Public display of deposited theses

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

• GORDILLO BEL, DIDAC: De la caponera al búnquer. Evolució de la fortificació des de mitjans del segle XIX a mitjans del segle XX a Catalunya.
  
  Author: GORDILLO BEL, DIDAC
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, CIVIL AND URBAN HERITAGE AND REFURBISHMENT OF EXISTING BUILDINGS
  Department: Departamento de Representación Arquitectónica (RA)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: ONECHA PEREZ, ANA BELEN | SÁNCHEZ RIERA, ALBERTO
  Thesis abstract: The thesis is composed, apart from the general introduction, of four interconnected chapters but which could be independent. The first is an overview of the evolution of fortification from antiquity to the middle of the 20th century. The second is the development of fortification in defensive enclosures since the middle of the 19th century, taking into account the curtains and bastions that gradually became low until they became covered caponiers, bastions that in principle are small forts that are part of a set but which could be independent in isolated forts, with crenellated galleries, embrasures with artillery pieces or plans protected only by parapets to place cannons to fire uncovered, and at the back of everything the tower divided into floors where the slingshots are located with the pieces to shoot at a long distance, both in slingshots under cover and pieces located on parapet at the highest point. Tortosa is taken as an excuse, because its case can be extrapolated to others in Catalonia. The fourth part is the realization of the bunker figure. There are enough cases here because unfortunately Catalonia, like the rest of the State, suffered a civil war. In this part, you can see how the bunkers were foreseen and how they gradually materialized with normalizing models that already came from before. Finally, the last part is the concrete explanation of the evolution of the bunker caponera and how it has become more and more camouflaged and more armored as the destructive power of the weaponry increases, how the traditional fortification has disappeared .
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• PULESTON, THOMAS PAUL: Monitoring and optimal operation of vanadium redox flow batteries
  
  Author: PULESTON, THOMAS PAUL
  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: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: SERRA PRAT, MARIA | COSTA CASTELLO, RAMON
  Thesis abstract: The rapid transition to a sustainable energy paradigm demands efficient and cost-effective energy storage systems to manage the inherent intermittency and unpredictability of renewable energy sources. Redox flow batteries appear as a promising option for large scale stationary applications, given their versatility, safety, and the possibility to scale energy and power independently. Among them, All-Vanadium Redox Flow Batteries (VFBs) have garnered the most interest, standing out for the long service life that stems from employing a single active element. Despite their potential, VFBs still face some challenges that limit their widespread implementation. This thesis tackles two of these major challenges. The first is electrolyte imbalance, a discrepancy of active species concentrations between the two sides of the system, which represents the primary cause of capacity loss. To address it, a comprehensive study is conducted on how battery capacity depends on various sources of imbalance and their interactions, culminating in a systematic procedure for recovering the capacity of imbalanced VFBs. The second challenge is the lack of direct methods for determining key system variables, such as vanadium species concentrations, the state of charge, state of health, and internal parameters. To overcome this issue this thesis develops advanced nonlinear estimation strategies, which reconstruct variables of interest using only easily measurable signals, thus providing a practical alternative to costly or complex sensor setups. Finally, the aforementioned estimation and imbalance management proposals are effectively integrated into a cohesive operational strategy, developing a control framework to optimise performance, prevent unsafe conditions, and maximise capacity.By addressing these critical challenges, this work delivers practical, cost-effective solutions that enhance VFB monitoring, capacity recovery, and overall operation. These advancements contribute to expanding the capabilities of the VFB technology, fostering broader integration within sustainable energy systems.
  

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

• AGRELO LESTÓN, ASIER: Development of metal-enhanced TiO2-based photocatalysts for hydrogen production
  
  Author: AGRELO LESTÓN, ASIER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 02/04/2025
  Deposit END date: 15/04/2025
  Thesis director: LLORCA PIQUE, JORDI | SOLER TURU, LLUIS
  Thesis abstract: Human activity has led to rising greenhouse gas levels, altering climate patterns and intensifying weather events. Therefore, a transition to a decarbonized energy system is needed, with hydrogen as a promising energy vector alongside solar and wind energy. However, current hydrogen production methods, such as steam methane reforming, generate significant CO2 emissions. Sunlight-driven water splitting offers a sustainable alternative, though efficiency improvements are required for industrial viability.This PhD thesis focuses on developing novel TiO₂-based catalysts for photocatalytic hydrogen production.Chapter 3 was conducted with the SYMAC team from Université Toulouse 3-Paul Sabatier. A TiO₂ catalyst was decorated with Cu nanoparticles stabilized by quinidine and compared to a sample prepared via incipient wetness impregnation (IWI) using L-ascorbic acid. The quinidine-stabilized sample exhibited 5 times superior activity under UV, as well as activity enhancement under Uv-visible irradiation. UV-vis spectroscopy revealed a plasmonic band relative to Cu, and a decrease in the bandgap was confirmed by Tauc plots. XRD confirmed Cu deposition and predominant anatase phase of the TiO2. TEM confirmed presence of Cu nanoparticles that XAS and XPS identified predominant metallic nature with minor oxide contributions.Chapter 4 was carried out with the Supra- and Nanostructured Systems group at Universitat de Barcelona (UB). Hybrid TiO₂ photocatalysts were prepared with Au(I) complexes and Au(0) systems were developed as co-catalysts. Three catalyst series incorporating coumarin-based ligands were evaluated under light and heat. Two (1 wt.% co-catalyst) were prepared via IWI and ball milling (BM), while a third (0.25 wt.% Au) was synthesized by IWI. IWI-prepared samples showed superior activity, achieving up to 2.7 times the H₂ production of conventional Au/TiO₂. UV-vis spectroscopy confirmed plasmonic bands relatives to Au and Tauc plots revealed bandgap narrowing. TEM, HAADF-STEM, and XPS confirmed the presence of Au nanoparticles with a predominant metallic nature.Chapter 5 focused on Pt/TiO₂ photocatalysts synthesized by BM, optimized through a design of experiments (DoE) approach. The most active sample was 1.4 times more efficient than an IWI-prepared Pt/TiO2 reference under UV light irradiation. HAADF-STEM-EDX revealed Pt atoms dispersed on TiO₂, with post-reaction growth into nanoparticles while there was presence of some Pt atoms dispersed. XPS confirmed partial Pt reduction during the reaction.Chapter 6 explored bimetallic PdCu photocatalysts with a total metal loading of 1 wt.%. A Pd:Cu atomic ratio of 1:2 was chosen after a screening from 3:1 to 1:3. The bimetallic sample outperformed theoretical activity of the combination of thus metals under UV light by 27%, and Cu incorporation enhanced H₂ production under UV-vis irradiation. BM-prepared samples were 1.2 times more active than IWI ones. Pd stability was improved with Cu incorporation, as seen in long-term tests, with less activity loss compared to monometallic Pd. Raman spectroscopy indicated strong metal-support interactions. UV-vis spectroscopy and Tauc plots showed enhanced visible absorption and bandgap narrowing, respectively. HAADF-STEM-EDX revealed bimetallic PdCu nanoparticles in BM samples, whereas IWI samples had separate Pd and Cu nanoparticles. BM also constrained Pd growth, as Pd nanoparticles in the monometallic sample grew 3.5 times during the reaction. XPS showed Pd reduction in both samples, with complete reduction in BM-prepared catalysts, further supported by H₂-TPR.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• FERNANDEZ, MARIANO TOMAS: Numerical techniques for the solution of thermal problems in the context of geophysical inversions
  
  Author: FERNANDEZ, MARIANO TOMAS
  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: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: DIEZ MEJIA, PEDRO | ZLOTNIK MARTINEZ, SERGIO
  Thesis abstract: The thermal structure of the Earth’s interior contains key information for the understanding of geodynamic processes, including plate tectonics, mantle convection, and the Earth’s overall thermal evolution. In particular, it is relevant to describe the geometry of the Lithosphere-Asthenosphere Boundary (LAB), separating the rigid Lithosphere from the ductile Asthenosphere. Accurately characterising this interface is key for the understanding of the thermal and mechanical structure of the Earth. Most models used in practice involve a formulation that is not physically sound, at least, in some part of the domain. These models involve smearing out regions or empirical estimations that do not fulfil the energy equilibrium equations. These estimates are useful in practice, but a formulation that respects physical principles would be preferable. This thesis focuses on developing forward solvers that allow for the computation of physically sound temperature fields within an inversion problem. The structure of the forward problem is altered by imposing the location of the LAB on the interior of the domain. The mathematical statement of this problem is presented in two versions and numerical methods to obtain solutions are developed and tested. The first solver enforces the isotherm condition by splitting the domain into Lithosphere and Asthenosphere, such that the LAB is a boundary to both, and explicitly adds equations to impose the condition. The second solver finds a mantle velocity field that enforces the isotherm condition indirectly. While the first solver needs to restore flux continuity by adding conditions, the second needs a velocity field that complies with the isotherm condition, both providing valuable information to improve geophysical understanding. The methodologies are tested across different scenarios and LAB geometries, using synthetic and non-synthetic temperatures to assess their performance in geophysical inversions. Results demonstrate that the domain-splitting solver reliably and efficiently recovers the LAB geometry, making it suitable for large-scale applications. The second solver, although computationally expensive and sensitive to parameter choices, also constitutes a robust solver. This thesis contributes to advance in the geophysics field by providing robust tools for thermal modelling. The tools have the potential to improve our understanding by solving partial differential equations providing insights into the thermal and mechanical properties of the Earth.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• ARÉVALO SOLER, JOSEP: Control of a grid of multiple AC and DC sub-systems interconnected with power converters
  
  Author: ARÉVALO SOLER, JOSEP
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: GOMIS BELLMUNT, ORIOL | PRIETO ARAUJO, EDUARDO
  Thesis abstract: High Voltage Direct Current (HVDC) offers clear advantages for long distance electrical transmission. This is why its implementation is rising in the interconnection of remote renewable energy and interconnection between islanded Alternating Current (AC) grids, as is the case in Europe. The majority of these systems are currently developed as point-to-point systems. However, Multiterminal High Voltage Direct Current (MT-HVDC) systems will be built shortly. The critical elements in these systems are the Interconnecting Power Converters (IPCs) that enable the transformation between AC and DC. These converters mainly use the Modular Multilevel Converter (MMC) technology, which can be controlled by leveraging the energy stored inside its cells to achieve its control objectives.The control strategy of these converters is diverse, and different control objectives can be implemented. Two subgroups exist: grid-forming (GFM) and grid-following (GFL) strategies. The main aim of the first one is to form the grid (AC and/or DC), while the second assumes a stable grid (AC and/or DC) with which to interchange power. The control strategy applied to be grid-forming or grid-following is not unique, and different control architectures are already proposed in the literature. Thus, studying the effect of combining these control architectures on the same system’s stability and performance is crucial.The main objective is to solve the question of how to properly assign and combine these roles in the emerging MT-HVDC grids to ensure stability and proper system response.Firstly, the stability of point-to-point links is studied. This includes a study on the interaction between AC and DC sides when AC-GFM and AC-GFL converters are in the same point-to-point link. It is seen how the different levels of energy buffering capability affect the level of interactions between AC and DC sides. Then, the extension of point-to-point links to MT-HVDC systems is studied. A crucial role in this case is the DC-GFM control. Thus, the stability of HVDC systems is studied when two different DC-GFM control strategies are applied.Secondly, MT-HVDC systems are studied. These systems introduce additional complexities. A key challenge in these systems is the optimal assignment of control roles to IPCs. One of the studies presents a novel methodology to optimize the control role assignment of IPCs by considering both small-signal stability and control performance. This methodology accounts for multiple power flow scenarios and analyzes the steady-state deviations and small-signal stability following selected events. The results of this study highlight the importance of control role assignment in enhancing system stability and performance.From the results extracted from the previously mentioned study, a dynamic control role assignment is proposed to solve the problems previously identified. Traditionally, the control role of IPCs has been static, with little consideration given to dynamically changing the control mode of these converters in real-time operations. However, this study advocates for a dynamic approach to IPC control role assignment, suggesting that allowing transmission system operators to adjust the control roles in response to varying conditions can lead to improved system performance, enhanced stability, and greater operational flexibility.Finally, the research also addresses the advantages of dual-port GFM control in hybrid AC/DC systems. Unlike traditional GFM and GFL controls, which must be carefully assigned to individual IPC terminals, dual-port GFM control imposes a stable voltage on both AC and DC terminals, making it suitable for deployment across all IPCs regardless of network configuration. The findings of this study indicate that dual-port GFM control offers several significant benefits, making it a promising solution for enhancing HVDC systems’ stability and dynamic performance.
  
• SALDAÑA GONZÁLEZ, ANTONIO EMMANUEL: Supervised Learning for Optimal Investment Planning in Active Distribution Networks
  
  Author: SALDAÑA GONZÁLEZ, ANTONIO EMMANUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: SUMPER, ANDREAS | ARAGÜÉS PEÑALBA, MÒNICA
  Thesis abstract: Due to the exponential growth of electric vehicles and distributed generation in distribution networks, potential congestion in power lines, transformers, and voltage deviations is expected to increase in the coming years. For this reason, the development of modern distribution planning strategies to strengthen grid infrastructure needs to be studied, considering its dynamics and impacts.This thesis proposes a simulation-based optimization model for active distribution network expansion, capturing nonlinear complexities through AC power flows, voltage stability, and operational constraints. The formulation includes an objective function, constraints, and both traditional and flexible planning actions, focusing on determining the optimal battery power and capacity over projected horizons to defer infrastructure investments.Additionally, this thesis reviews and compares smart grid measurement devices based on their technical specifications and potential applications in distribution network operation and planning. A recurrent neural network model is also presented for medium- and long-term load forecasting using historical consumption data from medium-voltage (MV) transformer stations. This forecasting model was later integrated with an investment planning model to compare passive and flexible reinforcement actions in a real case study in Spain.Finally, supervised learning models (Random Forest, XGBoost, LSTM, and SVM) were trained using the proposed optimization model to predict and minimize investment costs, thereby identifying the most effective approach for DSO planning applications. This methodology was tested on a CINELDI network under various electric vehicle charging expansion scenarios and is intended for use in connection request applications.
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• ÁLVAREZ GONZÁLEZ, ANA: BIOFERTILIZERS AND BIOSTIMULANTS FROM MICROALGAE GROWN IN WASTEWATER Characterization and Agronomic Trials
  
  Author: ÁLVAREZ GONZÁLEZ, ANA
  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: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: UGGETTI, ENRICA
  Thesis abstract: Chemical fertilizers have played a crucial role in modern agriculture, enabling high productivity rates to meet the demands of a rapidly growing global population. However, it is now evident that its overuse poses significant environmental risks. Biofertilizers have emerged as a promising alternative. Microalgae are photosynthetic microorganisms that show great potential as biofertilizers. They can survive in diverse environments, including wastewater. Using microalgae in wastewater treatment not only produces treated water suitable for reuse, but also generates microalgal biomass that can be converted in valuable bioproducts, including biofertilizers. Moreover, microalgae can produce compounds that function as biostimulants. This doctoral thesis aims to contribute to sustainable agriculture by developing biofertilizers and biostimulants derived from microalgae cultivated in wastewater. The research demonstrates that microalgae can act as an environmentally friendly, effective, and safe alternative to chemical fertilization. First, a microalgal biomass was grown using urban wastewater in 470L High Rate Algal Pond (HRAP) and analyzed in order to study its safety. The nutrient content was: 7.6% N, 1.6% P, and 0.9% K. The biomass did not present pathogens and the content of heavy metals was below the threshold established by the Regulation (EU) 2019/1009. Out of 29 organic compounds analyzed in wastewater and only 3 of them (caffeine, hydroxycinnamic acid, and bisphenol A) were found in the biomass. Then, the efficacy of the biomass as a biofertilizer was studied in two agronomic trials, in a greenhouse, using basil and lettuce plants. These experiments concluded that the best results were obtained by mixing the biomass with the chemical fertilizer, which allowed to reduce the dose of fertilizer by 50%. Then, a novel biofertilizer was also developed by encapsulating microalgae in an organic matrix (polylactic acid) using nanotechnology, in order to make slower the release of nutrients. A nutrient release experiment was performed and the results showed that the encapsulation successfully reduced the nutrient release rate. A life cycle and economic analysis were performed comparing lettuce production using microalgae biofertilizers with inorganic fertilizer. The life cycle assessment revealed that the production of lettuce with the microalgal biomass produced in a wastewater treatment plant has less impact in 10 out of 11 impact categories than the production of lettuce with inorganic fertilizer (ammonium nitrate in this case). The biofertilizer was cost-competitive, being potentially 30% cheaper than inorganic fertilizers. Finally, the microalgal biomass was also studied as a source of biostimulants compounds. Three microalgal strains (Scenedesmus sp., Synechocystis sp., and Phormidium sp.) were grown in wastewater using closed photobioreactos of 2.5L. The results showed that the three strains produced similar phytohormones profile, with indole-3-acetic acid (IAA) being the most abundant. The three strains produced a higher concentration of proteins than carbohydrates. Scenedesmus sp was then grown in the 470L HRAP using wastewater. This biomass presented a high concentration of phytohormones, in particular cytokinins (TZ, 21 mg/gDW) and auxins (IAA, 7 mg/gDW). The microalgal extracts were applied to 35-days-old lettuce plants, some of which were subjected to draught stress. The results showed no significant differences for stressed plants. Plant growth was also compared to a control group that received tap water instead of the microalgal extract. In this case, fresh weight increased by 12–13% when microalgae extracts were applied.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• VIDAL MONTES, RUBÉN: Thermo-Hydro-Mechanical-Chemical Impacts of High-Temperature Aquifer Thermal Energy Storage
  
  Author: VIDAL MONTES, RUBÉN
  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: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: OLIVELLA PASTALLE, SEBASTIAN | SAALTINK, MAARTEN WILLEM
  Thesis abstract: High Temperature Aquifer Thermal Energy Storage (HT-ATES) involves the injection and extraction of non-isothermal fluids into aquifers and triggers thermo-hydro-mechanical-chemical processes. These processes must be analysed and understood for obtaining safe and efficient HT-ATES systems. This thesis aims to deepen the understanding of these processes, provide methods and solutions that can be easily and straghtforwardly implemented, for assessing the impact and feasibility of these systems and iii) forecast the system's long-term performance.First, the coupled thermo-hydro-mechanical finite (THM) element code CODE_BRIGHT has been verified against several tests of a benchmark for thermo-hydraulic processes (TH) in geothermal situations. This code has been used in the development of other methods of the thesis. It has been showed that CODE_BRIGHT is competent in performing all these tests.Second, a method that can be used to develop analytical and semi-analytical solutions for calculating reaction rates for non-isothermal cases has been developed. The method assumes that aqueous and mineral reactions are in equilibrium. The chemistry has been decoupled from the TH processes. In the chemical part of the method, batch calculations are performed to obtain dissolution or precipitation of minerals and water chemistry changes due to temperature variations. The TH part consists of calculating temperature and spatial and temporal derivatives of temperature. From this, one can easily calculate both the chemical composition of groundwater and the rates of mineral precipitation or dissolution. The method facilitates comprehension of the dominant reactive transport processes, mineral reaction rates and porosity changes. The application of this method for simulating a HT-ATES system resulted in a reduction of computational costs by a factor of seven compared to a conventional coupled thermo-hydro-chemical numerical code.Third, a dimensional and numerical analysis of the THM behaviour of a pilot HT-ATES system has been proposed. Three dimensionless numbers that could be easily implemented have been obtained: Peclet number and two numbers for the hydraulic and thermal strains. The Peclet number, which has been decomposed in conductive and dispersive terms, is useful to identify the dominant TH flux (advection, dispersion or conduction). Hydraulic and thermal strains numbers relate the strain generated by changes of hydraulic head and temperature, respectively, with respect the initial total strain of the system. This study's findings have revealed information about the main TH fluxes and their domain areas, evolution of the energy efficiency of the system over time and the role of the hydraulic and thermal loads generated by the injection and extraction of hot water in the vertical displacement of the terrain. The study has provided information about the behaviour and efficiency of the system to long term operation.Finally, an analytical solution for calculating ground surface uplift due to point non-isothermal injections which takes into account thermal and hydraulic head changes has been presented. The main advantage of this solution is its easy implementation in a superfast way, in terms of computational cost, in comparison to a standard thermo-hydro-mechanical code. This solution has been verified satisfactorily against results from a coupled THM numerical model and field data (levelling and PS-INSAR) in a leakage case in a geothermal power plant. The results have demonstrated the contribution of hydraulic head and temperature to ground surface displacements and have facilitated an understanding of the effect of the natural geothermal gradient. The solution is useful for forecasting ground displacement resulting from point injections and extractions under various conditions and time scales.
  
• ZHANG, SHENG: Study on rock fragmentation mechanism and ball loading parameter matching in ball mill
  
  Author: ZHANG, SHENG
  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: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: RODRIGUEZ DONO, ALFONSO
  Thesis abstract: AbstractRock fragmentation in ball mills is a key topic in rock mechanics with broad scientific and engineering significance. However, the understanding of the mechanical mechanisms and ball loading optimization based on dynamic and static principles is still incomplete. The dynamic changes in both rock and ball sizes during milling add complexity, while the process involves multiple breakage mechanisms, including abrasion, compression, and impact. This study examines rock fragmentation characteristics and mechanisms under these three types of forces.(1) The indentation of spherical indenter on rock was studied through laboratory experiments and CODE_BRIGHT numerical simulations, revealing the transition of rock failure from a " jump-type " to a plastic deformation mode under the influence of indenter size. The mechanical mechanisms of rock fragmentation during spherical indentation were analyzed in terms of fracture characteristics and stress fields. (2) The fragmentation characteristics of rock under the impact of spherical indenters of varying sizes were analyzed, and an energy model for indenter impact fragmentation based on fractal theory was established. The mechanical mechanism of spherical indenter-induced fragmentation was explained from a mechanical perspective.(3) The stage-wise variation of the multi-fractal characteristics of ball milling particle size under the influence of rock abrasiveness was analyzed. Based on abrasiveness tests and PFC2D numerical simulations, the wear characteristics and evolution patterns of steel balls in the ball milling process were quantitatively described.Subsequently, a ball charge parameter calculation method was proposed based on the energy consumption laws of spherical indentation impact and compression. Building on this, a ball replenishment strategy based on Markov chain theory was developed and validated through laboratory case studies.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• RABOST GARCIA, GENÍS: Microfluidics for sweat monitoring
  
  Author: RABOST GARCIA, GENÍS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: CASALS TERRE, JASMINA | FARRÉ LLADÓS, JOSEP
  Thesis abstract: This thesis began with the goal of revolutionizing continuous monitoring through the use of sweat. Over the course of this research, the field of sweat monitoring has evolved significantly, being consolidated as the most convenient non-invasive alternative to blood analysis. This thesis compiled the knowledge acquired during these years across different areas related to the design of a microfluidic sweat platform.Initially, a perspiration model was developed as an in vitro experimental setup to enable realistic and cost-effective testing of microfluidic sweat platforms. Sweat gland dimensions and structure were replicated using on-plane soft lithography, solving the fabrication challenges associated. A functional prototype was successfully operated with appropriate skin surface characteristics, demonstrating its use with adhered microfluidic devices. A microfluidic platform integrating custom electrochemical sensors was developed for the measurement of sweat volume, sweat conductivity and sweat lactate. Continuous monitoring has been proven for extended periods of time (exceeding 1 hour) with robustness and reproducibility. This system was incorporated into a complete wearable device featuring remote communication and embedded computation, becoming a novel tool for sports monitoring. The device was validated in on-body trials to assess the accuracy of the output parameters to the final user, for both sweat-based variables (sweat loss, sodium and sodium loss) and blood bioequivalence predictions (lactate).Additionally, a novel microfluidic design for the chrono-sampling of sweat was explored in vitro. It combines a passive valve and pump to renovate the volume in a sensing chamber in a cyclic manner. The mismatch between the absorption rate of the passive pump and the sweat generation at the inlet was found to disconnect the fluid, restoring the passive valve function once surpassed. The system's characteristics can be adjusted to different requirements by modifying the valve widths or passive pump properties. However, the fabrication of this design requires high resolution, which can limit throughput and complicating the current large human testing involved in a microfluidic sweat platform. Therefore, new materials and fabrication techniques at the laboratory were explored to reduce the design to test time and enhance production capacity. In summary, the initial vision of a novel microfluidic sweat wearable platform capable of providing non-invasive, real-time measurements of a variety of biomarkers has been accomplished. Moreover, several promising research lines have emerged, including advancements in perspiration models, microfluidic design, fabrication scalability and algorithm development. Finally, this research has led to the development of a commercially available product, demonstrating that continuous monitoring through sweat is now a market-ready technology.
  

DOCTORAL DEGREE IN PHOTONICS

• HEITHOFF, MAXIMILIAN: Exciton engineering for quantum confinement in an electrostatically defined PN-junction
  
  Author: HEITHOFF, MAXIMILIAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 26/03/2025
  Deposit END date: 08/04/2025
  Thesis director: KOPPENS, FRANK | RESERBAT-PLANTEY, ANTOINE
  Thesis abstract: We investigate the physics of quantum-confined excitons in an electrostatically defined PN junction. Such a PN junction can be generated in an encapsulated monolayer \MoSe{} along the patterned edge of a top-gate electrode. Applying a voltage gradient between the top and bottom gates results in the formation of an in-plane electric-field gradient in the depletion region and strong doping gradients in the P- and N-doped regions of the PN junction. The exciton experiences an attractive force within the electric field gradient and repulsion from exciton-charge carrier interactions. The combined effects are sufficiently strong to quantize the number of available excitonic states within the potential. We show measurements of these quantum-confined excitons in reflection contrast and photoluminescence spectroscopy. We demonstrate how the confinement potential results in fine structure splitting with linearly polarized excitonic states that are aligned either along or perpendicular to the top gate edge. The states can be gradually tuned between linear and circular polarization using an out-of-plane magnetic field. Our particular sample geometry, where the formation of the PN junction electrically isolates the sample from ground, allows us to investigate the electrostatic model of a photo-biased PN junction, with the bias voltage as an additional tuning parameter of the confinement potential. The bias voltage is modified by the measurement itself and varies with the location of the measurement. We demonstrate how the combined impact of exciton dissociation and Auger-assisted hot-hole tunneling modifies the bias voltage over a timescale up to $\qty{100}{\s}$. The bias voltage can be further controlled using a second laser, which enables the tuning of the energy of the quantized states over the range of $\qty{15}{\meV}$. Ultimately, these findings allow us to simulate the exact shape of the confinement potential and to investigate how the in-plane electric field modifies the internal exciton structure, impacting the exciton oscillator strength, lifetime, and dissociation. The results of this thesis illustrate the possibilities to pattern tailored exciton potential shapes for photonic and quantum technologies.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• PÉREZ PORTERO, ADRIÁN: Contributions to RFI detection, mitigation, and excision for GNSS receivers and spaceborne microwave radiometers
  
  Author: PÉREZ PORTERO, ADRIÁN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 24/03/2025
  Deposit END date: 04/04/2025
  Thesis director: CAMPS CARMONA, ADRIANO JOSE | PARK, HYUK
  Thesis abstract: Radio Frequency Interference (RFI) poses significant challenges to remote sensing systems, particularly affecting Global Navigation Satellite System-Reflectometry (GNSS-R) and microwave radiometry. This thesis advances two interconnected areas of remote sensing: geophysical parameter retrieval using signals of opportunity and RFI impact assessment on Position, Navigation, and Timing (PNT) systems. The research develops novel approaches for RFI detection, mitigation, and excision across multiple remote sensing platforms, with particular emphasis on space-qualified systems.The first part of this work advances GNSS-R instrumentation through the development of an experimental testbed and simulator. Laboratory measurements in controlled environments provided critical insights into GNSS-R signal characteristics, enabling systematic validation of signal processing algorithms. The research demonstrates the feasibility of continuous Earth observation through opportunistic platforms, specifically integrating GNSS-R instruments in commercial aviation for applications including weather nowcasting and maritime route optimization. Analysis of polarimetric data revealed significant limitations in current receiver architectures, particularly in processing Left-Hand Circular Polarization (LHCP) signals and reconstructing Stokes parameters. This continued with work conducted at JPL in 2023, analyzing data from the SMAP-R mission which modified its radar payload for GNSS-R reception. The dual capability for forward and backward scattering measurements from the same platform enabled comparative analysis of scattering mechanisms. Leveraging SMAP-R's fully polarimetric reflectometry measurements, we investigated bistatic radar scattering characteristics across varied surface conditions. The analysis focused on two aspects: comparing scattering regime behaviors across different terrains, and developing a prediction model that derives backward-scattering characteristics from forward-scattering measurements. This work extends the theoretical understanding of bistatic scattering mechanisms while providing validation through spaceborne measurements.The second part addresses RFI challenges through three complementary approaches: spectrum monitoring systems, hardware-efficient algorithms, and polarimetric detection methods. A key contribution is the development of an automatic RFI Detection, Location, and Classification (RFIDLC) system for GNSS bands, utilizing a six-sector antenna array design for real-time processing between 1525 and 1625 MHz. For Synthetic Aperture Radar (SAR) applications, novel algorithms operating on 1-bit quantized signals enabled RFI mitigation despite severe quantization effects. The FPGA implementation achieved significant resource reduction through innovative overclocking and serialization techniques while maintaining space qualification requirements.A major advancement is the development of the Polarimetric Kurtosis detector for microwave radiometry, extending conventional kurtosis-based detection to the full-polarimetric domain through a four-dimensional measurement derived from Stokes parameters. This technique demonstrates enhanced sensitivity to polarized interference signals, particularly in scenarios where conventional detection methods show limitations. The research validates these approaches through experimental testing on both ground-based and spaceborne platforms, establishing a foundation for future RFI mitigation systems in space-based Earth observation missions.
  
• ROIG MARÍ, CARLOS: Instance-level Recognition for Image Understanding
  
  Author: ROIG MARÍ, CARLOS
  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: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: MARQUES ACOSTA, FERNANDO | VARAS GONZÁLEZ, DAVID
  Thesis abstract: Image understanding is a fundamental task in computer vision as it aims to enable machines to visually comprehend the real world. In this thesis, the task of image understanding is addressed through the combination of instance-level recognition systems and Large Multimodal Models (LMMs). To do so, the thesis is structured in three parts, starting with a study of deep metric learning techniques for creating rich image embeddings spaces. Then, the implementation of instance-level recognition systems specifically focused on landmark recognition using content-based image retrieval. And finally, enhance the capabilities of LMMs by incorporating instance-level recognition results in order to generate improved image descriptions with instances. The first part of this thesis focuses on advancing deep metric learning methods. A novel Smooth Proxy-Anchor Loss is proposed to address the problem of having noisy labels in training data. The proposed loss introduces confidence-based sample weighting, soft proxy assignment, and adaptive margins to mitigate the negative impact of mislabeled samples, demonstrating superior performance on real-world data. Building on top of this foundation, the thesis extends the selective weighting of samples to a selective weighting of features, through the Generalized Local Attention Pooling (GLAP) method. GLAP dynamically weights different regions of feature maps according to their informational content, enabling better representation learning while reducing computational requirements. Evaluations on multiple benchmark datasets show the significant improvements of using GLAP over state-of-the-art approaches.The second part introduces the Multi-Scale Transformer-based Feature Combination (MSTFC) method for instance-level landmark recognition. This approach applies a transformer-based attention mechanisms to select and combine relevant information from feature maps. These feature maps are extracted from multiple scales and have different spatial resolutions. The combination of these multi-scale feature maps results in a compact global representation that is used for image retrieval. The MSTFC method achieves a superior performance on the challenging landmark retrieval datasets, outperforming existing approaches on the Google Landmarks Dataset v2 and the Revisiting Oxford and Paris benchmarks.Finally, the thesis explores the enhancement of Large Multimodal Models by incorporating instance-level recognition results to generate more accurate and detailed image descriptions. By bridging specialized instance-level recognition systems with the generic understanding capabilities of LMMs, this integration demonstrates how domain-specific computer vision techniques can be combined with multimodal techniques for comprehensive image understanding.Through these contributions, the thesis advances the field of image understanding across multiple levels, from robust feature learning in real-world noisy dataset, to effective techniques for combining the information of feature maps in deep metric learning, then expanded to multi-scale representation for instance-level recognition, and ultimately to the integration of specialized instance-level systems with modern multimodal frameworks.
  
• SARMIENTO CALDERÓ, MANUEL: Contextualization of Spatio-temporal Action Localization Systems and Media Content Applications
  
  Author: SARMIENTO CALDERÓ, MANUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 02/04/2025
  Deposit END date: 15/04/2025
  Thesis director: MARQUES ACOSTA, FERNANDO | VARAS GONZÁLEZ, DAVID
  Thesis abstract: Spatio-temporal action localization is a field of computer vision that determines both the spatial and temporal locations of actions taking place within a video. This particular task is one of the cornerstones of video understanding due to its inherent complexity. Impressive scientific advances in the artificial intelligence and computer vision industry have led to a significant performance increase.Nevertheless, even state of the art systems struggle to recognize actions that involve some kind of interaction between people, objects, or with the scene. This limitation arises because current spatio-temporal action localization models neglect contextual information when identifying a person's actions. Specifically incorporating contextual cues in these models can help to address this challenge. Furthermore, the integration of spatio-temporal action localization systems into multimedia content applications presents several challenges. The primary difficulties lies in finding ethical and practical use cases and addressing the computational requirements to run these models in production.The goal of this industrial PhD is to solve the above problems. The lack of contextual information is addressed in different forms. This thesis, is focussed on two different approaches. First, a novel system to explicitly model the relations of the different actors and objects in a scene, which includes a novel structure to model long-term temporal information is proposed. Second, an innovative multi-modal method to combine task specific features to improve action recognition is introduced. These developed contextualization systems are evaluated on different datasets. The results demonstrate the effectiveness of the proposed systems. Regarding the applications, this PhD is focused on finding, implementing and exploiting specific applications of spatio-temporal localization system for media content. The developed applications consists of an improved system for search and recommendations on video content, an smart cropping method to generate image and videos of any desired aspect ratio from another video, and the improvement of a system to generate highlight keyframes of football matches.
  
• WOODWARD RIQUELME, ALEJANDRO BENJAMÍN: Contextual Speech Recognition
  
  Author: WOODWARD RIQUELME, ALEJANDRO BENJAMÍN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 02/04/2025
  Deposit END date: 15/04/2025
  Thesis director: MARQUES ACOSTA, FERNANDO | VARAS GONZÁLEZ, DAVID
  Thesis abstract: Although Automatic Speech Recognition (ASR) technology has achieved remarkable improvements in transcription accuracy in recent years, it still struggles to correctly transcribe certain words. In particular, proper nouns often exhibit lower accuracy due to their unique pronunciations and alternative spellings. To address these challenges, contextualisation is commonly integrated into ASR models to improve the transcription of rare proper nouns and disambiguate between similar-sounding proper nouns.This industrial PhD thesis focuses on the development of contextualisation systems for ASR models. The ASR technology employed in this thesis is used to generate automatic transcripts for podcast content. The objective of the contextualisation system is to improve the accuracy of proper nouns; for example, the names of podcast shows, hosts, and guests.The contextualisation system developed in this thesis is composed of two parts. First, an ingestion pipeline gathers proper nouns relevant to the podcast episode to be transcribed. This pipeline has an automated component that extracts proper nouns from the metadata of each podcast episode, such as the title and description, using tools like a named entity recogniser. Additionally, a module that allows the manual addition of proper nouns to specific podcast shows has been developed. The second part, which represents the most relevant contribution of this thesis, is a novel ASR contextualisation algorithm based on deep neural networks. The contextualized ASR model utilises the gathered proper nouns, resulting in an improvement in accuracy when compared to the same model without contextualization capabilities.The accuracy of the ASR system developed in this thesis is evaluated and analysed using episodes from popular public podcast shows. A human evaluation of the word error rate was employed during this assessment.This evaluation compares the quality of the ASR model system's transcripts to those provided publicly by the podcast content creators. The results show that the system developed in this thesis produces transcripts that contain four times fewer errors than the transcripts offered by podcast hosting providers.The contextualization method is also evaluated on a public dataset and compared to state-of-the-art methods. The results show that the contextualization method proposed in this thesis significantly outperforms the existing systems.
  

DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH

• PACHÓN GARCIA, CRISTIAN: Contributions on dimensionality reduction and interpretable machine learning
  
  Author: PACHÓN GARCIA, CRISTIAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH
  Department: Department of Statistics and Operations Research (EIO)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: DELICADO USEROS, PEDRO FRANCISCO
  Thesis abstract: This thesis is divided into two parts. The first one is devoted to dimensionality reduction for large data sets, while the second one focuses on the field of Interpretable Machine Learning. Part of the material presented in this thesis has been published either in journals or workshops. Concretely, the original work of Chapter 1 can be found in Delicado and Pachón-García (2024a). Regarding Chapter 3, the original publication is Pachón-García et al. (2024) and the material of Chapter 4 is Hernández-Pérez et al. (2024). Finally, Chapter 5 is intended to be sent to a journal, but Delicado and Pachón-García (2024b) is a preprint version.To begin with, we present a set of algorithms implementing multidimensional scaling (MDS) for large data sets. MDS is a family of dimensionality reduction techniques using a n×n distance matrix as input, where n is the number of individuals, and producing a low dimensional configuration: a n × r matrix with r << n. When n is large, MDS is unaffordable with classical MDS algorithms because their extremely large memory and time requirements. We compare six non-standard algorithms intended to overcome these difficulties. They are based on the central idea of partitioning the data set into small pieces, where classical MDS methods can work. Two of these algorithms are original proposals. In order to check the performance of the algorithms as well as to compare them, we have done a simulation study. In addition, an open-source R package implementing the algorithms has been created.Regarding the field of machine learning (ML), it is worth noting that its presence in our society is increasing, which brings with it the need to understand the behaviour of ML mechanisms, including machine learning predictive algorithms fed with tabular data, text, or images, among other types of data. Therefore, this thesis focuses on the problem of interpretability. On the one hand, we present SurvLIMEpy, an open-source Python package that implements the SurvLIME algorithm. This method allows to compute local feature importance for machine learning algorithms designed for modelling Survival Analysis data. The presented implementation uses a matrix-wise formulation, which allows to speed up the execution time. Additionally, SurvLIMEpy assists the user with visualisation tools to better understand the result of the algorithm. The package supports a wide variety of survival models, from the Cox Proportional Hazards Model to deep learning models such as DeepHit or DeepSurv. We study the ability of the algorithm to capture the importance of the features by means of a simulation study.With the goal of employing SurvLIMEpy, we train and compare three types of machine learning algorithms for Survival Analysis: Random Survival Forest, DeepSurv and DeepHit, using the SEER database to model cutaneous malignant melanoma. Our work underscores the importance of explainability methods for interpreting black-box models and provides insights into important features related to melanoma prognosis.On the other hand, we consider the field of Functional Data Analysis in order to provide it with interpretability tools. Designing interpretability methods for functional data models implies working with a set of features whose size is infinite. In the context of scalar on function regression, we propose an interpretability method based on the Shapley value for continuous games, a mathematical formulation that allows to fairly distribute a global payoff among a continuous set players. The method is illustrated through a set of experiments with simulated and real data sets. The open source Python package ShapleyFDA is also presented.
  

DOCTORAL DEGREE IN STRUCTURAL ANALYSIS

• TAHERZADEH FARD, ALIREZA: On the study of delamination and failure of composite materials under static and cyclic loads
  
  Author: TAHERZADEH FARD, ALIREZA
  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: Normal
  Deposit date: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: BARBU, LUCIA GRATIELA | OÑATE IBAÑEZ DE NAVARRA, EUGENIO
  Thesis abstract: Composite materials, particularly fiber-reinforced polymers and fiber metal laminates have gained significant attention in industries such as aerospace, automotive, and marine engineering due to their high strength-to-weight ratio, excellent fatigue resistance, and corrosion durability. Despite these advantages, their structural performance is often limited by various damage mechanisms, including fiber failure, matrix cracking, and delamination. Among these, delamination is one of the most critical failure modes, as it can significantly compromise structural integrity. The accurate prediction and modeling of delamination and its interaction with other damage mechanisms remain a major challenge in the field of computational mechanics. This thesis aims to develop a robust constitutive model capable of predicting these failure mechanisms within a homogenized framework, enabling computationally efficient and physically realistic simulations.The research begins with an extensive evaluation of existing models for intra-laminar and inter-laminar damage mechanisms. Conventional modeling approaches, including stress-strength-based criteria, fracture mechanics methods, and cohesive zone models, are examined to determine their suitability for delamination damage prediction. By utilizing previously developed numerical frameworks within Kratos Multiphysics, the fundamental aspects of damage modeling are explored and benchmarked against experimental data. The key challenge addressed in this thesis is the integration of these theories into a homogenized computational approach, which eliminates the need for explicit layer-wise modeling while preserving accuracy in capturing damage initiation and propagation.To achieve this, a delamination homogenization theory is developed, allowing for the efficient representation of inter-laminar failure without the computational burden of explicitly modeling each interface. This framework is further extended to cyclic loading conditions, where fatigue-induced damage plays a crucial role in long-term structural degradation. The fatigue model incorporates a damage evolution law calibrated against experimental S-N curves, enabling the accurate prediction of crack growth rates (da/dN) under various loading conditions. The proposed methodology is validated through standardized benchmark test cases, demonstrating its capability in capturing both intra-laminar and inter-laminar damage progression.The applicability of the developed model is assessed through a series of component-level simulations to ensure its real-world usability. One of the primary case studies involves the open-hole problem, a well-known benchmark in composite mechanics, which is analyzed under both tensile and bending conditions. These simulations help evaluate stress concentration effects and the initiation and growth of delamination cracks. Additionally, a cross-beam member—previously studied with a steel material—is reanalyzed using a composite material, incorporating both delamination and intra-layer damage mechanisms. These case studies illustrate the efficiency and accuracy of the homogenized approach in predicting failure mechanisms under complex loading and geometrical conditions.The findings of this research contribute to the advancement of composite damage modeling by offering a computationally efficient framework for predicting delamination and intra-laminar damage. The homogenized approach significantly reduces preprocessing complexity while maintaining a high level of accuracy in failure prediction, making it particularly suitable for large-scale structural applications. Future research directions include incorporating fiber bridging effects, extending the framework to dynamic and thermal loading conditions, and utilizing mixed strain/displacement finite elements. Additionally, the application of machine learning techniques to enhance predictive capabilities presents an exciting avenue for further investigation.
  

DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION

• GARCÍA HARO, ALAN: Isla de frío de los parques urbanos: Hacia la definición de parámetros de composición para la optimización del efecto de enfriamiento en distintos contextos climáticos mediante análisis remoto
  
  Author: GARCÍA HARO, ALAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 02/04/2025
  Deposit END date: 15/04/2025
  Thesis director: ROCA CLADERA, JOSE NICASIO | ARELLANO RAMOS, BLANCA ESMARAGDA
  Thesis abstract: Due to their composition, generally characterized by the predominant presence of vegetation and permeable soils, urban parks exhibit lower temperatures compared to other areas of the city. In many cases, this thermal reduction extends to the surrounding areas, generating the phenomenon known as the "park’s cool island" (PCI). This effect makes parks essential elements for regulating and mitigating urban heat, a problem exacerbated by the urban heat island effect, the global increase in temperatures, and the growing frequency and intensity of extreme heat events associated with climate change. These situations pose significant threats to public health, disproportionately affecting vulnerable groups and increasing heat-related mortality rates. Moreover, the limited availability of updated and detailed climatic data hinders the planning and design of effective mitigation strategies at the local level.This research aims to establish design parameters that optimize the cool island effect of urban parks (PCI) in various climatic contexts, employing remote sensing techniques. To achieve this, a flexible methodology was developed based on satellite data analysis and statistical models, adaptable to both the availability of information and the specific characteristics of each case study. The methodology is structured into three main stages: 1) quantification of the intensity and spatial extent of the cool island effect generated by parks; 2) estimation of physical descriptors derived from remote sensing data; and 3) statistical analysis of the influence of the physical characteristics of parks and their surroundings on cool island effect indicators.This study focuses on the cases of Barcelona (Mediterranean climate) and Mexicali (hot arid climate), selected for their contrasting climatic conditions and differing levels of institutional data availability. Initial results reveal that in Barcelona, with 86 urban parks, the average daytime summer PCI intensity was 1.51°C with a spatial extent of 78.02 meters, whereas Mexicali, with 435 parks, recorded an intensity of 0.90°C and a spatial extent of 119.03 meters. A notable contrast emerges in these parameters, as two parks in Barcelona showed no cool island effect (2.3%), while in Mexicali, this number increased to 133 parks (30.6%). The results demonstrate that vegetation is the primary regulator of urban temperature in both cities. In Mexicali, explanatory models incorporating variables derived from NDVI and supervised land cover classification using Random Forest achieved R² values exceeding 90% in spring and summer. In Barcelona, although NDVI was also relevant, the analysis highlighted limitations related to proximity to the sea and forested areas.In conclusion, this research establishes a methodological framework to define design parameters for urban parks using remote sensing data, tailored to the functional and temporal needs of each context. This represents a significant step toward developing specific tools for urban planning decision-making, integrating key considerations for regulating and mitigating urban heat.