journal article·2020-06

Modeling of Temperature Gradients During Short Time Dilatometry Testing

Robert Goldstein, Tareq Eddir, Ethan Buchner, Robert Cryderman, Andrew Banka, Andrew Senita

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Abstract

Dilatometry test systems are commonly used for characterizing the transformation behavior of steels. For rapid heating and quenching, small specimens are commonly utilized in combination with induction heating and gas quenching. In these systems, the steel test article is assumed to have a uniform temperature throughout the sample. This is a good assumption for slow heating and cooling rates; however, for simulating induction hardening cycles, this assumption may not be accurate. Using computer models, it is possible to predict the temperature dynamics of the sample, both radially and axially, during the thermal processing cycle (heating and cooling). O1 tool steel specimens 4 mm diameter by 10 mm long were utilized for heating and quenching tests on a DIL805L dilatometer to characterize and model heating and cooling temperature gradients. Specimens instrumented with multiple thermocouples were induction heated and helium gas quenched. The test data and geometry were evaluated with 1-D and 2-D induction heating models along with 3-D CFD cooling models to characterize transient temperature gradients. The goal of the modeling is to better characterize temperature corrections required when rapid heating and cooling processes are used to determine transformation temperatures in induction hardenable steels. There were limited temperature gradients during heating at 50 °C/s, but large temperature variations were developed during quenching with helium. An investigation was undertaken to evaluate alternate cooling system designs to provide improved temperature uniformity during the cooling process.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Microstructure and Mechanical Properties of Steels · Induction Heating and Inverter Technology · Metallurgy and Material Forming

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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