Extracting elastic-plastic properties from experimental loading-unloading indentation curves using different optimization techniques

Kang, Ji Jun; Becker, Adib A.; Wen, Wu; Sun, Wei

Abstract

This work is focused on the determination of elastic-plastic material properties from indentation loading-unloading curves using optimisation techniques and experimental data from instrumented indentation tests. Three different numerical optimisation methods (namely, FE analysis, dimensional mathematical functions and simplified mathematical equations approaches) have been used to determine three material properties; Young's modulus, yield stress and work-hardening exponent. The predictions of the material properties from the three approaches have been validated against the values obtained from uniaxial tensile tests and compared to the experimental loading-unloading curves. In general, the elastic-plastic material properties predicted from these three proposed optimisation methods estimate the Young's modulus to within 6% and the yield stress and work-hardening exponent to within 12%, compared to the values obtained from the uniaxial tensile tests.

Citation

Kang, J. J., Becker, A. A., Wen, W., & Sun, W. (2018). Extracting elastic-plastic properties from experimental loading-unloading indentation curves using different optimization techniques. International Journal of Mechanical Sciences, 144, https://doi.org/10.1016/j.ijmecsci.2018.05.043

• Journal Article Type: Article
• Acceptance Date: May 21, 2018
• Online Publication Date: May 21, 2018
• Publication Date: Aug 1, 2018
• Deposit Date: Jul 4, 2018
• Publicly Available Date: May 22, 2019
• Journal: International Journal of Mechanical Sciences
• Print ISSN: 0020-7403
• Electronic ISSN: 0020-7403
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 144
• DOI: https://doi.org/10.1016/j.ijmecsci.2018.05.043
• Keywords: Indentation; Finite element analysis; Optimization;; Elastic-plastic; Material properties
• Public URL: https://nottingham-repository.worktribe.com/output/960867
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0020740317323378
• Contract Date: Jul 4, 2018