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Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled-Data Control of a Semi-Active Suspension with Magnetorheological Dampers
No full textThis paper presents a novel control design methodology for a magnetorheological (MR) damper-based semi-active suspension system operating under communication-induced time delays, which introduce nonlinear sampled-data dynamics. To address these challenges, a linear matrix inequality (LMI) framework is developed for synthesizing the current controller, with the dual goals of enhancing ride comfort and safety while ensuring system stability and robustness against road disturbances. The proposed approach deliberately avoids the use of Lyapunov-Krasovskii functionals, offering a more practical and computationally efficient alternative. Experimental results confirm that the proposed MR damper model outperforms traditional Lyapunov-Krasovskii-based methods. Additionally, two simulated road profiles are used to evaluate the suspension system¿s behavior, further demonstrating the effectiveness of the proposed control strategy.This work was supported in part by UC3M’s grants for young doctors (Grant No. 2024/00741/001) and by the grant [PID2022-136468OB-I00] funded by MCIN/AEI/10.13039/501100011033, and by “ERDF A way of making Europe”
Las manifestaciones del fantasma en la narrativa de Javier Marías
No full textPrograma de Doctorado en Humanidades por la Universidad Carlos III de MadridPresidenta: Natalia Álvarez Méndez.- Secretario: Daniel Andreas Verdu Schumann.- Vocal: Raquel Velázquez Velázque
Implementación del criptosistema postcuántico CRYSTALS-Kyber y análisis de sus trazas de consumo de potencia para la ejecución de ataques por canal lateral
No full textLa llegada de la computación cuántica ha supuesto un cambio en los estándares criptográficos actuales, ya que los algoritmos cuánticos son capaces de resolver los problemas
matemáticos sobre los que se basan muchos sistemas criptográficos tradicionales. CRYSTALS-Kyber es uno de los sistemas criptográficos propuestos por el NIST como
estándar criptográfico, con el propósito de estar preparados ante la llegada de la computación cuántica.
En este trabajo se pretende comprobar si el algoritmo CRYSTALS-Kyber puede exponer información sensible por un canal lateral. Para ello, cargaremos el código en un dispositivo capaz de extraer trazas de consumo de potencia, y utilizaremos el método TVLA (Test Vector Leakage Assessment) para comprobar si existe una correlación entre
el consumo de potencia del dispositivo Chipwhisperer y la información sensible.
Tras evaluar 10.000 trazas, el resultado obtenido no es concluyente al no haber alcanzado el valor objetivo de TVLA, pero la trayectoria obtenida muestra una uniformidad lo
suficientemente alta como para estimar que, en caso de obtener más trazas, TVLA logrará alcanzar el valor objetivo, sugiriendo que sí puede haber una correlación entre las trazas de consumo de potencia y la información sensible.Grado en Ingeniería Informátic
Advanced methods for orbital uncertainty characterization applied to the Space Surveillance and Tracking
No full textMención Internacional en el título de doctorTesis por compendio de publicacionesThe large growth of human-related space activity in the last years has led to the overpopulation of objects orbiting the Earth, most of them being space debris, which jeopardizes the exploitation and sustainability of the space environment. For this reason, space agencies and government institutions are fostering space situational awareness activities to ensure the safety of spacecraft operations, improving their capabilities to detect and predict hazards to active and future space missions. Those activities are based on space surveillance and tracking activities, aimed at detecting space objects using sensor networks, estimating and predicting their orbits, and creating a catalog of objects to store their information for purposes such as manoeuvre detection, conjunction analysis, re-entry predictions, or fragmentation detection.
The quality of those services relies not only on the accurate estimation of the objects state, but also on its associated uncertainty. However, most common orbit determination systems in space surveillance activities, based on batch least-squares estimation, disregard the uncertainty present in the dynamic and measurement models of the space system. This leads to a lack of realism in the uncertainty estimates of those processes, which deteriorates significantly the reliability of space situational awareness products.
This dissertation focuses on advanced methodologies for uncertainty characterization and quantification in space surveillance and tracking applications, with the ultimate goal of developing accurate yet efficient methodologies to improve uncertainty realism with direct applicability to operational environments. First, one of the main drawbacks of most uncertainty characterization models is that realistic values of such model parameters are not available. Therefore, a robust framework to quantify the uncertainty in dynamic and measurement models is developed in this dissertation, based on observing the system uncertainty with orbital differences between estimated and predicted orbits and applying
simple yet flexible and physically-based uncertainty models suitable to tackle specific error sources. These models are tailored to the most relevant errors in Earth’s orbits, namely the atmospheric drag and solar proxies prediction in LEO, solar radiation pressure, or observation biases, distinguishing between different orbital regimes. Along this dissertation, these uncertainty quantification methods are consolidated in more complex applications to catalogs of objects to quantify uncertainty models common to multiple spacecraft, and then the characterization of the atmospheric drag uncertainty is improved by means of stochastic models including time correlation. This dissertation in focused on the operational applicability of the developed methodologies and the assessment of its capabilities in terms of covariance realism, which is validated in complex simulation environments but also with real observations as final verification of their performance.El gran crecimiento de la actividad espacial relacionada con el ser humano en los últimos años ha provocado la sobrepoblación de objetos orbitales alrededor de la Tierra, la mayoría de ellos basura espacial, lo que pone en peligro la explotación y sostenibilidad del espacio. Por este motivo, las agencias espaciales y las instituciones gubernamentales están fomentando actividades de conocimiento de la situación espacial para garantizar la seguridad de las operaciones espaciales, mejorando sus capacidades para detectar y predecir peligros para las misiones espaciales activas y futuras. Estas actividades se basan en actividades de vigilancia y seguimiento espacial, cuyo objetivo es detectar los objetos mediante redes de sensores, estimar y predecir sus órbitas, y crear un catálogo de objetos para almacenar su información con fines como la detección de maniobras, el análisis de conjunciones, la predicción de reentradas o la detección de fragmentaciones.
La calidad de esos servicios depende no sólo de la estimación precisa del estado del objeto, sino también de su incertidumbre asociada. Sin embargo, la mayoría de los sistemas de determinación de órbita habituales en las actividades de vigilancia espacial, basados en la estimación de mínimos cuadrados, no tienen en cuenta la incertidumbre presente en los modelos dinámicos y de medidas. Esto conduce a una falta de realismo en las estimaciones de incertidumbre de dichos procesos, lo que deteriora significativamente la fiabilidad de los productos de conocimiento de la situación espacial.
Esta tesis se centra en metodologías avanzadas para la caracterización y cuantificación de la incertidumbre en aplicaciones de vigilancia y seguimiento espacial, con el objetivo último de desarrollar metodologías precisas pero eficientes para mejorar el realismo de la incertidumbre con aplicabilidad directa a entornos operativos. En primer lugar, uno de los principales inconvenientes de la mayoría de los modelos de caracterización de la incertidumbre es que no se dispone de valores realistas de dichos parámetros del modelo. Por lo tanto, en esta tesis se desarrolla un marco robusto para cuantificar la incertidumbre en modelos dinámicos y de medidas, basado en la observación de la incertidumbre del sistema con diferencias orbitales entre las órbitas estimadas y las predichas, y en la aplicación de modelos de incertidumbre sencillos pero flexibles y con base física, adecuados para abordar fuentes de error específicas. Estos modelos se adaptan a los errores más relevantes en las órbitas terrestres, como el rozamiento atmosférico, la predicción de proxies solares, la presión de la radiación solar o los sesgos de observación, distinguiendo entre los distintos regímenes orbitales. A lo largo de esta tesis, estos métodos de cuantificación de la incertidumbre se consolidan en aplicaciones más complejas a catálogos de objetos para cuantificar modelos de incertidumbre comunes, y posteriormente se mejora la caracterización de la incertidumbre del rozamiento atmosférico mediante modelos estocásticos con correlación temporal. Esta tesis se centra en la aplicabilidad operativa de las metodologías desarrolladas y en la evaluación de sus capacidades de mejora del realismo de covarianza, que se valida en entornos de simulación complejos pero también con observaciones reales como verificación final de su rendimiento.Programa de Doctorado en Ingeniería Aeroespacial por la Universidad Carlos III de MadridPresidente: Rafael Vázquez Valenzuela; Secretario: Michele Maestrini; Vocal: Aaron Jay Rosengre
Fast recovery mode for micro-meteoroid impacts: A LISA mission study
No full textThis article studies and provides a plausible solution to address the effects of micro-particle impacts on the LISA mission. The influence of these undesired events are analysed using a set of 8 worst-case impact conditions from an ESA database of more than 200,000 impacts that captures the anticipated micro-meteoroid environment that the LISA spacecraft may encounter in a span of its envisioned 6.5 years of mission. Based on the results of this analysis, a novel operational mode called SCIHOLD is proposed to provide fast recovery from micro-meteoroid impacts. The performance of the SCIHOLD mode is validated using a LISA high-fidelity, non-linear simulator in two steps. Firstly, the identified 8 worst-case impacts are evaluated in nominal and dispersed conditions in a Monte Carlo campaign, and secondly, larger impacts beyond the ones in the database are simulated to assess the recovery limits of the proposed recovery mode. The results show that the proposed operational mode is successful in recovering the LISA spacecraft from the impacts, and most importantly, that this is achieved with a mean overall recovery time of 92.5 s, a considerable reduction compared to a full re-acquisition scenario typically lasting hours.This work was part of the APSIS project that received funding by the European Space Agency under contract No. 4000129430/19/NL/CRS/hh. Dr. Marcos gladly acknowledges funding as Beatriz Galindo Distinguished Senior Investigator by the Spanish Government, and additional funding by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of “Research Funds for Beatriz Galindo Fellowships” (SPACEROBCON-CMUC3M), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation)
Code Rejuvenation: From Vector Compiler Intrinsics to Portable Standardized SIMD
No full textLegacy code is hard to refactor, and often times, the effort needed to rejuvenate old code is substantial. In particular, compiler intrinsics are often used for clearly and unambiguously expressing low-level vectorization. It is not uncommon for C++ codebases to make use of compiler intrinsics, especially if high performance is critical. Nevertheless, they can be verbose and hard to debug. The C++ standard library introduces std::simd, which is emerging as a high level abstraction for expressing vectorization, allowing for more readable and portable code. Additionally, many of the transformations from compiler intrinsics to std::simd expressions are straightforward and mechanical. However, refactoring code from compiler intrinsics to std::simd can be time-consuming and bug-prone, especially when unfamiliar with the new syntax. With the help of static analysis techniques, it is possible to automatize the process, and ensure code correctness when applying the transformation. In this paper, we introduce a set of techniques to assist developers in the process of migrating existing code bases to a standardized approach for expressing vectorization that is portable to multiple architectures.Funding for APC: Universidad Carlos III de Madrid (Agreement CRUE-Madroño 2025
Reconstruction of the transient plume cross-section of a pulsed plasma thruster
No full textThe exhaust of a small ablative pulsed plasma thruster (PPT), fed with polytetrafluoroethylene and operated at 1000V of discharge voltage and 6µF of capacitance, is characterized by means of a novel diagnostic system. The technique time-reconstructs its plume cross-sectional expansion, and consists of an array of electrostatic wire probes biased at the ion saturation regime. The two-dimensional and time-dependent ion current distribution is reconstructed from the probe data using a variable separation algorithm. The new method is valid for plumes of both unsteady and steady-operation electrical plasma thrusters. The PPT plume contains at least three distinct ion groups with different mean velocities, with the second one carrying the major part of the ion current. Spatially, the plume exhibits a single-peaked profile in the direction perpendicular to the PPT electrodes, while in the direction parallel to them it features two peaks and a greater divergence angle. A small spatial asymmetry involving a deviation of the current towards the cathode and to one of the sides of the channel is also present.This work was initiated with the support of the ESPEOS project, funded by the Agencia Estatal de Investigación (Spanish National Research Agency) under Grant number PID2019-108034RB-I00/AEI/10.13039/501100011033. Additional support was provided by the ADAPT project, which fully supports this work at the time of publication, co-funded by the Agencia Estatal de Investigación (Spanish National Research Agency) and the European Union under Grant number PID2023-150052OB-I00
Artificial Intelligence-Based Methods for Drug Repurposing and Development in Cancer
No full textDrug discovery and development remains a complex and time-consuming process, often hindered by high costs and low success rates. In the big data era, artificial intelligence (AI) has emerged as a promising tool to accelerate and optimize these processes, particularly in the field of oncology. This review explores the application of AI-based methods for drug repurposing and natural product-inspired drug design in cancer, focusing on their potential to address the challenges and limitations of traditional drug discovery approaches. We delve into various AI-based approaches (machine learning, deep learning, and others) that are currently being employed for these purposes, and the role of experimental techniques in these approaches. By systematically reviewing the literature, we aim to provide a comprehensive overview of the current state of AI-assisted cancer drug discovery workflows, highlighting AI's contributions to accelerating drug development, reducing costs, and improving therapeutic outcomes. This review also discusses the challenges and opportunities associated with the integration of AI into the drug discovery pipeline, such as data quality, interpretability, and ethical considerations.This study was supported in part by grants from the Spanish Ministry of Science and Innovation and the European Regional Development fund (PID2020-119792RB-I00), the Institute of Health Carlos III (RD21/0001/0022, Spanish Network of Advanced Therapies, TERAV-ISCIII), and the Fundación Mutua Madrileña (project: FMM-AP16030-2024). SHG is supported by a UC3M-PhD research training scholarship (PIPF)
Design and characterisation of new low-alloyed alumina forming ferritic/martensitic steels
Get PDFNew efficient energy generation systems require materials capable of withstanding aggressive environments. The Cr-rich oxides formed by commercial stainless steels are not protective enough, so alumina (Al2O3) forming steels such as alumina-forming austenitic (AFA) steels and FeCrAl have been proposed as possible materials. However, they are prone to irradiation swelling or exhibit poor creep resistance. This study aims to develop a new kind of alloy, an Alumina Forming Ferritic-Martensitic steel, which combines the superior oxidation resistance from an alumina scale with the creep and irradiation swelling resistance of a martensitic structure. Thermodynamic simulations guided the alloy design of five Fe-Cr-Ni-Al compositions through a powder metallurgy route, ending with Spark Plasma Sintering of solid samples. EBSD and TEM analysis of the samples showed martensite in 4 out of the 5 sintered alloys, with various levels of retained austenite or ferrite in their structures. Tensile and small punch tests from room temperature to 500 degrees C demonstrated comparable mechanical properties to other AFA steel and to T91 and 316L, candidate materials for nuclear applications. After exposure to air at 800 degrees C for 500 h, the designed alloys formed protective aluminium oxide scales with corrosion rates similar to 316L and orders of magnitude better than T91. The results show that the developed alloys are promising for components subjected to aggressive environments and elevated temperatures.This work has been developed through grant PID2019-109334RB-C32 funded by AEI, and funding for APC: Universidad Carlos III de Madrid (Agreement CRUE-Madroño 2024)
Essays on the Economics of Gender
Get PDFPrograma de Doctorado en Economía por la Universidad Carlos III de MadridPresidenta: Liberta González.- Secretario: Luigi Minale.- Vocal: Paula Gobb