199 citations · 302 across the 61 of their papers we have counts for
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Physics-informed Kolmogorov-Arnold networks (PIKANs) for noise-robust reconstruction of boiling heat flux from infrared measurements
Siavash Khodakarami, Parimala Vardhan Vydyula, Aniruddha Bora +2
Recovering a noise-amplified inverse quantity from corrupted boundary data is a recurring problem in physics-informed learning for real-world applications. Specifically, small pert…
Multi-fidelity surrogates for mechanics of composites: from co-kriging to multi-fidelity neural networks
Haizhou Wen, Elham Kiyani, Gang Li +3
Composite materials exhibit strongly hierarchical and anisotropic properties governed by coupled mechanisms spanning constituents, plies, laminates, structures, and manufacturing h…
H3PC: Hypersonic, High-Order, High-Performance Code with Adaptive Mesh Refinement and Real Chemistry
Ahmad Peyvan, Khemraj Shukla, George Em Karniadakis
We have developed a hypersonic high-order, high-performance code (HPC) utilizing the ``Trixi.jl" framework in order to simulate both non-reactive and chemically reactive compre…
Predicting Crack Nucleation and Propagation in Brittle Materials Using Deep Operator Networks with Diverse Trunk Architectures
Elham Kiyani, Manav Manav, Nikhil Kadivar +2
Phase-field modeling reformulates fracture problems as energy minimization problems and enables a comprehensive characterization of the fracture process, including crack nucleation…