Multi-fidelity surrogates for mechanics of composites: from co-kriging to multi-fidelity neural networks

ArXi:2605.02871v1 Announce Type: cross Composite materials exhibit strongly hierarchical and anisotropic properties governed by coupled mechanisms spanning constituents, plies, laminates, structures, and manufacturing history. This intrinsic complexity makes predictive modeling of composites expensive, because repeated experiments and high-fidelity simulations are needed to cover large design spaces of material, structure, and manufacturing.