Predicting Open-Hole Laminates Failure Using Support Vector Machines With Classical and Quantum Kernels

arXiv:2405.02903v1 Announce Type: cross
Abstract: Modeling open hole failure of composites is a complex task, consisting in a highly nonlinear response with interacting failure modes. Numerical modeling of this phenomenon has traditionally been based on the finite element method, but requires to tradeoff between high fidelity and computational cost. To mitigate this shortcoming, recent work has leveraged machine learning to predict the strength of open hole composite specimens. Here, we also propose using data-based models but to tackle open hole …

abstract arxiv cs.ce cs.lg cs.na element failure fidelity machines math.na modeling numerical quantum quantum kernels support support vector machines type vector