Quenching is one of the primary processes to improve mechanical properties in steels, particularly hardness. Quenching is well established for different geometries of individually treated steel components; while in-steam quenching of large diameter continuously cast steel bar has several specific features which are difficult and costly to experimentally optimize. The end-quench Jominy test has been used extensively to study the hardenability of different steel grades. Different numerical, analytical, and empirical models have been developed to simulate the Jominy process and to understand quenching of steels. However, it is not straight forward to translate experimental data from Jominy test on instream quenched large diameter continuously cast products. Therefore, in this work, coupled thermal, mechanical, and metallurgical models were used to simulate the end-quench Jominy test and in-stream quenched industrial round billets with a goal to obtain similarity of experimental structure and properties for both quenched products. For this purpose, finite element analysis (FEA) was employed using the software FORGE (by Transvalor). Used thermophysical properties were generated by JMATPro software. The evolution of microstructure during quenching and resulting hardness were simulated for AISI 4130, and AISI 4140 steel grades. The cooling rates at different positions in the Jominy bar were determined by simulation and compared to experimental. After verification and validation, the FEA simulation was utilized to predict different phases and hardness at different conditions in industry produced round billets. Additionally, relations between Jominy positions and radial positions in the billet were established allowing us to predict structure and properties in inline quenched continuously cast bar having different diameters.

This paper presents a method for calculating quench severity based on hardness profile matching. The new method has the potential to eliminate the need for Jominy end-quench testing as required in the traditional Kern approach. To assess the accuracy of the proposed method, a test bar and Jominy bar were machined from 2-in. bar stock and heat treated in accordance with ASTM A255. The test bar was quenched in a draft-tube system with a water velocity of 6 ft/s. An excel workbook was programmed to calculate the quenched hardness profile based on prior austenite grain size and steel chemistry. The calculations were in good agreement with measured Jominy hardness as were the quench severities determined by the Kern method and the proposed hardness profile matching technique.

A method of predicting tempered hardness of mixed microstructures has been formulated, which uses the quenched hardness and steel chemistry as independent variables. This calculation is based upon a method first proposed in 1947 by Crafts and Lamont for mixed microstructures and modified using the 1977 chemistry-based, tempered martensite hardness calculation of Grange, Hribal, and Porter. Tempered hardness predictions were examined using Jominy end-quench bars tempered between 204°C (400°F) and 649°C (1200°F). The measured Jominy hardness after tempering was used to make adjustments to the Crafts and Lamont parameters used in the hybrid model. Both plain carbon (SAE 1045) and low alloy (SAE grades 8620, 4130, 4142, and 5160) were used to evaluate the chemistry-based hardness prediction. In combination with a ASTM A255 Jominy hardenability calculation, the proposed calculation can be used to predict the quenched and tempered hardness profile of a round bar based upon chemistry, quench severity, and tempering temperature.

Accurate simulation of phase transformation during quenching of steels requires comprehensive knowledge of thermal and physical properties of the material. In cases when reliable material data are not available they can be obtained by a two-stage inverse method proposed in the paper. It includes a Jominy test of a specimen with thermocouples. At the first stage, we obtain TTT diagrams by means of analyzing cooling curves for several regions of the specimen obtained from experimental results. The second stage includes correction of material thermo-physical properties, i.e. the thermal conductivity and specific heat for each phase as well as estimation of the latent heat for each phase transformation. Parameters fitting is carried out iteratively by comparing FEM simulation and experimental results. Varying of parameters is performed with evolutionary methods of multi-parameter optimization. The developed method is implemented in QForm commercial software.