Identification of ductile fracture model parameters for three ASTM structural steels using particle swarm optimization  

作　　者：Ya-zhi ZHU Shi-ping HUANG Hao HONG 

机构地区：[1]Department of Structural Engineering,Tongji University,Shanghai 200092,China [2]School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,China [3]China-Singapore International Joint Research Institute,Guangzhou 510700,China [4]Shanghai Municipal Engineering Design Institute(Group),Co.,Ltd.,Shanghai 200092,China

出　　处：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2022年第6期421-442,共22页浙江大学学报（英文版）A辑（应用物理与工程）

基　　金：the National Natural Science Foundation of China(No.51908416);the Shanghai Pujiang Program(No.19PJ1409500);the Fundamental Research Funds for the Central Universities,China。

摘　　要：Accurate prediction of ductile fracture requires determining the material properties,including the parameters of the constitutive and ductile fracture model,which represent the true material response.Conventional calibration of material parameters often relies on a trial-and-error approach,in which the parameters are manually adjusted until the corresponding finite element model results in a response matching the experimental global response.The parameter estimates are often subjective.To address this issue,in this paper we treat the identification of material parameters as an optimization problem and introduce the particle swarm optimization(PSO)algorithm as the optimization approach.We provide material parameters of two uncoupled ductile fracture models—the Rice and Tracey void growth model(RT-VGM)and the micro-mechanical void growth model(MM-VGM),and a coupled model—the gurson-Tvergaard-Needleman(GTN)model for ASTM A36,A572 Gr.50,and A992 structural steels using an automated PSO method.By minimizing the difference between the experimental results and finite element simulations of the load-displacement curves for a set of tests of circumferentially notched tensile(CNT)bars,the calibration procedure automatically determines the parameters of the strain hardening law as well as the uncoupled models and the coupled GTN constitutive model.Validation studies show accurate prediction of the load-displacement response and ductile fracture initiation in V-notch specimens,and confirm the PSO algorithm as an effective and robust algorithm for seeking ductile fracture model parameters.PSO has excellent potential for identifying other fracture models(e.g.,shear modified GTN)with many parameters that can give rise to more accurate predictions of ductile fracture.Limitations of the PSO algorithm and the current calibrated ductile fracture models are also discussed in this paper.

关 键 词：Parameter calibration Void growth model(VGM) Gurson-Tvergaard-Needleman(GTN)model A36 steel A572 Gr.50 steel A992 steel Particle swarm optimization(PSO) 

分 类 号：TG142.41[一般工业技术—材料科学与工程] TP18[金属学及工艺—金属材料]