Dynamic Plasticity Model for Rapidly Heated 1045 Steel Up to 1000 °C

Published

August 27, 2021

Author(s)

Steven Mates, Shengyen Li

Abstract

The National Institute of Standards and Technology (NIST) developed an experimental technique to measure the dynamic flow stress of metals under rapid heating to study their time-dependent plastic response when heating times are short enough to interrupt or bypass thermally driven microstructural evolution. Such conditions may exist as chips are formed in the machining process. Measurements of American Iron and Steel Institute1045 steel behavior up to 1000 °C showed complex thermal softening due to dynamic strain aging effects and the diffusion-limited austenite transformation process beginning at the A1 temperature (712 °C). This paper proposes a constitutive model to capture the flow stress and hardening evolution of 1045 steel under rapidly heated conditions for simulating metal cutting. The model combines the Preston-Tonks Wallace plasticity model, which uses five parameters to capture complex rate- and temperature-sensitive strain hardening, with a dual-rate sensitivity model to capture the response of rapidly heated 1045 steel. Finally, a strain-rate-dependent Gaussian function is introduced to capture dynamic strain aging effects, which act over a narrow range of temperatures that change with strain rate. The proposed model is compared to existing plasticity models for 1045 steel over the range of data available and at a representative machining condition.

Citation

Journal of Research (NIST JRES) -

Volume

126

NIST Pub Series

Journal of Research (NIST JRES)

Pub Type

NIST Pubs

Download Paper

https://doi.org/10.6028/jres.126.026

Local Download

Keywords

carbon steel, constitutive model, high strain rate, high temperature, machining simulations

Citation

Mates, S. and Li, S. (2021), Dynamic Plasticity Model for Rapidly Heated 1045 Steel Up to 1000 °C, Journal of Research (NIST JRES), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/jres.126.026, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=931687 (Accessed November 20, 2024)