Extending interior-point methods to nonlinear second-order cone programming: Application to finite-strain elastoplasticity

Interior-point methods (IPMs) are well suited for solving convex nonsmooth optimization problems which arise for instance in problems involving plasticity or contact conditions. This work attempts at extending their field of application to optimization problems involving either smooth but nonconvex or nonsmooth but convex objectives or constraints. A typical application for such kind of problems is finite-strain elastoplasticity which we address using a total Lagrangian formulation based on logarithmic strain measures. The proposed interior-point algorithm is implemented and tested on 3D examples involving plastic collapse and geometrical changes. Comparison with classical, Newton-Raphson/return mapping methods show that the IPM exhibits good computational performance, especially in terms of convergence robustness. Similar to what is observed for convex small-strain plasticity, the IPM is able to converge for much larger load steps than classical methods.