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Author

Jay Mahishi

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Sep 2026

PINNA: Physics‐Informed Neural Networks Architecture for Implicit Governing Physics With Interpretability

PINNA is validated across three fundamentally different benchmarks: two composite‐material problems involving nonlinear stress‐strain behavior and multistage failure, and a large‐scale 1‐D laminar combustion problem governed by stiff chemical kinetics, thermal transport, and reduced fluid mechanics.

Zheng-Tao Yao, Philippe Hawi, V. Aitharaju et al. · 0 citations

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