An integrated optimization strategy based on Kriging model and multi-objective particle swarm optimization(PSO) algorithm was constructed.As a new surrogate model technology,Kriging model has better fitting precision for nonlinear problem.The Kriging model was adopted to replace computer aided engineering(CAE) simulation as fitness function of multi-objective PSO algorithm,and the computation cost can be reduced greatly.By introducing multi-objective handling mechanism of crowding distance and mutation operator to multiobjective PSO algorithm,the entire Pareto front can be approximated better.It is shown that the multi-objective optimization strategy can get higher solving accuracy and computation efficiency under small sample.
The simulation of injection molding process requires a stable algorithm to model the molten polymer with non-isothermal non-Newtonian property.In this paper,a staggered and iterative scheme is particularly designed to solve the velocity-pressure-temperature variables.In consideration of the polymer characteristic of high viscosity and low thermal conductivity,the non-Newtonian momentum-mass conservation equations are solved by the Crank-Nicolson method based split (CNBS) scheme,and the energy conservation equation with convective character is discretized by the characteristic Galerkin (CG) method.In addition,an arbitrary Lagrangian Eulerian (ALE) free surface tracking and mesh generation method is introduced to catch the front of the fluid flow.The efficiency of the proposed scheme is demonstrated by numerical experiments including a lid-driven cavity flow problem and an injection molding problem.
