http://hdl.handle.net/10366/4349 Wed, 22 Apr 2026 22:11:38 GMT 2026-04-22T22:11:38Z http://hdl.handle.net/10366/170882 [EN] Roof modelling provides useful information for energy analysis, but the methodologies traditionally applied are based on data acquired through aerial vehicles. This requirement makes necessary two data acquisition campaigns: one from indoors and another from outdoors. However, most energy studies can be performed using regularized and simplified models where most of the information of the exhaustive acquisitions is not used. Therefore, this paper proposes a semi-automatic procedure for the 3D modelling of roofs using indoor point clouds, reducing the acquisition campaigns to the indoors campaign. The methodology is based on the hypothesis that surfaces have no thickness, which makes the algorithm especially useful in industrial environments where there are no false ceilings and therefore, the contribution of the roof in the energy behaviour of the building is more important. The methodology is tested on six different scenarios, obtaining their regularized models with relative errors lower than 2% in ideal conditions. Fri, 01 Apr 2022 00:00:00 GMT http://hdl.handle.net/10366/170882 2022-04-01T00:00:00Z http://hdl.handle.net/10366/170881 [EN] This study investigates the application of soft magnetic composite (SMC) materials in alternator core manufacturing for bladeless wind turbines operating under the principle of vortex-induced vibration (VIV), employing additive manufacturing (AM) technologies. Through a comparative analysis of alternator prototypes featuring air, SMC, and iron cores, the investigation aims to evaluate the performance of SMC materials as an alternative to the most commonly used material (iron) in VIV BWT, by assessing damping, resonance frequency, magnetic hysteresis, and energy generation. Results indicate that while alternators with iron cores exhibit superior energy generation (peaking at 3830 mV and an RMS voltage of 1019 mV), those with SMC cores offer a promising compromise with a peak voltage of 1150 mV and RMS voltage of 316 mV, mitigating eddy current losses attributed to magnetic hysteresis. Notably, SMC cores achieve a damping rate of 60%, compared to 67% for air cores and 59% for iron cores, showcasing their potential to enhance the efficiency and sustainability of bladeless wind turbines (BWTs). Furthermore, the adaptability of AM in optimizing designs and accommodating intricate shapes presents significant advantages for future advancements. This study underscores the pivotal role of innovative materials and manufacturing processes in driving progress towards more efficient and sustainable renewable energy solutions. Tue, 25 Jun 2024 00:00:00 GMT http://hdl.handle.net/10366/170881 2024-06-25T00:00:00Z http://hdl.handle.net/10366/170869 [EN] This study presents a comprehensive exploration centred on the morphology and surface structure of bladeless wind turbines (BWTs) aimed at optimizing their wind energy harvesting capability. Unlike conventional wind technology where vortex-induced vibration (VIV) is seen as problematic due to aeroelastic resonance, this effect becomes advantageous in BWT energy harvesters, devoid of frictional contact or gears. The primary objective of this study is to develop an optimal BWT design for maximizing energy output. Specifically, this study delves into optimizing the energy performance of these VIV wind energy harvesters, investigating how the geometry (shape and roughness) influences their operating range, known as Lock-In range. The results demonstrate how variations in geometry (convergent, straight, or divergent) can shift the Lock-In range to different Reynolds numbers (Re), modelled by the equation: Re (max Lock-In) = 0.30 α + 4.06. Furthermore, this study highlights the minimal impact of roughness within the considered test conditions. Wed, 27 Mar 2024 00:00:00 GMT http://hdl.handle.net/10366/170869 2024-03-27T00:00:00Z http://hdl.handle.net/10366/170868 [EN] InfraRed Thermography (IRT) has proven to be a valuable diagnostic tool due to its real-time, remote, and non-destructive operation yielding accurate detection of the position of defect areas in building façade ceramic tiling. Ceramic tiles coating building façades are widely used throughout the world because of their technical and aesthetic characteristics. However, the detachment of ceramic tiles and the water infiltration in deep layers are still common problems. So, this paper proposes active infrared thermography as a thermographic acquisition mode, in contrast to the common use of passive thermography, and segmentation of defect areas and automation in the thermal image processing as added values never before proposed in the ceramic tiling thermographic inspection. For that, specimens of ceramic tiling for building façades were tested under different laboratory conditions, with inserted corks (simulating detachments), and by injecting water into holes drilled in the back surfaces (simulating water infiltration), as defects. Good results have been obtained in all the tests, both in dry and wet conditions in the specimens and for surfaces with homogeneous and heterogeneous surface properties, serving the introduction of this workflow for a first and fast inspection in ceramic tiling building façades. Future research will work with the fine-tuning phase of the methodology by applying it to real case studies. Tue, 01 Mar 2022 00:00:00 GMT http://hdl.handle.net/10366/170868 2022-03-01T00:00:00Z http://hdl.handle.net/10366/170867 [EN] Infrastructure inspection is fundamental to keep its service performance at the highest level. For that, special attention should be paid to the most severe defects in order to be able to subsequently mitigate or even eliminate them. Therefore, this paper introduces the combination of an automatic thermogram pre-processing algorithm and a Deep Learning (DL) model, Mask R-CNN, applied to thermal images acquired from different infrastructures (buildings, heritage sites and civil infrastructures) with water-related problems and thermal bridges. The pre-processing algorithm developed is based on thermal fundamentals. As an output, the thermal contrast between defect and defect-free areas is increased in each image. Then, Mask R-CNN is trained using the pre-processing algorithm outputs as input dataset to automatically detect, segment and classify each defect area. The training process of Mask R-CNN is improved by the prior application of the proposed pre-processing algorithm in terms of time. This shows the capacity of thermal fundamentals to improve the performance of the DL models for their application to the InfraRed Thermography (IRT) field. In addition, DL models are introduced for the first time in the thermographic inspection of water-related problems and thermal bridges when inspecting an infrastructure. Mon, 18 Apr 2022 00:00:00 GMT http://hdl.handle.net/10366/170867 2022-04-18T00:00:00Z http://hdl.handle.net/10366/170864 [EN] Renewable hydrogen is an emerging solution to the need for decarbonization of the current society, with local deployments being at the core of most implementations. It is currently in early stage of implementation, so there are not many previous experiences to standardize decision-making and the most relevant criteria. However, the lack of experts in the field of renewable hydrogen makes it difficult to design an optimal value chain. For this reason, this paper proposes a specific framework based on Geographic Information Systems, Multi-Criteria Decision Analysis and Intelligent Optimization (specifically two Genetic Algorithms denoted as Methods A and B) for the decision-making regarding the selection of optimal sites for the implementation of the renewable energy value chain from a holistic perspective; that is, considering topographic, economic, social, environmental, and demand criteria. The proposed framework is validated through the comparison of its results with those of the most extended methods in the state of the art. The results show that the application of the proposed framework implies an increase in accuracy in the determination of the locations with the highest Land Suitability Index for the renewable hydrogen value chain. Specifically, an increase in accuracy of 1.35 % (Method A) and 3.25 % (Method B) is observed with respect to the most widely used method in the literature: Analytic Hierarchy Process. Spain has been selected as a case study to validate the applicability of the proposed framework, which has facilitated the identification the optimal municipalities for the local implementation of renewable hydrogen in the country. It has been demonstrated that of the 60 projects in advanced levels of development, 87% (50 projects) have a high level of Land Suitability Index placing them in the first quartile of the ranking. In terms of investment, these projects represent around €468 million (87.7 %). It can therefore be concluded that the renewable hydrogen financing strategy of Spain can be slightly improved with the results of the proposed framework. Sat, 15 Feb 2025 00:00:00 GMT http://hdl.handle.net/10366/170864 2025-02-15T00:00:00Z http://hdl.handle.net/10366/170840 [ES] La biomasa, Tipos de biomasa, Procesos de transformación de la biomasa, La valorización de la biomasa mediante combustión, Las centrales termoeléctricas de biomasa, El mercado eléctrico, Situación actual y marco legislativo, Pretratamiento de la biomasa, La caldera de combustión de biomasa, El ciclo agua-vapor, La turbina de vapor, El generador, Sistemas eléctricos de alta, media y baja tensión, Sistemas auxiliares.; [EN] Biomass, Types of biomass, Biomass transformation processes, Biomass valorization through combustion, Biomass thermal power plants, The electricity market, Current situation and legislative framework, Biomass pretreatment, The biomass combustion boiler, The water-steam cycle, The steam turbine, The generator, High, medium and low voltage electrical systems, Auxiliary systems. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10366/170840 2018-01-01T00:00:00Z http://hdl.handle.net/10366/170839 [ES] La biomasa, Tipos de biomasa, Procesos de transformación de la biomasa, La valorización de la biomasa mediante combustión, Las centrales termoeléctricas de biomasa, El mercado eléctrico, Situación actual y marco legislativo, Pretratamiento de la biomasa, La caldera de combustión de biomasa, El ciclo agua-vapor, La turbina de vapor, El generador, Sistemas eléctricos de alta, media y baja tensión, Sistemas auxiliares.; [EN] Biomass, Types of biomass, Biomass transformation processes, Biomass valorization through combustion, Biomass thermal power plants, The electricity market, Current situation and legislative framework, Biomass pretreatment, The biomass combustion boiler, The water-steam cycle, The steam turbine, The generator, High, medium and low voltage electrical systems, Auxiliary systems. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10366/170839 2018-01-01T00:00:00Z http://hdl.handle.net/10366/170838 [ES] El libro CENTRALES TÉRMICAS DE CICLO COMBINADO trata de exponer al lector los principios de funcionamiento y los principales equipos y sistemas que componen una central de ciclo combinado. A los largo del libro se describen con todo detalle las posibles configuraciones, los equipos principales, las turbinas de gas, las turbinas de vapor, la caldera de recuperación, el ciclo agua-vapor y los sistemas auxiliares. Dedica especialmente más de 100 páginas a describir el generador y los sistemas eléctricos de alta, media y baja tensión de la central. El libro no da nada por sabido, tiene un marcado carácter práctico y pretende convertirse en una guía de referencia incluso para personal no técnico.; [EN] The book COMBINED CYCLE POWER PLANTS aims to explain to the reader the operating principles and the main equipment and systems that make up a combined cycle power plant. Throughout the book, the possible configurations, main equipment, gas turbines, steam turbines, heat recovery steam generator, steam-water cycle, and auxiliary systems are described in detail. It dedicates over 100 pages specifically to describing the generator and the high, medium, and low voltage electrical systems of the plant. The book assumes no prior knowledge, has a distinctly practical focus, and intends to become a reference guide even for non-technical personnel. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10366/170838 2018-01-01T00:00:00Z http://hdl.handle.net/10366/170837 [ES] El libro CENTRALES TÉRMICAS DE CICLO COMBINADO trata de exponer al lector los principios de funcionamiento y los principales equipos y sistemas que componen una central de ciclo combinado. A lo largo del libro se describen con todo detalle las posibles configuraciones, los equipos principales, las turbinas de gas, las turbinas de vapor, la caldera de recuperación, el ciclo agua-vapor y los sistemas auxiliares. Dedica especialmente más de 100 páginas a describir el generador y los sistemas eléctricos de alta, media y baja tensión de la central. El libro no da nada por sabido, tiene un marcado carácter práctico y pretende convertirse en una guía de referencia incluso para personal no técnico.; [EN] The book COMBINED CYCLE POWER PLANTS aims to explain to the reader the operating principles and the main equipment and systems that make up a combined cycle power plant. Throughout the book, the possible configurations, main equipment, gas turbines, steam turbines, heat recovery steam generator, steam cycle, and auxiliary systems are described in detail. It dedicates over 100 pages to describing the generator and the high, medium, and low voltage electrical systems of the plant. The book assumes no prior knowledge, has a strong practical focus, and intends to become a reference guide even for non-technical personnel. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10366/170837 2018-01-01T00:00:00Z http://hdl.handle.net/10366/170834 [EN] This study explores how urban morphological and environmental factors influence Urban Heat Islands (UHIs) using a geospatial modeling approach. The aim of the research is to develop a methodology to assess UHI effects, emphasizing the role of urban morphology, land use, and vegetation in nighttime heat accumulation. A micro-scale analysis with a 50 m resolution is conducted by integrating a custom QGIS plugin with open-access data, ensuring broad applicability. The 50 m resolution was chosen because it allows for the capture of local variations in UHI intensity while maintaining the scalability of the urban analysis across different city contexts. Non-parametric statistical analyses (ANOVA, Kruskal–Wallis H test, and correlation assessments) were used to evaluate the relationships between the urban parameters—wind corridors, altitude, vegetation (NDVI), surface water (NDWI), and the Sky View Factor (SVF)—and Nighttime Land Surface Temperature (LST). Given that UHI variations during summer, particularly in cities of the Iberian Peninsula, are closely linked to summer heat severity, this factor was considered to classify the cities for the study. Correlation analyses confirm that all tested factors influence LST, with wind corridors being the least significant. The model performance evaluation shows the highest errors in cities with lower summer severity (RMSE = 1.586 °C, MAE = 1.2686 °C, MAPE = 6.99%) and the best performance in warmer cities (RMSE = 1.4 °C, MAE = 1.14 °C, MAPE = 4.5%). Validation in four cities of the Iberian Peninsula confirmed the model’s reliability, with the worst RMSE value of 2.04 °C. These findings contribute to a better understanding of the factors driving UHIs and provide a scalable assessment framework. Wed, 28 May 2025 00:00:00 GMT http://hdl.handle.net/10366/170834 2025-05-28T00:00:00Z http://hdl.handle.net/10366/170832 [EN] The fi­rst appearance of concern for the good condition of a building dates back to ancient times. In recent years, with the emergence of new inspection technologies and the growing concern about climate change and people’s health, the concern about the integrity of building structures has been extended to their analysis as insulating envelopes. In addition, the growing network of historic buildings gives this sector special attention. Therefore, this study presents a comprehensive review of the application of two of the most common and most successful Non-Destructive Techniques (NDTs) when inspecting a building: InfraRed Thermography (IRT) and Ground-Penetrating Radar (GPR). To the best knowledge of the authors, it is the fi­rst time that a joint compilation of the state-of-the-art of both IRT and GPR for building evaluation is performed in the same work, with special emphasis on applications that integrate both technologies. The authors briefly explain the performance of each NDT, along with the individual and collective advantages of their uses in the building sector. Subsequently, an in-depth analysis of the most relevant references is described, according to the building materials to be studied and the purpose to be achieved: structural safety, energy efficiency and well-being, and heritage preservation. Then, three different case studies are presented with the aim of illustrating the potential of the combined use of IRT and GPR in the evaluation of buildings for the purposes defi­ned. Last, the final remarks and future lines are described on the application of these two interesting inspection technologies in the preservation and conservation of the building sector. Mon, 05 Sep 2022 00:00:00 GMT http://hdl.handle.net/10366/170832 2022-09-05T00:00:00Z http://hdl.handle.net/10366/170831 [EN] The orography of the terrain is a key factor for the electrification of vehicles, especially regarding public transport and electric buses. This work deals with the analysis of the use of mobile laser scanning, both terrestrial and aerial, for the evaluation of the orography of urban areas. First, the minimum point density required is evaluated to estimate the slope. The results show that point densities of 1 point/m2, measured with aerial laser scanning, are adequate for the task. Based on this, the design of a route for public transport is presented including the requirements concerning key transit points, maximum slope, and others. Based on the proposed route design, the transformation to an electrified route is analyzed from an economic and environmental point of view. The results show that the implementation of electric buses vs. diesel buses in cities with steep slopes (up to 7%) reduces greenhouse gas emissions (32.59%) as well as economic costs (18.10%). Thu, 29 Jun 2023 00:00:00 GMT http://hdl.handle.net/10366/170831 2023-06-29T00:00:00Z http://hdl.handle.net/10366/170829 [EN] The presence of shadows is one of the main disadvantages of photovoltaic solar panel installations in urban environments. This article analyses their effect on solar installations performed on urban elements where the use of solar energy can be considered novel: bus shelters. For this purpose, the PVGIS tool is used in combination with a new methodology for the extraction of the shadow horizon profile from LiDAR point clouds. The results show a 29.90% and 37% reduction of calculated solar radiation using horizon profiles derived from LiDAR point clouds of 0.5 pts/m2 and 1 pt/m2, respectively, versus no horizon profile. By taking shading into account, thanks to this study it is possible to make a more realistic prediction of the use of the electrical energy generated by the sun to cover urban energy consumption in bus shelters. Results show that the energy surplus produced overall allows these elements to be converted into charging points for light electric vehicles, allowing up to 35 units per day/bus shelter to be charged. The use of bus shelters as a place to generate clean energy through solar energy and charge light vehicles makes it possible to move towards sustainable and environmentally friendly cities. Tue, 31 Oct 2023 00:00:00 GMT http://hdl.handle.net/10366/170829 2023-10-31T00:00:00Z http://hdl.handle.net/10366/170828 [EN] Currently, spatial modeling is of particular relevance as it enables the understanding of the patterns and spatial variability of an event, the monitoring and prediction of the spatial behavior of a variable, the optimization of resources, and the evaluation of the impacts of a phenomenon of interest. Research carried out recently on variables related to solar energy budgets has been of special relevance due to its applications and developments in machine learning (ML) and deep learning (DL). These algorithms are crucial to improve the efficiency, precision, and applicability of remote sensing, allowing greater decision making with more reliable and timely data. Thus, this work proposes a systematic and rigorous methodology for searching research articles about the latest advances and contributions related to the modeling of radiative energy budgets using novel techniques and algorithms in some of the most relevant international scientific databases (Scopus, ScienceDirect, ResearchGate). Search parameters were applied using tracking methods through various filters, specific classifiers, and Boolean operators. The results allowed for an analysis of search trends and citations in the last 5 years related to the topic of interest and the number of most relevant articles for this research, analyzed through specialized metrics and graphs. Additionally, this methodology was classified into four categories of importance for refined and articulated searches in this evaluation: (i) according to the applied interpolation methods, (ii) according to the remote sensors used, (iii) according to the applications in different fields of knowledge. As a relevant fact and with an essentially prospective purpose, a subchapter of this review was dedicated to the latest advances and developments applied to (iv) spatial modeling of terrestrial radiation through ML, this method being a tool that opens multiple alternatives for data processing and analysis in the development and achievement of objectives in the field of geotechnologies. A quantitative comparison was conducted on the predictive performance results between the classification/regression algorithms found in the studies explored in this review. The evaluation confirmed the existence of a persistent shortage of studies in recent years within the geotechnologies field, particularly concerning the comparison of spatial distribution modeling techniques developed and implemented through ML for incident solar and terrestrial radiation. Therefore, this work provides a synthesis and analysis of the most used and novel techniques in the modeling of solar energy budgets, their limitations, and biggest challenges. Wed, 07 Aug 2024 00:00:00 GMT http://hdl.handle.net/10366/170828 2024-08-07T00:00:00Z http://hdl.handle.net/10366/170798 [ES] Este capítulo analiza la aplicación de tecnologías IoT para la supervisión preventiva del uso de equipos de protección individual (EPI) en el ámbito sanitario durante situaciones pandémicas. El trabajo parte del problema de que, en contextos de alta presión asistencial, la verificación del uso correcto de los EPI suele depender de inspecciones visuales y de factores humanos, lo que dificulta el control efectivo, la trazabilidad y la prevención de contagios entre profesionales sanitarios. Como propuesta, se plantea un sistema digital y de bajo coste basado principalmente en tecnología RFID, capaz de identificar al personal sanitario y a los EPI utilizados, verificar si el acceso a determinadas áreas clínicas se realiza con la protección obligatoria, y registrar datos de uso, tiempos de exposición y trazabilidad del material. El sistema incorpora antenas de lectura, etiquetas RFID flexibles, tarjetas de identificación personal y una aplicación informática para la gestión y supervisión en tiempo real. Los resultados muestran que esta solución permite validar accesos, emitir alertas ante usos inadecuados, controlar el tiempo de utilización de los EPI y adaptar los requisitos de protección según zonas hospitalarias y riesgos específicos. Además, favorece la gestión logística, el control de inventario y la detección de deficiencias en los protocolos de seguridad. En conjunto, el estudio concluye que el uso de IoT en entornos sanitarios puede mejorar la seguridad laboral, optimizar recursos y reducir el riesgo de contagio en escenarios de emergencia sanitaria.; [EN] This chapter analyzes the application of IoT technologies for the preventive monitoring of personal protective equipment (PPE) use in healthcare settings during pandemics. The work stems from the problem that, in contexts of high healthcare pressure, verifying the correct use of PPE often depends on visual inspections and human factors, hindering effective control, traceability, and the prevention of infections among healthcare professionals. As a proposal, a low-cost digital system based primarily on RFID technology is presented. This system is capable of identifying healthcare personnel and the PPE used, verifying whether access to specific clinical areas is carried out with the required protection, and recording data on usage, exposure times, and material traceability. The system incorporates reading antennas, flexible RFID tags, personal identification cards, and a software application for real-time management and monitoring. The results show that this solution allows for access validation, the issuance of alerts for inappropriate use, monitoring of PPE usage time, and the adaptation of protection requirements according to hospital areas and specific risks. Furthermore, it facilitates logistics management, inventory control, and the detection of deficiencies in safety protocols. Overall, the study concludes that the use of IoT in healthcare settings can improve workplace safety, optimize resources, and reduce the risk of contagion in public health emergencies. Wed, 01 Jan 2020 00:00:00 GMT http://hdl.handle.net/10366/170798 2020-01-01T00:00:00Z