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Implementation of an adaptive meta-model for Bayesian finite element model updating in time domain

机译:贝叶斯有限元模型时域更新的自适应元模型实现

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摘要

This work explores the feasibility of integrating an adaptive meta-model into a finite element model updating formulation using dynamic response data. A Bayesian model updating approach based on a stochastic simulation method is considered in the present formulation. Such approach is combined with a surrogate technique and an efficient model reduction technique. In particular, an adaptive surrogate model based on kriging interpolants and a model reduction technique based on substructure coupling are implemented. The integration of these techniques into the updating process reduces the computational effort to manageable levels allowing the solution of complex problems. The effectiveness of the proposed strategy is demonstrated with three finite element model updating applications.
机译:这项工作探讨了使用动态响应数据将自适应元模型集成到有限元模型更新公式中的可行性。在本公式中考虑了基于随机仿真方法的贝叶斯模型更新方法。这种方法与替代技术和有效的模型简化技术结合在一起。特别地,实现了基于克里金插值的自适应代理模型和基于子结构耦合的模型简化技术。将这些技术集成到更新过程中,可将计算工作量降低到可管理的水平,从而可以解决复杂的问题。三种有限元模型更新应用程序证明了所提出策略的有效性。

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