On multi-objective based constitutive modelling methodology and numerical validation in small-hole drilling of Al6063/SiCp composites

Junfeng Xiang, Lijing Xie*, Feinong Gao, Yu Zhang, Jie Yi, Tao Wang, Siqin Pang, Xibin Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Discrepancies in capturing material behavior of some materials, such as Particulate Reinforced Metal Matrix Composites, by using conventional ad hoc strategy make the applicability of Johnson-Cook constitutive model challenged. Despites applicable efforts, its extended formalism with more fitting parameters would increase the difficulty in identifying constitutive parameters. A weighted multi-objective strategy for identifying any constitutive formalism is developed to predict mechanical behavior in static and dynamic loading conditions equally well. These varying weighting is based on the Gaussian-distributed noise evaluation of experimentally obtained stress-strain data in quasi-static or dynamic mode. This universal method can be used to determine fast and directly whether the constitutive formalism is suitable to describe the material constitutive behavior by measuring goodness-of-fit. A quantitative comparison of different fitting strategies on identifying Al6063/SiCp's material parameters is made in terms of performance evaluation including noise elimination, correlation, and reliability. Eventually, a three-dimensional (3D) FE model in small-hole drilling of Al6063/SiCp composites, using multi-objective identified constitutive formalism, is developed. Comparison with the experimental observations in thrust force, torque, and chip morphology provides valid evidence on the applicability of the developed multi-objective identification strategy in identifying constitutive parameters.

Original languageEnglish
Article number97
JournalMaterials
Volume11
Issue number1
DOIs
Publication statusPublished - 11 Jan 2018

Keywords

  • Composites
  • Constitutive modelling
  • Drilling
  • Measured noise
  • Multi-objective identification
  • Varying weighting

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