Detalhes bibliográficos
| Resumo: | Rail temperature prediction plays a crucial role in ensuring railway safety, as extreme temperatures can cause local buckling and track instability. This study conducts a reliability- based sensitivity analysis of a previously developed prediction model using MATLAB and UQLab. Two analyses were performed: a global sensitivity analysis considering all parameters as random variables and a Data-Driven Sensitivity Analysis incorporating measured data for key variables to refine the model and enhance its practical applicability. Results indicate that uncertainties in convection and solar absorption are the most influential parameters affecting the response statistics of the rail temperature predictions. Future work will focus on refining parameter distributions and conducting Monte Carlo simulations to improve model accuracy and assess its reliability in unmeasured conditions. |
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| Autores principais: | Frigeri, Ary V.N. |
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| Outros Autores: | Bosse, Rubia M.; Piloto, Paulo A.G.; Minhoto, Manuel |
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| Assunto: | Railway prediction model temperature sensitivity analysis |
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| Ano: | 2025 |
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| País: | Portugal |
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| Tipo de documento: | comunicação em conferência |
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| Tipo de acesso: | acesso aberto |
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| Instituição associada: | Instituto Politécnico de Bragança |
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| Idioma: | inglês |
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| Origem: | Biblioteca Digital do IPB |
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