5 citations · 13 across the 8 of their papers we have counts for
8 papers
A Physics-Data-Driven Bayesian Method for Heat Conduction Problems
Xinchao Jiang, Hu Wang, Yu li
In this study, a novel physics-data-driven Bayesian method named Heat Conduction Equation assisted Bayesian Neural Network (HCE-BNN) is proposed. The HCE-BNN is constructed based o…
A novel generative reverse net assisted evolution algorithm for expensive-computational optimizations
Yu Li, Hu Wang, Ziming Wen +1
Simulation-based optimization is a useful method for practical design problems. However, it is difficult for complicated problems due to expensive-computational costs. A popular wa…
Machine Learning based parameter tuning strategy for MMC based topology optimization
Xinchao Jiang, Hu Wang, Yu Li +1
Moving Morphable Component (MMC) based topology optimization approach is an explicit algorithm since the boundary of the entity explicitly described by its functions. Compared with…
Image-based reconstruction for the impact problems by using DPNNs
Yu Li, Hu Wang, Wenquan Shuai +2
With the improvement of the pattern recognition and feature extraction of Deep Neural Networks (DPNNs), image-based design and optimization have been widely used in multidisciplina…
Image-Based Reconstruction for a 3D-PFHS Heat Transfer Problem by ReConNN
Yu Li, Hu Wang, Xinjian Deng
The heat transfer performance of Plate Fin Heat Sink (PFHS) has been investigated experimentally and extensively. Commonly, the objective function of the PFHS design is based on th…
IRA assisted MMC-based topology optimization method
Kangjia Mo, Hu Wang, Zhenxing Cheng +1
An Iterative Reanalysis Approximation (IRA) is integrated with the Moving Morphable Components (MMCs) based topology optimization (IRA-MMC) in this study. Compared with other class…