREIXA TERRADAS, JORDI | MARTÍNEZ QUIROGA, VÍCTOR MANUEL
  Thesis abstract: Ensuring safety in Nuclear Power Plants (NPPs) requires a deep understanding of their phenomenology, in the context of the deterministic safety assessment. Scaling plays a key role in this understanding, as it is necessary to downscale the complex thermal-hydraulic systems of NPPs to the scale of Integral Test Facilities (ITFs) for research. Constructing a full-scale NPP for experimental purposes is not economically feasible, making downscaling an essential approach. However, achieving a perfect scale model is impossible, as neither engineering nor scientific designs can fully satisfy all scaling requirements to preserve phenomena across different scales.This thesis investigates scaling distortions in several accident scenarios, including the Intermediate Break Loss-of-Coolant Accident (IBLOCA), Steam Generator Tube Rupture (SGTR), and a Main Steam Line Break (MSLB) in a Pressurized Water Reactor (PWR). The research examines the impact of preserving environmental heat losses and the Froude number in horizontal legs, as preserving the latest is essential for stratification, which influences droplet entrainment and reflooding in LOCA scenarios. Additionally, environmental heat losses play a crucial role in replicating plant energy balance, both of which significantly affect coolant discharge through the break. The study also assesses the effects of two different scaling approaches on heat losses and their associated distortions. Furthermore, this research aims to propose methodologies for quantifying, reducing, and mitigating scaling distortions in these scenarios.In this thesis, the Power-to-Volume Scaling Tool (PVST), which is based on the Power-to-Volume scaling methodology, was modified to automate input and output processing, also allowing for downscaling capabilities. Coupled with pre- and post-processing scripts, this modification enabled automated batch generation of validated hybrid and Scaled nodalizations for RELAP5 at any scale. These nodalizations were then used to simulate all the aforementioned scenarios and post-process the results. The hybrid and scaled nodalizations are based on the OECD/NEA ROSA-2 project in the Large-Scale Test Facility (LSTF). These nodalizations employ multiple scaling rationales, varying the treatment of horizontal legs and heat losses, either preserving or not preserving the Froude number and ideal heat losses.Additionally, a first-of-its-kind Best Estimate Plus Uncertainty Plus Scale (BEPU-PS) methodology-built upon the BEPU GRS method with the added incorporation of scaling considerations-was applied to Test 2. This approach preserved ideal heat losses and the Froude number in horizontal legs to quantify scaling distortions in a wide range of scale and compare them to the inherent uncertainties of the ITF and RELAP5.The main phenomenology of the studied scenarios was analyzed across multiple scales and scaling rationales. In IBLOCA scenarios, scaling distortions were observed when the Froude number was not preserved in horizontal legs and when ideal heat losses were not maintained, leading to variations in Peak Cladding Temperature (PCT) and changes in coolant distribution within the primary system of the PWR hybrid-scaled design. Additionally, scaling rationales that preserved ideal heat losses and the Froude number tended to reduce scaling distortions related to PCT, mass distribution, and the timing of emergency core cooling system injections. The BEPU-PS scales bands, along with Spearman's rank correlation coefficients, revealed that the primary contributors to widening the BEPU bands were the discharge coefficient, the scaling number parameter had a significantly lower statistical relevance according to Spearman's rank correlation coefficients.Regarding SGTR-MSLB scenarios, the study highlighted that SGTR scenarios exhibited no significant scaling distortions when the L/Dh ratio was. Additionally, no evidence of scaling distortions was found in MSLB scenario.
  

DOCTORAL DEGREE IN PHOTONICS

• AMUAH, EMMANUEL BAFFU: Probing structural coherence across a light-induced double phase transition
  
  Author: AMUAH, EMMANUEL BAFFU
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 14/04/2025
  Reading date: 11/06/2025
  Reading time: 10:00
  Reading place: ICFO Auditorium
  Thesis director: WALL, SIMON ELLIOT | JOHNSON, ALLAN STEWART
  Thesis abstract: Strongly-correlated materials have emerged as one of the most active areas of research in Condensed Matter Physics. Interests in these materials arise mainly from the pliability of their properties, offering the possibility of tailoring these materials for specific applications. This is, in turn, due to the rich interplay of interactions between electronic, orbital and lattice degrees of freedom. This complex coupling of the different degrees of freedom, on the other hand, makes strongly-correlated materials difficult to understand.Ultrafast spectroscopy offers the possibility of resolving this bottleneck and provides insight into aspects of correlated materials crucial for enhancing our understanding of these materials. One such aspect is photoinduced phase transitions, where light drives a symmetry change in a material. To date, research has focused on using light to force materials to cross a single structural transition. In this work, we investigate the possibility of making multiple phase jumps with a single pulse of light. A suitablesystem for such study is the manganite, Pr0.5Ca1.5Mn04, which despite its prospects remains less explored. This layered manganite exhibits multiple phase transitions of electronic, orbital and structural origins, as a function of temperature. The presence of more than one phase transition in Pr0.5Ca1.5Mn04 allows us to examine the possibility and mechanism of multi-phase transition, an aspect of photoinduced phase transition that has hitherto not received much attention. The physics of the manganites is strongly dictated by the dynamics of Jahn-Teller phonons, which occur at a very high frequency (>15 THz). Studies involving these phonons thus call for setups with a very high time resolution.This thesis first discusses the construction of a novel setup that makes use of few-cycle pulses from the visible to the near infrared wavelength regions. Then, leveraging on the capabilities of this setup, we undertake ultrafast measurements on Pr0.5Ca1.5Mn04 in two parts: the linear and nonlinear pumping regimes. In the linear regime, we perform broadband, low-fluence measurements to characterize the sample. From this, we identify key structural and electronic changes that occur during the thermal transition pathway, allowing us to map out the sample into different symmetry regions, in agreement with literature. In the nonlinear pumping regime, we study the fluence dependence of the changes identified from the linear regime. By analyzing the coherent lattice response, we find indications of both single and double phase transitions occurring.
  
• BATLLE PORRO, SERGI: Near-field photocurrent in correlated 2D moiré materials
  
  Author: BATLLE PORRO, SERGI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 14/05/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: KOPPENS, FRANK | STEPANOV, PETR
  Thesis abstract: Since the discovery of graphene, two-dimensional (2D) materials have garnered significant attention from the condensed matter physics community owing to their potential to engineer new physical, optical, and mechanical properties. The 2D material class now includes insulators (hexagonal boron nitride, hBN), semiconductors (transition metal dichalcogenides, TMDs), superconductors (NbSe2), topological insulators (Bi2Te3), and ferromagnets (CrI3). Beyond their inherent properties, layered materials allow for new characteristics through vertical stacking. Recent developments have led to the discovery of moiré materials, in which electronic properties are significantly altered by twisting adjacent 2D layers.The discovery of superconductivity in magic-angle twisted bilayer graphene (MATBG) marked a milestone in moiré physics, initiating a rapidly growing field. The resulting phase diagrams of other high-Tc superconductors, MATBG, serve as a platform for exploring highly tunable strongly correlated states. At a twist angle of approximately 1.1°, the "magic angle,” MATBG shows significant band flattening near the Dirac points, reducing the Fermi velocity and making the kinetic energy smaller than the repulsive Coulomb interactions. This results in superconductivity and various emergent phases dominated by many-body physics, including correlated insulators, orbital magnetism, nematic orders, and topological states.Moiré materials with large superlattice unit cells facilitate the exploration of strongly correlated phenomena at low charge carrier densities. Local back-gate electrodes enable capacitive tuning between strongly correlated states in-situ, a unique feature not available in other high-Tc superconductors. Advances in scanning probe techniques have allowed researchers to determine local properties at the sub-nanometer scale. Scattering-type scanning near-field optical microscopy (s-SNOM) is particularly suited for exploring MATBG because it can measure scattering and photovoltage signals at the nanometer scale while simultaneously probing mesoscopic electron transport. Utilizing a groundbreaking cryo-near-field nanoscopy method, we will conduct s-SNOM measurements at cryogenic temperatures (as low as 8 K) to assess the optical and photovoltage near-field responses. This approach employs energies in the mid-infrared (MIR) and terahertz (THz) ranges, which align with the anticipated optical transition energies in the band structures of these materials. The primary objectives of this thesis are to ascertain the pertinent optical and thermoelectric coefficients in twisted moiré materials, evaluate the impact of inhomogeneities through gate-tuned near-field photovoltage and optical measurements, visualize correlated phenomena and broken symmetry states, and comprehend the nature of dephased signals in various measurements. This dissertation seeks to highlight crucial advancements in quantum phases, quantum nano-optoelectronics, and thermoelectricity, while supporting interest in unresolved questions, such as the characteristics of low-temperature correlated states. Additionally, it outlines future objectives for near- and far-field photovoltage experiments.
  

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

• DOROST, POROCHISTA: Nanoparticles made of poly(gamma-glutamic acid) derivatives for drug delivery systems
  
  Author: DOROST, POROCHISTA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 14/03/2025
  Reading date: 10/06/2025
  Reading time: 11:30
  Reading place: Aula de audiovisuales del DEQ en la ETSEIB (Planta G-2)Campus Diagonal Sud, Edifici PIAvda. Diagonal, 64708028 Barcelonahttps://etseib.upc.edu/ca
  Thesis director: GARCIA ALVAREZ, MONTSERRAT
  Thesis abstract: Polymers have become one of the primary options in biomedical fields due to their diverse properties, functionalities, and applications. Characteristics such as mechanical strength, biocompatibility, and biodegradability have made these materials highly attractive for various medical applications. One of the most intriguing applications of these polymers is drug delivery. Biodegradable polymers and copolymers are the primary materials used for producing temporary medical and pharmaceutical devices. These polymers can be chemically synthesized or naturally produced.Biotechnological polymers, produced through biotechnological processes, have garnered significant attention due to two major advantages. First, they are derived from renewable resources; second, as they are biologically produced, they are usually biocompatible, biodegradable and bioresorbable. Therefore, modifying these polymers to tune their properties or functionalities is an effective strategy for developing biomedical materials.Poly(γ-glutamic acid) PGGAH is a biocompatible and biodegradable poly-γ-peptide with carboxylic side groups that can be substituted to modify the polymer’s properties. In this study, PGGAH was hydrophobically and cationically modified. Through hydrophobic modification and altering the hydrophilic properties, amphiphilic copolymers were produced, capable of self-assemble into nanoparticle systems for drug encapsulation and controlled release. This modification was carried out by partial esterification of carboxylate side groups with 4-phehyl-butyl bromide (4-PhBBr). Further decoration to produce stealth and targeting nanoparticles was achieved by reaction of some remaining carboxylate side groups with amino ended poly(ethylene glycol) (NH2-PEG) and NH2PEG derivatized with folic acid, respectively. Cationic modification of this biodegradable polymer enabled the formation of nanopolyplexes with DNA. This modification was carried out by esterification of carboxylate side groups with cationic 2-bromoethyl trimethylammonium bromide (BrETABr). The obtained derivatives were used to prepare nanoparticles through emulsion solvent evaporation or nanoprecipitation dialysis techniques. Nanoparticles with an approximate size of 100 to 380 nm were obtained, demonstrating their potential as drug delivery systems capable of encapsulating the anticancer drug doxorubicin.The chemical structure of the derivatives were characterized using proton and carbon-13 nuclear magnetic resonance (NMR) spectroscopy, and the physicochemical properties by gel permeation chromatography (GPC), and thermal gravimetric analysis (TGA). Functional group analysis was conducted through Fourier-transform infrared spectroscopy (FT-IR). Hydrolytic degradation was monitored by 1H NMR, while the appearance of the nanoparticles was observed using scanning electron microscopy (SEM), and their size and surface charge were determined by dynamic light scattering (DLS) and zeta potential measurements, respectively.For the hydrophobic copolymer series, cytotoxicity assays were carried out, confirming the low toxicity of the synthesized derivatives. Drug encapsulation and release was initially evaluated under physiological conditions, revealing that the release rate was higher in acidic pH and affected by the degree of polymer modification. On the other hand, cellular uptake nanoparticle tests demonstrated that the nanoparticles successfully penetrated cancer cells. The results of this study indicate that the biotechnological polymer PGGAH is a promising material for designing and developing biodegradable drug delivery systems with potential therapeutic applications for challenging diseases in pharmacological treatment.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• CARREÑO MEGIAS, XAVIER: Ground-based GEOSAR system using DVB-S/S2 signals of opportunity and FPGA based correlators
  
  Author: CARREÑO MEGIAS, XAVIER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 06/05/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: BROQUETAS IBARS, ANTONI
  Thesis abstract: The SAR satellite missions from Geostationary Orbits (GEOSAR) offer short revisit times of less than 24 hours, which are essential for monitoring fast-evolving phenomena. A first mission has recently been launched in China, and other missions are being studied or proposed in Europe and the USA, with applications ranging from water cycle monitoring to terrain stability assessment. All of these missions share the need for precise orbit determination at Geostationary Orbits (GEO) to enable the formation of well-focused SAR images.By employing Field-Programmable Gate Array (FPGA) technology, digital correlators have been designed to be used in an interferometric orbit determination system. The system has been validated for obtaining orbital estimates using phase observables from the correlator outputs, which can be used to determine the satellite's trajectory. The implemented system tracks TV broadcasting telecommunication satellites, using the transmissions as signals of opportunity (SoOp). Urban reflectors are utilised to form large interferometric baselines with respect to the developed receiver.Precise orbital determination is crucial for Synthetic Aperture Radar (SAR). Simulation studies were conducted for a monostatic configuration and a ground-based bistatic configuration to assess the impact of orbital parameter estimation errors on SAR image focusing. An autofocusing technique based on entropy minimization optimisation has been studied to improve the focusing of the GEOSAR images affected by residual orbital errors, allowing for the relaxation of orbit precision requirements to the order of hundreds of metres. Using the same transmitters of opportunity as in the interferometric system, a ground-based SAR (GB-GEOSAR) passive system has been designed and implemented. A multichannel coherent receiver is employed to capture echo data from a close by urban scene. A range compression module, based on the design of the interferometric correlators, is employed to process the echo data by correlating it with the main satellite signal, which acts as a reference for the matched filter process. Azimuth compression, based on the orbital data from the interferometric system, is then applied to obtain SAR-focused images. These images can be used to study GEOSAR concepts and serve as proof of concept for the capabilities of a passive system, which could be employed for monitoring local regions with low deployment costs.Interferometric and polarimetric techniques can be applied to GB-GEOSAR images, which could be used in topographic or earth deformation mapping and surface type classification. An experimental evaluation based on images of urban and mountainous areas near the university campus has enabled the identification of the challenges, potentials, and limitations of the developed system.
  
• DÍEZ GARCÍA, RAÚL: New Methods for Radio Frequency Interference Mitigation in Microwave Radiometry
  
  Author: DÍEZ GARCÍA, RAÚL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 24/04/2025
  Reading date: 20/06/2025
  Reading time: 10:00
  Reading place: Sala de Graus, edifici C4-002, ETSETB, Campus Nord, Barcelona
  Thesis director: CAMPS CARMONA, ADRIANO JOSE
  Thesis abstract: Radio Frequency Interference (RFI) has emerged as the most critical challenge to the effective exploitation of the microwave spectrum for Earth observation. RFI consists of non-natural emissions that obscure the radiometric signals measured by microwave radiometers. The presence of RFI degrades the accuracy and completeness of radiometric measurements. This is evident, for example, in the European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, which, despite operating in the protected L-band, is severely affected by interference. This PhD thesis presents innovative approaches to mitigate this issue, with a particular focus on Synthetic Aperture Interferometric Radiometers, which have been insufficiently studied in the context of RFI.This PhD thesis introduces several novel RFI detection and mitigation techniques, including autocorrelation-based detection, non-linear decomposition using Empirical Mode Decomposition (EMD), and data-adaptive mitigation via the Karhunen-Loève Transform (KLT). These methods address some of the limitations of existing approaches and have been evaluated with simulated data using standard performance metrics. Furthermore, a new algebraic interpretation of mitigation is provided, bridging the gap between RFI detection and signal transformation methods, and introducing novel performance evaluation metrics.In addition to the theoretical contributions, this thesis includes experimental validation of the proposed techniques using real-world data. The practical feasibility and performance of whiteness-based detection and KLT-based mitigation techniques are demonstrated in realistic scenarios. The research also explores the effects of signal quantization on mitigation techniques, a relevant concern for digital radiometer implementations.
  
• GARRIDO ATIENZA, ALEJANDRA: Qualitative Algorithm for Microwave Colonoscopy
  
  Author: GARRIDO ATIENZA, ALEJANDRA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 30/04/2025
  Reading date: 12/06/2025
  Reading time: 10:00
  Reading place: Aula de Teleensenyament (Edifici B3 - Ricardo Valle Sala 103 Planta 1, Campus Nord)
  Thesis director: ROMEU ROBERT, JORDI | GUARDIOLA GARCIA, MARTA
  Thesis abstract: This thesis develops and validates an innovative algorithm for colorectal cancer (CRC) detection using microwaves, integrating it into endoscopic procedures. Validation includes ex-vivo, in-vivo, and clinical trials. The algorithm enhances polyp detection by exploiting dielectric contrast between healthy and cancerous tissues, addressing colonoscopy limitations. It normalizes signals, calibrates artifacts, reconstructs images, and applies automatic detection to improve sensitivity and specificity.Key calibration strategies include First Frame Subtraction, Similar Frame Subtraction, Antenna-Pair Subtraction, and Previous Frames Averaging to isolate polyp scattering. Automatic detection methods, such as Exponential Smoothing and Target-to-Clutter Ratio Thresholding, enable polyp identification regardless of anatomy. The algorithm undergoes extensive preclinical testing with phantom models, ex-vivo tissues, and in-vivo pig trials, evaluating detection accuracy through sensitivity, specificity, and mismatch metrics. A pilot clinical trial validates real-world performance.Optimization involves refining a phantom model to simulate colonoscopy conditions and tuning algorithm parameters for a second clinical trial. These advancements position microwave-based detection as a promising CRC screening alternative. The research demonstrates the potential of microwave imaging to improve diagnostics, offering real-time, automated polyp detection with meaningful clinical impact.
  
• SARMIENTO CALDERÓ, MANUEL: Contextualization of Spatio-temporal Action Localization Systems and Media Content Applications
  
  Author: SARMIENTO CALDERÓ, MANUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 02/04/2025
  Reading date: 13/06/2025
  Reading time: 10:00
  Reading place: Aula Merit, edifici D5-010, Campus Nord, Barcelona
  Thesis director: MARQUES ACOSTA, FERNANDO | VARAS GONZÁLEZ, DAVID
  Thesis abstract: Spatio-temporal action localization is a field of computer vision that determines both the spatial and temporal locations of actions taking place within a video. This particular task is one of the cornerstones of video understanding due to its inherent complexity. Impressive scientific advances in the artificial intelligence and computer vision industry have led to a significant performance increase.Nevertheless, even state of the art systems struggle to recognize actions that involve some kind of interaction between people, objects, or with the scene. This limitation arises because current spatio-temporal action localization models neglect contextual information when identifying a person's actions. Specifically incorporating contextual cues in these models can help to address this challenge. Furthermore, the integration of spatio-temporal action localization systems into multimedia content applications presents several challenges. The primary difficulties lies in finding ethical and practical use cases and addressing the computational requirements to run these models in production.The goal of this industrial PhD is to solve the above problems. The lack of contextual information is addressed in different forms. This thesis, is focussed on two different approaches. First, a novel system to explicitly model the relations of the different actors and objects in a scene, which includes a novel structure to model long-term temporal information is proposed. Second, an innovative multi-modal method to combine task specific features to improve action recognition is introduced. These developed contextualization systems are evaluated on different datasets. The results demonstrate the effectiveness of the proposed systems. Regarding the applications, this PhD is focused on finding, implementing and exploiting specific applications of spatio-temporal localization system for media content. The developed applications consists of an improved system for search and recommendations on video content, an smart cropping method to generate image and videos of any desired aspect ratio from another video, and the improvement of a system to generate highlight keyframes of football matches.
  
• WOODWARD RIQUELME, ALEJANDRO BENJAMÍN: Contextual Speech Recognition
  
  Author: WOODWARD RIQUELME, ALEJANDRO BENJAMÍN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 02/04/2025
  Reading date: 18/06/2025
  Reading time: 10:00
  Reading place: Aula de Teleensenyament (Edifici B3 - Ricardo Valle Sala 103 Planta 1, Campus Nord)
  Thesis director: MARQUES ACOSTA, FERNANDO | VARAS GONZÁLEZ, DAVID
  Thesis abstract: Although Automatic Speech Recognition (ASR) technology has achieved remarkable improvements in transcription accuracy in recent years, it still struggles to correctly transcribe certain words. In particular, proper nouns often exhibit lower accuracy due to their unique pronunciations and alternative spellings. To address these challenges, contextualisation is commonly integrated into ASR models to improve the transcription of rare proper nouns and disambiguate between similar-sounding proper nouns.This industrial PhD thesis focuses on the development of contextualisation systems for ASR models. The ASR technology employed in this thesis is used to generate automatic transcripts for podcast content. The objective of the contextualisation system is to improve the accuracy of proper nouns; for example, the names of podcast shows, hosts, and guests.The contextualisation system developed in this thesis is composed of two parts. First, an ingestion pipeline gathers proper nouns relevant to the podcast episode to be transcribed. This pipeline has an automated component that extracts proper nouns from the metadata of each podcast episode, such as the title and description, using tools like a named entity recogniser. Additionally, a module that allows the manual addition of proper nouns to specific podcast shows has been developed. The second part, which represents the most relevant contribution of this thesis, is a novel ASR contextualisation algorithm based on deep neural networks. The contextualized ASR model utilises the gathered proper nouns, resulting in an improvement in accuracy when compared to the same model without contextualization capabilities.The accuracy of the ASR system developed in this thesis is evaluated and analysed using episodes from popular public podcast shows. A human evaluation of the word error rate was employed during this assessment.This evaluation compares the quality of the ASR model system's transcripts to those provided publicly by the podcast content creators. The results show that the system developed in this thesis produces transcripts that contain four times fewer errors than the transcripts offered by podcast hosting providers.The contextualization method is also evaluated on a public dataset and compared to state-of-the-art methods. The results show that the contextualization method proposed in this thesis significantly outperforms the existing systems.
  

DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH

• BLANC BLOCQUEL DI MARCO, AUGUSTO: Derivatives and risks
  
  Author: BLANC BLOCQUEL DI MARCO, AUGUSTO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH
  Department: Department of Statistics and Operations Research (EIO)
  Mode: Normal
  Deposit date: 13/03/2025
  Reading date: 03/06/2025
  Reading time: 11:00
  Reading place: Aula de Teleensenyament, edifici B3, Campus UPC Barcelona Nord
  Thesis director: ORTIZ GRACIA, LUIS
  Thesis abstract: This thesis aims to provide solutions to real world problems by the use and development ofstate-of-the-art quantitative finance techniques. The first part of this work tackles the challenge of digital options hedging, particularly, at the-money digital options near maturity. The problem stems from the fact that a digitaloption has a discontinuous payoff at the strike price and has a huge delta and gamma nearexpiration. This problem is well-known among practitioners and academics. In this work, weconsider a general setting for hedging at-the-money digital options near maturity by meansof a bull spread. We solve different optimization problems, with the aim of minimizing theprobability of sub-hedging the digital option at maturity, considering transaction costs andilliquidity issues. Our contribution consists in the fact that we determine the compositionof the bull spread that minimizes the probability of sub-hedging a digital option given thatthe cost of hedging is below a certain threshold. We consider traditional and state-of-the-artmodels for driving the dynamics of the underlying asset. We also introduce the modelingof the illiquidity issue in the optimization problem, and solve that optimization problem.Finally, we calibrate one model to real market data and solve the optimization problem withtransaction costs with the calibrated model.In the second part of this work we intend to create financial tools to fight against climatechange. Over the last five years there have been increasing concerns about the impact ofcryptocurrency mining on climate. One of the main effects of climate change is its impacton agriculture and food production. In addition, climate change has clear consequencesfor human health. We propose novel bitcoin-denominated derivatives contracts on carbonbonds to address this problematic. This paper creates novel financial products which couldhelp the regulatory authorities impact the climate in an indirect fashion, agglutinating twodesired financial outcomes (hedging and volatility transfer) in a single financial instrument.Particularly, the instrument can be used by governments to hedge against climate change andinfluence the prices of carbon bonds and cryptocurrencies. In order to price this product, wedevelop novel parameter estimation techniques based on Shannon wavelets.The third part of this work also revolves around climate change, finance and mathematics.In this work we put forward a methodology to calculate the impact of an increase of the earth’sglobal surface temperature on the probability of default of a company from the agriculturesector. Extreme temperatures have a negative impact on asset prices in all sectors. Weperform a regression of firm’s stock value with predictors S&P 500 and temperature anomaliesand observe that an increase of temperature anomalies has a negative impact on the stockof the firm considered in this work. When modelling temperature anomalies time series it isimportant to identify points in time where a significant change occurs in the behaviour of thedata. These points are called breakpoints. Then, we model the time series of temperatureanomalies by means of segmented linear regression, where the breakpoints are estimatedby means of a wavelet analysis. We calibrate a Merton model with real stock data of thecompany and estimate the probability of default based on the probability that the assetvalue of the firm is below the liabilities level. We proceed to use the regression model toforecast future values of the firm’s stock influenced by the predicted temperature anomaliesand estimate a new probability of default.
  

DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION

• MORALES FLORES, PALOMA: La incidencia de las actuaciones de pacificación viaria en la consolidación del capital social. La experiencia de la Supermanzana de Sant Antoni en Barcelona
  
  Author: MORALES FLORES, PALOMA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION
  Department: Department of Architectural Technology (TA)
  Mode: Article-based thesis
  Deposit date: 30/04/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: MARMOLEJO DUARTE, CARLOS RAMIRO
  Thesis abstract: This doctoral thesis explores the intricate relationship between urban design and the formation of social capital (SC), using the traffic calming of public space in the Sant Antoni Superblock in Barcelona as a case study. Starting from the premise that social interactions are fundamental to community development, SC is adopted as a conceptual framework, recognising its impact on individual and collective well-being. In this sense, SC is configured as a preventive tool with great potential to address the current challenges of an ageing society, characterised by an increase in single-person households and an increase in situations of dependency, as well as a growing sense of loneliness. The progressively multicultural nature of society, driven by the sustained increase in migration necessary to meet the demands of the labour market, requires the development of support networks that, on the one hand, complement the work of public social services and, on the other, contribute to strengthening social cohesion.According to the literature, SC is not an individual attribute, but an emergent property of social structures, rooted in interpersonal relationships. For this reason, the public administration has an essential role in the provision and management of spaces, especially those of public ownership, which act as catalysts for the intersubjective relationships that shape SC. However, beyond the mere provision of facilities, the design of public space acquires critical relevance by influencing patterns of human activity and the quality of life of people.In contrast to the traditional approach of macro-scale studies based predominantly on surveys, this research proposes a complementary micro-scale analysis, focused on the direct observation of behavioural patterns in public space as evidence of SC. In other words, we consider social manifestations in public space as symptoms of a more complex condition: SC. In this way, we seek to understand how the design and management of public space influence social interactions at the micro level, contributing to a deeper and more granular understanding of SC in the urban context.A mixed methodology is used, which integrates: 1) a literature review, 2) urban analysis, 3) observation of the behaviour of people in public space, and 4) analysis of social capital indicators.Various attributes of urban design are considered with the aim of elucidating their impact on the promotion of SC, such as: the tactical and structuring nature, spatial typologies (squares, courtyards, passages), connectivity, proximity, level of pedestrianisation, personalisation and permeability of building facades at ground level, among other characteristics of the environment.The results reveal that urban interventions, both structuring and tactical, increase social activity compared to traditional urban design. However, structuring interventions of a permanent nature and characterised by the use of durable and low-maintenance materials such as concrete, generate greater diversity of uses and attract a wider public, as opposed to tactical interventions of an ephemeral and modular nature, which use more affordable elements such as paint and wood. This study offers valuable lessons for future urban interventions, emphasising the importance of a context-sensitive design, the balance between different users, social cohesion and long-term maintenance as key elements for the creation of inclusive spaces that foster social capital.
  
• PIASEK VINOCUR, GONZALO: Vulnerabilidad + regeneración = población en peligro de expulsión. Aprendizajes para una regeneración urbana inclusiva
  
  Author: PIASEK VINOCUR, GONZALO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION
  Department: Department of Architectural Technology (TA)
  Mode: Article-based thesis
  Deposit date: 13/05/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: GARCIA ALMIRALL, MARIA PILAR | MUXI MARTINEZ, ZAIDA
  Thesis abstract: This proposal is within the framework of a research project ‘Socio-spatial indicators for the improvement of building stock in vulnerable areas. Action criteria for the cases of the Metropolitan Areas of Barcelona and Bilbao’ (RE-INHABIT RTI2018-101342-B-I00), financed by the National Research Agency (AEI for its Spanish name). This framework project’s hypothesis is that most dense Spanish and European cities face the growing problematic of urban soil shortage, making it necessary to improve the existing housing stock.This work, framed within the ‘Urban and Architectural Management and Valuation’ Doctoral Program from Barcelona’s School of Architecture (Polytechnic University of Catalonia), aims to study the urban regeneration phenomenon in areas of high vulnerability from a broad perspective, taking into consideration both the physical and social components of the neighborhoods. Starting from the hypothesis that ‘most organized neighborhoods get more work and financial help’ – idea that was repeated regularly throughout a set of interviews – the main objective is to study the impact of urban regeneration policies in vulnerable areas of Barcelona at a social, physical-urban and socioeconomic level, in their links with the organizational component of the territories.If most organized neighborhoods receive most aid, it is interesting to ask what it means to be a more organized neighborhood; then, which are the conditions that make certain areas of the city promote higher levels of social interaction. Thus, based on the construction of a socio-residential vulnerability index, in its relation with another index of social capital (depicting the levels of social interaction) and another one of social infrastructure (focusing on the characteristics of spaces of social encounter) applied to the city of Barcelona, we seek to provide knowledge on innovative ways of studying and intervening with comprehensive policies focusing on the most disadvantaged areas of our cities. Likewise, a mapping and critical analysis of the existing urban regeneration instruments is carried out, with the intention of studying their impact, emphasizing the concepts of gentrification and the potential expulsion of residents. Using quantitative and qualitative research techniques and triangulation, the aim is to identify the real impacts of urban regeneration in the territory, while capturing the representations of both residents and actors from local entities and the public administration.In short, based on an analysis focused on a series of case studies in the city of Barcelona, the aim is to identify gaps, space for improvement, and innovative alternatives for both the study and the intervention in urban regeneration aimed at vulnerable neighborhoods, ensuring actions that tend to mitigate their adverse effects, the rooting of the resident population, the containment of rents, and sustainable local development. At the same time, the role of the beneficiaries of the programs is emphasized and a greater impact of these and of local organizations in the processes of improvement of their own environments is ensured, achieving greater appropriation and participation in regeneration instruments. Also, the purpose of this work is to achieve a methodology susceptible of being extrapolated to other processes of urban improvement.The results have allowed, broadly speaking, to explain the role of social infrastructure in the generation of social capital, and how both elements are key when thinking about the improvement of vulnerable neighborhoods. Likewise, the need to propose integrated approaches (both in research techniques and in the ways of intervening in the territory), if the intention is to regenerate to integrate and not to expel.
  

DOCTORAL DEGREE IN URBANISM

• LUZURIAGA TORRES, MARÍA FERNANDA: Ecologías [des]tejidas. Un discurso sobre la 'relación'.
  
  Author: LUZURIAGA TORRES, MARÍA FERNANDA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN URBANISM
  Department: Department of Urbanism, Territory and Landscape (DUTP)
  Mode: Normal
  Deposit date: 06/05/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: SOTOCA GARCIA, ADOLFO
  Thesis abstract: This research addresses the theme of coexistence, a concept of increasing relevance in the current context, marked by the economic, social, and environmental crises that have been manifesting globally since the beginning of this century. These crises have challenged the fragmented visions of Western modernity's urban thought, which divide reality into dichotomies such as: nature-culture, center-periphery, subject-object, public-private, or masculinity-femininity, compelling us to adopt new ways of thinking about space and its project. In this context, 'ecology' and 'body' have become key notions for rethinking coexistence among 'differents': human and non-human beings, desires, intentions, economies, ecosystems. The Amazon, being a place where diverse actors, peoples and nationalities, forms of spatial production, territorial conflicts over the extraction of natural resources, and imaginaries about space converge, is a place where the project of coexistence becomes particularly relevant.However, traditionally the Amazon has been represented through Western approaches that, implicitly, reproduce colonial matrix values and homogenizing visions of the region. This research, which focuses on the Tena canton, in the Ecuadorian Amazonian foothills, proposes a dual objective. On the one hand, it seeks to develop a new perspective that recognizes the invisibilized bodies and their multiple forms of relationship with the territory, overcoming reductionist visions. And, on the other hand, this research aims to rethink coexistence in a fragmented space: the Amazon is neither a primeval forest nor a purely rural space, but a dislocated territory where 'differents' coexist: peoples and nationalities, intentions, ways of life that produce a multiplicity of 'ecologies'.To fulfill this dual objective, it has been necessary to develop a specific interpretation methodology, which has been redefined throughout the course of the research. It is not, therefore, the rigid application of a pre-established protocol. While it has been required to collect and analyze both quantitative and qualitative data, as well as reconstruct the state of the art on the Amazon in urban studies. However, from the limitations and problems of insufficiency identified in this first stage, we realized that it was necessary to determine a coherent form of research, consistent with the characters of 'vacillation' and 'instability' of the Amazonian space. Hence, an approach to other disciplinary fields such as anthropology and sociology has been fundamental. This has allowed us to combine tools, resources, discourses, and concepts, paving the way to enter into 'relationship' with these complex realities, from our own bodily experience.Thus, traversing the territories and attentive to the characters constructed in the singularity of their daily lives, it was possible to establish a relationship between two key elements: socio-spatial analysis and the use of decolonial conceptual tools such as Eduardo Viveiros de Castro's 'cannibal thinking' and Silvia Rivera Cusicanqui's 'ch'ixi'. The socio-spatial analysis is carried out through the construction of a series of 'microhistories', analyzing the dynamics of 'power', 'resistance', and 'cannibalization' in the Amazonian space, paying special attention to the relationship between 'body' and 'territory'. The postulated hypothesis is that the dynamics of relationship can be interpreted as a result of the knowledge of bodies, which are patterns of resistance that make coexistence possible. Resistance understood as an active defense of human and non-human life, overcoming Western matrix discourses.
  

DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY

• SANMARTI MARTINEZ, CLAUDIA: La volta de maó de pla tibada, element essencial de l'arquitectura de Domènech i Montaner
  
  Author: SANMARTI MARTINEZ, CLAUDIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 19/05/2025
  Deposit END date: 30/05/2025
  Thesis director: ONECHA PEREZ, ANA BELEN | GRAUS ROVIRA, RAMON
  Thesis abstract: Domènech i Montaner, a cultured architect and up-to-date with European developments, found in construction an ally to shape his architecture. In this, he did not stray too far from the dictates of Viollet-le-Duc: only a new architecture would emerge if new structural principles were used. However, Viollet’s suggestions sparked new research in Domènech, and the evolution of his architecture eventually diverged from some of these principles.At the beginning of his professional career, Domènech left the structural iron ostentatiously visible, in the best tradition of structural rationalism spreading across Europe. But for him, construction is not a neutral matter; it also has a political dimension, like the fight for the Catalan language or the defense of Catalan civil rights. Brick construction would be identified as the genuinely Catalan form of construction and would be mythologized by the Modern Catalan School. The use of the diaphragm arch, the cultivation of the thin brick wall, and the exaltation of the vault should also be interpreted from this perspective.Although the tile vault was a technique of medieval origin and was widespread across much of the Mediterranean basin, in Catalonia, from the mid-19th century, it began a great expansion, combined with metal rod ties, especially in industrial architecture. The models of English mills were imported but improved and adapted to the country’s construction tradition.Domènech’s early works combine the constructive knowledge of the country’s professional masonry and its "Catalan construction" with the introduction of iron as a structural element. However, the technique of tile vault, in jack archs, balconies and stairs, is used for very small spans: it helps to construct his architecture, but it does not configure it in any special way.But since the ambitious project of the Hospital de Sant Pau and la Santa Creu, the essential element of Domènech i Montaner’s architecture is the tile vault with iron ties. The vault defines all of his spaces (barrel, bohemian, ribbed, tracery, with pendentives, tiled, plastered...) and is tensioned on its extrados by very sophisticated iron structures, which are never visible. The vault is the unit of aggregation, the element of re-signification of representative spaces, and the most functional instrument for service spaces.Domènech is not alone on this path. Before him, some of his prestigious colleagues in the profession were also working with the constructive possibilities offered by the tile vault technique, like Guastavino, who was thriving in the United States, and Gaudí, who was experimenting with its geometric and structural expressiveness. Around the Barcelona School of Architecture, there was a collective awareness of the importance of this technique as a defining feature of Catalan architecture.Lluís Domènech, and the early stage of his son Pere Domènech’s work, were so convinced of the potential of this system that they applied it to all kinds of buildings: hospitals, rental housing, theaters, warehouses, and factories. They experimented with its possibilities in combination with iron, taking spans to the limits and optimizing the structural material to be used. It reached the point where they even moved the rod ties and hoops away from the most efficient placement height, in order to give the supporting role of the spatial prominence to arches, vaults, and domes.But when the time came to introduce reinforced concrete and steel as structural grids in architecture, Domènech did not have time to change strategy. For him, the cultivation of "Catalan construction," and all that it represented, was and remains his path of discovery.
  
• ZHANG, RUIJIE: Spatial Form, Urban Governance, and People’s Experience: A Study on the Regeneration of Historic Environments in China from a Public Value Perspective (2000-2020)
  
  Author: ZHANG, RUIJIE
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
  Department: Department of Architectural Technology (TA)
  Mode: Article-based thesis
  Deposit date: 29/05/2025
  Deposit END date: 12/06/2025
  Thesis director: BOSCH GONZÁLEZ, MONTSERRAT | MARTI CASANOVAS, MIQUEL
  Thesis abstract: This Ph.D. thesis, grounded in public value theory, explores the influence of spatial form, urban governance, and people's experience on the realization of public value in China's historic environment regeneration (HER) from 2000 to 2020. Addressing the dilemma of "destructive construction" versus "frozen preservation" currently faced by historic districts in China, this study emphasizes the crucial role of integrating public value into the HER process for promoting sustainable urban development. The thesis aims to provide a theoretical framework and practical guidance for public value-oriented urban renewal through an in-depth study of China's historic district regeneration practices. By employing multi-dimensional and multi-layered analysis, the research seeks to uncover the complex factors influencing historic district regeneration and offer viable solutions to promote social equity and cultural heritage preservation. The main objectives include: assessing the creation of public value through the realization of the "publicness" of spatial form; examining urban governance's role in balancing stakeholder interests while proposing sustainable, people-centered strategies for equitable regeneration; and developing a multi-dimensional framework integrating spatial form, urban governance, and people's experience to explore their impact on public value in China's historic environment regeneration. Employing methods such as case studies, questionnaire surveys, and structural equation modeling (SEM), this research analyzes the relationships among spatial form, urban governance, and people’s experience from the perspective of public perception, constructing a hexagon public value model. The findings offer a reference for urban managers and planners in balancing historic preservation, economic development, and public interests.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• FANG, XIN: FAULT DIAGNOSIS AND PROGNOSIS APPROACH USING DATA-DRIVEN STRUCTURALLY GENERATED RESIDUALS
  
  Author: FANG, XIN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 26/05/2025
  Deposit END date: 06/06/2025
  Thesis director: PUIG CAYUELA, VICENÇ | BLESA IZQUIERDO, JOAQUIN
  Thesis abstract: In this thesis, we will propose methods to combine structural analysis methods and data-driven techniques, extending the applicability of conventional model-based diagnosis methods and proposing an extension to the prognosis. Some researchers have already explored similar ideas: for instance, there are some researchers have tried to use techniques like Grey-box recurrent neural networks to generate residuals in order to develop hybrid fault diagnosis methods. Another outstanding research is about combining state-space neural networks and model-decomposition methods for fault diagnosis. However, these studies focus more on the diagnosis part without considering the extension to the prognosis. Furthermore, most of the existing prognostic approaches are based on application-dependent methods that extract features of the measured variables.In this dissertation, we will apply the idea of extending residuals or analytical redundancy relations (ARRs) analysis from diagnosis part to prognosis part, including several enhancements as avoiding the need to have the mathematical model of the system and considering modelling uncertainty using interval methods. In this thesis, some data-driven structurally generated residuals will be used with the analysis purpose. Given agraphic (or textual) system description and the available input/output measurements, the structure of ARRs between some inputs and outputs can be determined with the aid of the Structural Analysis (SA) of the system. Then, using a machine learning data-driven approach applied to historical non-faulty data, analytical relations between inputs and outputs can be obtained. Thereby, instead of finding ARRs from a physical-mathematical model, ARRs are obtained by combining SA and data-driven approaches. For the linear system, functions calibrated by means of the System Identification Tool-box of MATLAB® will be used for identification. And to deal with general non-linear systems, the adaptive network fuzzy inference system (ANFIS) data-driven approach is used to implement the diagnosis system. Once the ANFIS model has been identified, it is reformulated in linear parameter varying (LPV) form. Then, a fault detection scheme based on a zonotopic LPV Kalman filter and pole placement method is developed. Finally, a fault isolation scheme based on an improved Demptser-Shafer reasoning approach is proposed.Residuals are used for fault detection purposes activating fault signals when residual values reach anomalous values. In addition, it is possible to predict future faults by means of the detection of anomalous residual deviations. Once an anomalous change in the residual trend has been detected, it is proceeded to estimate when this residual deviation will result in a fault detection and therefore which will be the Remaining Useful Life (RUL) time of the system. For this purpose, the future residual evolution is estimated by means of a regressor function. Nominal and interval parameters of regressor function are estimated with available residual data providing nominal and interval values of the RUL of the system.Along this dissertation, two study cases: a brushless direct current (BLDC) motor and a well-known case study based on a four-tanks system have been used to illustrate the effectiveness of the proposed methods and algorithms.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• MOHAMMADPOOR FASKHODI, MAHTAB: Unobtrusive Ultra-short-term HRV Analysis for the Identification of Physiological States in Healthy People
  
  Author: MOHAMMADPOOR FASKHODI, MAHTAB
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Normal
  Deposit date: 19/05/2025
  Deposit END date: 30/05/2025
  Thesis director: GARCIA GONZALEZ, MIQUEL ANGEL
  Thesis abstract: In recent years, heart rate variability (HRV) has become an essential tool for assessing the function of the autonomic nervous system (ANS), reflecting the balance between the sympathetic (SNS) and parasympathetic (PNS) systems. A high HRV indicates a healthy ANS and better adaptability to stress. It is measured non-invasively using electrocardiography (ECG) or photoplethysmography (PPG), providing information about cardiovascular health, stress responses, and physiological resilience. Factors such as exercise, metabolic processes, and recovery influence HRV, making it useful for characterizing human regulatory systems.HRV is also used in the sports field to optimize performance through personalized training. Analysis methods include time-domain, frequency-domain, and non-linear techniques. However, the growing demand for real-time assessments has driven the development of very short-term HRV analysis (less than 5 minutes), facilitated by wearable devices such as smartwatches and fitness trackers. These devices allow real-time health monitoring through on-demand self-assessments, improving quality of life.Wearable technology, such as smartwatches and health monitors, has grown significantly, offering real-time tracking of biosignals, physical activity, and sleep patterns. Nonetheless, challenges persist due to a lack of transparency in the methods used to calculate HRV in these devices. This thesis addresses these challenges by developing techniques for very short-term HRV assessments, focusing on monitoring health status and physiological changes in healthy individuals, including tracking sleep stages, arousal states, and postural changes.Accurate heartbeat detection is essential for reliable HRV calculations, which are critical for both clinical diagnostics and consumer health applications. This requires identifying QRS peaks in ECG signals or pulses in PPG signals and improving quality through preprocessing and feature extraction. This dissertation explores algorithms to optimize the accuracy of heartbeat detection, advancing HRV evaluation and cardiac monitoring in wearable devices.HRV analysis begins with heartbeat detection, using algorithms based on signal morphology and inter-beat interval features. Designing reliable beat detectors for ambulatory environments presents a challenge, as they must be non-invasive and effective in real-world scenarios. Therefore, one of the main objectives is to improve the accuracy and reliability of beat detection, thereby optimizing HRV evaluation and cardiac monitoring.This thesis addresses two main challenges: (1) reliable heartbeat detection in ambulatory environments using wearable sensors and (2) very short-term HRV measurements to identify physiological states in healthy individuals. Accurate detectors and analytical techniques are developed to improve the precision of beat detection and the identification of physiological states.In conclusion, the thesis proposes a theoretical framework for non-invasive methods of HRV estimation and monitoring physiological changes through ultra-short-term analysis. It details materials, methods, and novel techniques, emphasizing the relevance of these approaches to understanding autonomic nervous system function and cardiovascular health. This thesis aims to make a significant contribution to the field of mobile health (m-health), enabling reliable monitoring in everyday life.
  

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

• LOU, YAKE: Bimetallic catalysts for hydrogen production and purification
  
  Author: LOU, YAKE
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Change of supervisor
  Deposit date: 16/05/2025
  Deposit END date: 29/05/2025
  Thesis director: LLORCA PIQUE, JORDI | GUO, YUN | JIMÉNEZ DIVINS, NÚRIA
  Thesis abstract: In Chapter 3, CeO2-supported mono- and bi-metallic Co-Rh catalysts prepared by incipient wetness impregnation (IWI) and mechanochemical method (also called ball milling, BM) were used to investigate the DRM reaction. The Co and Rh of fresh catalysts were identified as 5-20 nm nanoparticles and small clusters. Monometallic Rh catalysts showed intimate Rh-CeO2 interaction. The BM method enhanced the catalysts' CO2 activation ability more effectively than the IWI method, resulting in less carbon deposition and graphitization. Overall, the Rh/CeO2-IWI exhibited the best DRM reaction performance among all catalysts due to the moderate interaction between Rh and CeO2, and Rh-Co/CeO2-BM prepared with 50 Hz exhibited a better DRM reaction performance than that of the bimetallic IWI catalyst due to the synergy effect between Co and Rh and CeO2.In Chapter 4, mono- and bi-metallic CoRh catalysts supported on MG70 prepared by IWI and BM methods were synthesized to investigate the DRM reaction. The Co and Rh of fresh MG70-supported bimetallic catalysts were identified as single atoms and small clusters. Besides, the Co and Rh were in intimate contact in the BM sample, which was beneficial to strengthen the interaction between Co and Rh. The stronger interaction between Co, Rh, and MG70 in the BM sample compared with that of the IWI sample helped stabilize smaller metal particle sizes after stability tests. Moreover, the use of bimetallic Co-Rh catalysts prepared by the BM method enhanced the redox properties of MG70-supported Co-Rh catalysts, which helped to decrease carbon graphitization. Overall, the Co+Rh/MG70-BM prepared with 50 Hz exhibited the best DRM reaction performance due to the excellent synergy effect between Co and Rh and the support MG70.In Chapter 5, we investigated the CO-PROX reaction activity of Pt/Al2O3 and a trace amount of Cu-modified Pt/Al2O3 prepared by the strong electrostatic adsorption method. The atomically dispersed Cu2+ was located on Pt nanoparticles, making Pt in a more electrondeficient state and maximizing the Pt-CuOx interface. The more electron-deficient state of Pt helped to weaken the CO adsorption, alleviating the CO poison effect. Besides, the Pt-CuOx interface played a role as an additional O2 activation site, enhancing the O2 activation ability. The CO-PROX reaction of Pt/Al2O3 and Pt-Cu/Al2O3 both followed the HCOO- intermediate route, and the introduction of Cu accelerated the decomposition of HCOO- intermediate. Overall, the addition of Cu enhanced the CO-PROX reaction activity of Pt/Al2O3 in the low-temperature and high-temperature range.In Chapter 6, Bi-modified Pt/Al2O3 catalysts were prepared by a two-step incipient wetness impregnation method to further widen the low-temperature operation window of the CO-PROX reaction. After introducing Bi, Pt nanoparticles tended to be located on Bi2O3 nanoparticles, creating a Pt-O-Bi interface. The redox ability of Pt-x Bi/Al2O3 gradually increased and the chemical state of Pt was gradually in a more electron-deficient state with the increase of Bi loading, therefore improving the O2 activation and decreasing the CO adsorption. Besides, the H2 activation ability was enhanced with increasing the Bi loading. The enhanced H2 activation ability facilitated forming HCOO- intermediates, thus strengthening the promotion effect of H2 at low temperatures. However, the enhanced H2 activation ability played a negative effect at high temperatures due to the enhanced H2 oxidation reaction. Overall, the Pt-0.5 Bi/Al2O3 exhibited the best CO-PROX reaction performance.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• KHARE, PRASUNIKA: Simulation and Modeling of C+L+S Multiband Optical Transmission for the OCATA Time Domain Digital Twin
  
  Author: KHARE, PRASUNIKA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 19/05/2025
  Deposit END date: 30/05/2025
  Thesis director: VELASCO ESTEBAN, LUIS DOMINGO | SIMOES DA COSTA, NELSON MANUEL
  Thesis abstract: This thesis focuses on implementing more robust control and management strategies such as those based on machine learning to enhance intelligence and drive towards autonomous operation is crucial for the future of optical communications. In this regard, this thesis aims at three specific objectives: The first objective is to develop a multiband optical transmission simulator. It can be challenging to conduct simulations on a fully loaded MB system with hundreds of channels. In addition, in MB optical transmission, the Inter-channel Stimulated Raman Scattering (ISRS) becomes a major effect, which adds more complexity. In view of that, the Fourth Order Runge-Kutta in Interaction Picture (RK4IP) method is evaluated as an alternative to reduce time complexity, which is complemented with an adaptive step size algorithm to further reduce the computation time. We show that RK4IP provides an accuracy comparable to that of SSFM with reduced computation time, which enables its application for MB optical transmission simulation. The second objective focuses on developing models for C+L+S Multiband Optical Transmission System In this objective of this thesis, we focus on modelling MB optical transmission to provided fast and accurate QoT estimation and propose Machine Learning (ML) approaches based on neural networks, which can be easily integrated into an Optical Layer Digital Twin (DT) solution. We start by considering approaches that can be used for accurate signal propagation modelling. Even though solutions like the Splitstep Fourier method (SSFM) for solving the non-linear Schrödinger equation (NLSE) cannot be used for QoT estimation due to their very high time complexity. Therefore, ML modelling approaches are considered to be integrated in the OCATA DT, where models predict optical signal propagation in the time domain. Being able to predict the optical signal in the time domain, as it will be received after propagation, opens opportunities for automating network operation, including connection provisioning and failure management. The third objective of this thesis is to develop a semi-analytical model for measuring the gain profile of amplifiers in both fully loaded and partially loaded conditions of the metro- access network. The power imbalance is one of the issues associated with transitioning to a metro-access merged network. Additionally, maintaining these two separate networks (metro and access) is both complicated and costly. The node that interconnects the two networks must perform O-E-O conversions on the data traversing between them. The current network system uses ROADM in nodes, which is all optical and requires no O-E-O conversion. Therefore, this goal primarily focuses on characterizing the parameters of EDFA present in reconfigurable optical add-drop multiplexers (ROADMs) with the aim of achieving a balance between flexibility, complexity, and cost. These nodes must be thoroughly characterized regarding optical losses, power consumption, and other metrics. Once evaluated, the performance of these nodes can be modelled to enable the SDN controller to incorporate them into the network.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• GIRONA BADIA, JAUME: Grid-forming strategies for Renewable Energy Sources
  
  Author: GIRONA BADIA, JAUME
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 29/05/2025
  Deposit END date: 12/06/2025
  Thesis director: GOMIS BELLMUNT, ORIOL | PRIETO ARAUJO, EDUARDO
  Thesis abstract: Modern power systems are increasingly integrating a larger share of renewable energy resources to mitigate climate change. These renewable resources are gradually replacing conventional power plants, which employ synchronous machines for power generation. Synchronous generators behave as voltage sources governed by their electromechanical dynamics. Moreover, they possess intrinsic inertia, which stabilizes the network frequency. In contrast, renewable energy sources primarily use power electronics converters to connect to the electrical grid. The behavior of power electronics is dominated by their implemented control strategies, as their physical dynamics are substantially faster.Currently, the most widely used control approach for converters is grid‐following control. This strategy drives converters to behave as current sources. However, the AC network requires voltage sources for operation and stability. Thus, the integration of grid-following converters displaces voltage-source generators with current-source devices, potentially affecting system stability and dynamics.To improve overall network stability, grid‐forming control was introduced. Grid-forming converters operate as voltage sources and may incorporate virtual inertia. Virtual inertia is emulated because power electronics lack rotating mass. Moreover, by behaving as voltage sources, grid-forming converters contribute to system stability.The present thesis provides a fundamental assessment of both grid‐following and grid‐forming control strategies. First, the internal controls of grid-following converters are analyzed, and their key components are defined. Then, different implementations of the internal control strategies of grid-forming converters (synchronization control and voltage control) are explored, and the most suitable configuration is assessed in different chapters. Specifically, a tuning methodology for the voltage control is presented, which accounts for the power electronics' inherent limitations. This methodology is employed to identify the optimal control structure based on the specific configuration of the implemented AC connection filter. Later, the industry-class synchronization controls are examined, focusing on their behavior when employing a frequency estimator. Afterwards, the limitations of renewable resources when operating the power electronics in grid‐forming mode are investigated. To allow renewable energy sources to operate in grid-forming mode despite their limitations, this thesis introduces a Resource‐Aware Grid‐Forming (RAGFM) control. RAGFM strategy aims to maximize the frequency response, considering the resource limitations. The proposed control is validated through various analytical studies and simulations. RAGFM control is also simulated for a single-stage photovoltaic power plant. This topology exhibits a non-linear relationship between the DC-link voltage and power generation, which introduces significant control challenges. Thus, RAGFM operation is validated under this specific operating condition. Finally, the proposed control structure is further validated through experimental results.This work contributes to enhancing the integration of renewable resources through grid-forming control, supporting the transition to a more sustainable energy future.
  
• HERNÁNDEZ MATHEUS, ALEJANDRO: Machine Learning Methods for Smart Grid Operation with LECs
  
  Author: HERNÁNDEZ MATHEUS, ALEJANDRO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 27/05/2025
  Deposit END date: 10/06/2025
  Thesis director: ARAGÜÉS PEÑALBA, MÒNICA | BULLICH MASSAGUÉ, EDUARD
  Thesis abstract: Recent technological developments in renewable energy have enabled a shift in the energy generation capacity closer to the consumption. This evolution has led to a decentralisation process that is required for the coordination of generation and demand in electric power systems. Consequently, the energy sector is transitioning towards a more decentralised control due to these prosumers and active consumers, who cooperate for the management and control of storage systems and flexible demand. A resulting framework attempting to solve the challenges associated with this decentralisation is that of local energy communities (LECs) representing local, self-organising entities that operate autonomously or semi-autonomously within an electricity grid. At the same time, digitalisation has rendered machine learning a key tool for improving processes in several sectors, as in the case of electrical power systems. This thesis starts by analysing LECs and their integration to smart distribution grids. Ultimately, developing a definition for these entities. Then, an analysis on machine learning is assessed to generate an understanding of its capabilities, aiming to discover a relationship between the operation of LECs and existing machine learning algorithms. Finally, with this knowledge, a framework is developed to forecast congestions lines with machine learning in smart distribution with renewable and local energy communities presence, showing the capabilities machine learning can have in complex power systems.
  

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

• MARTÍNEZ VIOL, VÍCTOR: Towards Generalisable Fault Detection in Smart Buildings: Hybrid Modelling, Calibration, and Transfer Learning Strategies
  
  Author: MARTÍNEZ VIOL, VÍCTOR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRONIC ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Article-based thesis
  Deposit date: 19/05/2025
  Deposit END date: 30/05/2025
  Thesis director: ROMERAL MARTINEZ, JOSE LUIS | DELGADO PRIETO, MIGUEL
  Thesis abstract: The building sector represents a significant portion of global energy consumption, accounting for over one-third of the total energy used worldwide. Within this sector, Heating, Ventilation, and Air Conditioning (HVAC) systems are the most substantial energy consumers, responsible for 40-60% of a building's energy demand. Consequently, enhancing the energy efficiency of HVAC systems is crucial for reducing global energy demand and mitigating associated environmental impacts. International initiatives, such as the revised Energy Performance of Buildings Directive (EPDB), underscore the importance of digitalisation and advanced monitoring techniques as key enablers for improving building energy performance.This thesis addresses the need for improved supervision and monitoring of building energy assets, concentrating specifically on the development and application of Fault Detection and Diagnosis (FDD) methodologies for HVAC systems. The main objective is to advance the state-of-the-art by systematically exploring a range of data-driven and model-based strategies. The research first evaluated the performance of an Adaptive Neuro-Fuzzy Inference System (ANFIS) when modelling energy consumption, confirming its utility for detecting deviations from predicted HVAC behaviour. Building on this, the research advanced to classification-based FDD, addressing the need for robustness against previously unseen fault types. A two-stage approach using One-Class Support Vector Machines (OC-SVM) for novelty detection and multi-class Support Vector Machine (SVM) for diagnosis, enhanced by dimensionality reduction techniques, demonstrated improved robustness and reliability compared to standard classification methods.The inherent challenge of data scarcity in practical FDD applications led to the exploration of transfer learning. Recognising the significant operational dissimilarities between different HVAC installations, a tailored semi-supervised transfer learning methodology was developed, introducing a novel dissimilarity filter based on source model confidence. This approach significantly outperformed standard transfer learning techniques when applied to dissimilar Air Handling Units (AHU) datasets and highlighted the necessity of addressing domain shift in HVAC applications.To further mitigate data scarcity, the focus turned to hybrid modelling, aiming to create accurate digital twins of HVAC systems useful for developing advanced FDD strategies. An automated calibration methodology using Bayesian optimisation was successfully applied to a complex, coupled AHU-building model in Modelica. This yielded a high-fidelity model from limited historical data, demonstrating a scalable approach to developing accurate digital representations without extensive system knowledge. Finally, this hybrid model framework was extended for synthetic fault data generation. This provides a valuable tool for generating comprehensive datasets needed to train and test advanced FDD algorithms, especially useful for new or replicated buildings.In summary, this thesis presents a comprehensive investigation into enhancing HVAC system efficiency through advanced monitoring and FDD. It validates the effectiveness of diverse strategies, ranging from foundational regression and classification techniques enhanced with novelty detection, to sophisticated solutions like tailored transfer learning and hybrid model-based synthetic data generation. The research highlights the critical importance of addressing data scarcity and domain dissimilarity, offering practical methodologies to overcome these prevalent challenges. The findings contribute significantly to the development of more robust, reliable, and widely applicable FDD systems, paving the way for substantial energy savings and improved sustainability in the building sector.
  

DOCTORAL DEGREE IN ENGINEERING, SCIENCES AND TECHNOLOGY EDUCATION

• GABRIEL CERNA, PEDRO VICTOR: Sistema Adaptativo de Aprendizaje Utilizando Motores de Machine Learning Aplicado a la Enseñanza de la Ingeniería Gráfica
  
  Author: GABRIEL CERNA, PEDRO VICTOR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENGINEERING, SCIENCES AND TECHNOLOGY EDUCATION
  Department: Institute of Education Sciences (ICE)
  Mode: Normal
  Deposit date: 29/05/2025
  Deposit END date: 12/06/2025
  Thesis director: PEREZ POCH, ANTONI | TORNER RIBE, JORDI
  Thesis abstract: One of the greatest challenges in education has always been the diversity of individual characteristics among students, contrasted with an educational system that seeks to standardize learning to cater to the majority. This approach often leads to frustration: high-ability students feel constrained by a pace that doesn’t match their potential, while others struggle to keep up with the accelerated progression of the curriculum.Historically, ideal models such as the Confucian system of “one student, one teacher” have been highly regarded. However, implementing such personalized approaches in today’s society is nearly unfeasible. Furthermore, the rapid evolution of technology and global changes, such as the COVID-19 pandemic, have underscored the urgent need to adapt education to new realities and diverse needs.This work presents a web-based content recommendation system designed to address the specific needs of each learner. It features a gamified graphical interface to make learning more engaging and offers a variety of activities, including puzzles, quizzes, and reading comprehension exercises, all designed for sessions lasting no more than 17 minutes per day.After each activity, the system prescribes content for the next session based on an initial assessment and a machine learning engine, specifically a k-nearest neighbors (KNN) algorithm. This engine compares the student’s performance with that of others who share similar characteristics, ensuring personalized recommendations.Additionally, a heuristic engine identifies difficulties in related sub-topics, adjusting recommendations not only for the core subject but also for connected areas. This holistic approach ensures a more comprehensive and adaptive learning experience.The system has been tested in three experiments, evolving into a fully functional, gamified web platform that adapts the complexity of questions in real time. Currently, it is being implemented in primary education, with over 20,000 users across Spain and Latin America. Its success demonstrates its potential for application across various educational levels, not limited to university settings.
  

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

• ARIAS GARCIA, FRANCISCO ITURIEL: THERMOFORMING PROCESS ANALYSIS FOR IN-MOLD ELECTRONICS DEVICES
  
  Author: ARIAS GARCIA, FRANCISCO ITURIEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Normal
  Deposit date: 20/05/2025
  Deposit END date: 02/06/2025
  Thesis director: FONTDECABA BAIG, ENRIC
  Thesis abstract: In-Mold Electronic technology enables the creation of three-dimensional shaped electronic surfaces by combining printed electronics with In-Mold Decoration. This innovative approach enables the integration of electronic circuits into a wide range of complex and diverse applications, going from automotive interiors to consumer electronics. The manufacturing process for IME devices demands that all materials involved, including adhesives, endure the rigorous transformation conditions to ensure functionality and reliability of the final device. Adhesives, while critical for securing surface-mounted components and maintaining circuit integrity, possess properties that can significantly influence film deformation during the thermoforming process. These deformations can have a great impact on the overall performance and durability of the device. This research is dedicated to thoroughly examining the effects of the structural adhesive on film deformation during the thermoforming process, as well as the subsequent impact on device functionality. The study meticulously investigates how varying quantities and disposition placements of structural adhesives affect the film’s stretching behaviour during both thermoforming process and injection molding, comparing printed and hybridized samples. The research findings reveal that hybridized samples, those with structural adhesive, exhibit deformation patterns distinct from printed samples. Specifically, areas around the adhesive show reduced stretching, while regions farther from the adhesive compensate with increased stretching. This compensation often leads to overstretching in certain areas, which, in some cases, results in circuit discontinuities and compromised electrical performance. Moreover, the variation in stretching not only affects the circuit integrity but also alters the final positioning of electronic components. This misalignment can cause components to shift from their intended locations, potentially leading to device malfunctions or failures. To address these challenges, the study recommends adjusting the amount and placement of structural adhesive based on localized deformation patterns. By tailoring the adhesive application, unnecessary stretching can be minimized, ensuring both the mechanical and electrical integrity of the device. Additionally, further analysis during the injection molding process highlighted that careful management of adhesive quantity effectively secures all components in their designated positions without compromising functionality. The insights gained from this research are critical for the design and manufacturing of IME devices. They provide guidelines for optimizing adhesive placement and quantity, ultimately enhancing the reliability, performance, and yield of functional devices in high-volume production.
  

DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT

• RIDOLFO, SHARON: Ultrafine particles characterization from different transport sources
  
  Author: RIDOLFO, SHARON
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT
  Department: Department of Mining, Industrial and ICT Engineering (EMIT)
  Mode: Article-based thesis
  Deposit date: 29/05/2025
  Deposit END date: 12/06/2025
  Thesis director: AMATO, FULVIO | QUEROL CARCELLER, XAVIER
  Thesis abstract: Ultrafine particles (UFP), defined as airborne particulates with an aerodynamic diameter smaller than 100 nm, are of particular concern due to their ability to penetrate deep into the respiratory system and even reach the brain directly via the olfactory bulb, with potential to cause a wide range of adverse health effects. In response to the growing evidence of health risks associated with UFP, the World Health Organization (WHO) has recently issued ‘Good practice statements’ emphasizing the need of integrating UFP in terms of particle number concentration (PNC) into existing air quality monitoring systems (WHO, 2021). In line with these recommendations, the new European Air Quality Directive (AQD, 2024/2881/EC) requires the monitoring of PNC and particle number size distribution (PNSD) in urban, and of PNC in rural supersites and pollution hotspots, including traffic, harbors, airports, and industry, among others (EU, 2024). In this context, the present PhD thesis investigates the concentrations, size (and some chemicals) patterns and source contributions of UFP in transport environments, including a review of existing literature on PNC-PNSD, as well as experimental studies conducted at an airport, harbor, road traffic and urban background (UB) in Barcelona (NE Spain) and a subway in Valencia (E Spain). The review aimed to assess the instruments used, analyze results, and identify knowledge gaps in PNC-PNSD across transport environments. It highlighted under-studied areas needing further investigation and provided key insights for the field campaigns. The findings identified road traffic as the main contributor to PNC in urban areas, with commuting modes influenced by proximity to traffic and meteorological conditions. It also emphasized the need for harmonizing measurement protocols due to significant variations in methods, particularly in lower (finer) particle size detection limits.The experimental studies revealed substantial variability in PNC and PNSD, driven by differences in emission sources and site-specific conditions. The airport recorded the highest PNC, dominated by aircraft activity, particularly taxiing and takeoff, while the subway exhibited the lowest. Nucleation mode particles (<25 nm) were especially elevated at the airport and road traffic site, indicating the influence of fresh emissions and secondary formation from gaseous precursors. In contrast, the harbor showed a dominant Aitken mode (25-100 nm) linked to ship emissions. Diurnal trends further reflected localized source activity, with distinct peaks observed in line with transport operations, except in the subway, where PNC remained relatively stable. PNSD was unimodal below 20 nm at the airport and traffic sites, unimodal around 20-30 nm at the harbor, and flatter at the subway, suggesting a lack of significant local sources of UFP. Notably, no second mode (40-90 nm), commonly associated to diesel emissions, was observed at the road traffic site, indicating a possible decline in larger diesel-related particles due to the implementation of EURO 5 and 6/V and VI standards and the Barcelona Low Emission Zone (LEZ). Source apportionment analyses confirmed aviation and shipping as dominant contributors to UFP at the airport and harbor, respectively, while chemical characterization revealed specific tracers such as aluminum (airport), chromium and barium (traffic), vanadium and nickel (harbor), and copper (subway), among others.
  

DOCTORAL DEGREE IN PHOTONICS

• AGAZZI, COSTANZA: Bridging Fast Volumetric Imaging and Mechanical Stimulation: A Platform for Studying Mechanosensitive Neurons Functionality Onset in C. elegans Embryos
  
  Author: AGAZZI, COSTANZA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 20/05/2025
  Deposit END date: 02/06/2025
  Thesis director: KRIEG, MICHAEL
  Thesis abstract: In Caenorhabditis elegans, the embryo develops within the protective confines of an eggshell, shielded from direct interactions with the outside world. In this isolated environment, neuronal mechanosensory circuits, responsible for translating physical forces into biochemical signals, are among the first to emerge during development. While their primary function is to mediate interactions with the external mechanical world, they also play a significant role in broader physiological and behavioral processes, including synaptic plasticity and social bonding. C. elegans neurons responsible for the sense of touch arise very early during embryogenesis, long before any physical interaction, raising the question: when does the nervous system first awaken to the mechanical world it has yet to experience?Unraveling the onsets of mechanosensation has critical implications for neuroscience and human health, as its dysregulation is linked to various diseases and neurodevelopmental disorders. For example, studies on mouse models of autism spectrum disorder (ASD) have demonstrated that the timing of mechanosensory disruptions during embryogenesis plays a pivotal role in determining the severity of the condition. Despite its importance, our understanding of when mechanosensitivity first emerges remains limited, also due to the practical and ethical challenges of studying the application of mechanical forces to developing neural systems.To address these challenges, the goal of this project was to develop a multifunctional experimental platform that combines precision mechanical stimulation with live volumetric imaging, enabling the investigation of induced calcium signals in the developing neural system of C. elegans embryos. Central to this platform is a custom open-top light sheet fluorescence microscope, optimized for fast, 3D imaging of calcium dynamics. The imaging unit is integrated with a fiber-optic-based nanoindenter, which provides precise force application and quantitative characterization of the mechanical properties of the sample. This setup allows for controlled mechanical stimulation while capturing real-time neuronal activity, facilitating the analysis of how and when external forces influence mechanosensory circuits during critical developmental stages.Using this platform, we conducted proof-of-concept experiments to explore mechanosensory responses in C. elegans embryos. These studies validated the system's ability to trigger and record precise neuronal activity, demonstrating its experimental effectiveness. Preliminary findings suggest that mechanosensory functionality might begin to emerge during the late stages of embryogenesis of C. elegans embryos, offering a glimpse into the elusive timing of sensory circuits development. Overall, this work sets the stage for future investigations into how these circuits awaken and their vital role in early neural development.
  
• LO GERFO MORGANTI, GIULIA: Excitons in Motion: Linking Structure and Transport in Energy Materials
  
  Author: LO GERFO MORGANTI, GIULIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 26/05/2025
  Deposit END date: 06/06/2025
  Thesis director: VAN HULST, NIEK
  Thesis abstract: The growing global energy demand, coupled with the need to reduce CO2 emissions, highlights the urgency of developing sustainable energy solutions. Despite its vast potential, solar energy remains underutilized due to technological challenges. Most solar technologies— including photovoltaics (PV), concentrated solar power, and artificial photosynthesis— depend on three core processes: light absorption, energy conversion, and energy transport. Understanding how light is converted and transmitted— primarily via exciton diffusion— in materials ranging from semiconductors to biomimetic and biological systems is essential for improving the performance of both optoelectronic devices and natural photosynthesis.This thesis examines how dimensionality, defects, and molecular geometry affect exciton diffusion, aiming to uncover structure-function relationships that govern energy transport in energy-related materials. Using advanced spatiotemporal microscopy — including Time-Correlated Single-Photon Counting Microscopy, Transient Reflection Microscopy, and a novel technique developed by my group, Structured Excitation Energy Transfer (StrEET) — this research investigates exciton diffusion in organic semiconductors, 2D perovskites, transition metal dichalcogenides (TMDCs), and bio-inspired systems.Key findings show that dimensionality critically influences exciton mobility. In Y6 organic films — a leading non-fullerene acceptor for organic photovoltaics — I performed the first direct measurements of exciton diffusion, revealing that confinement enhances mobility. Combined with morphological tuning via additives, diffusion coefficients increase by over 50%. In 2D perovskites, increasing thickness boosts both diffusion and anisotropy, yielding diffusion lengths well beyond those of conventional organic systems.TMDC studies reveal that, beyond dimensionality, defects and substrate interactions significantly affect exciton mobility. In suspended monolayers, multiple transport regimes — rapid, negative, and slow diffusion — are observed, each constrained by trap states and sensitive to structural and environmental changes.Lastly, this work explores how molecular packing and geometry influence exciton transport in bio-inspired systems like porphyrin films and bacterial LH2 networks. Using the novel highly sensitive StrEET technique, I conducted the first direct measurements of exciton transport in photosynthetic systems. Denser molecular packing enhances diffusion while reducing exciton lifetimes; the optimal diffusion length, comparable to that of top organic semiconductors, arises from a balance between these competing effects, offering insights into the design of artificial light-harvesting systems.Overall, this research demonstrates that excitonic transport can be engineered by tuning material properties such as dimensionality, defect density, and molecular organization. These findings provide guiding principles for developing more efficient optoelectronic and bio-inspired energy technologies, supporting the transition to sustainable energy solutions.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• EL MADAFRI BENNIS, ISMAIL: Confounding Factors-Aware Hierarchical Deep Learning for Sustainable Edge Wildfire Detection
  
  Author: EL MADAFRI BENNIS, ISMAIL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SUSTAINABILITY
  Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
  Mode: Article-based thesis
  Deposit date: 20/05/2025
  Deposit END date: 02/06/2025
  Thesis director: PEÑA CARRERA, MARTA | OLMEDO TORRE, NOELIA
  Thesis abstract: Wildfires present a significant threat to ecosystems, property, and human life, underscoring the need for accurate, adaptable, and efficient detection systems. This thesis introduces a novel approach to wildfire detection that addresses key limitations in accuracy, adaptability, and sustainability, emphasizing real-world deployment and resource-conscious design. Through three interconnected studies, the research develops a structured, confounding factors-aware framework that progresses from dataset creation to efficient, real-time deployment solutions.The first study establishes a confounding factor-aware wildfire dataset and a multi-task learning framework to address false positives caused by challenging elements, such as clouds, fog, and reflections. By training models on both fire classification and confounding element identification, this approach significantly reduces false alarms, enhancing model precision in complex detection scenarios. The second study advances this framework by incorporating a hierarchical domain-adaptive learning approach that integrates forest-specific and non-forest datasets. This dual-dataset strategy, with shared and specialized layers, enhances the model’s ability to generalize across diverse environmental conditions, providing a more adaptable solution for varied forest contexts.Building on these foundations, the third study introduces knowledge distillation to transfer insights from a complex, hierarchically trained model to a lightweight model optimized for edge devices, such as drones. This approach maintains high detection accuracy while minimizing computational demands, supporting sustainable deployment. A novel metric, the Confounding Element Specificity (CES), is also introduced to evaluate the model’s ability to handle confounding elements in real-world settings, contributing to efficient resource deployment and accurate monitoring.Together, these studies propose a structured, scalable framework for wildfire detection that combines technical rigor with practical, sustainability-focused applications. The findings contribute adaptable, high-accuracy models intended for real-world implementation and offer a foundation for further research in sustainable, AI-driven environmental monitoring and wildfire management.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• GHAFFARI POUR JAHROMI, NEGIN: The geometry of vision: A comparative study of Persian architecture and miniature painting as a unified system (Ilkhanid and Timurid periods)
  
  Author: GHAFFARI POUR JAHROMI, NEGIN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE
  Department: Department of History and Theory of Architecture and Communication Techniques (THATC)
  Mode: Normal
  Deposit date: 26/05/2025
  Deposit END date: 06/06/2025
  Thesis director: AZARA NICOLAS, PEDRO
  Thesis abstract: This doctoral thesis explores the shared geometric foundations of Persian architecture and miniature painting between 1256 and 1550, spanning the Ilkhanid, Timurid, and early Safavid periods. It argues that both art forms are governed by a unified visual and symbolic system rooted in Persian cosmology and Islamic intellectual traditions.Combining historical research, visual analysis, and geometric reconstruction using tools such as AutoCAD, Illustrator, and Rhino, the study examines architectural structures (domes, iwans, courtyards) and miniature compositions side by side. Sources include architectural plans, treatises by mathematicians like Buzjani, Al-Biruni, and Al-Kashi, and illustrated manuscripts preserved in collections such as the Bibliothèque nationale de France.The thesis demonstrates that both architecture and miniature painting utilize similar spatial strategies—layered compositions, symbolic depth, and geometric order—eschewing linear perspective to create immersive, contemplative environments. It identifies recurring elements such as ornamental geometry, garden motifs, and architectural symbols across both media.Comparative case studies align miniature representations with real architectural sites, revealing formal and conceptual correspondences. These findings suggest that Persian visual culture operated as a coherent system where geometry functioned as both an aesthetic principle and a reflection of divine harmony.By bridging artistic and architectural traditions, the thesis contributes a new interdisciplinary model to Islamic art history and highlights the cultural continuity between intellectual, visual, and spatial practices in Persian civilization. The Geometry of Vision offers a new lens through which to understand how Persian visual culture articulates a unified geometry of space, symbol, and spirit.