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Bayesian Uncertainty Quantification and Propagation in Structural Dynamics Simulations
| Content Provider | Semantic Scholar |
|---|---|
| Author | Papadimitriou, Costas |
| Copyright Year | 2014 |
| Abstract | A computational framework for Bayesian uncertainty quantification and propagation (UQ+P) in structural dynamics is presented. High performance computing techniques are integrated with Bayesian techniques to efficiently handle large-order models of hundreds of thousands or millions degrees of freedom, and localized nonlinear actions activated during system operation. Fast and accurate component mode synthesis (CMS) techniques, consistent with the finite element model parameterization, are employed to achieve drastic reductions in the model order and the computational effort. Surrogate models are also used to substantially speed-up computations, avoiding full system re-analyses. Significant computational savings are achieved by adopting parallel computing algorithms to efficiently distribute the computations in available multi-core CPUs. Important issues related to the computational efficiency of the Bayesian asymptotic approximations versus the stochastic simulation algorithms for conventional or high performance computing environments are discussed. Implementation issues for Bayesian UQ+P for linear and nonlinear structural dynamics models using vibration measurements are emphasized. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://paginas.fe.up.pt/~eurodyn2014/CD/papers/014_SKN_ABS_2016.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
