3 papers
math.NA2026
Compression of Polyconvex Envelopes of Isotropic Functions via Monotonic Input Convex Neural Networks
Timo Neumeier, Julian Salmon
This work presents a novel neural-network compression approach for polyconvex envelopes of isotropic functions. The approach relies on a classical sufficient criterion for polyconv…
math.NA2025
Neural Network Enhanced Polyconvexification of Isotropic Energy Densities in Computational Mechanics
Loïc Balazi, Timo Neumeier, Malte A. Peter +1
We present a neural network approach for fast evaluation of parameter-dependent polyconvex envelopes, which are crucial in computational mechanics. Our method uses a neural network…
cs.CE2024
Hierarchical Rank-One Sequence Convexification for the Relaxation of Variational Problems with Microstructures
Maximilian Köhler, Timo Neumeier, Malte. A. Peter +2
This paper presents an efficient algorithm for the approximation of the rank-one convex hull in the context of nonlinear solid mechanics. It is based on hierarchical rank-one seque…