Determination of Johnson Cook Parameters in Turning of Micro and Nano Reinforced Aluminum Composites using Trust Region Reflective Algorithm
Ravi Sekhar1, T. P. Singh2
1Ravi Sekhar*, Research Scholar, Symbiosis Institute of Technology (SIT), Symbiosis International (Deemed University) (SIU), Pune.
2T. P. Singh, Thapar Institute of Engineering and Technology, Patiala, India. Email:
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 1712-1716 | Volume-8 Issue-12, October 2019. | Retrieval Number: L31831081219/2019©BEIESP | DOI: 10.35940/ijitee.L3183.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Accuracy of shear stress estimations plays a vital role in correct prediction of cutting forces in machining. In this study, efforts were directed to obtain better flow stress estimates through determination of novel Johnson Cook (JC) parameters for a number of micro and nano reinforced composite materials. Trust region reflective algorithm (non linear least squares) was used to determine optimum JC constants for each developed material subjected to varying machining parameters under high strain rate conditions. The newer JC constants yielded substantially better shear stress estimates as compared to base alloy JC constants; thus in turn improving cutting force predictability in machining of developed composite materials.
Keywords: Metal Matrix Composites, Cutting Forces, Shear Stress, Johnson Cook, Non linear least Squares
Scope of the Article: Algorithm Engineering