Tackling climate change effects worldwide brings the interest of many donor countries with expertise to (co)develop solutions into beneficiary countries through international cooperation. The solutions proposed can be either too solution-driven, understood as a donor country selling its knowledge / products, or on the other hand, too locally problem-driven, which is desirable in theory, but facing practical limitations such as time or scale constraints when closing to outside influences. A methodology that tries to join both (apparently opposing) sides, with their advantages and disadvantages of problem and solution driven hasn’t been explored yet.For exploring how this can be done, in this research 2 case studies are analyzed: the Bangladesh Delta Plan 2100 (BDP2100), a nation-wide long term holistic plan on the Bangladeshi Delta, and a group of Coastal Water Management initiatives, a set of continuous efforts to adopt livelihoods to the dynamic situation in the coastal regions of Bangladesh. These cases are analyzed through interviews and desk research to determine to what extent are they problem and solution driven compared to proposed frameworks and pointing how can they be improved. From these analyses, a combined framework is proposed where problem and solution driven approaches are joined taking the best from each perspective. The result is meant to be a first guiding tool for decision-makers in donor and beneficiary countries that face the dilemma between taking local and foreign elements for developing solutions. Resumen Hacer frente a los efectos del cambio climático en todo el mundo atrae el interés de muchos países donantes con experiencia para (co) desarrollar soluciones en los países beneficiarios, a través de la cooperación internacional. Las soluciones propuestas pueden ser demasiado orientadas a la solución, entendidas como un país donante que vende sus conocimientos / productos o, por otro lado, demasiado localmente orientadas a los problemas, lo que es deseable en teoría, pero enfrentan limitaciones prácticas como limitaciones de tiempo o escala cuando se cierran a influencias externas. Aún no se ha explorado una metodología que intente unir a ambas partes (aparentemente opuestas), con las ventajas y desventajas de soluciones basadas en desarrollo netamente de problemas y desarrollo netamente de soluciones. Para explorar cómo se puede combinar esto, en esta investigación se analizan 2 casos de estudio: el Bangladesh Delta Plan 2100 (BDP2100), un plan holístico a largo plazo a nivel nacional en el delta de Bangladesh, y un grupo de iniciativas de gestión costera del agua, un conjunto de esfuerzos continuos para adoptar medios de vida a la situación dinámica en las regiones costeras de Bangladesh. Estos casos se analizan a través de entrevistas e investigaciones teóricas para determinar en qué medida están orientados a los problemas y soluciones en comparación con los marcos propuestos, y señalan cómo pueden mejorarse. A partir de estos análisis, se propone un marco combinado donde se unen los enfoques impulsados por problemas y soluciones, tomando lo mejor de cada perspectiva. El resultado pretende ser una primera herramienta de guía para los tomadores de decisiones en los países donantes y beneficiarios que enfrentan el dilema entre tomar elementos locales y extranjeros para desarrollar soluciones.

Abstract: Infrastructure plays an essential role in the economy and has a positive impact on social stability. In this regard, bridges are a fundamental component of infrastructure; however, most of the bridges currently under operation were constructed a long time ago and have even passed their useful life. Certainly, Flaig & Lark (2000) noted that most of the current bridges in the UK were built between 1,950 and 1,970. Furthermore, Steve Kroft (2014) indicated that almost 70,000 bridges (one out of every nine bridges) in America are structurally deficient. Consequently, it is necessary to develop fast and efficient inspection techniques that meet current requirements, and that could potentially replace the highly- subjective visual observation methods. This research presents a critical comparison among different Machine-Learning algorithms that are currently used in image classification problems and applied them into the automated recognition of cracks in reinforced concrete images so that they can be used as an alternative for the existing inspection methods. Moreover, ensembles with different combinations of the evaluated models were tested as an incentive to improve the performance of individual models. In total, four algorithms that based their operation in mathematical formulations and 10 different architectures of Convolutional Neural Networks were included. The results showed that the Random Forest classifier outperformed the other mathematical classifiers and performed similarly to the best of the neural networks. In addition, it was found that the ensembled models achieved little or no improvement concerning the best of the classifiers included in the stack. Resumen: La infraestructura desempeña un papel esencial en la economía de los países y tiene un efecto positivo en la estabilidad social de las personas. A este respecto, los puentes son un componente fundamental de la infraestructura; sin embargo, la mayoría de los puentes actualmente en funcionamiento se construyeron hace mucho tiempo e incluso han pasado su vida útil. Ciertamente, Flaig y Lark (2000) observaron que la mayoría de los puentes actuales del Reino Unido se construyeron entre 1.950 y 1.970. Además, Steve Kroft (2014) indicó que casi 70.000 puentes (uno de cada nueve puentes) en USA son estructuralmente deficientes. Por consiguiente, es necesario desarrollar técnicas de inspección rápidas y eficientes que cumplan los requisitos actuales y que puedan sustituir a los métodos de inspección visual altamente subjetivos. Esta investigación presenta una comparación crítica entre los diferentes algoritmos de aprendizaje a máquina que se utilizan actualmente en los problemas de clasificación de imágenes y los aplica al reconocimiento automatizado de grietas en las imágenes de concreto reforzado para que puedan utilizarse como alternativa a los métodos de inspección existentes. Además, se ensayaron conjuntos con diferentes combinaciones de los algoritmos de aprendizaje evaluados como incentivo para mejorar el rendimiento de los modelos individuales. En total, se incluyeron cuatro algoritmos que basaban su funcionamiento en formulaciones matemáticas y 10 arquitecturas diferentes de Redes Neuronales Convolucionales. Los resultados mostraron que el clasificador Random Forest superó a los otros clasificadores matemáticos y tuvo un rendimiento similar a la mejor de las redes neuronales. Además, se encontró que los modelos ensamblados lograron poca o ninguna mejora en lo que respecta al mejor de los clasificadores incluidos en el conjunto.

Abstract: Complex networks emerge as a natural framework to describe real-life phenomena involving a group of entities and their interactions, i.e., a social net-work. Furthermore, other problems involve a collection of networks, such as multi-layer, temporal, or brain networks (connectomes). With the increasing availability of graph-shaped data and associated meta-data, i.e., node or edge attributes, machine learning (ML) techniques on networks have risen in popularity. However, there are still several challenging issues to be addressed concerning feature engineering, graph representation, visualization, and general graph mining applications. This thesis contributes to bridging the gap between ML and complex net-works. We investigate dynamics on networks such as discrete and continuous- time random walks, in two directions. First, we develop a multi-scale anomaly detection algorithm on attributed networks. We exploit the link between graph signal processing and the Markov stability framework used in community detection, for spotting anomalous nodes in multiple contexts of the network. Second, we introduce a generalization of assortativity on networks operating on scalar and categorical node attributes. These coefficients turn out to be useful descriptors to build network fingerprints, so that we can perform supervised graph classification, i.e., predicting the toxicity of molecules or classifying Reddit discussion threads. Besides, we develop an unsupervised approach to learn graph embeddings from a collection of networks. By learning a non-linear mapping from input graphs to a lower-dimensional feature space, we obtain useful graphs representations used in graph visualization, clustering, and classification, e.g., predicting people’s gender based on their structural connectome. Finally, we propose a principled approach to identify stable biomarkers for schizophrenia diagnosis in the human connectome. From an ML perspective, the problem is stated as an embedded feature selection scheme for graph classification. By doing so, we identify the affected-core in schizophrenia, highlighting increasing performance when structural and functional neural features are combined. Resumen: Las redes complejas emergen como marco general en la descripción de problemas reales que incluyen entidades y sus interacciones, ex., redes sociales. Además, otros problemas incluyen colecciones de redes tales como redes multi nivel, redes temporales o redes del cerebro. Con el incremento de la disponibilidad de datos en forma de grafos y metadatos asociados, ex., atributos en nodos o ejes, técnicas de aprendizaje automático en redes han incrementado en popularidad. Sin embargo, múltiples desafíos siguen aún sin ser resueltos, relacionados con representación de grafos, ingeniería de características en grafos, visualización y aplicaciones generales de minería de datos sobre grafos. Esta tesis doctoral contribuye a cerrar la brecha entre dos campos del conocimiento emergentes: aprendizaje automático y ciencia de redes. En esta tesis se investigan sistemas dinámicos sobre redes en la extracción de características estructurales en redes y se introduce una generalización de asortatividad en redes. Dicha asortatividad permite definir descriptores de grafos útiles en la construcción de huellas digitales de redes utilizadas en problemas de aprendizaje supervisado en clasificación de grafos, ex., predicción de toxicidad en moléculas o clasificación de redes sociales Reddit. Además, esta tesis propone un nuevo método no supervisado para crear embeedings de grafos. Gracias a la estimación de una función no lineal, se puede mapear grafos enteros en espacios euclideanos, preservando la similaridad entre grafos de origen. Finalmente, se propone un algoritmo para el diagnóstico de esquizofrenia en el cerebro humano usando connectomes, destacando las regiones del cerebro afectadas por la enfermedad mostrando resultados de alta confiabilidad utilizando distintas representaciones neuronales.

Abstract: There are too many reinforced concrete (RC) columns built before mid-1970s without sufficient transverse reinforcement. By now, we understand quite well the importance of transverse reinforcement in allowing a column to maintain its integrity under large displacement reversals in the nonlinear range of response. Poorly confined RC columns undergo a fast decay in resistance due to formation of criss-crossing inclined cracks, which can cause an abrupt failure or more gradual disintegration and trigger collapse of the structure. Those columns need to be strengthened to increase their drift capacity. Although there are several alternatives to retrofit RC columns, they often require specialized workmanship and equipment, and involved installation procedures. An easy-todesign and easyto-implement retrofit technique is examined here. It consists of external posttensioned clamps fastened around the column. Results of tests on full-scale RC columns furnished with the proposed clamps suggest the clamps can be effective in increasing column shear strength and drift capacity. Resumen: Muchas columnas de concreto reforzado construidas antes de mediados de la década de 1970 tienen insuficiente refuerzo transversal. Hace solo un par de décadas que se entendió la importancia del refuerzo transversal para permitir que una columna mantenga su integridad bajo grandes desplazamientos en el rango de respuesta no lineal. Las columnas de concreto reforzado mal confinadas sufren una rápida disminución de la resistencia debido a la formación de grietas, que pueden causar una falla abrupta o una desintegración más gradual y desencadenar el colapso de la estructura. Es necesario reforzar dichas columnas para aumentar su capacidad de deriva. Aunque existen varias alternativas para reforzar columnas de concreto reforzado, a menudo requieren mano de obra y equipo especializados, además de procedimientos de instalación complicados. Aquí se examina una técnica de reforzamiento fácil de diseñar e implementar. La técnica consta de abrazaderas presforzadas externas fijadas alrededor de la columna. Los resultados de laboratorio de las columnas de concreto reforzado a gran escala equipadas con las abrazaderas propuestas sugieren que las abrazaderas pueden ser efectivas para aumentar la resistencia al corte y la capacidad de deriva de la columna.

Abstract: The forthcoming industrial environments will require a high level of automation to be flexible. In this sense, Industry 4.0 encourages the integration of new autonomous systems digitally interconnected that can interact with humans. This thesis is developed at CIM 4.0 in the frame of the FIXIT project aiming to produce an autonomous system integrated by a UAV and a UGV. As a result, a combined system that complies with the Industry 4.0 requirements is created and mainly serves an operator by performing inspection tasks. This work is focused on redesigning the UAV airframe. Normally these structures are manufactured with some conventional techniques like molding which limits building complex structures and presents high costs in most cases. In this sense, the scope is to create a personalized structure at a lower price than the standard airframes by implementing one of the industry 4.0 pillars: additive manufacturing. The topology optimization method is integrated into the design process to create a mass-customized structure with optimum structural properties. The role of Additive manufacturing in this work is crucial to obtain an innovative, customized system with an optimum cost considering the prices on the market. The thesis is performed in different phases, starting from the definition of the UAV configuration and the propulsion system. Then a multi-material comparison and the analysis of different airframe designs are performed considering the cost and structural performance. Following this is the detailed design, in which other necessary features like the landing system, devices’ supports, and protection structures are designed. Finally, is performed the manufacturing phase in which a functional prototype is printed through FDM technology. The result is a lightweight customized airframe with good mechanical properties and optimum cost that is well integrated with the electronic components and landing system, enabling its autonomous performance characterized by repeatability and effectiveness. Esta tesis se desarrolla en el marco del proyecto FIXIT en el Centro de Manufactura Integrada (CIM) 4.0 con el objetivo de crear un sistema autónomo integrado por un Vehículo Aéreo No Tripulado (UAV) y un Vehículo Terrestre No Tripulado (UGV). Resultado: Como resultado, se crea un sistema combinado que cumple con los requisitos de la Industria 4.0 y que principalmente sirve a un operador para realizar tareas de inspección. En este sentido, el objetivo de este proyecto de tesis es crear una estructura personalizada a un precio inferior al de las estructuras estándar mediante la implementación de uno de los pilares de la Industria 4.0: la fabricación aditiva. El método de optimización de la topología se integra en el proceso de diseño para crear una estructura personalizada con propiedades estructurales óptimas. El papel de la fabricación aditiva en este trabajo es crucial para obtener un sistema innovador y personalizado con un costo óptimo, teniendo en cuenta los precios del mercado. La tesis se realiza en diferentes fases, comenzando desde la definición de la configuración del UAV y el sistema de propulsión. Luego se realiza una comparación de materiales múltiples y se analizan diferentes diseños de la estructura del UAV teniendo en cuenta el costo y el rendimiento estructural. A continuación, se lleva a cabo el diseño detallado, en el que se diseñan otras características necesarias como el sistema de aterrizaje, los soportes de dispositivos y las estructuras de protección. Finalmente, se realiza la fase de fabricación en la que se imprime un prototipo funcional mediante la tecnología de Fabricación por Deposición Fundida (FDM). El resultado es una estructura personalizada y ligera con buenas propiedades mecánicas y un costo óptimo que se integra bien con los componentes electrónicos y el sistema de aterrizaje, lo que permite su funcionamiento autónomo caracterizado por la repetibilidad y la efectividad.

Abstract: The need for measurable data from physical assets to actively feed a living Digital Twin (DT) is paramount. The requirements and needs that the gathered data should fulfill in order to be practically implemented in the stream data pipeline are heterogeneous, some of them general and other case-specific. This article summarizes a set of identified challenges and requirements for a seamless infusion of well-established Structural Health Monitoring (SHM) systems within DT platforms, without the objective of solve all of them. This identification is performed based on a review of traditional SHM systems with a vast array of information sources as well as on the review of techniques for the systematic digitalization of existing assets. On the other hand, ten real demo cases belonging to Ashvin, an H2020 Research and Innovation project, are providing real world testing beds for an active development of SHM infused in DT systems. Multiple information sources are studied in those sites, which also enriches with more realism, the identification of requirements and challenges presented herein. These assets provide a perspective to researchers about practical implications of these needs.

Abstract: This thesis proposes an update to the NS-047 technical standard of the aqueduct and sewerage company of Bogota for storm drain design, introducing the comprehensive and modern UPC methodology. The research addresses the limitations of the current standard, emphasizing the importance of critical parameters such as flow depth and velocities for pedestrian and vehicle safety during storms. By considering a wide range of hydrologic and hydraulic factors, the UPC method provides a realistic representation of stormwater behavior and enables better system understanding and optimization. The adoption of UPC is expected to enhance stormwater management, promoting safety and sustainability in urban flood control. The application of the UPC methodology to a real-life case study, the CASU road project in Bogotá, demonstrates its effectiveness in optimizing storm drain design. The analysis identified areas for improvement, resulting in a revised approach with strategically located storm drains that effectively controlled runoff while reducing the number of structures. This optimization not only saves costs but also minimizes risks for road users. The comparison between EAAB and UPC methodologies highlights the superiority of the UPC method in terms of its comprehensive approach, graphical outputs, and ability to incorporate multiple roadways. To further improve storm drains designs, experimentation is recommended to determine capture coefficients for different structures, especially in low points critical for drainage efficiency and flood prevention. Obtaining accurate capture coefficients through real-world experiments will enhance the overall stormwater management performance and inform design decisions. By complementing the EAAB standard with the UPC methodology and conducting experimentation for capture coefficients, this research aims to provide a clearer, practical, and more effective storm drain design approach for infrastructure projects in Bogotá and other areas in Colombia.

Abstract: Claystone degradation under the effect of freezing and thaw cycles represents a key aspect in the production of erodible material in mountain ranges. Erosion processes have numerous potential consequences such as dam filling, increment in slope instability, increase of badlands, among others. Due to the possible effects related to erosion, numerous research processes have been carried out following primarily experimental approaches based on both soil physical characteristics and mechanical properties. However, these have been based on a macroscopic scale. This document presents the development of a research process based on the implementation of numerical models aimed at representing the processes involved in freezing and thawing phenomena on porous media and their effect on potential changes in soil microfabric. A calibration and validation process of the proposed numerical models was carried out based on experimental measurements of the thermal behavior of soil samples subjected to freezing and thawing cycles. Using the numerical relationships found, a methodology for determining the soil water retention curve (SWRC) was established (as a first approximation) based on a quick and relatively simple freezing and thawing test under undrained conditions. Simultaneously, and following the main objective of the research, the microfabric state during cyclic freezing and thawing was established following the relationship between SWRC and pore size distribution (PSD), as well as the possible hysteresis between freezing and thawing processes. The significant effect of these thermodynamic processes on the state of the terrain, was identified particularly in regard to increased erodibility. One possible cause for particle detachment necessary for erosion processes to occur lies in the development of macroporosity along with the existence of gaps between pore families in the PSD. This behavior was observed through the developed numerical processes. The combined effect of freezing and thawing cycles leads to an increase in soil erodibility. Finally, though a constitutive model-based approach, the cryogenic suction paths associated with freezing and thawing processes under the modification of the soil’s microstructure were established. A final perspective to soil's mechanical degradation is presented in terms of the hydraulic work associated with the cryogenic suction paths developed within the soil mass. Both the progressive evolution of the microstructure (through PSD) and the values of hydraulic work associated with each cycle show an attenuation in the incremental change as the cycles continue. Due to the numerical nature of the approximations and the trends found, further cyclical laboratory tests should be carried out. However, these represent a novel approach to the degradation phenomenon as well as the effects associated with the soil water retention curve.

Abstract: Dissolved air flotation (DAF) is considered better than conventional gravity settling (CGS) for the treatment of algal-laden waters, and ballasted sedimentation (BS), a high-rate separation process, is now often used instead of CGS. Our initial literature search did not identify DAF-BS comparisons for the removal of algae and cyanobacteria from algal laden waters. The objective of this benchscale study was to compare DAF with BS and CGS for the treatment of water from a eutrophic waterway (Bay of Quinte, ON). The study was performed mid-summer when there was substantial algal growth. The optimized BS jar tests had 3% lower average turbidity removal than the DAF jar tests, however BS required 33% more coagulant, as well as 0.25 mg/L anionic polymer and microsand additions. The removal of cyanobacteria and algae (quantified using chlorophyll-a and c-phycocyanin concentrations) by DAF and BS were very similar, and they were superior to that achieved by CGS. The DOC removals and the disinfection by-products formation potential (DBPFP) of DAF and BS treated water were also similar. Based on the chlorophyll-a and c-phycocyanin removals, both BS and DAF performed better than CGS and can be considered suitable for the treatment of algal/cyanobacteria laden waters.

Abstract: The aim of this research was to investigate the combustion behaviour of coal and biomass blends using a pilot-scale bubbling fluidised bed reactor. The blends were prepared with a traditionally used biomass fuel (i.e. wood) and selected rich in alkali-metals biomass fuels (i.e. wheat straw and spent coffee grounds (SCG)) to investigate the potential of SCG as a fuel and the effect of ilmenite on agglomeration tendency when used as an additive and alternative bed material. To elucidate the interaction between the fuels in the blends and the effect of ash composition, thermogravimetric and ash fusibility studies were performed looking at both the parent fuels and blends. Initially, thermogravimetric studies focused on understanding the thermal decomposition of coal blended with by-products (spent coffee ground (SCG), and coffee husk (CH)) of coffee crop. Blends with wood were included for comparison purpose. The blends were prepared by blending coal with biomass at 10, 30 and 50 wt%. The experiments were performed under inert and oxidising conditions to elucidate the thermal behaviour and fuel interactions. The results showed that the inclusion of either spent coffee grounds or coffee husk in coal combustion can enhance the combustion performance. Indeed, the blends with spent coffee grounds were found to be more reactive than those with coffee husk and with similar characteristics to the blends with wood. It was attributed to the existence of synergistic effects. These results offer compelling evidence of the potential of by-products from the coffee crop, especially spent coffee grounds for energetic applications. The study of ash fusibility characteristics investigated the ash fusibility temperatures under oxidising conditions of coal ash blended with ash from spent coffee grounds. Blends with wheat straw ash were included for comparison purpose. Particular attention was paid to the blending ratio effect on ash fusibility temperatures. The results showed that SCG is an interesting fuel in co-processing due to the low ash content and high ash fusibility temperatures when blended with coal. The high ash fusibility temperatures of the blends were attributed to the high content of CaO, MgO, and P2O5 in SCG with negligible content of SiO2 and Cl, complementing the high content of Al2O3 and Fe2O3 in coal. Evidence from this study suggests that the high ash fusion temperatures in the blends of coal with spent coffee grounds can reduce the common operational issues related to biomass ash such as agglomeration. This can also provide confidence for large scale thermochemical conversion systems fuelled by such kind of coal and biomass blends to be able to maintain long-term stable operation. The final part of this research focused on co-combustion experiments in a pilot-scale BFB aiming to investigate the potential of SCG as a fuel, and ilmenite as an additive and alternative bed material. For comparison purpose blends of coal with wheat straw and wood pellets were also combusted in the same BFB reactor under similar combustion conditions. Similarly, kaolin and bauxite, and silica sand were compared to ilmenite when used as an additive and alternative bed material, respectively. The inclusion of biomass in coal combustion showed marked differences in the temperature profiles, gas emissions, and combustion performance. The results showed that coal and SCG blends can be combusted for energy applications with improved combustion efficiency compared to wheat straw and wood commercial pellets. Nevertheless, high N content in SCG represents a challenge in terms of NOx emissions that should be addressed.