Abstract

Inconel 718 is a well-known nickel-based superalloy used for high-temperature applications. The aim of the present study was to formulate a constitutive equation (CE) that can be used to account for the deformation behavior of Inconel 718. Compression tests were performed using Gleeble 3800, a thermomechanical simulator, at temperatures ranging from 900 to 1200 °C, at strain rates varying from 0.1 to 10/s. Before compression tests, each specimen was rapidly heated to the desired test temperature while the initial contact pressure was kept relatively low. Thus, compression was performed while the temperature of the entire system, including the specimen and the die, was not uniform. Before conducting an upsetting finite element analysis to determine CE parameters, the heating conditions applied in the Gleeble tests were first subjected to a Joule heating analysis, to simulate the temperature distribution in each specimen prior to the compression process. The spatial temperature distribution of the specimen and the die were determined using a Joule heating analysis, and these results were used as input data for the subsequent finite element analysis of the compression process. From this, the parameters in the obtained Hansel–Spittel equation were estimated for each temperature condition, by employing the regression optimization method, which was used to minimize the deviation between experimental and simulated load values. To validate this optimization process, the experimentally measured flow stresses with respect to the strain rate for each temperature condition were compared with the forming load, determined by the finite element analysis of the compression process using the optimized CE obtained in the present study. It was confirmed that when the optimization process was applied, there was a decrease in the root mean square error. The major findings confirmed the validity of the CE optimization method combined with Joule heating analysis for determining the CE’s parameters for high-temperature applications.

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