Optimizing method for molding process of fiber-reinforced polymer composite parts

An optimizing method for a molding process of a part made of a fiber-reinforced polymer composite, comprising:

• (S1) establishing a Python library required for calculation;
• wherein the Python library comprises an Abaqus library and a genetic algorithm library, and the Abaqus library comprises an abaquesConstants library, a caeModules library, and an odbAccess library;
• (S2) setting simultaneous minimization of molding time, temperature gradient, and residual stress as an optimization goal;
• (S3) setting a variable interval for holding temperature, heating rate, and cooling rate among molding process parameters followed by assigning values to the holding temperature, heating rate, and cooling rate using a random function;
• (S4) establishing a macroscopic thermochemical model of the part according to dimensions and molding environment of the part by using a finite element method, and assigning a material property to the macroscopic thermochemical model;
• analyzing evolution of temperature and curing degree of the fiber-reinforced polymer composite during the molding process of the part by using a heat transfer analysis module;
• rewriting the macroscopic thermochemical model into a thermochemical model function of the molding process parameters, wherein a temperature boundary is applied by transmitting curing process parameters to a first subroutine, and the curing process parameters are randomly generated;
• importing the first subroutine followed by job submission to output calculation results;
• extracting a minimum curing degree in the macroscopic thermochemical model from the calculation results;
• calculating a maximum temperature gradient during the molding process;
• and exporting temperature-time data at a center of the part;
• (S5) establishing a two-dimensional representative volume element (RVE) model by using a Python script from the Python library based on a proportion of individual components and size of a fiber in the fiber-reinforced polymer composite;
• analyzing an elastic modulus change of a resin of the fiber-reinforced polymer composite during the molding process by using a cure hardening instantaneous linear elastic (CHILE) model;
• analyzing stress and strain transformations during the molding process by using a static general module;
• rewriting a microscopic thermomechanics model in the two-dimensional RVE model into a thermomechanics model function of the curing process parameters and simultaneously incorporating the temperature-time data exported in step (S4) as a predefined field into the two-dimensional RVE model;
• importing a second subroutine followed by job submission, wherein the second subroutine is an Abaqus user subroutine;
• and extracting the residual stress from calculation results of Abaqus;
• (S6) calculating a total time of the molding process;
• wherein the total time comprises a heating time, a holding time, and a cooling time;
• (S7) writing a dynamic penalty function, and evaluating a violation-constrained molding process parameter among the molding process parameters using the dynamic penalty function;
• (S8) writing a main function of a genetic algorithm, defining a population size, the number of generations, a crossover distribution index, and a mutation distribution index;
• and calling the thermochemical model function, the thermomechanics model function, and the dynamic penalty function to evaluate individual fitness;
• and
• (S9) plotting a multi-objective optimized Pareto optimal solution set according to the individual fitness, and selecting a set of molding process parameters satisfying actual needs from multiple sets of molding process parameters provided by the multi-objective optimized Pareto optimal solution set, so as to generate an optimized molding process.