Model Dimension Reduction in Non-linear Finite Element Dynamics of Solids and Structures

A general approach to the dimension reduction of non-linear finite element models of solid dynamics is presented. It is shown how for the Newmark implicit discretization in time the computationally most expensive phase in the equilibrium iteration, namely the solution of the system of linear equations for displacement increments, can be formulated in an approximation basis of much reduced dimension. Similarly, the explicit Newmark algorithm can be also written in a reduced-dimension basis, and the computation time savings in that case follow from an increase in the stable time step length. In addition, the empirical eigenvectors are proposed as the basis in which to expand the incremental problem. This basis achieves approximation optimality by using the observation of the response of the full model to construct a reduced basis which reproduces the full system in a statistical sense. Because of this “global” time viewpoint, the basis need not be updated as with reduced bases computed from a linearization of the full finite element model. If the dynamics of a finite element model is expressed in terms of a small number of basis vectors, the asymptotic cost of the solution with the reduced model is lowered. At the same time, numerical experiments indicate that by using reduced models substantial savings can be achieved even in the pre-asymptotic range. The presented method is expected to become a useful tool in applications requiring a large number of repeated non-linear solid dynamics simulations, such as convergence studies, design optimization, and design of controllers of mechanical systems.