Vol.128, No.1, 2021, pp.87-108, doi:10.32604/cmes.2021.015227
Parameters Calibration of the Combined Hardening Rule through Inverse Analysis for Nylock Nut Folding Simulation
  • İlyas Kacar*
Faculty of Engineering, Department of Mechatronics Engineering, Niğde Ömer Halisdemir University, Niğde, Turkey
* Corresponding Author: İlyas Kacar. Email:
Received 02 December 2020; Accepted 16 April 2021; Issue published 28 June 2021
Locking nuts are widely used in industry and any defects from their manufacturing may cause loosening of the connection during their service life. In this study, simulations of the folding process of a nut’s flange made from AISI 1040 steel are performed. Besides the bilinear isotropic hardening rule, Chaboche’s nonlinear kinematic hardening rule is employed with associated flow rule and Hill48 yield criterion to set a plasticity model. The bilinear isotropic hardening rule’s parameters are determined by means of a monotonic tensile test. The Chaboche’s parameters are determined by using a low cycle tension/compression test by applying curve fitting methods on the low cycle fatigue loop. Furthermore, the parameter calibrations are performed in the finite element simulations by using an optimization approach based on the inverse analysis. Dimensional accuracy for the nut is of primary concern due to the tolerance constraints of the nut manufacturers. Experimental diameter and height measurements of the folded locking nut are compared with those obtained from the optimized model. The results reveal that the folding dimensions can be predicted more accurately when the model parameters are determined by using the combined hardening rule. The calibrated parameters are presented for the folding and cycling deformation processes.
Optimization; Chaboche kinematic hardening; bilinear isotropic hardening; nylock nut folding; genetic algorithm
Cite This Article
Kacar, . (2021). Parameters Calibration of the Combined Hardening Rule through Inverse Analysis for Nylock Nut Folding Simulation. CMES-Computer Modeling in Engineering & Sciences, 128(1), 87–108.
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