粘塑性本构模型材料参数识别的降维优化方法及其应用

Dimensionality Reduction Optimization Method about Material Parameter Identification of Viscoplastic Constitutive Models and Its Application

关键词:  粘塑性  本构模型  材料参数识别  降维优化方法  推进系统  热端部件  高温合金

Key words:  Viscoplasticity  Constitutive models  Material parameter identification  Dimensionality reduction optimization method  Propulsion system  Hot section  Superalloy

摘要:

为了建立简单高效的材料参数优化方法，将张量形式的本构方程降低维度，表达为标量形式的本构方程，利用Matlab软件完成了标量本构模型与数学优化算法的一体化集成，开发了材料参数优化程序组，获得了FGH96，K417G，IC10，DD26高温合金不同温度下的材料参数，并利用有限元软件Abaqus软件Material library模块对材料参数进行存储管理。结果显示：所建立的参数优化方法计算代价小，优化效率高，操作相对简单，可快速自动地获得粘塑性模型的材料参数；调用计算程序及Material library模块中的相关数据，能够较为精确地模拟高温合金的短时拉伸性能与长时蠕变性能，可完成复杂温度场下涡轮叶片的蠕变分析。

Abstract:

The aim of this investigation is to develop a simple and efficient material parameter optimization method. The constitutive tensor equations were rearranging to scalar ones. The integration of the scalar constitutive model and mathematical optimization algorithm was achieved by Matlab software， and the material parameter optimization program was developed. The material parameters of FGH96，K417G，IC10，DD26 at different temperatures were obtained. The Material library module of Abaqus software was used to store and manage these material parameters. The results show that the developed parameter optimization method had the advantages of low calculation cost， high optimization efficiency， and relatively simple implementation. The material parameters of viscoplastic model could be obtained efficiently and automatically by this optimization method. Calling the routines and the material parameters in the Material library module， the short-term tensile properties and the long-term creep properties of these superalloys were simulated accurately. The creep analysis of a turbine blade under complex temperature fields was further completed.