Hybrid Physics-Data Models for Simulating Material Behavior Across the Scales

Speaker: Iuri Rocha

Time: 15:00 - 15:45

Location: 0.W100 Turing, Building 28

Zoom: link

Abstract: We increasingly rely on high-performance materials and structures for a wide range of applications, from wind turbines to medical implants. Yet, due to their highly-optimized nature, these materials have also become increasingly difficult to design and study using experimental techniques alone. In my talk I will go through a few of my group’s recent developments on computational modeling of material across the scales. We will quickly come to the conclusion that the models are so computationally expensive that designing new materials would take decades of simulations. I will present how we use machine learning to accelerate these models, including hybrid models with intact physics-based components directly embedded in neural network architectures. I will then wrap up with a GNN-based approach we recently developed for microscale simulation of material behavior, and show how it fits within our broader vision of hybrid models for computational mechanics.

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Speaker: Joep Storm

Abstract:

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