The use of parametric reduced-order models in stochastic structural dynamics: Application to uncertainty propagation analysis

H. A. Jensen, F. Mayorga, D. J. Jerez, M. A. Valdebenito

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

An efficient formulation for uncertainty propagation analysis of complex structural models is presented. The formulation is based on parametric reduced-order models. Fixed-interface normal modes and interface modes are approximated in terms of a set of support points in the uncertain parameter space. The potential time-consuming step of computing the modes for different values of the model parameters needs to be performed only at those support points. Based on these approximate modes, reduced-order matrices can be updated efficiently during the simulation process associated with the uncertainty propagation analysis. The effectiveness of the proposed parametric model reduction technique is demonstrated by means of an application problem.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 29th European Safety and Reliability Conference, ESREL 2019
EditoresMichael Beer, Enrico Zio
EditorialResearch Publishing Services
Páginas2754-2760
Número de páginas7
ISBN (versión digital)9789811127243
DOI
EstadoPublicada - 2020
Evento29th European Safety and Reliability Conference, ESREL 2019 - Hannover, Alemania
Duración: 22 sept. 201926 sept. 2019

Serie de la publicación

NombreProceedings of the 29th European Safety and Reliability Conference, ESREL 2019

Conferencia

Conferencia29th European Safety and Reliability Conference, ESREL 2019
País/TerritorioAlemania
CiudadHannover
Período22/09/1926/09/19

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