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  • In this contribution we concentrate on the SFEM based on polynomial chaos expasion (PCE) used for approximation of the model response in the stochastic space. Fast evaluation of the PCE can be then used within Monte Carlo (MC) or Markov chain Monte Carlo (MCMC) sampling so as to quantify the uncertainty in model output, to compute the structural reliability or to update the uncertainty in model inputs based on experimental data.
  • In this contribution we concentrate on the SFEM based on polynomial chaos expasion (PCE) used for approximation of the model response in the stochastic space. Fast evaluation of the PCE can be then used within Monte Carlo (MC) or Markov chain Monte Carlo (MCMC) sampling so as to quantify the uncertainty in model output, to compute the structural reliability or to update the uncertainty in model inputs based on experimental data. (en)
Title
  • Polynomial chaos-based methods for uncertainty quantification and reliability analysis
  • Polynomial chaos-based methods for uncertainty quantification and reliability analysis (en)
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  • Polynomial chaos-based methods for uncertainty quantification and reliability analysis
  • Polynomial chaos-based methods for uncertainty quantification and reliability analysis (en)
skos:notation
  • RIV/68407700:21110/13:00209415!RIV14-GA0-21110___
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  • P(GA13-24027S), P(GAP105/11/0411), P(GAP105/12/1146)
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  • 97107
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  • RIV/68407700:21110/13:00209415
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  • uncertainty quantification; stochastic finite elements; polynomial chaos; stochastic Galerkin; stochastic collocation (en)
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  • [358F4BC65E9C]
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  • Janouchová, Eliška
  • Kučerová, Anna
  • Sýkora, Jan
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  • 21110
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