Inverse identification of constitutive parameters of Ti_2AlNb intermetallic alloys based on cooperative particle swarm optimization

作     者：Linjiang HE Honghua SU Jiuhua XU Liang ZHANG 

作者机构：College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2018年第31卷第8期

页      面：1774-1785页

核心收录：

学科分类：082502[工学-航空宇航推进理论与工程] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 0825[工学-航空宇航科学与技术] 

基　　金：financial support of the National Natural Science Foundation of China (No. 51475233) 

主　　题：Constitutive parameters Cooperative particle swarmoptimization Finite element modelling Inverse identification Ti2A1Nb intermetallic alloys 

摘      要：Ti_2AlNb intermetallic alloy is a relatively newly developed high-temperature-resistant structural material, which is expected to replace nickel-based super alloys for thermally and mechanically stressed components in aeronautic and automotive engines due to its excellent mechanical properties and high strength retention at elevated temperature. The aim of this work is to present a fast and reliable methodology of inverse identification of constitutive model parameters directly from cutting experiments. FE-machining simulations implemented with a modified Johnson-Cook（TANH） constitutive model are performed to establish the robust link between observables and constitutive parameters. A series of orthogonal cutting experiments with varied cutting parameters is carried out to allow an exact comparison to the 2 D FE-simulations. A cooperative particle swarm optimization algorithm is developed and implemented into the Matlab programs to identify the enormous constitutive parameters. Results show that the simulation observables（i.e., cutting forces, chip morphologies, cutting temperature） implemented with the identified optimal material constants have high consistency with those obtained from experiments,which illustrates that the FE-machining models using the identified parameters obtained from the proposed methodology could be predicted in a close agreement to the experiments. Considering the wide range of the applied unknown parameters number, the proposed inverse methodology of identifying constitutive equations shows excellent prospect, and it can be used for other newly developed metal materials.