Proposed Integration Method Research Articles

TWO SIMPLE FAST INTEGRATION METHODS FOR LARGE-SCALE DYNAMIC PROBLEMS IN ENGINEERING

A new simple explicit two-step method and a new family of predictor–corrector integration algorithms are developed for use in the solution of numerical responses of dynamic problems. The proposed integration methods avoid solving simultaneous linear algebraic equations in each time step, which is valid for arbitrary damping matrix and diagonal mass matrix frequently encountered in practical engineering dynamic systems. Accordingly, computational speeds of the new methods applied to large system analysis can be far higher than those of other popular methods. Accuracy, stability and numerical dissipation are investigated. Linear and nonlinear examples for verification and applications of the new methods to large-scale dynamic problems in railway engineering are given. The proposed methods can be used as fast and economical calculation tools for solving large-scale nonlinear dynamic problems in engineering.

Hourglass Control in Rigid-Plastic Finite Element Analysis

The finite element method, based on rigid-plastic formulation, is widely used to simulate metal forming processes. In order to improve the computational efficiency of the rigid-plastic FEM, one-point integration is used to evaluate the stiffness matrix with four-node rectangular elements and eight-node brick elements. In order to control the hourglass modes, hourglass strain rate components were introduced and included in the effective strain rate definition, Numerical tests have shown that the proposed one-point integration scheme reduces the stiffness matrix evaluation time without deteriorating the convergence behavior of Newton-Raphson method. Simulations of a ring compression, a plane-strain closed-die forging and the three-dimensional spike forging processes were carried out by using the proposed integration method. The simulation results are compared to those obtained by applying the conventional integraiton method in terms of the solution accuracy and computational efficiency.