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physics.comp-ph2026
Physics-Informed Reduced-Order Operator Learning for Hyperelasticity in Continuum Micromechanics
Hamidreza Eivazi, Henning Wessels
Physics-informed operator learning is an attractive candidate for surrogate modeling of microstructures, especially in multiscale finite-element simulations. Its practical use, how…
physics.comp-ph2026
EquiNO: A Physics-Informed Neural Operator for Multiscale Simulations
Hamidreza Eivazi, Jendrik-Alexander Tröger, Stefan Wittek +2
Multiscale problems are ubiquitous in physics. Numerical simulations of such problems by solving partial differential equations (PDEs) at high resolution are computationally too ex…
physics.comp-ph2025
A Neural Operator based Hybrid Microscale Model for Multiscale Simulation of Rate-Dependent Materials
Dhananjeyan Jeyaraj, Hamidreza Eivazi, Jendrik-Alexander Tröger +3
The behavior of materials is influenced by a wide range of phenomena occurring across various time and length scales. To better understand the impact of microstructure on macroscop…