An inverse analysis to identify the Johnson-Cook constitutive model parameters for cold wire drawing process

Abstract

Johnson-Cook constitutive equation was utilized to model the 10100 copper and AA 1100 aluminum wires at the cold wire drawing process. Initial Johnson cook parameters were determined through quasi-static tensile tests at different strain rates. Analytical and finite element with VUHARD subroutine solutions were implemented to calculate the drawing forces using the Johnson cook parameters. Wire drawing experiments were carried out at different drawing conditions with two areal reductions and four drawing speeds with the strain rate ranged from 37 s−1 to 115 s−1 and wire drawing forces were measured using a load cell connected to the drawing die. Results showed that the Johnson cook model with parameters determined from a quasi-static condition was not able to predict the material behavior at the wire drawing process with a moderate strain rate. In order to modify the initial JC parameters an inverse analysis approach was adopted. An objective function was defined based on analytical and experimental drawing forces differences with respect to JC parameters. Using the Newton–Raphson method, new JC parameters were identified by minimizing the objective function. Updated Johnson cook parameters showed much more correlation with experimental results.

Assessing the Feasibility of Cold Forming of Automotive Parts from Quenched and Partitioned Martensitic Stainless Steels

“…It must be emphasized that while the J-C model is capable of simulating materials experiencing deformations under variable strain rate and temperature conditions, its application in scenarios where strain is the only variable does not diminish its simulation capabilities. In situations where only strain varies, as observed in previous studies [16][17][18][19] and the present paper, the J-C model is capable of independently handling this variable. This is due to the model's formulation, which accounts for the inherent independence of strain, strain rate, and temperature by representing them as separate factors in the equation.…”

“…Likewise, in ref. [17] the authors find a good agreement of the numerical data with regard to the prediction of the behavior of copper and aluminum alloys when being processed through a cold wire drawing cycle, or in ref. [18], where the authors explore the simulation of the oscillating cold-forming process by using the J-C model coupled with different unloading models, finding that one of the combinations could successfully describe the experimentally observed deformation.…”

“…On the other hand, in another work [ 16 ] the authors analyze the prediction capabilities of the model regarding the simulation of a steel material when subjected to the cold roll‐beating, finding that the data of the true stress generated during the simulated procedure are consistent with those obtained with experimental methods. Likewise, in ref [17]. the authors find a good agreement of the numerical data with regard to the prediction of the behavior of copper and aluminum alloys when being processed through a cold wire drawing cycle, or in ref.…”

“…On the other hand, in another work [17] the authors analyze the prediction capabilities of the model regarding the simulation of a steel material when subjected to the cold roll-beating, finding that the data of the true stress generated during the simulated procedure are consistent with those obtained with experimental methods. Likewise, in [18] the authors find a good agreement of the numerical data with regard to the prediction of the behavior of copper and aluminum alloys when being processed through a cold wire drawing cycle, or in [19], where the authors explore the simulation of the oscillating cold forming process by using the J-C model coupled with different unloading models, finding that one of the combinations could successfully describe the experimentally observed deformation. It must be emphasized that while the J-C model is capable of simulating materials experiencing deformations under variable strain rate and temperature conditions, its application in scenarios where strain is the only variable does not diminish its simulation capabilities.…”

A combined experimental and numerical approach that eliminates the non-uniqueness associated with the Johnson-Cook parameters obtained using inverse methods

“…The determined material model parameter set is used in the computational or analytical models and validated with experimental results. Although experiments such as uniaxial, isothermal compression testing of cylindrical specimens [13], laser peening [14], and cold wire drawing [15] have been used for validation purposes, the most widely used experimental technique is based on orthogonal machining.…”