Output details

Bridging proper orthogonal decomposition methods and augmented Newton-Krylov algorithms: An adaptive model order reduction for highly nonlinear mechanical problems

Time-dependent problems involving small time scales can be tremendously expensive to solve numerically. This paper revisits traditional incremental solution strategies by reusing the past time solutions to fasten the current time increments by orders of magnitude. This work has led to a PhD study at AIRBUS Toulouse, where this algorithm is extended to capture buckling modes in composite laminates. This paper has been cited by important actors of the reduced order modelling community, notably from Stanford and Mines ParisTech.