Doctoral School

Reading date: 24/06/2026

• ERBS, FLORENCE AMANDINE: AI-enhanced Passive Acoustic Monitoring of Tropical Freshwater Environments
  
  Author: ERBS, FLORENCE AMANDINE
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 28/05/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: ANDRE SANCHEZ, MICHEL
  Thesis abstract: Tropical freshwater ecosystems, particularly in the Amazon basin, are among the world’s most vulnerable environments, facing escalating pressures from human activities such as overexploitation, pollution, and habitat degradation. Effective conservation efforts are constrained by the scarcity of long-term monitoring data, as traditional visual survey methods are often unsuitable for the high turbidity of Amazonian waters and the complex floodplain habitat mosaics where seasonally inundated lakes, channels, and forests make species detection challenging. This dissertation addresses these challenges by developing an innovative and scalable monitoring framework using Artificial Intelligence (AI)-enhanced Passive Acoustic Monitoring (PAM) focused on three ecological indicator species: the pink river dolphin (Inia geoffrensis), the tucuxi (Sotalia fluviatilis), and the Amazonian manatee (Trichechus inunguis).The research is presented as a compendium of two scientific publications that integrates longterm autonomous acoustic monitoring with Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), to automate species detection in complex and noisy freshwater soundscapes. The first study focuses on Amazonian river dolphins, exploiting their near-continuous production of echolocation clicks for presence detection. The developed CNN classifier achieved a high average precision of 0.95 and successfully discriminated between dolphin clicks and impulsive interferences like rain and boat engine noise. This automation enabled the tracking of synchronized seasonal movements into floodplain bay and river channel habitats following the annual flood pulse. Furthermore, the study provided rare insights into the seasonal use of flooded forests revealing regular dolphin presence during high-water periods. Additionally, it quantified the spatio-temporal overlap between dolphins and boat traffic, establishing a baseline for assessing anthropogenic noise exposure in core habitats.The second study applied a similar AI-enhanced approach for detecting the Amazonian manatee, a cryptic species characterized by inconspicuous surfacing behavior and a previously poorly described vocal repertoire in the wild. By training a CNN model on wild vocalizations, the research provided the first detailed characterization of the wild Amazonian manatee’s vocal repertoire, identifying four distinct call types, and leading to new insights into the vocal behavior of the species in the floodplains. The analysis of vocal parameters, including repetition rates and frequency characteristics, revealed that Mamirau´a Lake, where the species was presumed absent, serves as a critical nursery habitat.This dissertation demonstrates that the integration of PAM and machine learning offers a noninvasive, cost-effective, and performant tool for monitoring biodiversity in remote tropical freshwater environments. The transition from manual acoustic analysis to automated processing allows for efficient conversion of high-volume acoustic datasets into ecological insights, facilitating the identification of critical habitats, supporting the understanding of floodplain ecological processes, and advancing the assessment of anthropogenic impacts and ecosystem health. These findings provide a robust foundation for a standardized Amazonian monitoring framework to support evidence-based conservation for these endangered species and their ecosystems.
  

Reading date: 25/06/2026

• GAMARRA GAMARRA, MARÍA DEL PILAR: Comportamiento Ético: Identidad Moral, Atención Moral y su papel en la Construcción del Liderazgo Ético
  
  Author: GAMARRA GAMARRA, MARÍA DEL PILAR
  Programme: DOCTORAL DEGREE IN BUSINESS ADMINISTRATION AND MANAGEMENT
  Department: Department of Management (OE)
  Mode: Normal
  Deposit date: 30/04/2026
  Reading date: 25/06/2026
  Reading time: 15:30
  Reading place: Seminari 1 DOE - Planta 7 de l'ETSEIB-UPCDefensa, acte públic: meet.google.com/afg-drtc-azc
  Thesis director: OLIVELLA NADAL, JORGE | GIROTTO, MICHELE
  Thesis abstract: When a leader acts without ethics, the entire organization is shaken; when leadership is exercised with integrity, it inspires sustainable cultures and strengthens social trust. This doctoral thesis addresses the challenge of understanding how leaders perceive and enact their own ethical behavior, focusing on two fundamental internal drivers: moral identity and moral attentiveness. These factors, often invisible in everyday organizational discourse, distinguish formal leadership from authentic leadership capable of generating legitimacy, resilience, and commitment in complex contexts.The research is grounded in a clear diagnosis: financial scandals, corporate misconduct, and growing social demands for transparency have placed ethics at the center of the business agenda. However, most previous studies have examined ethical leadership from the perspective of subordinates or within Anglo-Saxon contexts, leaving aside the leader’s own viewpoint and the analysis of specific cultural realities such as the Spanish context. This is the gap that the thesis seeks to address.The study is developed in two phases. The first presents a bibliometric analysis and a systematic review of more than thirty years of scientific literature, identifying three theoretical pillars of ethical leadership: values-based theories, cognitive moral development theory, and social learning theory. This review highlights the fragmentation of existing approaches and the scarcity of empirical studies focused on leaders’ self-perceptions, as well as the need to incorporate variables such as gender, age, and hierarchical level.The second phase builds an empirical model applied to the Spanish context. To this end, the classic ethical leadership scale is psychometrically validated and adapted to leaders’ self-perceptions through exploratory and confirmatory factor analyses, reliability tests, and structural equation modeling. The process includes expert review, pilot testing, and the administration of questionnaires to a sample of managers from different sectors. The result is a robust, context-adapted scale that identifies three dimensions of self-perceived ethical leadership: integrative decision-making, the reinforcement of ethical behaviors, and the leader’s personal example as a role model.The findings show that moral identity and moral attentiveness significantly influence these dimensions, albeit in different ways. The internalization of moral identity predicts the integration of ethical principles into decision-making, while the symbolization of moral identity and reflective moral attentiveness explain the tendency to reinforce ethical behaviors. In addition, variables such as gender, age, managerial experience, and hierarchical position act as moderators, indicating that ethical leadership emerges through the interaction of personal and professional characteristics.Overall, this thesis demonstrates that ethical leadership is not an abstract code or a superficial discourse, but a practice rooted in the leader’s internal coherence, reflected in decision-making, and projected onto organizational culture, contributing to the development of more just and sustainable organizations.
  

• JULIAN TRUJILLO, EDWIN CRISTIAN: Modelización Flexible y actividad matemática en Ingeniería: análisis de la interpretación, simulación y validación de sistemas dinámicos no lineales
  
  Author: JULIAN TRUJILLO, EDWIN CRISTIAN
  Programme: DOCTORAL DEGREE IN ENGINEERING, SCIENCES AND TECHNOLOGY EDUCATION
  Department: Institute of Education Sciences (ICE)
  Mode: Normal
  Deposit date: 12/05/2026
  Reading date: 25/06/2026
  Reading time: 12:00
  Reading place: Aula ferroviària. 2.08. Edifici VGA. EPSEVGAvda. Victor Balaguer 108800 Vilanova i la Geltrú
  Thesis director: GOMEZ URGELLES, JOAN VICENÇ
  Thesis abstract: The teaching of differential equations in engineering remains marked by a dissociation between procedural rigor and the need to interpret, simulate, and validate dynamic systems in professional settings. This dissertation examines how a Flexible Modeling approach transforms the mathematical activity of engineering students when their work with differential equations shifts away from isolated solution procedures toward exploration, comparison, and model-based justification. Adopting a situated, longitudinal, and mixed-methods design, the study articulated didactic units, computational laboratories, and discipline-based projects, which were analyzed through the triangulation of academic products, artificial intelligence auditing, laboratory work, and technical defenses. The analysis reveals a consistent shift toward forms of mathematical activity centered on parametric sensitivity, dynamic system interpretation, and the technical validation of results. In particular, simulation functioned as an environment for epistemic contrast, while the auditing of automated responses strengthened students’ ability to question results that were inconsistent with the Jacobian, the phase plane, and the physical plausibility of the phenomenon. The dissertation concludes that Flexible Modeling shifts the focus of instruction from algorithmic execution toward interpretation, validation, and technical justification, although this process shows uneven appropriation depending on students’ prior mathematical background. In this sense, mathematics is repositioned as a language of diagnosis and auditing in the age of automation
  

• TANGIRALA, SRI KALYAN: Understanding coupled processes in Unconventional Geothermal Systems for enhancing safety and longevity
  
  Author: TANGIRALA, SRI KALYAN
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Normal
  Deposit date: 27/05/2026
  Reading date: 25/06/2026
  Reading time: 11:00
  Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, Building C1, Room 002, Barcelona
  Thesis director: VILARRASA RIAÑO, VÍCTOR
  Thesis abstract: To scale up electrification using geothermal energy, a widespread deployment of unconventional systems, like Enhanced Geothermal Systems (EGS), is needed even in regions located away from tectonic hotspots. This thesis investigates the coupled processes governing these systems, specially focusing on (i) hydraulic stimulation and associated induced seismicity of natural fracture-based EGS, (ii) heat exchange and economic viability of Closed-Loop Geothermal Systems (CLGS), (iii) long-term circulation in hydraulic fracture-based EGS, and (iv) the optimization of Flow Control Devices (FCDs) to mitigate thermal breakthrough in hydraulic fracture-based EGS and ensure a consistent electricity generation over the lifetime of these systems. Initially, the thesis outlines how the field of geothermal energy evolved throughout the decades in terms of its electricity generation capability from traditional hydrothermal systems to recent developments in hydraulic fracture-based EGS. To explore the influence of total volume of injected water on the maximum-magnitude earthquake in EGS, coupled Hydro-Mechanical (HM) models of shear stimulation of a single pre-existing fracture have been conducted using a suite of injection protocols and injection rates. Simulation results indicate that there is no particular injection protocol better (safer) than the rest in terms of induced seismicity and permeability enhancement. Results suggest that the injection protocol employed has a stronger effect on the maximum magnitude earthquake than total volume of injected water. This thesis evaluates the practical performance of CLGS through coupled Thermo-Hydraulic (TH) models. The assessment focuses on the decline in production temperature and the electricity generation capacity of these systems during long-term circulation, alongside their economic profitability. The results demonstrate that high circulation flow rates, necessary to generate MW-levels of electricity, lead to a rapid drop in production temperature and electricity generation capacity. When combined with very high drilling costs, these factors render CLGS economically unprofitable in regions outside high geothermal gradients, challenging the claims of universal scalability. Finally, the intricacies of the coupled thermo-hydro-mechanical (THM) processes in hydraulic fracture-based EGS during long-term circulation are modeled. Cooling of the rock matrix induces a thermoelastic increase in the apertures of fractures, effectively reducing the pumping power, but that, in turn, might also lead to increasing flow non-uniformity and thermal breakthrough if not managed properly. Measures to prevent thermal breakthrough like the use of FCDs have also been studied. While FCDs increase the required pumping power in the system, they restrict flow non-uniformity during circulation and effectively prevent thermal breakthrough, ensuring a consistent trend in net-electricity generation during the extended lifetime of the EGS project.In summary, this thesis reiterates the importance of understanding coupled processes in subsurface energy systems to enhance both safety and longevity in geothermal operations. By identifying key limitations and proposing physically-grounded strategies to reduce their impacts, this work contributes to extending the lifetime of unconventional geothermal systems for decades beyond the standard 30-year period.
  

• TORRES LERMA, JOSE ANTONIO: Additive manufacturing constraints in topology optimization using a perimeter functional and a null space algorithm
  
  Author: TORRES LERMA, JOSE ANTONIO
  Programme: DOCTORAL DEGREE IN STRUCTURAL ANALYSIS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 19/05/2026
  Reading date: 25/06/2026
  Reading time: 12:00
  Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus North Gran Capitan S/N 08034 Barcelona
  Thesis director: FERRER FERRE, ALEX | OTERO GRUER, FERMÍN ENRIQUE
  Thesis abstract: In the context of lightweight structural design, this thesis addresses the incorporation of additive manufacturing constraints into topology optimization in a simple, general, and computationally efficient manner. In particular, the focus is placed on two key limitations arising in additive manufacturing processes: the minimum length scale and overhang constraints. Existing approaches often rely on complex modifications of the governing physics or on additional mechanical constraints, leading to increased computational cost and implementation complexity.To overcome these limitations, this work proposes a unified framework based on regularized perimeter constraints, which can be consistently applied to both density-based and level-set formulations. To the best of the author’s knowledge, this represents the first extension of perimeter-based methods to the local enforcement of additive manufacturing constraints. Nonlinear smoothing extensions are introduced to solve the overhang constraints, while we include the definition of minimum thickness constraints through an isoperimetric analogy. A dual discretization strategy is also developed to enforce the constraints locally.In parallel, an extended null space optimization algorithm is proposed to efficiently handle the resulting multi-constraint problems while requiring minimal parameter tuning. The method is shown to be applicable to density-based approaches, shape optimization, and level-set methods with topological derivatives. Furthermore, two acceleration strategies are investigated - namely, a subiteration approach and a quasi-Newton method - demonstrating improved convergence behavior through the incorporation of nonlinearities in geometrical functionals.The results show that the proposed methodology provides an effective and computationally efficient framework for enforcing additive manufacturing constraints, while maintaining flexibility across different design representations. The combination of perimeter-based constraints and a robust optimization algorithm offers a promising alternative to existing approaches, particularly for large-scale and complex applications.