| Data-driven multiscale finite-element method using deep neural network combined with proper orthogonal decomposition S Kim, H Shin Engineering with Computers 40 (1), 661-675, 2024 | 25 | 2024 |
| Deep learning framework for multiscale finite element analysis based on data-driven mechanics and data augmentation S Kim, H Shin Computer Methods in Applied Mechanics and Engineering 414, 116131, 2023 | 20 | 2023 |
| Development of Homogenization Data-based Transfer Learning Framework to Predict Effective Mechanical Properties and Thermal Conductivity of Foam Structures W Lee, S Kim, HJ Sim, JH Lee, BH An, YJ Kim, SY Jeong, H Shin Composites Research 36 (3), 205-210, 2023 | 4 | 2023 |
| Accelerating the data-driven multiscale finite element analysis for elastoplastic materials by using proper orthogonal decomposition and transformer architecture S Kim, H Shin Computer Methods in Applied Mechanics and Engineering 437, 117827, 2025 | | 2025 |
| Design of thermal conductivity of mercapto group-activated graphene/epoxy nanocomposites using the molecular dynamics simulation and Gaussian process regression-based Bayesian … H Wang, S Kim, J Lee, H Shin Surfaces and Interfaces 56, 105571, 2025 | | 2025 |
| A Data-driven Multiscale Analysis for Hyperelastic Composite Materials Based on the Mean-field Homogenization Method S Kim, W Lee, H Shin Composites Research 36 (5), 329-334, 2023 | | 2023 |
| MLP, GR, RBF 인공신경망을 이용한 분자 동역학 데이터 기반 초탄성 구성방정식 모델링 김수한， 왕호림， 이원주， 안병혁， 김유정， 이주호， 신현성 대한기계학회 논문집 A 권 47 (1), 49-57, 2023 | | 2023 |
