A machine learning-based surrogate model for optimization of truss structures with geometrically nonlinear behavior HT Mai, J Kang, J Lee Finite Elements in Analysis and Design 196, 103572, 2021 | 48 | 2021 |
A novel deep unsupervised learning-based framework for optimization of truss structures HT Mai, QX Lieu, J Kang, J Lee Engineering with Computers 39 (4), 2585-2608, 2023 | 31 | 2023 |
A robust physics-informed neural network approach for predicting structural instability HT Mai, TT Truong, J Kang, DD Mai, J Lee Finite Elements in Analysis and Design 216, 103893, 2023 | 12 | 2023 |
A robust unsupervised neural network framework for geometrically nonlinear analysis of inelastic truss structures HT Mai, QX Lieu, J Kang, J Lee Applied Mathematical Modelling 107, 332-352, 2022 | 12 | 2022 |
Physics-informed neural energy-force network: a unified solver-free numerical simulation for structural optimization HT Mai, DD Mai, J Kang, J Lee, J Lee Engineering with Computers 40 (1), 147-170, 2024 | 11 | 2024 |
Optimum design of nonlinear structures via deep neural network-based parameterization framework HT Mai, S Lee, D Kim, J Lee, J Kang, J Lee European Journal of Mechanics-A/Solids 98, 104869, 2023 | 7 | 2023 |
An improved blind Kriging surrogate model for design optimization problems HT Mai, J Lee, J Kang, H Nguyen-Xuan, J Lee Mathematics 10 (16), 2906, 2022 | 4 | 2022 |
A damage-informed neural network framework for structural damage identification HT Mai, S Lee, J Kang, J Lee Computers & Structures 292, 107232, 2024 | | 2024 |