90 citations · 305 across the 20 of their papers we have counts for
7 papers · 1 filter
Prediction of Effective Elastic Moduli of Rocks using Graph Neural Networks
Jaehong Chung, Rasool Ahmad, WaiChing Sun +2
This study presents a Graph Neural Networks (GNNs)-based approach for predicting the effective elastic moduli of rocks from their digital CT-scan images. We use the Mapper algorith…
Prediction of Yield Surface of Single Crystal Copper from Discrete Dislocation Dynamics and Geometric Learning
Wu-Rong Jian, Mian Xiao, WaiChing Sun +1
A yield surface of a material is a set of critical stress conditions beyond which macroscopic plastic deformation begins. For crystalline solids, plastic deformation occurs through…
Physics-constrained symbolic model discovery for polyconvex incompressible hyperelastic materials
Bahador Bahmani, WaiChing Sun
We present a machine learning framework capable of consistently inferring mathematical expressions of hyperelastic energy functionals for incompressible materials from sparse exper…
Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria
Karl A. Kalina, Philipp Gebhart, Jörg Brummund +3
We present a framework for the multiscale modeling of finite strain magneto-elasticity based on physics-augmented neural networks (NNs). By using a set of problem specific invarian…
Discovering interpretable elastoplasticity models via the neural polynomial method enabled symbolic regressions
Bahador Bahmani, Hyoung Suk Suh, WaiChing Sun
Conventional neural network elastoplasticity models are often perceived as lacking interpretability. This paper introduces a two-step machine learning approach that returns mathema…
Synthesizing realistic sand assemblies with denoising diffusion in latent space
Nikolaos N. Vlassis, WaiChing Sun, Khalid A. Alshibli +1
The shapes and morphological features of grains in sand assemblies have far-reaching implications in many engineering applications, such as geotechnical engineering, computer anima…
Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties
Nikolaos N. Vlassis, WaiChing Sun
In this paper, we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generativ…