Theses authorised for defence

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

BAGHERZADE GHAZVINI, MINA: A Data-driven Intelligent Decision Support Framework for Process Operation Management. An Application to Gas Turbine Process.
Author: BAGHERZADE GHAZVINI, MINA
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: 25/07/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: SANCHEZ MARRE, MIQUEL | ANGULO BAHON, CECILIO
Thesis abstract: This thesis presents a data-driven framework for enhancing the management and maintenance of industrial processes, exemplified through a case study involving gas turbines. The research focuses on several key areas: preprocessing operational data, identifying operational modes, analysing transitions between these modes, and detecting patterns for predictive maintenance. The research proposal begins with detailed data preprocessing to ensure the quality and usability of data. It then introduces methods for automatically recognising distinct operational modes using an ensemble of clustering techniques The research also explores the modelling of transitions between these operational states, capturing the dynamic nature of industrial processes. Furthermore, the Cluster-based Matrix Profile method is proposed to detect significant operational patterns that indicate potential issues or efficiencies, essential for developing predictive maintenance strategies. Overall, the framework developed in this thesis offers a systematic approach to improve decisionmaking, reliability, and efficiency in managing industrial processes. Although initially applied to gas turbines, this framework holds the potential for broader applications across various industrial systems.

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

ESCUDERO RODRIGO, DIEGO: Dealing with the Anchoring Problem in Robotic Kitting using Behavior Trees
Author: ESCUDERO RODRIGO, DIEGO
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: 01/09/2025
Reading date: 15/10/2025
Reading time: 11:30
Reading place: Sala Polivalent de l'INTE, Campus Diagonal Sud, Edifici PC (Pavelló C)., ETSEIB, Av. Diagonal, 647 08028 Barcelona
Thesis director: ARANDA LÓPEZ, JUAN | ALQUEZAR MANCHO, RENATO
Thesis abstract: Industrial flexible manufacturing is a production method designed to adapt quickly to changes in product variety and volume. This is enabled by robots and perception systems capable of managing high-mix and high-volume production, ensuring quality and being easy to program. Flexible machines receive different types of parts using in-feed systems, and which types are used depends on the product that should be built. An important step is to provide to these machines all the parts required to be used during the production; this step is named as robotic kitting. Robotic kitting means the creation of parts assortment to be used later and these parts are selected from one or more containers in which there are different types of them randomly distributed. The procedure involves gathering the different parts to be moved and placed in a preparation area. In this area, the different parts are reassembled into a kit.The aim of this research was to develop an anchoring framework for Robotic `Intelligent' Kitting, a generalization of robotic kitting that incorporates symbols and their manipulation. Since symbols are required to solve this problem, the anchoring problem must be considered. This anchoring framework should enable generalist robots to anchor objects and actions required for a new task, through human-robot interaction and learning mechanisms. Our framework is based on automatically generated code and a human supervised approach, in which robot learning and human-robot interaction are used to anchor percepts and instructions to symbols during commissioning or reconfiguration phase. Genetic programming is a known technique for code generation that allows learning programs from scratch. So, it was combined with behavior trees for anchoring symbolic actions (e.g., find-part) to robot instructions at sensori-motor level (e.g., move-arm-to).An algorithm that combines genetic programming with conditional behavior trees (GP-CBT) is proposed. The core of the algorithm is composed by specific genetic operators, an evaluation criterion and the fallback swapper. As making easy the interaction with the operator is essential for our framework, this algorithm has been extended in order to generate action nodes automatically, allow the user to add task requirements, and update prior knowledge from previously learned tasks.

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

LÓPEZ GÓMEZ, PATRICIA VICTORIA: Multifunctional hydrogels for advanced regenerative therapies
Author: LÓPEZ GÓMEZ, PATRICIA VICTORIA
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 Materials Science and Engineering (CEM)
Mode: Normal
Deposit date: 19/09/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: MAS MORUNO, CARLOS | MEHWISH, NABILA
Thesis abstract: Implant-associated infections remain one of the most critical challenges in the biomedical field. Despite advances in aseptic surgical techniques and antibiotic therapies, the persistence of bacterial colonization on implant surfaces -often involving biofilm formation- continues to compromise clinical outcomes. Conventional treatment strategies, including the systemic administration of antibiotics, local drug delivery systems, and surgical debridement, often fail to effectively eradicate biofilms, particularly those formed by pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. Concurrently, the field of tissue engineering demands implantable materials that not only support tissue regeneration but also provide active defense against infection. However, most currently available materials fall short of achieving this dual function. In contaminated or high-risk environments, this shortcoming becomes especially critical. To address these limitations, there has been a growing focus on developing next-generation biomaterials that are no longer passive scaffolds but bioactive and dynamic systems capable of interacting with the biological milieu in real time. In this context, biofunctionalization has emerged as a powerful strategy to enhance both regenerative and antimicrobial properties of biomaterials. Among the different bioactive tools available, peptides have shown considerable promise due to their tunable chemistry, modular architecture, and high specificity. This thesis focuses on two peptide motifs with complementary bioactivities: RGD, which promotes cell adhesion, and hLf1-11, a broad-spectrum antimicrobial peptide derived from human lactoferrin. Together, these peptides represent a rational platform for engineering multifunctional materials that address the dual challenge of infection control and tissue integration. Specifically, the present work investigates the integration of RGD and hLf1-11 peptides into three hydrogel-based material systems, each representing a distinct level of biofunctionality and design complexity: • Chapter I examines the modification of alginate, a naturally derived but bioinert polymer, with RGD-hLf1-11 to evaluate stem cell behavior and antimicrobial activity. • Chapter II explores a fully synthetic PEG-based hydrogel system functionalised with these peptides and incorporating a protease-sensitive crosslinker to enable bioactivity and controlled degradation. • Chapter III focuses on self-assembling peptide hydrogels, where both structural assembly and biological function are encoded at the molecular level, enabling the formation of intrinsically bioactive materials without further modification. Collectively, these platforms offer a comparative and progressive approach toward the design of multifunctional hydrogels. This work not only demonstrates the feasibility of dual viii biofunctionalization but also highlights the critical roles of molecular architecture, crosslinking strategy, and material origin in shaping biological responses. Ultimately, this thesis contributes to the development of smart biomaterials that are both cell-instructive and antibacterial, aligning with the growing clinical need for adaptable, multifunctional solutions in regenerative medicine and infection-prone environments.

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

ABENZA MARTÍNEZ, MISAEL: Exploring multi-barrier approaches for impacted urban groundwater reclamation in Sant Adrià de Besòs basin
Author: ABENZA MARTÍNEZ, MISAEL
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: 19/09/2025
Reading date: 24/10/2025
Reading time: 10:30
Reading place: Sala Audiovisuals (Enginyeria Química)ETSEIB - UPCCampus Diagonal Sud, Edifici PI (Pavelló I). Av. Diagonal, 647 08028 Barcelona
Thesis director: GIBERT AGULLO, ORIOL | VÁZQUEZ SUÑÉ, ENRIC
Thesis abstract: This thesis aims to identify and assess the treatment of water sourced from the Sant Adrià del Besòs aquifer using various types of technologies, in accordance with the compliance of the regulations regarding its composition and potential uses, along with the costs required for its operation.Moreover, it enables the identification of the removal efficiency of each contaminant at each stage of the pilot plant process.Finally, the results of the dissolved ions obtained from treatment through nanofiltration were modelled using the SEDFM model.

DOCTORAL DEGREE IN CIVIL ENGINEERING

ALARCÓN FERNÁNDEZ, DANIEL: A model for the aero‐hydro‐servo‐elastic analysis of floating offshore wind turbines based on a co‐rotational formulation
Author: ALARCÓN FERNÁNDEZ, DANIEL
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: Normal
Deposit date: 12/09/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: MOLINS BORRELL, CLIMENT
Thesis abstract: Nowadays, there is an increasing, despite reduced, number of models capable of performing fully coupled aerohydro‐servo‐elastic simulations in the time domain for the analysis of floating offshore wind turbines (FOWTs).Historically, in its beginnings, these models widely adopted rigid multibody systems (RMS) formulations todescribe the global dynamics response of the complete system. However, their incapability to determine theinternal stress‐strain state of hyperstatic components, in conjunction with the irruption of platform conceptswith higher structural complexity, promoted the development of a second generation of models adoptingflexible multibody systems (FMS) formulations. Whose main strategy, because they were fundamentally anevolution of the firsts, relied on describing the dynamic response of the flexible components by superimposinga first‐order deformational analysis over their spatial rigid‐body configuration. Nevertheless, because theindustry has quickly trended in the last decades toward bigger and more powerful wind turbines, somecomponents of the system have suffered from increasing slenderness and flexibility. As is the case of the rotorblades or the tower, which are starting to require the adoption of non‐linear analyses to assess their dynamicresponse and their internal stress state properly.In this context, there is an incipient but reduced number of models capable of performing fully coupled nonlineardynamic structural analyses of FOWTs. However, they are mostly strictly restricted to one‐dimensionalbeam type elements, forcing the adoption of approximated local load mapping procedures during the detailedengineering design phase. For that reason, a new advanced fully coupled model based on the Finite ElementsMethod (FEM) is proposed in the present thesis. Its main advantages lie in the ability to perform non‐lineardynamic analyses in time domain of complex structural models composed of multiple finite elements ofdifferent nature. This feature allows a more precise definition of the real structural behaviour and, therefore,leads to more detailed internal stress‐strain state analyses without the need of adopting additional techniques.The underlying balance equations of the model have been derived based on the Element Independent Corotational(EICR) method, whose foundations were laid in the work developed by C. C. Rankin and F. A. Broganin the 1980s and later readapted and improved by C.A. Felippa and B. Haugen in the 2000s. However, becauseit was initially mainly focused on non‐linear quasi‐static structural analysis, a detailed and consistent extensionto non‐linear dynamics based on continuum mechanics theory has been developed in the framework of thepresent thesis research.To evaluate the performance of the proposed structural model, it has been verified based on a set ofcomputational mechanics benchmarks available in the literature on non‐linear dynamics of flexible bodies.While the fully coupled aero‐hydro‐servo‐elastic model for the analysis of FOWTs has been validated based onthe experimental data provided in the framework of the Offshore Code Comparison, Collaboration, Continued,with Correlation and unCertainty (OC6) international project promoted by the International Energy Agency(IEA).

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

SERRACANTA PUJOL, BERTA: Accelerating the Cloud: An Application-Agnostic Approach to Network and Compute Optimization
Author: SERRACANTA PUJOL, BERTA
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: 19/09/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: CABELLOS APARICIO, ALBERTO | RODRÍGUEZ NATAL, ALBERTO
Thesis abstract: This thesis explores how to enhance the performance of cloud applications by addressing inefficiencies across both the network and compute layers of modern distributed systems. As cloud-native applications grow more complex and are deployed across heterogeneous, geographically distributed infrastructures, traditional abstractions, though foundational for scalability and modularity, have begun to constrain opportunities for global coordination and responsiveness. To overcome these limitations, this work introduces two complementary approaches: one that improves network resource utilization without requiring developer involvement, and another that enhances compute-side elasticity through a smarter, more proactive autoscaling mechanism. Both approaches are guided by a common design philosophy: introducing context-aware intelligence in a minimally disruptive way, maintaining full compatibility with existing architectures, infrastructure, and developer workflows.The first part of the thesis focuses on Network-Application Integration (NAI), specifically targeting performance improvements in inter-datacenter communication. To this end, it proposes an application-agnostic solution based on extended Berkeley Packet Filter (eBPF) and eXpress Data Path (XDP) technologies. By dynamically identifying and separating short and long Transmission Control Protocol (TCP) flows at the network ingress, the system enables differentiated routing through distinct network tunnels, thereby mitigating queuing delays and reducing flow completion times. A key advantage of this approach is that it operates transparently, requiring no modifications to applications or developer-provided annotations, making it highly deployable within existing environments. Testbed experiments demonstrate that this technique significantly reduces latency and improves resource utilization in hybrid, multi-datacenter scenarios.The second part of the thesis turns to the compute domain, focusing on autoscaling mechanisms in Kubernetes-managed microservice environments. Recognizing the limitations of existing reactive scaling strategies, the work develops a control-theoretic model of the Kubernetes Horizontal Pod Autoscaler (HPA), formally analyzing its stability and responsiveness. Based on these insights, a new context-aware HPA is introduced, which incorporates upstream CPU metrics from the application’s service graph to anticipate downstream load changes. This proactive strategy enables more efficient and stable scaling decisions, improving responsiveness and reducing latency during traffic spikes. Notably, it achieves these gains without relying on complex performance models or machine learning, preserving simplicity and compatibility with standard Kubernetes tooling.Overall, the two approaches presented in this thesis offer practical methods for improving the performance and efficiency of distributed cloud applications, with a focus on compatibility with existing systems and workflows. Rather than proposing disruptive architectural changes, both solutions extend current abstractions to introduce additional context-awareness where it can be most effective. The results suggest that incremental, deployable enhancements to orchestration and networking layers can help address emerging challenges in scalability and responsiveness, making them suitable candidates for integration into real-world cloud-native environments.

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

BENAVIDES ALCIVAR, JULIO DARIO: Thermo-mechanical performance of steel slag asphalt mixtures and their potential for urban heat mitigation
Author: BENAVIDES ALCIVAR, JULIO DARIO
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 CONSTRUCTION ENGINEERING
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Article-based thesis
Deposit date: 19/09/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: APONTE HERNÁNDEZ, DIEGO FERNANDO | LÓPEZ MONTERO, TERESA
Thesis abstract: This doctoral thesis focuses on the study of steel slag from electric arc furnaces as a technically and environmentally viable substitute for natural aggregates in asphalt mixtures. While the primary objective was to evaluate its thermo-mechanical behaviour and potential for urban heat island (UHI) mitigation, other fundamental aspects were also addressed to validate its real-world application in sustainable urban pavements, such as moisture resistance, fatigue performance and cracking behaviour.Through a series of experimental investigations, structured as independent yet complementary chapters, the influence of steel slag on the physico-chemical, mechanical, and thermal properties of asphalt mixtures was analysed, along with its integration into embedded solar collector systems (ASC).Initially, the physical, morphological, and chemical properties of steel slag were characterised to understand its effect on aggregate–bitumen adhesion and moisture resistance (ITSR). Through bitumen affinity tests, digital image analysis, and ITSR testing, it was demonstrated that steel slag improves resistance to moisture damage—even under total replacement—due to its high surface roughness and its composition rich in metallic oxides.In a second stage, partial replacement of natural aggregates by steel slag in the fine fractions was evaluated. Similar benefits were observed in terms of moisture resistance, with density remaining within conventional ranges. This result suggests that the use of steel slag in fine fractions may overcome previous limitations related to increased total mix weight.Subsequently, the mechanical behaviour was addressed through indirect tensile strength, stiffness, and fatigue tests. Mixtures with different levels of slag replacement and bitumen film thicknesses (TF) were designed and evaluated using four-point bending and strain sweep (EBADE) tests. The results showed that increasing the slag content raises mixture stiffness but reduces fatigue resistance, an effect attributed to the material's hardness and its tendency to decrease the effective bitumen film thickness. However, a well-optimised mixture—such as HMA_SL* with a corrected TF—achieved performance similar to the control mixture, even under critical temperature conditions.Furthermore, crack resistance was assessed using the Fénix test, which showed that although slag-containing mixtures require more energy to initiate cracking, their post-failure behaviour tends to be more brittle. Nevertheless, the mixture optimised in terms of bitumen film thickness showed significant improvements in toughness (IT) and fracture energy (GF), highlighting that adjusting the binder content is essential to mitigate this limitation.In parallel, the thermal properties of the mixtures were investigated through both experimental tests and numerical simulations (FEM). It was observed that steel slag reduces the thermal conductivity of the mixture, slowing down its cooling rate and thus extending the compaction window. While this also lengthens the required cooling time prior to traffic opening, the simulations accurately predicted thermal evolution, facilitating better design and process control.Finally, the application of steel slag in asphalt pavements with embedded solar collectors (ASC) was explored, aimed at UHI mitigation and thermal energy recovery. Dense mixtures containing steel slag (AC16D + AC22D) exhibited favourable thermal balance, reducing surface temperature by up to 16.3 °C and improving heat collection efficiency compared to gap-graded mixtures with the same material (BBTM11-B + AC22D). This performance confirms its potential as a functional material for sustainable urban applications.Altogether, the findings of this thesis validate steel slag as a technically sound, functional, and environmentally competitive material for the development of both structural and functional asphalt mixtures, contributing to more sustainable urban paving practices.
SANG, XIAOHAN: Real-time Data-driven Safety Assessment for Building Structures
Author: SANG, XIAOHAN
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 CONSTRUCTION ENGINEERING
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Change of supervisor + Article-based thesis
Deposit date: 10/09/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: KONG, QINGZHAO | ROCA FABREGAT, PEDRO
Committee:
     PRESIDENT: SHI -, ZHONGQI
     SECRETARI: ZHOU, ZHIGUANG
     VOCAL: ZHOU, HONGYUAN
Thesis abstract: The evolution mechanism of structural performance remains a critical research topic in structural mechanics. Cracks, serving as indicators of performance deterioration, manifest physically at the meso-scale as processes of crack initiation and propagation, while at the macro-scale, they correspond to the global responses of structural stiffness degradation and load-bearing capacity attenuation. Traditional manual inspection methods are time-consuming and labor-intensive, and the acquired data are often unsuitable for direct application in structural evolution analysis. Consequently, this study focuses on developing performance evolution methodologies for crack-damaged buildings, aiming to enhance assessment efficiency and provide robust support for the lifecycle safety management of large-scale urban building structures.This research primarily addresses crack evolution prediction, crack-embedded finite element modeling techniques, rapid finite element modeling methods, and automated crack embedding approaches. Firstly, based on the curvature characteristics of reinforced concrete (RC) members, a method for predicting crack locations according to curvature variations is proposed and validated for accuracy through four-point bending tests. Secondly, to further improve prediction precision, an initial-condition-free crack prediction method is introduced. This approach, grounded in nonlinear bond-slip theory, is capable of describing extreme scenarios of reinforcement-concrete debonding, and its feasibility is experimentally verified.Regarding crack embedding within finite element models, this study presents a method for calculating the flexibility matrix of cracked elements based on strain energy release rate theory, along with modification techniques adaptable to diverse boundary conditions. Simultaneously, a novel simulation method utilizing nonlinear spring elements is proposed for unreinforced masonry structures, and its effectiveness is experimentally validated. Building upon this, a method for embedding cracks into masonry structures is further developed. This method simulates the alterations in tensile-compressive and shear behavior of post-cracking elements by adjusting the mechanical properties of planar elements and spring elements.Finally, a computer vision data-driven geometric adaptive modular finite element modeling method is proposed. This technique enables rapid acquisition of geometric information for frame structures, facilitating swift modeling and condition assessment. Additionally, to address the challenge of automated crack embedding in finite elements, a labeled crack embedding method is introduced. By assigning labels containing information on crack position, orientation, and boundary conditions, rapid integration of crack data is achieved.In summary, this study yields significant advancements in performance analysis methods for damaged buildings. It establishes theoretical formulations for crack location prediction and develops modeling approaches for damaged beams, columns, and walls, thereby laying a scientific foundation for constructing a structural performance evolution analysis framework.

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

CAMÓS VIDAL, ROBERT: Design and characterization of an unobtrusive ECG monitoring system for wheelchairs
Author: CAMÓS VIDAL, ROBERT
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: Normal
Deposit date: 16/09/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: ROSELL FERRER, FRANCISCO JAVIER | SUDRIA ANDREU, ANTONI
Thesis abstract: This work was carried out within the framework of the “Doctorats Industrials” program, in collaboration with Regner Engineering S.L., a company specialized in the manufacturing of wheelchair solutions, and the Universitat Politècnica de Catalunya.As cardiovascular diseases (CVDs) remain the leading cause of death globally, and people with disabilities are at increased risk, the need for continuous, non-obtrusive heart monitoring becomes urgent. Three high-growth markets relevant to Electrocardiography (ECG) monitoring in wheelchairs were analyzed. First, the global wheelchair market is growing steadily, with powered models showing strong demand. Next, wearable and medical wearable markets are expanding rapidly, driven by advances in sensor integration and healthcare needs. Finally, the mHealth and IoHT sectors are experiencing major growth due to digital health trends and remote monitoring. Together, these markets highlight strong commercial potential for the proposed system.This PhD thesis presents the design and validation of a novel unobtrusive ECG monitoring system fully embedded into a wheelchair, tailored to the daily needs of individuals with mobility impairments.The developed solution integrates single-lead ECG sensors into the wheelchair’s armrests, using active electrodes powered by a bootstrapped supply to ensure ultra-high input impedance and high Common Mode Rejection Ratio (CMRR) in front of electrode impedance mismatch. This design allows the system to operate under both direct conductive contact (similar to dry electrodes) and indirect capacitive coupling (through clothing), without requiring hardware changes.Furthermore, the ECG sensor includes a protection circuit against electrostatic discharges (ESD), compliant with IEC 61000-4-2, which has been accurate designed and simulated in order not to degrade the high input impedance. The system also features Bluetooth connectivity and a modular backend, aiming for future scalability and industrial application.Sensor characterization was performed using an original experimental setup with an AC coupling inside a Faraday cage, allowing the measurement of very high input impedance values at low frequencies, i.e.191 fF at 50 Hz and common-mode rejection ratios (CMRR) up to 76.1 dB. Real-ECG recording tests with a volunteer wearing a cotton shirt confirmed accurate signal acquisition, with 117 µV RMS amplitude for the ECG and 31 dB of Signal to Noise Ratio (SNR).The research successfully achieved its goals by designing and validating a reliable unobtrusive ECG system for wheelchairs, meeting both clinical and industry standards. It lays a strong foundation for future developments in health monitoring. The proposed solution lays the foundation for future integration into chairs, beds, vehicle seats or even wearable technologies. It marks an important advance toward reliable, non-intrusive ECG monitoring for people with limited mobility, with both clinical and commercial potential.

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

SAVADKOOHI, MARJAN: An Advanced Control Strategy for Optimizing HVAC System Performance in Non-Residential Buildings
Author: SAVADKOOHI, MARJAN
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: Normal
Deposit date: 10/09/2025
Reading date: 24/11/2025
Reading time: 11:00
Reading place: Place: ETSECCPBUPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
Thesis director: CASALS CASANOVA, MIQUEL | MACARULLA MARTÍ, MARCEL
Thesis abstract: This PhD research addresses the scientific and practical challenges in implementing advanced control systems (ACS) for HVAC optimization in non-residential buildings. While adaptive and predictive strategies, especially model predictive control (MPC) and neural network (NN)-based methods, have shown promise in research, real-world deployment remains limited. Barriers include insufficient building historical data, technical limitations of HVAC systems, lack of building energy management systems (BEMS) standardization, and low institutional readiness. To address these, this thesis uses a dual-method approach combining empirical analysis and simulation-based experimentation.First, a survey of 676 non-residential buildings evaluates BEMS practices, focusing on HVAC control, data storage, and predictive control adoption. While smart metering and sensors are increasingly common, predictive control is reported in only 0.6% of buildings. Key barriers identified include a lack of environmental data logging, obsolete HVAC systems that do not support integration with predictive control technologies, limited technical expertise among building operators, and insufficient investment frameworks, particularly in the public sector.To respond to data and implementation challenges, the second part develops and evaluates NN-based predictive controllers using a calibrated building energy model. Eight NN models are trained on varying amounts of historical data to assess impacts on prediction accuracy and HVAC performance. Validations use consistent KPIs for thermal comfort and energy efficiency. Results show that 1–4 months of data are needed for acceptable performance, reaching a performance threshold after two years. Data preprocessing helps in data-limited cases (<100 instances), but adds little value with larger datasets, suggesting a context-specific role.Further analysis explores operational and climatic sensitivities. In cold climates and post-HVAC shutdown periods (e.g., Monday mornings), models struggle due to sparse training data. Performance improves mid-week and in warm zones, highlighting the need for diverse and climate-adapted training data. Compared to rule-based scheduling, NN controllers consistently improve energy use and comfort, especially when supported by adequate data and system configuration.This thesis offers novel insights into deploying intelligent HVAC control systems. It identifies data thresholds for effective predictive control, clarifies preprocessing roles, and provides guidance on model adaptation to climate and operations. It also highlights broader needs such as standardizing data acquisition, training energy professionals, and fostering public-private collaboration to reduce implementation risk. The findings support scalable predictive control in practice and contribute to the goals of energy efficiency, smart building management, and decarbonization.

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

MONCADA RAMÍREZ, ANÍBAL ANDRÉS: Coupled modelling and sustainability assessment of polymeric reinforced soil retaining structures subjected to environmental conditions
Author: MONCADA RAMÍREZ, ANÍBAL ANDRÉS
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 GEOTECHNICAL ENGINEERING
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Normal
Deposit date: 05/09/2025
Reading date: 20/10/2025
Reading time: 11:00
Reading place: ETSECCPB.UPC, Campus NordBuilding C2. Classroom: 212C/Jordi Girona, 1-308034 Barcelona
Thesis director: PUIG DAMIANS, IVAN | OLIVELLA PASTALLE, SEBASTIAN
Thesis abstract: The focus of this Thesis are reinforced soil structures with polymeric (or geosynthetic) reinforcement elements. These materials are known for their rate-dependent behaviour, that is, time, load, temperature, and, to some extent, humidity, will affect their mechanical response. Depending on the geographic location of the structure, in-air and in-soil conditions can vary widely in temperature values and moisture content. Moreover, current climate change conditions, which are only expected to worsen with time, have shown drastic changes in local and global climate patterns, highlighting the need to better understand the response of reinforced soil structures to changing conditions. Coupled (thermo-hydraulic) numerical simulations were carried out to better understand how atmospheric climate influences in-soil conditions of a reinforced soil mass, namely, temperature, moisture content, and degree of saturation. Results allow for a better understanding on in-soil response to changing atmospheric conditions, as well as a valuable precursor for future coupled modelling attempts.Pullout tests were carried out using polyester strap reinforcements to study the effect of in-soil temperature in the soil-reinforcement response (i.e., pullout strength and friction interaction factors). Likewise, different geometries, vertical pressures, and installation techniques were tested to evaluate the overall pullout response of strap reinforcements, possible damages due to displacements and their consequences in the long-term, as well as reinforcement stiffness and extensibility. Results are useful in practical- and research-related fields as they allow to determine the soil-reinforcement interaction factor in a wide range of conditions and provide a better understanding of the temperature dependencies in the mechanical response of polyester.Polymeric materials will suffer from long-term deformations when subjected to constant load conditions. This phenomenon, also known as creep, will depend on the load level as well as temperature conditions. Analytical and numerical models usually rely on the selection of a single stiffness value to determine the response of polymeric materials. The selection of this value is not trivial, as it will depend on time, load, and temperature. With the aim of providing a numerical tool to simulate the long-term response of reinforced soil structure, a coupled viscoplastic constitutive model with temperature, load, and relative humidity dependencies was developed. Model parameters were calibrated using a wide dataset of laboratory measured creep master curves and later implemented in a finite element software.Polymeric materials cover a wide range of solutions in the fields of civil, mining, and geotechnical engineering. A key advantage of these materials is their reduced environmental impact, attributed to reductions in the use of granular material and subsequent transportation efforts. This Thesis goes a step beyond environmental impacts and into sustainability assessments of reinforced soil walls. For this, different facing elements and backfill material alternatives were analysed. Assessments include environmental, social/functional, and economic requirements. A probabilistic approach was used for the environmental and economic requirements. Results use idealized scenarios to evidence the advantages and/or disadvantages of different alternatives for reinforced soil walls with rigid facings. Finally, the procedure and results serve as example and/or starting point for future sustainability assessments, which are expected to be determining in future infrastructure projects.
YAZDANI CHERATI, DAVOOD: Hydromechanical Simulation of Argillaceous Rocks for Radioactive Waste Disposal Applications
Author: YAZDANI CHERATI, DAVOOD
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 GEOTECHNICAL ENGINEERING
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Normal
Deposit date: 28/07/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: VAUNAT, JEAN | GENS SOLE, ANTONIO
Thesis abstract: Argillaceous claystones are primarily composed of clay particles of sedimentary origin andcontain a substantial amount of chemically precipitated cement, often calcium carbonate, whichacts as a bonding agent. Due to their favorable properties—such as low permeability, minimalmolecular diffusion, self-sealing capabilities, and high retention capacity for radionuclides—theyare considered suitable host geomaterials for the deep geological disposal of radioactive waste.However, fractures within these geomaterials, induced by excavations or post-disposal processes,can create preferential pathways for radionuclide migration, potentially influencing theperformance of the disposal system. Therefore, these problems should be numerically evaluated.However, due to their complex behavior, modeling argillaceous rocks presents a significantchallenge. Under shearing, these geomaterials exhibit anisotropy, creep, and quasi-brittle failurecharacterized by significant post-peak softening and strain localization. This study aims toinvestigate the hydromechanical response of Callovo-Oxfordian (COx) argillaceous claystones tolaboratory tests, field excavations, and post-disposal processes by employing the argillite modelsimplemented in the CODE-BRIGHT program. The argillite models are adopted since they caneffectively reproduce the key characteristics of argillaceous materials. Additionally, throughoutthis thesis, several other constitutive models are applied to simulate the behavior of materialsinteracting with the COx, including soft and rigid supports, and swelling materials. The outcomesof this thesis provide significant insight into the hydromechanical behavior of argillaceous rocks,thereby contributing to a more accurate evaluation of the disposal process.

DOCTORAL DEGREE IN MARINE SCIENCES

ENRIQUEZ HIDALGO, ANDRES MAURICIO: Decision Support System for Coastal Area Management in Response to Flooding and Coastal Erosion: A Case Study of Tumaco-Nariño
Author: ENRIQUEZ HIDALGO, ANDRES MAURICIO
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: Normal
Deposit date: 18/07/2025
Reading date: 14/10/2025
Reading time: 16:00
Reading place: Pontificia Universidad Javeriana Ak 7#40-62 Bogota Colombia
Thesis director: MESTRES RIDGE, MARC | ESPINO INFANTES, MANUEL | TORRES ABELLO, ANDRES EDUARDO
Thesis abstract: Flood and erosion risk management in coastal areas affected by these processes requires integrated and, when conditions allow, coupled approaches that combine physical, socioeconomic, and cultural factors. This thesis develops a methodology based on a decision support system (DSS), which operates in contexts with data scarcity and high uncertainty. This DSS integrates coupled numerical modeling (FLOW+SWAN), geospatial analysis, fuzzy logic (FL), machine learning (ML), and multi-criteria decision analysis (MCDA) with Monte Carlo simulations, offering a platform focused on risk characterization and the spatial prioritization of development pathways (DP) proposed in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC). Its flexible design allows for the combination of indices that consider hazard, vulnerability, and exposure, and the evaluation of DP such as hard and soft engineering measures, built environment adaptation, planned retreat or advancement, and nature-based solutions (NBS), adapted to coastal archetypes.Flood and erosion hazards are estimated based on coastal water levels that exceed land elevation and coastal slopes, considering significant wave height (SWH) and tidal range obtained through numerical modeling, and integrating as additive factors the influence of peak wave period (PWP) and wave direction (WDI). The degree of influence of oceanic forcing on shoreline displacement (SLD), analyzed using 30 years of data from the Landsat 5, 7, 8, and 9 collections with CoastSat, is quantified using a random forest. Vulnerability is defined based on elevation, terrain slope, and the normalized difference vegetation index (NDVI), while exposure is based on land use and land cover (LULC) and human settlements (HS); all these variables are derived from Sentinel-2 imagery processed using a convolutional neural network (ResNet). These layers are normalized and combined using fuzzy membership functions along with Monte Carlo simulations, which allows the generation of probabilistic risk maps derived from hazard, vulnerability, and exposure. In parallel, the DP are prioritized through MCDA, using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), enhanced with Monte Carlo simulations to incorporate the uncertainty associated with expert judgment. Finally, the optimal solutions are spatially assigned according to the risk distribution, sea level rise (SLR) scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) projected by NASA, and LULC and HS projections for the present, 2050, and 2100.The methodology developed constitutes the main result of this thesis. In its application to El Morro and Tumaco islands, in the Bay of Tumaco (Nariño – Colombia), the spatial allocation of DP shows a predominant combination of NBS, soft engineering, and built environment adaptation, distributed according to the level of risk, LULC, and HS. When comparing scenarios with and without numerical modeling, it is observed that the omission of modeling leads to a significant overestimation of risk areas, which implies managing approximately 284 more hectares than are necessary. Likewise, the inclusion of sea level rise (SLR) projected by the SSP scenarios allows the identification of 52 additional hectares requiring intervention in the long term. These differences demonstrate that the DSS is not only robust but also flexible, as it allows for the evaluation of scenarios with varying degrees of technical complexity and the adjustment of the risk threshold established in this case at the 95th percentile according to the decision maker’s level of risk tolerance.

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

AL ZEYADI, NOORA TALIB MOHAMMED: 3D printing of aluminum alloys under different extrusion techniques
Author: AL ZEYADI, NOORA TALIB MOHAMMED
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: 18/07/2025
Reading date: 17/11/2025
Reading time: 11:30
Reading place: UPC Facultat de Matemàtiques i Estadística Campus Diagonal Sud, Carrer de Pau Gargallo, 14, Distrito de Les Corts, 08028 Barcelona SALA D'ACTES
Thesis director: CABRERA MARRERO, JOSE MARIA | FENOLLOSA ARTÉS, FELIP
Thesis abstract: This doctoral research evaluated the feasibility of using various aluminum-based feedstocks in additive manufacturing (AM) to develop cost-effective and environmentally friendly alternatives to traditional metal fabrication. The study systematically examined AA6061 filament, AlSi10Mg granules (commercial and recycled), and AlSi10Mg powder paste across three AM techniques: Fused Deposition Modeling (FDM), screw-based extrusion, and Direct Ink Writing (DIW). The main objectives were to optimize printing, thermal debinding, and sintering parameters for each feedstock and AM technique, and to assess the resulting mechanical properties and microstructures of the fabricated parts.For printing, AA6061 filament processed via FDM achieved optimal results with a 0.8 mm nozzle diameter at 205 °C. AlSi10Mg granules (commercial and recycled) and AlSi10Mg powder paste, used in screw-based extrusion and DIW respectively, performed best with 0.6 mm nozzles and lower temperatures. These optimizations established critical baseline conditions for subsequent processing steps, emphasizing the distinct requirements of each material and technique.Thermal debinding, essential for removing polymeric binders before sintering, was optimized for each feedstock. For AA6061 filament, 550 °C with holding times up to 3 hours was most effective. For commercial AlSi10Mg granules, 350 °C for 3 hours yielded optimal results, a condition that also worked for recycled granules and powder paste. These parameters minimized defects and prepared the parts for successful sintering.Sintering parameters were rigorously optimized to ensure densification and desired mechanical properties. AA6061 filament was best sintered at 635 °C, while commercial AlSi10Mg granules and powder paste achieved optimal results at 600 °C. Recycled AlSi10Mg granules reached peak performance at 620 °C. All sintering was conducted for 3 hours under a nitrogen atmosphere with vacuum and oxygen traps. SEM analysis confirmed increased densification and uniform microstructures under these conditions.A pre-sintering pressing technique was introduced to further enhance densification and reduce porosity. This step significantly improved the relative density of sintered parts by 19.25–45.55%, with pressed samples achieving densities up to 93.65%. Mechanical testing showed that recycled AlSi10Mg granules provided the highest compressive strength (168.34 MPa), followed by commercial granules, AA6061 filament, and powder paste.
GARCÍA DE ALBÉNIZ LÓPEZ DE ABERÁSTURI, NEREA: Engineering zirconia surfaces with cell instructive and antibacterial properties
Author: GARCÍA DE ALBÉNIZ LÓPEZ DE ABERÁSTURI, NEREA
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: 29/07/2025
Reading date: 13/10/2025
Reading time: 10:30
Reading place: ESCOLA D'ENGINYERIA BARCELONA ESTC/Eduard Maristany, 16 (08019 Barcelona)934137400Planta 2 Aula A A2.13https://meet.google.com/ztp-qftd-pqu
Thesis director: JIMENEZ PIQUÉ, EMILIO | MAS MORUNO, CARLOS
Thesis abstract: Tetragonal zirconia polycrystals stabilized with 3 mol% yttria (3Y-TZP) has gained growing interest as an alternative to titanium for dental implants, owing to its excellent biocompatibility, high mechanical strength and corrosion resistance and superior aesthetics. Despite these advantages, the clinical performance of zirconia implants still depends on their ability to promote osseointegration while simultaneously minimizing the risk of bacterial colonization, a competitive process known as "race for the surface". Surface properties of dental implants, such as topography, chemistry, and wettability, critically influence the biological response at the tissue-implant interface. In particular, micro- and nanotopographies directly impact cell-material interaction and can modulate several cellular functions including adhesion, migration, proliferation, and differentiation. Similarly, these topographical features affect bacterial response, either promoting bacterial adhesion or, conversely, reducing colonization through antifouling or bactericidal effects. For this reason, surface modifications have become a widely explored strategy to enhance the biological performance of implants. Nevertheless, the major challenge lies in designing surfaces that simultaneously support osseointegration while also preventing bacterial adhesion.This PhD Thesis addressed this challenge by investigating different surface modification approaches to improve the biological performance of zirconia. The aim was to create topographies that simultaneously improve cell behavior while exhibiting antibacterial properties. In concrete, we developed and characterized a series of micro and nanostructured zirconia surfaces and evaluated their biological performance both in terms of human mesenchymal stem cell (hMSC) response and bacterial adhesion of different strains. Prior to experimental work, a comprehensive bibliographic review on topographical modification strategies for 3Y-TZP was conducted (Chapter I), highlighting existing knowledge gaps and guiding the selection of surface treatments. Following this, different surface modification techniques were employed, including hydrofluoric acid (HF) etching for generating nanotopography (Chapter II) and laser patterning via nanosecond (ns-) and femtosecond (fs-) laser to create defined microstructures (Chapter III). These techniques were also combined to evaluate a potential synergistic effect of hierarchically rough micro- and nanotopographies on the biological response (Annex I). Our findings demonstrate both chemical etching and laser patterning techniques successfully enhanced the biological performance of zirconia by improving the hMSCS behavior and reducing bacterial adhesion. However, their combination did not result in a synergistic improvement. Among all the surfaces, the 3 μm linear pattern (L3) created through fs-laser patterning offered the best balance by simultaneously enhancing hMSC adhesion, migration, and osteogenic differentiation, while significantly reducing the adhesion of Staphylococcus aureus and Pseudomonas aeruginosa bacteria. It also led to the most favorable biological outcome under competitive co-culture conditions. Furthermore, biofunctionalization of this topography using a multifunctional peptide containing both antimicrobial and cell-adhesive sequences showed promising synergistic biological effects (Annex II). Importantly, these improvements were achieved without compromising the mechanical integrity of the L3-patterned surface (Annex III). In conclusion, this PhD Thesis demonstrated that topographical modification of zirconia offers promising strategies for developing zirconia implant with improved biological performance, enhancing both osseointegration and antibacterial properties. Future directions should focus on integrating biochemical cues, in vivo validations, and complete assessment of the mechanical integrity.

DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT

YOUSEFIAN, MOHAMMAD: Evaluating the Impact of Corporate Social Responsibility on Financial Performance, Productivity, and Critical Success Factors in the European Mining Industry
Author: YOUSEFIAN, MOHAMMAD
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: Normal
Deposit date: 16/09/2025
Reading date: 21/10/2025
Reading time: 10:00
Reading place: Sala d'actes Escola Politècnica Superior d'Enginyeria de Manresa. EPSEM
Thesis director: BASCOMPTA MASSANÈS, MARC | SANMIQUEL PERA, LLUIS
Thesis abstract: Responsible and ethical business practices have gained prominence, particularly through Corporate Social Responsibility (CSR). Over four decades, CSR disclosure evolved significantly, increasingly appearing in dedicated reports. Each economic sector has established distinct CSR practices and standards, including the mining industry. In Europe, CSR is largely voluntary for SMEs, while larger firms follow internationally recognized guidelines. Despite its modest scale, European mining is essential to achieving sustainability and transitioning to a circular economy, yet SMEs hesitate in adopting CSR due to unclear financial implications.This thesis investigates CSR's impact on economic growth and management within the European mining sector, specifically examining macroeconomic and microeconomic indicators, financial performance, and decision-making. Data from 45 publicly listed European mining companies from 2018 to 2021 was analyzed using content analysis and fixed-effects panel regression models. Financial indicators studied include Return on Asset (ROA), Return on Equity (ROE), Net Profit Margin (NPM), Tobin’s Q, and labor productivity, alongside CSR ratings from CSRHub. Results revealed a consistently positive relationship between CSR performance and financial indicators, and partially positive effects on labor productivity.Furthermore, the relationship between CSR and Total Factor Productivity (TFP) was studied using Data Envelopment Analysis (DEA) and panel regression analysis on data from 40 mining firms and the World Bank. Findings indicated that CSR initiatives positively influence TFP, with transparency, training, health and safety, and resource management identified as significant contributing factors.Finally, the research identified Critical Success Factors (CSFs) for successful CSR implementation using fuzzy Delphi and Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodologies. An expert panel refined 16 initial factors down to 12, identifying biodiversity conservation, waste management, and energy efficiency as the most critical success factors strongly interconnected with other CSR elements.This comprehensive study underscores the value of CSR in enhancing financial and economic performance in the European mining industry and provides a clear framework for effective CSR implementation.

DOCTORAL DEGREE IN PHOTONICS

FERNÁNDEZ FERNÁNDEZ, GABRIEL: Learning particle dynamics: from diffusion to interactions
Author: FERNÁNDEZ FERNÁNDEZ, GABRIEL
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: 01/09/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: LEWENSTEIN, MACIEJ | MANZO, CARLO
Thesis abstract: Understanding how a complex system works from its components, such as a virus invading a cell or particles aggregating in a liquid, is a fundamental question in the study of nature that provides great biological benefits. To solve this question, it is interesting to observe the path taken by the components of a system, as this contains valuable information that helps us to characterize them and understand how they interact with each other. Advances in the last decade in the field of machine learning offer a promising numerical tool, as they allow the automatic extraction of relevant features and relationships, while also predicting the system's behavior.In this thesis, we focus on the analysis of particle trajectories observed in complex systems, addressing two fundamental aspects:the random and therefore difficult-to-characterize individual behavior, as occurs in the lungs, where we inhale air and oxygen diffuses into the capillaries of the alveoli; and behavior due to multiple ways of interacting, in some cases unknown, such as that of a large flock of birds migrating together.In particular, we consider three problems:1) the accurate estimation of parameters that characterize the anomalous diffusion observed in biological processes,2) the identification of significant parameters to describe stochastic processes,and 3) the extraction of the functional form of the multiple forces present in particle systems.To tackle each of the problems, we developed a specific machine learning model designed to extract meaningful information from trajectories and rigorously evaluated it on a series of simulated systems with known dynamics.The first method, KISTEP, predicts anomalous diffusion properties at each time step, for trajectory segments, and for a set of trajectories, allowing for detailed analysis at each level, based on individual trajectories. With this method, we participated in the AnDi Challenge 2, a scientific competition comparing computational methods dedicated to characterizing fractional Brownian motion trajectories that resemble biological phenomena observed in experiments such as cell endocytosis or protein immobilization.The second method, SPIVAE, helps to identify the minimal representation of stochastic processes thanks to its unsupervised, interpretable, and generative features. Furthermore, it is capable of generating new trajectories that reproduce the learned characteristics of the process. The analysis performed with SPIVAE revealed the expected parameters of BM, fractional BM, and confined BM, while it learned a nonlinear combination in the case of the scaled BM.The third method, FISGAE, employs a graph neural network to infer in an unsupervised manner the functional form of the forces acting between particles. FISGAE successfully learned the forces between 21 interacting particles with non-reciprocal linear forces, while in the more complex scenario of a Lennard-Jones gas, it learned well the force at short distances.In conclusion, this research provides methods to facilitate the analysis of particle systems directly from their trajectories, unlocking insights otherwise unavailable. The proposed methods have the potential to benefit experimental and theoretical researchers, and even artificial intelligence developers, by enabling a more comprehensive understanding of complex systems. Furthermore, the developed frameworks are ready for future improvements, which could be achieved through the integration of more sophisticated architectures, thereby paving the way for even more advanced applications and discoveries.
KOKABEE, OMID: High-power ultrafast optical parametric oscillators from the visible to mid-infrared
Author: KOKABEE, OMID
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: 09/07/2025
Reading date: 11/11/2025
Reading time: 10:00
Reading place: ICFO Auditorium
Thesis director: EBRAHIM-ZADEH, MAJID
Thesis abstract: The introduction of electric lighting in Architecture marked a profound transformation in its design conception, establishing artificial light as a fundamental element in the configuration of space. Unlike other artistic and architectural disciplines, artificial architectural lighting lacks a formalised Art History. Existing specialist literature remains largely focused on technical and quantitative aspects, frequently relegating the qualitative dimensions of light in space to a secondary status. Consequently, there is a notable absence of a specific vocabulary capable of accurately describing the qualitative effects of lighting in architecture. This lexical gap hampers the effective communication of lighting-related spatial concepts, ultimately to the detriment of architectural practice. In light of these challenges, and with the aim of improving both design and pedagogical methodologies, this research advocates for the establishment of a dedicated vocabulary for qualitative architectural lighting. It is predicated on the hypothesis that it is feasible to construct a consensual glossary that enables the precise articulation of the formal and spatial attributes of lighting effects within architectural environments. To substantiate this hypothesis, the research sets out two principal objectives: first, to identify the parameters that define the qualitative aspects of lighting and to compile the associated terminological corpus; second, to develop a lexical and visual dictionary in which each term is clearly defined and illustrated, thereby facilitating its comprehension and application in both academic and professional contexts, and contributing to the standardisation of a specific and practical language.The study adopts a qualitative methodological framework, centred on the linguistic analysis of texts describing architectural lighting projects, which have been published in specialised Spanish-language media. A rigorous, systematic, and replicable terminology methodology has been employed, drawing upon established principles from the field of Terminology studies and related research on lighting perception. The process integrates automated term extraction methods, enabling efficient handling of large data sets, and applies linguistic techniques adapted to the visual domain. The research identifies the principal parameters defining the formal qualities of architectural lighting as direction, colour, and distribution, followed by quantity, luminance, sources, informational content, perceptual effects, and others. Among these, the distribution parameter emerges as the most frequently cited and, thus, the most critical for both configuring and describing architectural lighting. Accordingly, the dictionary focuses on the most recurrent terms related to distribution, listed alphabetically as follows: accent lighting, ambient lighting, composed lighting, diffuse lighting, direct lighting, directed lighting, dispersed lighting, focalized lighting, general lighting, grazing lighting, homogeneous lighting, horizontal lighting, indirect lighting, integrated lighting, precise lighting, projected lighting, reflected lighting, uniform lighting, and vertical lighting. It has been demonstrated that each of these terms can be defined in a manner that supports clear, precise, and intelligible communication within architectural lighting discourse. Furthermore, it is feasible to identify corresponding visual representations that exemplify each definition, reinforcing their pedagogical and practical applicability. In conclusion, this research affirms the viability of developing a consensual glossary of terms to imporve the communication of the formal and spatial characteristics of lighting effects within architectural practice, which constitutes a foundational step toward the recognition and standardisation of qualitative lighting vocabulary in the discipline.
WU, YINA: Theoretical aspects of the interaction of free and tunneling electrons with low-dimensional photonic systems
Author: WU, YINA
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: 10/09/2025
Reading date: 24/10/2025
Reading time: 10:00
Reading place: ICFO Auditorium
Thesis director: GARCÍA DE ABAJO, JAVIER
Thesis abstract: In this thesis, we provided a theoretical description of how focused electron beams interact with low-energy excitations and generate nanoscale light, which is of great interest in the field of nanophotonics. In addition, we described light generation by tunneling electrons and applied this phenomenon to the detection of analytes through the changes that they produce in the far-field emitted intensity.Specifically, through detailed modeling, we have investigated the plasmonic behavior in nanostructured materials, the phononic responses in polar crystals, and light generation through inelastic electron tunneling. We also calculated the spectral distribution of energy losses experienced by fast electrons interacting with these excitations and obtained spatially resolved electron energy-loss spectra for diverse systems. Here, we summarize our key findings:In Chapter2, we explored that the infrared plasmon response of fluorine-doped indium oxide nanocube dimers is controlled by how the cubes touch: point and edge contacts produce a singular low-energy dipolar mode that vanishes when the gap opens, whereas face contacts give a smooth spectral shift. Electron energy loss spectroscopy measurements and simulations confirm this geometry-dependent behavior, challenging the assumption that all dimers are identical. These results provide new insights into gap plasmons for sensing and nonlinear optics applications.In Chapter3, our study of hexagonal boron nitride nano-ellipsoids shows that nonlocal effects rule the low-energy phonon polaritons when the particle size drops below a few tens of nanometers. An atomistic model that includes long-range dipole–dipole interactions explains both the surface-confined and bulk-like modes seen in monochromated scanning transmission electron microscopy-electron energy loss spectroscopy, while a simple local dielectric model misses the surface feature entirely. We also find that finite size and surface polarization reshape the vibrational spectrum. These results underline that any realistic design of mid-infrared hexagonal boron nitride devices must account for spatial dispersion at the atomic scale. By integrating advanced microscopy, atomistic theory, and computational modeling, this research provides a blueprint for studying vibrational excitations in low-dimensional polar materials. In Chapter5, it introduced a self-illuminating plasmonic biosensor driven by electron tunneling. The device utilizes an metal-insulator-metal tunnel junction with a gold nanowire metasurface on top, enhancing electron-to-light conversion via plasmonic resonance. The developed sensor demonstrates spatially uniform emission over large areas and exhibits high sensitivity for detecting thin polymer films and biomolecular layers. This work offers a practical platform suited for integrated biosensing without relying on external illumination sources. Hence, angle-resolved photodetection could provide deeper insights into plasmonic mode structures, leading to enhanced spectral selectivity and sensitivity. The interplay between electron probes, excitations, and nanoscale light generation offers numerous exciting opportunities for future research. We believe that the insights and methods presented in this thesis can contribute significantly to exploring these promising new directions.

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

BOUDRIKI SEMLALI, BADR EDDINE: Analysis of Helio-Geo-Ionospheric Proxies for Earthquake Risk Prediction
Author: BOUDRIKI SEMLALI, BADR EDDINE
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: 19/09/2025
Reading date: 12/11/2025
Reading time: 10:30
Reading place: Aula de Graus de l'ETSETB
Thesis director: CAMPS CARMONA, ADRIANO JOSE | PARK, HYUK
Thesis abstract: Earthquakes are among the most destructive natural disasters, causing significant infrastructure damage and casualties. Between 1998 and 2018, seismic events resulted in approximately 846000 fatalities and caused economic losses totaling US$661 billion, emphasizing their profound socioeconomic impact. While thousands of earthquakes occur each year globally, only a small number are significant enough to be detected by monitoring systems or felt by people. Although earthquakes cannot be prevented, efforts have been made to reduce their consequences through risk assessment and public preparedness initiatives. Despite these advances, a reliable early warning system for earthquakes remains insufficient. The absence of consistent, deterministic precursors to seismic events is a critical challenge in developing such systems. However, research has identified small detectable geophysical signal anomalies that may appear days to weeks before major earthquakes. These anomalies involve changes in thermal infrared emissions, ionospheric scintillation, disturbances in magnetic fields, etc. While these signals are not usually present, their detection could enhance forecasting capabilities. Remote Sensing (RS) is a promising technique that provides broad spatial coverage, high temporal resolution, and the capability to observe otherwise inaccessible areas, such as oceans, deserts, and mountains. RS systems allow for continuous monitoring of the Earth's surface and atmosphere, enabling the detection of potentially earthquake-related anomalies across the lithosphere, atmosphere, and ionosphere. This Ph.D. thesis studies the use of RS techniques for earthquake precursor detection and their recent advancements. It explores Lithosphere-Atmosphere-Ionosphere Coupling (LAIC), a multidisciplinary framework that explains how seismic stress and rock deformation in the lithosphere can trigger cascading effects in the atmosphere and ionosphere. The thesis also presents results from ongoing research into short- and medium-term earthquake forecasting using Earth observation data. The Ph.D. thesis examines several satellite-derived parameters: Land Surface Temperature (LST) anomalies, Ionospheric Scintillation (IS) indices, geomagnetic field variations, and space weather data. This work aims to contribute to understanding earthquake precursors and seeks to develop practical tools for better predicting seismic events, enhancing mitigation and early warning efforts.
MAS I MÉNDEZ, MIREIA: RADAR-BASED TECHNIQUES FOR CONTINUOUS MONITORING OF SOIL MOISTURE AND VEGETATION USING TIME SERIES ANALYSIS
Author: MAS I MÉNDEZ, MIREIA
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: 10/09/2025
Reading date: 28/10/2025
Reading time: 11:00
Reading place: Aula de Teleensenyament ETSETB, Campus Nord, Barcelona
Thesis director: FABREGAS CANOVAS, FRANCISCO JAVIER
Thesis abstract: Ongoing changes in climate and weather patterns have emphasized the need for improved observation and understanding of rapid land–atmosphere interactions, particularly those related to the water cycle. This thesis explores the use of high-temporal-resolution SAR to monitor soil and crop dynamics, aiming to support the development of future Earth Observation missions, especially from geosynchronous orbit with short revisit times.The research was conducted within the framework of the HydroSoil project, funded by ESA, which established a unique ground-based SAR observation facility. The system allows for continuous monitoring of fields with a temporal resolution of 10 minutes and a spatial resolution of 1 m2 in the boresight. Complemented by extensive meteorological and ground truth data, the facility offered an ideal setup to study short-term dynamics of SM and crop development, focusing on two crops: barley and corn.The first part of the study examines diurnal cycles in radar backscatter time series and its relationship with environmental variables such as atmospheric humidity, temperature, and dew formation. Time-frequency analysis using wavelets was applied to quantify how radar signals correlate with specific meteorological variables at different time scales. Following this, a two-layer surface scattering model was applied to better capture the effects of diurnal SM variations on radar backscatter. In particular, the model accounts for the formation of a transient wet layer at the soil surface during nighttime, followed by daytime evaporation. When integrated with a short-term change detection method, the model enabled the retrieval of soil moisture time series with improved accuracy, particularly under conditions of high incidence angles and during rapid transitions following precipitation.The second part of the thesis focuses on the radar response to crop development. It is shown that radar backscatter and interferometric coherence are sensitive to plant height and phenological stage, though these relationships weaken under dense vegetation. A new metric, the daily growth rate, was introduced to better characterize crop evolution, correlating better with radar observables than traditional static parameters. Additionally, diurnal cycles in backscatter, primarily driven by dew formation and atmospheric humidity, were consistently observed and quantified.The final part of the thesis investigates the scattering mechanisms underlying the radar signal using several polarimetric decomposition techniques. These tools allowed for a detailed temporal characterization of how radar signals respond to environmental variables and crop growth stages. While all decomposition methods provided valuable insights, each also presented limitations, particularly in high biomass conditions where traditional models tended to overestimate volume scattering due to saturation effects.To address these limitations, the NNED was applied, reducing inconsistent scattering artifacts and improving robustness especially under dense canopies. The study also highlights that attributing all volumetric scattering to cross-polarized channels is overly simplistic. It is suggested that future research should explore combinations of different decomposition methods and leverage time-series analysis to refine interpretations of crop–environment interactions.In conclusion, this work demonstrates the potential of high-temporal-resolution SAR for monitoring short-term variations in soil and vegetation conditions. By integrating advanced modeling, coherence analysis, and polarimetric decompositions, the thesis provides a comprehensive framework for improving the understanding of land surface processes. The findings contribute to the current development of SAR-based methods for precision agriculture and offer practical guidance for the design of future radar missions targeting environmental and agricultural monitoring applications.
PENG, JILUN: Development of innovative land applications for ESA's HydroGNSS mission
Author: PENG, JILUN
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: Article-based thesis
Deposit date: 16/09/2025
Reading date: 31/10/2025
Reading time: 10:00
Reading place: Aula de teleensenyament de l'ETSETB (Mòdul B3 primera planta, Campus Nord UPC)
Thesis director: CARDELLACH GALÍ, ESTEL
Thesis abstract: The research presented in this paper-based dissertation focuses on the development of products for the ESA HydroGNSS mission, including the Level 2 surface inundation algorithm, the exploitation of the coherent channel for the L1B product, and the development of a simplified coherent channel simulator.The first contribution of this work is the development of a water detection algorithm that is applicable to high and low sampling rate data. The integration of two low-sampling rate power-derived observables, the reflectivity and the power spread ratio, enables a more comprehensive characterization of surface properties. And, the incorporation of auxiliary background information mitigates the impact of spatial heterogeneity. The random forest classifier effectively captures nonlinear relationships, achieving results that meet accuracy requirements, with false positives primarily associated with wetland areas. Another advancement is the integration of two high-sampling rate complex-derived observables, one of which is introduced for the first time -- the normalized amplitude (NA). NA remains stable over land and shows minimal sensitivity to changes in coherence integration time. The findings indicate that the NA has greater feature importance than the coherence coefficient (CC), underscoring its relevance for water classification.The second contribution of this work involves an analysis of the impact of the right-hand circularly polarized signal on the water detection algorithm. The normalized power spread ratio in the right-hand circularly polarized signal exhibits a clearer distinction between land and water surfaces and shows higher consistency across various land types compared to its left-hand counterpart. Reflectivity in the right-hand circularly polarized exhibits increased overlap between land and water surfaces, which may negatively impact classification performance. For non-inland water surfaces, the surface type contributes negatively to the output, indicating that higher coherence indicators are required to mitigate its influence. Furthermore, posterior probabilities derived from Bayes’ theorem demonstrate that the combination of normalized power spread ratio and reflectivity enhances classification accuracy by reducing false positives.The third contribution focuses on the exploitation of the HydroGNSS coherent channel. An analysis was conducted to assess the sensitivity of coherence indicators to water surfaces. CC and NA were compared to the `full entropy' metric available in the CYGNSS product. The results indicate that NA exhibits a similar sensitivity to water surfaces as full entropy and remains stable regardless of the coherent integration time. In contrast, the CC demonstrates higher sensitivity to small water bodies but is strongly influenced by the integration time. Additionally, a new variable, high sampling rate reflectivity (HSRR), was developed from normalized amplitude applying a track-wise exponential fit to the low-rate calibrated reflectivity. HSRR exhibits good agreement with both CYGNSS L1 reflectivity and calibrated raw IF reflectivity, further validated through a forward model. To enhance its robustness, a noise threshold based on low sampling rate noise floor was introduced. Adjacent track analyses confirmed that it provides a higher resolution than current 1–2 Hz products, improving its applicability for detailed surface characteristic monitoring.The development of a simplified coherent channel simulator has contributed to better understanding the behavior of this new GNSS-R mode of operation, and is included as an annex. Until now, simulating high sampling rate complex GNSS-R signals reflected over land required complicated models with computationally expensive implementations. Being able to reduce the complexity of the modeling and its implementation and computing time has facilitated the generation of synthetic data that mimic the properties of the coherent channel.

DOCTORAL DEGREE IN STRUCTURAL ANALYSIS

VENGHAUS, HENNING: Advanced Finite Element Methods for Metal Forming and Manufacturing Process Simulation: An Application to Friction Stir Welding Analysis.
Author: VENGHAUS, HENNING
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 STRUCTURAL ANALYSIS
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Article-based thesis
Deposit date: 10/09/2025
Reading date: 10/11/2025
Reading time: 12:00
Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus NorthGran Capitan S/N 08034 Barcelona
Thesis director: CHIUMENTI, MICHELE | BAIGES AZNAR, JOAN | JUHRE, DANIEL
Thesis abstract: This work explores the benefits and challenges of advanced Finite Element Methods for metal forming and manufacturing processes. As these processes become increasingly complex, FEM has emerged as a crucial tool. It helps predict physical quantities, aiding engineers in decision-making and enhancing the efficiency of development and production chains.Metal forming often involves (nearly) isochoric behavior due to plastic deformations, which can cause the standard Finite Method to become unstable. To address the isochoric behavior and ensure local convergence of strains and stresses, this study utilizes mixed finite element formulations, including the displacement-pressure (u/p), displacement-strain (u/ε), and displacement-pressure-deviatoric strain (u/p/e) formulations. To mitigate the high computational cost of the u/ε and u/p/e formulations, the Adaptive Formulation Refinement (AFR) technique is developed. This technique selectively activates the enhanced formulations based on physical criteria or error estimation. The method's accuracy and convergence rate is studied and compare favorably to reference solutions. The method is successfully applied to quasi-brittle structural failure analysis.This work further addresses the practical application of advanced numerical methods to complex manufacturing problems, notably Friction Stir Welding (FSW), which is a solid-state welding technique. FSW is characterized by isochoric deformations, extremely high strain rates, and highly non-linear and temperature-dependent material behavior. An Embedded Finite Element Method is employed to simplify the modeling of complex geometries and moving boundary conditions. It uses a purely Eulerian framework and a discrete level-set function for tool modeling and works directly with CAD tool geometries. The simulation results align well with experimental data. A parameter study of process parameters is carried out to evaluate their impact on welding forces and temperature evolution, demonstrating the tool's usefulness in aiding development processes.To enhance usability, a Graphical User Interface (GUI) is developed for creating simulation input files and managing simulations. Additionally, a particle tracing algorithm is implemented to visualize material flow. This work aims to bridge the gap between academic research and practical engineering applications. It provides advanced, yet robust and efficient numerical tools for simulating metal forming and manufacturing processes.

DOCTORAL DEGREE IN SUSTAINABILITY

LIANG, NA: Design for Sustainability Transitions: Taoist-Inspired Approaches for Systemic Sustainability Transitions
Author: LIANG, NA
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: 19/09/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: SEGALAS CORAL, JORDI | LIU, XIN
Thesis abstract: In recent years, sustainability transitions have emerged as a critical research focus within sustainability science. This doctoral research explores sustainability transitions through a Taoist-inspired lens, integrating Eastern philosophical insights with systems thinking and leverage point theory. It develops two innovative frameworks—the Deep and Shallow Sustainability Intervention (DSSI) framework and the Transition Intervention Point (TIP) System—to address both deep cultural-paradigmatic shifts and shallow operational adjustments in sustainability transitions. The research progresses across three stages: establishing a philosophical foundation, constructing a theoretical framework, and designing a practical tool. Together, these contributions offer a holistic and strategic approach to sustainability transitions, enriching both theory and practice. The frameworks are being tested in real-world contexts, particularly within an EU-funded rural transformation project, laying the groundwork for future empirical research and application.
ROURA SALIETTI, MIREYA: Reuse of ICT devices as commons: A property rights governance model for collective access
Author: ROURA SALIETTI, MIREYA
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: Normal
Deposit date: 15/07/2025
Reading date: 09/10/2025
Reading time: 11:00
Reading place: Campus Nord, C6-E106
Thesis director:
Thesis abstract: Understanding the role of property rights in managing Information and Communication Technology devices, primarily computers, is fundamental to addressing resource waste and achieving digital inclusion and sustainability goals. Although ICT device acquisition, use, and disposal are predominantly governed by individual property, reuse ecosystems demonstrate significant benefits. In such ecosystems, diverse actors collaborate to recover discarded ICT devices, refurbish, maintain and deliver them at minimal environmental and economic cost to vulnerable populations. Based on Common-Pool Resources theory, this thesis introduces a model that applies a community property approach to govern the reuse of ICT devices, using the bundle of rights framework to organise and manage reuse ecosystems. Building on the eReuse initiative, developed through action-research by a multistakeholder community involved in computer refurbishment for social inclusion in Spain, it captures patterns of collective action, classifies participants by roles, and maps the property rights underpinning their interactions, ensuring fair relationships within the ecosystem. To assess the suitability and application in Ibero-American contexts, the model was evaluated in three reuse ecosystems in Argentina and Uruguay. Results indicate that, although local adaptation is often needed, the model works in practice and shows strong potential to inform the governance design in culturally aligned ICT reuse ecosystems. The model is operationalised through two digital tools, DeviceHub and Workbench, which facilitate the tracing of property changes in devices throughout their life cycle, while also collecting detailed usage and performance metrics. In eReuse, it was found that approximately 46% of discarded and donated devices could be reused, highlighting the premature recycling of functional equipment due to criteria such as accounting or software obsolescence. Data collected through these tools also enables more precise estimation of impacts and supports the creation of indicators for comparing digital inclusion strategies across various regions and scenarios. The results show that the CO2 equivalent efficiency of reusing devices ranges from 30% in areas with a higher proportion of renewable energy to 5% in regions dependent on fossil fuels, when compared to new devices. This underscores that reuse is not inherently efficient but is instead dependent on contextual factors. Furthermore, these findings emphasize the need for more granular data to refine these estimates and gain a better understanding of the full impact of ICT reuse in different contexts. Finally, this governance model was tested through practical case studies in real-world contexts. Our results demonstrate that the success or failure of reuse depends on the sociocultural context and barriers such as ensuring long-term maintenance and usability, which are more effectively mitigated in servitised reuse ecosystems, where maintainers and ICT agents ensure device performance in the face of rapid technological change. These insights contribute to bridging the gap between sustainability goals and ICT governance, highlighting the role of digitally enabled reuse ecosystems in fostering equitable, low-carbon digital transitions and generating local employment opportunities.

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

LÓPEZ URIBE, CRISTINA: Arquitectura radical al dominio público. Juan O’Gorman, programa escolar, 1932
Author: LÓPEZ URIBE, CRISTINA
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: 19/09/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: GARCIA ESTEVEZ, CAROLINA BEATRIZ | ROVIRA GIMENO, JOSE MARIA
Thesis abstract: This dissertation focuses on architect Juan O'Gorman's 1932 program for the construction of elementary schools in Mexico City. The main subject of this thesis is the group of 26 new schools designed by O'Gorman and his team and included in the official book Escuelas primarias, 1932, published in 1933.Although Juan O'Gorman's work has always been present in the historiography of Mexican architecture—particularly his houses—the school program has been little studied. The schools mark a mythical moment in the history of Mexican architecture, in which the architect's social responsibility went beyond the artistic expectations of the discipline. The primary schools, with their extreme and radical rationality, were first rejected by select circles of architecture and then mentioned only superficially by historiography for decades, solely to point them out as a serious mistake. However, these buildings have acquired a mythical aura at certain moments in the history of Mexican architecture. Through a critical and thorough analysis, the thesis aims to bring to light some overlooked aspects of Mexican functionalist architecture, to open up other possible avenues of research, and to construct new interpretations of a specific moment in 20th-century history—the 1930s.The research is based on the analysis and activation of primary sources and archival objects—letters, photographs, bureaucratic documents, pieces of stucco, government memoirs, pigments, promotional brochures, etc.—and on the material reality of the buildings that remain: half of the schools that were built. But, in addition, for the first time, it is based on a series of documents that have come to light after being systematically hidden for decades—although others remain hidden.This analysis stems from the need to explain and unravel the multifaceted reality in which primary schools emerged in 1932. O'Gorman implemented various avant-garde strategies that he used simultaneously in both his best-known houses and schools. Likewise, the analysis reveals a series of coincidences in time that forged a network of political, artistic, social, and cultural relationships around the object of study.The research also analyzes the reasons for the initial rejection of the school program, which can only be explained in its complex political conditions. In turn, these conditions will be analyzed not only as part of a local context, but as interconnected with other far-reaching international conditions—which were political, cultural, and even religious. In this way, the archival material—and the historical phenomena it explains—reveals an intertwined history that requires us to go beyond national borders and show its various transnational relationships. Recognizing the unquestionable vitality and social utility that the schools demonstrate after almost a century in many of the neighborhoods where they were built, the aim is to recover the provocative nature of an architecture that was perceived at the time as too new. The schools were an expression of the rights that had been fought for in Mexico during the revolution and were the repositories of a new communal way of understanding education, in line with the ethical principles of the Mexican leftist intelligentsia. The radical architecture's strategies of rupture, carefully designed and implemented for the most sophisticated members of the Mexican cultural elite, would pass, through school projects, to socializing projects, to the masses and to the “anonymous” characters of the metropolis: girls and boys, mothers and fathers from the poorest neighborhoods learning to help and contribute to the community collectively. The avant-garde's cherished goal of having the masses truly embrace the new architecture may have come true—albeit briefly—in Mexico City in the early 1930s.

Last update: 08/10/2025 04:45:18.