6 papers
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…
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…
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…
A Spatiotemporal Radar-Based Precipitation Model for Water Level Prediction and Flood Forecasting
Sakshi Dhankhar, Stefan Wittek, Hamidreza Eivazi +1
Study Region: Goslar and Göttingen, Lower Saxony, Germany. Study Focus: In July 2017, the cities of Goslar and Göttingen experienced severe flood events characterized by short wa…
DiffBatt: A Diffusion Model for Battery Degradation Prediction and Synthesis
Hamidreza Eivazi, André Hebenbrock, Raphael Ginster +6
Battery degradation remains a critical challenge in the pursuit of green technologies and sustainable energy solutions. Despite significant research efforts, predicting battery cap…
Enhancing Multiscale Simulations with Constitutive Relations-Aware Deep Operator Networks
Hamidreza Eivazi, Mahyar Alikhani, Jendrik-Alexander Tröger +3
Multiscale problems are widely observed across diverse domains in physics and engineering. Translating these problems into numerical simulations and solving them using numerical sc…