5 papers
A Convolutional Hierarchical Deep-learning Neural Network (C-HiDeNN) Framework for Non-linear Finite Element Analysis
Yingjian Liu, Monish Yadav Pabbala, Jiachen Guo +4
We present a framework for the Convolutional Hierarchical Deep-learning Neural Network (C-HiDeNN) tailored for nonlinear finite element analysis. Building upon the structured found…
WyckoffDiff -- A Generative Diffusion Model for Crystal Symmetry
Filip Ekström Kelvinius, Oskar B. Andersson, Abhijith S. Parackal +3
Crystalline materials often exhibit a high level of symmetry. However, most generative models do not account for symmetry, but rather model each atom without any constraints on its…
Large language model-empowered next-generation computer-aided engineering
Jiachen Guo, Chanwook Park, Dong Qian +2
Software development has entered a new era where large language models (LLMs) now serve as general-purpose reasoning engines, enabling natural language interaction and transformati…
Tensor-decomposition-based A Priori Surrogate (TAPS) modeling for ultra large-scale simulations
Jiachen Guo, Gino Domel, Chanwook Park +8
A data-free, predictive scientific AI model, Tensor-decomposition-based A Priori Surrogate (TAPS), is proposed for tackling ultra large-scale engineering simulations with significa…
Interpolating neural network: A novel unification of machine learning and interpolation theory
Chanwook Park, Sourav Saha, Jiachen Guo +8
Artificial intelligence (AI) has revolutionized software development, shifting from task-specific codes (Software 1.0) to neural network-based approaches (Software 2.0). However, a…