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Gemelos digitales basados en modelos subrogados para mantenimiento predictivo de infraestructuras ferroviarias

Authors: Blanco Jiménez, Fernando;

Gemelos digitales basados en modelos subrogados para mantenimiento predictivo de infraestructuras ferroviarias

Abstract

En este Trabajo de Fin de Grado se realizará un modelo subrogado que posteriormente será calibrado a través de unas medidas experimentales. A modo general, se establecerá un contexto acerca del mantenimiento preventivo y los gemelos digitales que ayudarán a comprender mejor la finalidad de este trabajo. Se desarrollará en profundidad los conceptos de algoritmo genético y subrogación que son herramientas útiles para realizar procesos de optimización. Por otro lado, se realizará un caso práctico para implementar en la práctica, los conceptos estudiados de los métodos de optimización. En último lugar, se estudiará el caso de estudio de este trabajo: La estructura E9 – Línea 1 de Metro de Sevilla. Se llevará a cabo un proceso de optimización de las variables sensibles de dicha estructura con el objetivo de establecer un modelo apto para poder determinar los valores de dichas variables críticas de manera que se pueda garantizar la integridad de la estructura siempre y cuando se realicen ensayos experimentales con una cierta periodicidad. Para la realización del trabajo, se exponen las definiciones de los métodos de optimización mediante algoritmos genéticos y subrogación, así como el funcionamiento externo e interno de los mismos. En el caso práctico de una viga simplemente apoyada que se presenta para contemplar dichos métodos, se llevan a cabo unos análisis analíticos y análisis mediante Elementos Finitos. Por último, se analizará la estructura de metro en la que se desarrollarán la definición de la misma, así como las pruebas de carga realizadas sobre esta. Se implementará un modelo de Elementos Finitos en ANSYS que será posteriormente una herramienta fundamental en el proceso de optimización llevado a cabo en MATLAB. De dicho proceso, se obtendrán una serie de resultados y se redactarán una serie de conclusiones.

In this Bachelor's Thesis, a surrogate model will be created and subsequently calibrated through experimental measurements. Generally, a context will be established about preventive maintenance and digital twins to help better understand the purpose of this work. The concepts of genetic algorithms and surrogacy, which are useful tools for optimization processes, will be developed in depth. On the other hand, a practical case will be carried out to implement the studied concepts of optimization methods in practice. Finally, the case study of this work will be examined: The E9 structure – Line 1 of the Seville Metro. An optimization process of the sensitive variables of this structure will be carried out to establish a suitable model to determine the values of these critical variables, ensuring the integrity of the structure as long as experimental tests are carried out periodically. To carry out the work, the definitions of optimization methods using genetic algorithms and surrogacy are presented, as well as their external and internal functioning. In the practical case of a simply supported beam presented to contemplate these methods, analytical analyses and analyses using Finite Elements are carried out. Finally, the metro structure will be analyzed, including its definition and the load tests performed on it. A Finite Element model will be implemented in ANSYS, which will later become a fundamental tool in the optimization process carried out in MATLAB. From this process, a series of results will be obtained, and a series of conclusions will be drafted.

Universidad de Sevilla. Grado en Ingeniería de Tecnologías Industriales

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Spain
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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