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math.NA2023
Resolution-independent generative models based on operator learning for physics-constrained Bayesian inverse problems
Xinchao Jiang, Xin Wang, Ziming Wen +1
The Bayesian inference approach is widely used to tackle inverse problems due to its versatile and natural ability to handle ill-posedness. However, it often faces challenges when…
math.NA2023
A novel reduced basis method for adjoint sensitivity analysis of dynamic topology optimization
Shuhao Li, Hu Wang, Jichao Yin +2
In gradient-based time domain topology optimization, design sensitivity analysis (DSA) of the dynamic response is essential, and requires high computational cost to directly differ…
math.NA2023
An efficient online successive reanalysis method for dynamic topology optimization
Shuhao Li, Hu Wang, Jichao Yin +2
In this study, an efficient reanalysis strategy for dynamic topology optimization is proposed. Compared with other related studies, an online successive dynamic reanalysis method a…