Multi-objective parameter identification and optimization for dislocation-dynamics-based constitutive modeling of Ti–6Al–4V alloy

• Published in: Journal of alloys and compounds Vol. 821; p. 153460
• Main Authors: Wang, Yuntian, Zeng, Xiangguo, Sheng, Ying, Yang, Xin, Wang, Fang
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 25.04.2020; Elsevier BV
• Subjects: Advanced genetic algorithm; Constitutive model; Constitutive models; Deformation mechanisms; Dislocation dynamics; Genetic algorithms; Hypercubes; Identification methods; Latin hypercube sampling; Mathematical models; Mechanical properties; Multiple objective analysis; Optimization; Parameter identification; Parameter optimization; Parameter sensitivity; Plastic deformation; Sensitivity analysis; Titanium base alloys; Ti–6Al–4V alloy; Yield strength; Ti–6Al–4V alloy; Constitutive model; Advanced genetic algorithm; Parameter optimization; Dislocation dynamics
• ISSN: 0925-8388; 1873-4669
• DOI: 10.1016/j.jallcom.2019.153460

Based on the plastic deformation mechanism and dislocation dynamics theory, a constitutive model to describe the mechanical behavior of the Ti–6Al–4V alloy over a wide range of strain rates and temperatures is proposed. The relationships between the constitutive model parameters and microstructural characteristics, as well as their physical significance, were described. The constitutive model contains 12 parameters. A new hybrid approach was developed to obtain the constitutive parameters from the existing experimental data. There were two main parts of the approach. First, to analyze the overall constitutive parameter sensitivity, the Latin hypercube sampling (LHS) and Spearman rank correlation (SRC) methods were applied. The effectiveness and accuracy of the parameter identification and sensitivity analysis results were improved significantly. Second, the parameter optimization was developed using an advanced genetic algorithm including the enhanced niche genetic algorithm, suspicious peak point judgment strategy, and local accuracy searching technology. Finally, the flow stress–plastic strain curve of the Ti–6Al–4V alloy over a wide range of strain rates and temperatures was reproduced through the proposed method. It was shown that the predicted results agreed reasonably well with the existing experimental data. •New method for building physically based constitutive model for Ti–6Al–4V is proposed.•Intelligent algorithms used to optimize multi-objective constitutive parameters.•Good agreement between the constitutive model prediction and experimental data.•Great reference for identification of other material constitutive parameters.•Applicable for sensitivity analysis and identification of constitutive parameters.