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Model-reduction techniques for Bayesian finite element model updating using dynamic response data

机译:利用动态响应数据进行贝叶斯有限元模型更新的模型简化技术

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摘要

This work presents a strategy for integrating a class of model reduction techniques into a finite element model updating formulation. In particular a Bayesian model updating approach based on a stochastic simulation method is considered in the present formulation. Stochastic simulation techniques require a large number of finite element model re-analyses to be performed over the space of model parameters during the updating process. Substructure coupling techniques for dynamic analysis are proposed to reduce the computational cost involved in the dynamic re-analyses. The effectiveness of the proposed strategy is demonstrated with identification and model updating applications for finite element building models using simulated seismic response data.
机译:这项工作提出了将一类模型归约技术集成到有限元模型更新公式中的策略。特别地,在本发明中考虑了基于随机模拟方法的贝叶斯模型更新方法。随机模拟技术需要在更新过程中对模型参数空间进行大量的有限元模型重新分析。提出了用于动态分析的子结构耦合技术,以减少动态重新分析所涉及的计算成本。通过使用模拟地震响应数据对有限元建筑模型进行识别和模型更新应用,证明了所提出策略的有效性。

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