APRÈN. Portal de la producció docent del professorat de la UPC

The exchange of momentum over complex terrain, especially within the Mountain Boundary Layer, is a multifaceted and highly variable phenomenon with significant implications for weather forecasting and atmospheric science. This research dives into the intricate dynamics of this exchange, focusing on a specific secondary circulation: the Cross-Valley Vortex (CVV). The CVV's formation, evolution, and interaction with various atmospheric factors are examined, with a particular emphasis on simulating its behavior during the CROSSINN IOP4 campaign using the Weather Research and Forecasting Model (WRF). The study adopts a two-fold approach, first assessing the consistency and comprehensiveness of the WRF simulation and then comparing its results to observational data. Synoptic scale analysis indicates a reasonable alignment between the simulation and reference data, despite notable variations attributed to model setup. However, when zooming into the Inn valley during IOP4, distinct discrepancies emerge. The morning outflow in the simulation differs from observations, leading to delayed inflow onset and reduced upvalley flow strength during the afternoon hours. These discrepancies significantly influence the valley atmosphere and the conditions for the formation of the CVV. Furthermore, the role of the Mountain-Plain Circulation (MPC) in the Inn valley's atmosphere and its interactions with the upvalley flow are explored. The MPC introduces complex multi-scale interactions, distinguishing the model from reference observational data. The inflow jet structure also exhibits complexity, with altitude and topographical features playing distinct roles. In the examination of the CVV, deviations from observational data are noted, mainly originating from variations in inflow strength and the presence of the MPC. The CVV in the simulation appears transient and insufficiently persistent to fully understand its temporal and structural evolution. WRF demonstrates the capability to replicate the CVV, even though with challenges due to specific characteristics of the valley-scale flow during IOP4, where the presence of the MPC hinders the CVV's formation during most of the afternoon. To gain a deeper understanding of the CVV, an environment characterized by a less transient valley atmosphere, pure upvalley flow, and fewer multiscale interactions is recommended for future research. This will provide the necessary conditions for a more comprehensive analysis of this complex atmospheric phenomenon.

In this project, a Formula Student rear wing is designed in CATIA V5, and its performance is tested aerodynamically through CFD simulations using Siemens Star CCM+. This design is meant to be a concept for a formula student car. First, important design aspects like the number of elements of the wing and their chord, angle of attack, and relative position are studied and compared by means of a cost function. When the final design is obtained a DRS (Drag Reduction System) with a study of the optimal opening angle is implemented and surface texturing is studied. To validate these results a scaled model is 3D printed and tested in a wind tunnel showing a good correlation (error below 10%). For this, the CAD with the final geometry is scaled and adapted to be 3D printed including features such as pressure taps tubes and holes for the joints of both half parts printed. Finally, a manufacturing process proposal based on bibliography is presented. The designed device produces a total downforce of 298.00 Newton with an efficiency of 2.53. The DRS angle study permits achieving an efficiency of 4.08 with a decrease in negative lift of 27.70%. These findings are robustly supported by wind tunnel outcomes, where the rear wing exhibits a �! of 4.02 and 5.75 with closed and open DRS respectively and the efficiencies were 2.60 and 4.23. The surfaces of the wing must be the smoothest possible to maximize performance validated with CFD simulations looking at surface texturing study results. Drawing insights from relevant literature, the most suitable (cost-effective) manufacturing method is determined to be the hot-wire cutting of foam enveloped in carbon fiber. This can be achieved as all the flaps of the wing have a constant section over the span.

This thesis focuses on investigating aerodynamic behaviors in ground vehicles and implementing passive drag-reduction techniques. The study is conducted using Computational Fluid Dynamics (CFD) simulations on the widely recognized DrivAer model. The study evaluates the effectiveness of several passive flow control strategies, such as a closed rim design for the wheels, virtual mirrors and a teardrop rear-end design, on reducing the drag coefficient (CD) and improving the overall vehicle efficiency. The main objective of the study is to determine how these passive strategies can minimize aerodynamic drag, which is crucial in enhancing fuel efficiency and range in both conventional internal combustion engine vehicles and electric vehicles. This is achieved by a comprehensive CFD simulation process using the RANS method and k − ω SST turbulence model. Each drag-reduction device is simulated under controlled conditions to compare the results against a base model, which excludes any drag-reduction modifications. The results of this research demonstrate that passive flow control strategies can play a significant role in reducing aerodynamic drag, thus contributing to energy efficiency and reduction of environmental impact. Overall, the thesis contributes valuable insights into the application of CFD simulations for vehicle design improvements and underscores the importance of aerodynamic efficiency in future automotive technologies.

This thesis investigates the impact of high-order numerical methods on the accuracy of aerodynamic and aeroacoustic results in Direct Noise Computations (DNC) using the Spectral Element Method (SEM). The analysis begins with the Taylor-Green Vortex (TGV) to demonstrate the fundamentals and benefits of high-order methods. The study then focuses on a NACA0012 airfoil to compute and compare aerodynamic and aeroacoustic results against benchmark data. For the TGV case, four different meshes were evaluated, each undergoing p-refinement, where the evolution of total kinetic energy and enstrophy where evaluated against the baseline solution. In the NACA0012 case, three meshes were tested: the second being an h-refinement of the first, and the third a p-refinement of the second. Aerodynamic parameters such as lift, drag, pressure coefficients, and RMS pressure polar distributions around the airfoil were analyzed. The TGV results indicated that increasing polynomial order reduces errors exponentially, while the simulation time per node and iteration scales linearly. Interestingly, the second-highest polynomial order yielded the best accuracy for three of the four meshes, suggesting that the highest order does not always produce superior results. For the NACA0012 airfoil, the aerodynamic results closely matched benchmark solutions, with the finest meshes delivering the highest accuracy. Additionally, the study confirmed that high-order methods effectively capture aeroacoustic phenomena, with smoother results observed on finer meshes. However, discrepancies in pressure fluctuation propagation led to a detailed mesh analysis, concluding that hp-refinement is essential for optimal aeroacoustic accuracy. In summary, this thesis demonstrates the potential of SEM for accurate and computationally efficient noise prediction, although achieving optimal results requires careful selection of hp-refinement for each specific scenario.

El objetivo del presente proyecto es evaluar el impacto en un aeropuerto de las características del aeropuerto Josep Tarradellas Barcelona – El Prat, debido a las modificaciones necesarias en la infraestructura para abastecer aeronaves con propulsión de hidrógeno. Para alcanzar el objetivo, el proyecto se ha divido en tres partes. La primera parte se centra en una evaluación del estado del desarrollo de la tecnología necesaria para la propulsión de hidrógeno. Entre estas tecnologías, se ha describe el funcionamiento de las aeronaves de hidrógeno y los principales desafíos en su desarrollo, los principales cambios en la cadena de suministro del hidrógeno líquido, desde la producción del hidrógeno hasta los métodos de distribución y almacenamiento en el aeropuerto. También se describen los principales cambios operacionales en la infraestructura de un aeropuerto. La segunda parte plantea cinco tipos de escenarios según diferentes visiones en la proyección de las operaciones con combustible de hidrógeno en un aeropuerto. Los escenarios varían desde la entrada de solo pequeñas y aviación privada en el mercado de la aviación, hasta llegar a tener todas las aeronaves que operan propulsadas por hidrógeno para 2060. Además, en esta segunda parte se ha estimado la demanda de hidrógeno para cada uno de los escenarios poniendo como referencia al Aeropuerto de Barcelona, en base al número de operaciones por tipo de aeronave anual desde 2016 hasta 2023 de la base de datos de AENA. En la tercera parte se examina las modificaciones en la infraestructura de un aeropuerto, utilizando el aeropuerto de Barcelona como referencia, para los escenarios planteados en la segunda parte. Los resultados muestran los sistemas e infraestructura que se necesitan para poder suministrar a un número determinado de operaciones, y una hoja de ruta estimada para los escenarios más realistas según la literatura actual, así como usos alternativos que se pueden dar al hidrógeno para la minimización de costes. Además, se presenta un breve análisis del impacto ambiental y económico del proyecto.

Behaviour of Young Adults Towards Air Travel Services investigates the air travel preferences, habits, and decision-making factors of young adults, aged 18-30, residing in the Barcelona region. The primary goal of the thesis is to understand the motivations, socio-demographic influences, and external factors that shape the air travel behaviours of this specific demographic. Through a comprehensive survey, data were collected on travel habits, flight frequency, income levels, travel purpose, and various service preferences such as convenience, flexibility, and brand perception. The research employed several analytical methods, including K-means clustering, a combined hierarchical and K-means clustering approach, and Principal Component Analysis (PCA). These methods were used to identify distinct traveller segments, assess how demographic factors influence travel decisions, and explore the underlying dimensions of travel behaviour. The survey results revealed that the respondents were primarily highly educated and fell into lower to middle-income categories, reflecting diverse but price-sensitive travel behaviours. Frequent travellers tended to prioritize convenience, while occasional travellers placed higher importance on affordability. Additionally, there was a clear divide in preferences for stopovers and direct flights, depending on income and travel frequency. The K-means clustering identified four key traveller segments: Mid-Income Moderate Stay travellers, Young Low-Income travellers, Affluent Short Stay travellers, and Extended Stay Mid-Income travellers. The combined clustering methodology further refined these groups, providing deeper insights into the socio-economic and behavioural drivers of travel decisions. These clusters illustrated that income, stay duration, and convenience are critical factors in distinguishing different groups of young travellers. The Principal Component Analysis, though limited by the low factorability of the dataset, indicated that the variables did not strongly align into distinct components, suggesting that the travel behaviour of young adults is influenced by a wide array of factors that do not easily condense into a few dimensions. The conclusions of the thesis highlight the importance of both price and convenience in shaping travel decisions, with socio-economic factors playing a critical role. Recommendations for airlines include the need to tailor services to different income segments, offering flexible schedules and budget-friendly options for young, price-sensitive travellers. Furthermore, the study acknowledges the growing awareness of environmental sustainability among young adults, suggesting that airlines should integrate environmentally friendly options into their services to appeal to this demographic. The findings underscore the necessity of future research to expand the sample size and include environmental considerations more explicitly in the analysis.

L'objectiu principal d'aquest treball és el disseny d'un sistema de lubricació completament mecànic per la moto E4 de l'equip MotoSpirit. El disseny també engloba totes les fases prèvies, essent aquestes l'argumentació sobre la necessitat de canviar el tipus de lubricació, l'estat de l'art actual sobre el tema i l'esquema del nou sistema que s'ha dissenyat. Un cop conegut el punt de partida, s'han realitzat els càlculs per dimensionar els components. El primer, i potser més important, ha estat la bomba ja que la resta són depenents. Els paràmetres de treball més rellevants s'han obtingut a través d'un programa d'ordinador molt potent. Després de conèixer les limitacions de la bomba s'han dissenyat els engranatges per proporcionar la velocitat de rotació adequada i els eixos per tal que aquests últims es puguin allotjar. En ambdós el material s'ha seleccionat acord amb l'ús que es preveu, i també s'ha realitzat un estudi de les geometries de cadascun per tal de garantir un ús continuat sense fallades. Aquestes últimes verificacions s'han determinat numèricament a través de normes estandarditzades i habituals en el sector. Els últims components que s'han dissenyat e incorporat al conjunt sencer de la moto en 3D han estat els allotjaments. No només s'han ideat per contenir la resta, sinó que també per mantenir la bona ergonomia del pilot durant la conducció. La impressió en 3D de tots els elements del nou sistema de lubricació ha permès verificar el correcte funcionament del sistema així com garantir que el muntatge real és possible.

In the context of numerical combustion, lookup thermochemical tables are widely used to reduce the computational cost of flame simulations. Traditionally, interpolation has been the method to access these tables. However, some studies have explored using artificial neural networks as an alternative to tabulation. These models have to be compared with traditional tabulation in terms of accuracy and computational cost to determine their viability. In the present work, a thermochemical table for H2-Air premixed flames is first calculated using the flamelet model under the mixture fraction and progress variable formulation. Then, different artificial neural networks are trained. Finally, the accuracy, smoothness, and computational cost of these models is discussed.

The Wide Field Monitor (WFM) is a wide field X-ray monitor in the (2-50) keV energy range onboard the Chinese-led eXTP (enhanced X-ray Timing and Polarimetry mission) Satellite. It consists of six identical coded mask cameras with an unprecedented combination of wide field of view and imaging capabilities. The development of the WFM is led by Spain, in particular by the Institute of Space Sciences (ICE-CSIC and IEEC) in Barcelona. One fundamental task as the responsible team for the instrument is the alignment of the instrument, which has a direct influence on the source location accuracy and instrument sensitivity. This master's thesis focuses on the internal alignment of the cameras, centered around two main studies. In the first study, the internal contributions to the misalignment are analyzed systematically using the worst-case tolerance accumulation method, to establish a mathematical expression that relates the alignment requirements with the manufacturing and assembly tolerances of the internal camera elements. The second study evaluates the stability of the alignment, in particular, against thermal deformations, on a fundamental element of the camera: the detector tray assembly. This study considers two scenarios: from the pre-launch to the on-orbit phase, and the on-orbit operational worst case. A Structural Mathematical Model (SMM) of the detector tray assembly is developed specifically for the purpose of evaluating its deformation due to thermal variation, through thermo-elastic Finite Element Analysis (FEA) using MSC Nastran. This work ultimately represents an improved understanding of how the tolerances on the internal camera elements accumulate, and provides valuable insight on the thermal deformation behavior of the detector plane. The studies performed will play a meaningful role in ensuring the WFM cameras fulfil the alignment and stability requirements, crucial to achieve the scientific goals of the WFM instrument.

La agricultura actual se enfrenta a amenazas constantes debido a las sequías recurrentes, las cuales afectan negativamente al desarrollo de los cultivos. Ante esta problemática, surge la necesidad de implementar soluciones innovadoras que permitan una gestión eficiente del agua. En este contexto, los sensores se han consolidado como una herramienta esencial en todo el mundo. ¿Por qué entonces utilizar sensores de humedad del suelo? La respuesta es simple: precisión. Estos dispositivos permiten a los agricultores tomar decisiones informadas sobre el riego al proporcionar datos en tiempo real a través del Internet de las Cosas (IoT). La conexión directa entre sensores y controladores automáticos de riego facilita la implementación de estrategias que evitan tanto el exceso como la escasez de agua en los cultivos. Además, la aplicación de técnicas de impresión electrónica sobre sustratos flexibles se presenta como una alternativa de bajo coste y respetuosa con el medio ambiente para fabricar estas tecnologías. Por lo tanto, las antenas-sensores portátiles se presentan como una opción prometedora en esta tesis. Su desarrollo se divide en varias etapas: una revisión exhaustiva del estado del arte, seguida por el diseño, simulación y optimización de la antena-sensor utilizando el software especializado CST Microwave Studio. Luego, se fabrican manualmente sobre sustratos flexibles y se evalúan los resultados experimentales en un banco de pruebas. Finalmente, se analizarán una serie de parámetros, como la sensibilidad y las figuras de mérito pertinentes, con el propósito de proporcionar un dispositivo totalmente funcional para la medición del contenido de humedad.

Topology Optimization is a well stablished computational technique tailored to optimize material distribution for a given domain by minimizing a cost function and fulfilling a set of constraints. However it is a very demanding technique where, specially for large scale optimization, the computational time becomes prohibitive. Thus, in this thesis different acceleration methodologies are presented in order to improve the current convergence velocities. First, we will deal with accelerating the resolution of the linear system of equations of the elastic problem by introducing the Conjugate Gradient iterative solver with adaptative tolerance. Second, we will also accelerate the optimization process by introducing the momentum term, widely used in machine learning gradient descent algorithms. Additionally, we will also introduce the matrix-free notation of the elastic problem in order to also address the memory limitations of assembling large stiffness matrix. Finally, a mixed acceleration of both elastic problem and optimization will be analysed to determine the best tuning parameters combinations.

This study explores the capabilities of neural networks to accurately predict the material properties of microstructures with complex-shaped void inclusions, while significantly reducing the computational time required compared to traditional computational homogenization methods. The core of this project involves generating datasets that include parameters defining superellipse and superformula-shaped inclusions within unit microcells, alongside the corresponding homogenized tensor components derived through computational homogenization. These datasets serve as the foundation for training a neural network to predict material properties based on the geometric parameters of the microstructural voids. This innovative approach not only integrates geometry, computational homogenization, and neural networks but also represents a substantial advancement in topology optimization. It provides a significant step towards extending microstructural parametric optimizers beyond the limits of finite element methods. The outcomes of this research offer a robust framework for understanding the influence of superellipse and superformula parameters, the mechanics of computational homogenization, the inner workings of neural networks, and the impact on material science and design.

This project consists on the construction of a database for the BiciMAD bike sharing system putting together several relevant data sources containing information such as weather, festivities, and bike station demand among others, as well as realizing a preliminary prediction study with 2 state of the art models. This database is tailored so that it is easy to explore different predictive techniques in order to optimize the prediction of future bikes demand in all the network. To build the database, the following sources have been used; BiciMAD database, containing the status of each bike docking station for every day and hour as well as the recorded bike trip transactions from January 2019 to December 2022 and DatosAbiertos Madrid, specifically Sistema Integral de Calidad del Aire del Ayuntamiento de Madrid, containing several weather variables such as temperature, precipitations, or wind speed in different locations of Madrid (weather stations) at each hour. Also, from DatosAbiertos we obtained information about the working days and holidays. The final dataset consists on a table where each row represents the state of a specific station in a specific hour, being the number of rows of the table stations × hours even though the number of stations was dynamic over time. For the preliminary prediction study over the dataset we have used XGBOOST optimized with Optuna and Graphic Convolutional Neural Networks in a static graph configuration, achieving higher performance for XGBOOST even though in the literature usually GCNN has better performance. As it was a preliminary study, we have not exploited the complete power of each solution. We have analyzed the model performance in several environments such as areas with different characteristics (office areas, residential areas and parks), or time spans with different weather (winter, spring, summer, and rainy days) and also special events such as holidays and work days, observing how the models react to those environments; in most cases capturing the effects present in each test scenario.

This study introduces a computational algorithm to analyze and simulate the self-healing mechanisms in materials, focusing on a novel mathematical model that incorporates reverse mechanical damage at gauss point level, while taking into account energy dissipation within a continuum mechanics framework. The model extends traditional damage formulations by integrating a self-healing function dependent on temperature, time, and the number of healing cycles for a vitrimer-like material. Using experimental data from a hyperbranched polyester (HBP) vitrimer allows to calibrate the damage and instrinsic healing processes without external intervention. While the model shows promising results, especially at higher temperatures, discrepancies at lower temperatures highlight the need for further refinement and validation using a broader range of materials and conditions.