WaiChing Sun

1. A review on data-driven constitutive laws for solids
   2024/05/06 by Jan N. Fuhg, Govinda Anantha Padmanabha, Fuhg, Jan Niklas +15 · 25 citations
   Engineering · #74-02 (Primary) #Advanced machining processes and optimization #Applied Physics (physics.app-ph) #Computational Engineering #Elasticity and Material Modeling #FOS: Computer and information sciences #FOS: Physical sciences #Finance #Machine Learning (cs.LG) #Metallurgy and Material Forming #and Science (cs.CE)
2. Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables
   2024/01/25 by Max Rosenkranz, Rosenkranz, Max, Karl A. Kalina +7 · 8 citations
   Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Elasticity and Material Modeling #Non-Destructive Testing Techniques
3. Physics-constrained symbolic model discovery for polyconvex incompressible hyperelastic materials
   2023/10/06 by Bahador Bahmani, WaiChing Sun, Bahmani, Bahador +1 · 5 citations
   Physics and Astronomy · Engineering · Mathematics · #Model Reduction and Neural Networks #Elasticity and Material Modeling #Tensor decomposition and applications
4. Neural networks meet anisotropic hyperelasticity: A framework based on generalized structure tensors and isotropic tensor functions
   2024/10/04 by Karl A. Kalina, Jörg Brummund, Kalina, Karl A. +5 · 9 citations
   Engineering · #Computational Engineering #Elasticity and Material Modeling #FOS: Computer and information sciences #Finance #and Science (cs.CE)
5. Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria
   2023/08/30 by Karl A. Kalina, Philipp Gebhart, Kalina, Karl A. +9 · 6 citations
   Computer Science · Engineering · #Advanced Mathematical Modeling in Engineering #Advanced Numerical Methods in Computational Mathematics #Composite Material Mechanics #Computational Engineering #FOS: Computer and information sciences #Finance #and Science (cs.CE)
6. Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings
   2021/07/24 by Bahador Bahmani, Bahmani, Bahador, WaiChing Sun +1 · 2 citations
   Engineering · Physics and Astronomy · #FOS: Computer and information sciences #Fluid Dynamics and Turbulent Flows #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Nuclear Engineering Thermal-Hydraulics
7. Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter
   2022/09/27 by Ruben Villarreal, Villarreal, Ruben, Nikolaos N. Vlassis +13 · 1 citation
   Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Optimal Experimental Design Methods #Probabilistic and Robust Engineering Design
8. Prediction of Effective Elastic Moduli of Rocks using Graph Neural Networks
   2023/10/30 by Jaehong Chung, Rasool Ahmad, Chung, Jaehong +7 · 2 citations
   Engineering · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Geophysics (physics.geo-ph) #Hydrocarbon exploration and reservoir analysis #Machine Learning (cs.LG) #Mineral Processing and Grinding #Rock Mechanics and Modeling