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.

Abstract: This study investigates the combustion characteristics of blends of bituminous coal (BC) with two by products of the coffee industry, spent coffee ground (SCG) and coffee husk (CH), at 10, 30, and 50 wt% using a thermogravimetric analyzer (TGA). For comparison purposes, blends of BC and wood pellets (WP) at the same mass ratios were also investigated. The thermal behavior and fuel interactions in the blends during combustion were characterized by the ignition index (Di), combustion index (S), and potential synergistic effects. The interactions between the materials in the blends led to an enhancement of up to 93.5% and 128.5% in Di, and 175.2% and 96.35% in S of the bituminous coal when blended at 50 wt% with SCG and CH, respectively. Furthermore, clear synergistic effects were observed with the combustion of BC-SCG blends, whereas the combustion of BC-CH blends did not show any appreciable synergistic effects.

Abstract: Adequate initial bolt preload is necessary to ensure the strength and stiffness of bolted connections. In this study, an experimental torque control method was used to determine the relationship between tightening torque and preload of nine Extended Hollo-Bolt (EHB) blind bolted connections to Concrete-Filled Steel Hollow Sections (CFSHS). In order to obtain the EHB nut factors, which allow to calculate the level of preload for any value of applied torque, torque versus preload curves were drawn based on the experimental results and curve fitting method was carried out. Bolt preload relaxation was also recorded for a period of 7 days while concrete hardening occurred. Additionally, a detailed 3D Finite Element (FE) model of the tightening stage of the EHB was established. The experimental and numerical results show that the nut factor for the EHB is higher than that of standard bolts and bolt relaxation is not affected by the concrete presence during the hardening stage. Adequate friction coefficients were proposed as well as an equation for calculating the residual preload of the EHB. Resumen: Es necesaria una precarga inicial adecuada del perno para garantizar la resistencia y rigidez de las conexiones atornilladas. En este estudio, se utilizó un método experimental de control de torque para determinar la relación entre el torque de apriete y la precarga de nueve conexiones empernadas ciegas Extended Hollo-Bolt (EHB) a secciones huecas de acero rellenas de concreto (CFSHS). Para obtener los factores de tuerca EHB, que permiten calcular el nivel de precarga para cualquier valor de torque aplicado, se dibujaron curvas de torque versus precarga con base en los resultados experimentales y se llevó a cabo el método de ajuste de curvas. También se registró la relajación de la precarga de los pernos durante un período de 7 días mientras se producía el endurecimiento del hormigón. Además, se estableció un modelo 3D detallado de elementos finitos (FE) de la etapa de apriete del EHB. Los resultados experimentales y numéricos muestran que el factor de tuerca para el EHB es mayor que el de los pernos estándar y la relajación del perno no se ve afectada por la presencia del concreto durante la etapa de endurecimiento. Se propusieron coeficientes de fricción adecuados así como una ecuación para calcular la precarga residual del EHB.

Abstract: Stochastic time series methods for load forecasting are the traditional methods used by electric power companies [1] because they can model seasonal and stochastic behavior of the load [2]. A load time series has patterns that repeat at different time scales such as daily, weekly or yearly. These patterns indicate that load can be predicted and the shortest seasonality component has the highest effect on the forecast. There might be conditions in which load is in different time resolutions, has a different amount of missing data or is under special events such as COVID-19 pandemic. Load forecasting methods should be able to perform well under these circumstances. On the other hand, neural networks are a wide research topic, they can learn [3] and have low forecasting errors [4]. In this work we explain the main characteristics of load demand in time, load forecasting and we compare stochas-tic time series methods with neural networks for load forecasting in terms of the error with respect to the real load. Resumen: Los métodos de series de tiempo estocásticos para pronósticos de carga son los métodos tradicionales usados por compañías de energía eléctrica [1] porque pueden modelar el comportamiento estocástico y estacional de la carga [2]. Una serie de tiempo de carga tiene patrones que se repiten en diferentes escalas de tiempo como diaria, semanal o anual. Estos patrones indican que la carga puede ser predicha y que el componente de estacionalidad más corto tiene el efecto más grande en el pronóstico. Pude que haya condiciones en las cuales la carga este en diferentes resoluciones de tiempo, tenga una diferente cantidad de datos faltantes o este bajo eventos especiales como la pandemia COVID-19. Los métodos de pronóstico de carga deberían ser capaces de llevarse a cabo bien bajo estas circunstancias. Por otra parte, las redes neuronales son un tema de investigación amplio, ellas pueden aprender [3] y tienen errores de pronóstico bajos [4]. En este trabajo explicamos las principales características de la demanda de carga en el tiempo, pronósticos de carga y comparamos métodos de serie de tiempo estocásticos con redes neuronales para pronósticos de carga en términos del error con respecto a la carga real. [1] H. Wang, B.-S. Li, X.-Y. Han, D.-L. Wang and H. Jin, "Study of Neural Networks for Electric Power Load Forecasting," Third International Symposium on Neural Networks - Advances in Neural Networks - ISNN 2006, Proceedings, Part II, pp. 1277-1283, 2006. [2] K. Berk, Modeling and Forecasting Electricity Demand, Siegen: Springer Spektrum, 2015. [3] H. Alfares and N. Mohammad, "Electric load forecasting: Literature survey and classification of methods," International Journal of Systems Science - IJSySc. 33, vol. 33, no. 1, pp. 23-34, 2002. [4] M. Singh and R. Maini, "Various Electricity Load Forecasting Techniques with Pros and Cons," International Journal of Recent Technology and Engineering (IJRTE), vol. 8, pp. 220-229, 2020.

Abstract: Krafla Geothermal Field is located inside the Krafla Caldera in the Northeast of Iceland. The tectonic settings consist of a central volcano and its corresponding fissure swarm formed due to extension from plate spreading. The central volcano has a collapsed caldera dating ~110.000 years (Sæmundsson, 2008). Within the Krafla post Caldera collapse period, the orientation of the different extensional eruptive fissures evidence rotation of the plate. The initial events evidence above 20 degrees from North strike, whereas more recent events shifted orientation to be closer to 15 degrees North (Árnason, 2020). This paper discusses the chronological evolution of the Fissure Swarm inside Krafla Caldera and the effect on the stratigraphic reconstruction made in 2019 to compare conceptual models of the south zone subareas: Hvíthólar, Vestursvæði, and Sandabotnaskarð. This paper derived from the MSc Thesis project 3D Conceptual Model Hvíthólar Sub-area, Krafla carried out in 2019. This paper complements other publications such as (Castillo et al,2020).

Abstract: This project revises the 3D conceptual model for the Hvíthólar sub-area in the South Zone of Krafla Geothermal Field. Hvíthólar is one of 6 sub-areas in south Krafla, located at the intersection of the south boundary of Krafla caldera, striking E-W, and the NNE-SSW oriented fissure swarms of the North Volcanic Zone. The model developed in this study extends along Vestursvæði, Þríhvrningar, Hvíthólar and Sandabotnaskarð sub-areas with a combined area of around 30 km2. Hvíthólar is the only southern sub-area connected to Krafla power station and has exhibited a considerable production decline over the period of 1990 – 2013. According to a lumped simulation, the Hvíthólar reservoir follows a two tank open system with a volume of 6.00004 km3. The Hvíthólar enthalpy is approximately 1200 kJ/kg; chemically it presents a low concentration of Cl−, and high CO2. To date, most studies support the hypothesis that Hvíthólar characteristics and behaviour are due to the lack of a heat recharge and that the sub-area is in a phase of waning or even becoming extinct. An improved understanding of heat source location and permeability variations will provide the basis of future utilisation decisions. This study presents two alternative conceptual models for Hvíthólar in addition the existing one, as a means to test the current conceptual model in order to determine the potential to extend the life of the asset. An update of the geological model was carried out based on data from shallow and deep wells along the southern part of Krafla geothermal field. This update combined with existing data from surface exploration was used to generate three conceptual models in Leapfrog Geothermal. The models focus on the location of heat source, and the permeability variation at the intersection between caldera boundary and fissure swarm. Each of the models are validated with TOUGH2 simulations. Resumen: Este proyecto revisa el modelo conceptual 3D para la subárea Hvíthólar en la Zona Sur del Campo Geotérmico Krafla. Hvíthólar es una de las 6 subáreas en el sur de Krafla, ubicada en la intersección del límite sur de la caldera de Krafla, con rumbo E-O, y los enjambres de fisuras orientados NNE-SSO de la Zona Volcánica Norte. El modelo desarrollado en este estudio se extiende a lo largo de las subáreas Vestursvæði, Þríhvrningar, Hvíthólar y Sandabotnaskarð con un área combinada de alrededor de 30 km2. Hvíthólar es la única subárea sur conectada a la central de energía de Krafla y ha mostrado una disminución considerable de la producción durante el período 1990 - 2013. Según una simulación de lumped, el reservorio de Hvíthólar sigue un sistema abierto de dos tanques con un volumen de 6.00004 km3. La entalpía de Hvíthólar es de aproximadamente 1200 kJ / kg; químicamente presenta una baja concentración de Cl−, y alta concentración de CO2. Hasta la fecha, la mayoría de los estudios apoyan la hipótesis de que las características y el comportamiento de Hvíthólar se deben a la falta de una recarga de calor y que la subárea se encuentra en una fase de menguante o incluso de extinción. Un mejor entendimiento de la ubicación de la fuente de calor y las variaciones de permeabilidad en el campo proporcionarán la base de futuras decisiones de utilización. Este estudio presenta dos modelos conceptuales alternativos para Hvíthólar además del existente, como un medio para probar el modelo conceptual actual con el fin de determinar el potencial para extender la vida útil del activo. Una actualización del modelo geológico basado en datos de pozos poco profundos y profundos a lo largo de la parte sur del campo geotérmico Krafla fue realizada. Esta actualización, combinada con los datos existentes de la exploración de la superficie, se utilizó para generar tres modelos conceptuales en3D utilizando Leapfrog Geothermal. Los modelos se centran en la ubicación de la fuente de calor y la variación de la permeabilidad en la intersección entre el límite de la caldera y el enjambre de fisuras. Cada uno de los modelos está validado con simulaciones TOUGH2.