36 citations · 64 across the 7 of their papers we have counts for
3 papers · 1 filter
Crack Path Prediction with Operator Learning using Discrete Particle System data Generation
Elham Kiyani, Venkatesh Ananchaperumal, Ahmad Peyvan +3
Accurately modeling crack propagation is critical for predicting failure in engineering materials and structures, where small cracks can rapidly evolve and cause catastrophic damag…
Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity
Benjamin Shih, Ahmad Peyvan, Zhongqiang Zhang +1
Neural operator learning models have emerged as very effective surrogates in data-driven methods for partial differential equations (PDEs) across different applications from comput…
RiemannONets: Interpretable Neural Operators for Riemann Problems
Ahmad Peyvan, Vivek Oommen, Ameya D. Jagtap +1
Developing the proper representations for simulating high-speed flows with strong shock waves, rarefactions, and contact discontinuities has been a long-standing question in numeri…