Details
| Original language | English |
|---|---|
| Pages (from-to) | 61-71 |
| Number of pages | 11 |
| Journal | Journal of Materials Processing Technology |
| Volume | 229 |
| Publication status | Published - 9 Sept 2015 |
Abstract
An easily applicable method to determine simplified heat transfer coefficients (HTCs), based on numerical modelling and heating experiments by means of response surface optimization (RSO) is introduced. The HTCs determined account for convective and radiative heat transfer. The approach leads to a phenomenological model that neglects phase transformation during heating. Consequently, the HTCs incorporate effects caused by the transformation enthalpy. For the steel 34CrNiMo6 an austenite grain growth model is parameterized and enhanced with a temperature-dependent activation energy to fit experimentally determined grain growth data. The grain growth model and the HTCs determined by RSO are combined into a numerical grain growth simulation for heating processes of large forging parts. Temperature trends of simulated heating processes using HTCs determined by RSO showed good agreement with experimental data and transferability of the HTCs to larger and more complex parts. The parameterized enhanced grain growth model was found to more accurately represent the measured data in the temperature range around 1100 °C than models from literature. Comparison of measured and calculated grain size evolution for temperatures in the range between 950 °C and 1100 °C revealed a very good agreement considering the uncertainties in grain size measurements and also a huge improvement compared to a conservative model. The grain growth simulation of the heating process of a large semi-finished crankshaft showed a significant difference in austenite grain size after the heating and before the forging process between core and near surface areas of above 100%. Consequently, either the optimization of the heating process or the consideration of the inhomogeneous grain size distribution for such parts are relevant for the subsequent thermomechanical treatment, as austenite grain size has an impact on both flow behavior and recrystallization kinetics.
Keywords
- Grain growth, Heat transfer coefficient, Heating process, Model parameterization, Numerical simulation, Tempering steel 34CrNiMo6
ASJC Scopus subject areas
- Materials Science(all)
- Ceramics and Composites
- Computer Science(all)
- Computer Science Applications
- Materials Science(all)
- Metals and Alloys
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Journal of Materials Processing Technology, Vol. 229, 09.09.2015, p. 61-71.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Holistic consideration of grain growth behavior of tempering steel 34CrNiMo6 during heating processes
AU - Herbst, Sebastian
AU - Besserer, Hans Bernward
AU - Grydin, Olexandr
AU - Milenin, Andrzej
AU - Maier, Hans Jürgen
AU - Nürnberger, Florian
N1 - Funding information: The authors thank the German Research Foundation (DFG) for financial support within the project NU297/2-1.
PY - 2015/9/9
Y1 - 2015/9/9
N2 - An easily applicable method to determine simplified heat transfer coefficients (HTCs), based on numerical modelling and heating experiments by means of response surface optimization (RSO) is introduced. The HTCs determined account for convective and radiative heat transfer. The approach leads to a phenomenological model that neglects phase transformation during heating. Consequently, the HTCs incorporate effects caused by the transformation enthalpy. For the steel 34CrNiMo6 an austenite grain growth model is parameterized and enhanced with a temperature-dependent activation energy to fit experimentally determined grain growth data. The grain growth model and the HTCs determined by RSO are combined into a numerical grain growth simulation for heating processes of large forging parts. Temperature trends of simulated heating processes using HTCs determined by RSO showed good agreement with experimental data and transferability of the HTCs to larger and more complex parts. The parameterized enhanced grain growth model was found to more accurately represent the measured data in the temperature range around 1100 °C than models from literature. Comparison of measured and calculated grain size evolution for temperatures in the range between 950 °C and 1100 °C revealed a very good agreement considering the uncertainties in grain size measurements and also a huge improvement compared to a conservative model. The grain growth simulation of the heating process of a large semi-finished crankshaft showed a significant difference in austenite grain size after the heating and before the forging process between core and near surface areas of above 100%. Consequently, either the optimization of the heating process or the consideration of the inhomogeneous grain size distribution for such parts are relevant for the subsequent thermomechanical treatment, as austenite grain size has an impact on both flow behavior and recrystallization kinetics.
AB - An easily applicable method to determine simplified heat transfer coefficients (HTCs), based on numerical modelling and heating experiments by means of response surface optimization (RSO) is introduced. The HTCs determined account for convective and radiative heat transfer. The approach leads to a phenomenological model that neglects phase transformation during heating. Consequently, the HTCs incorporate effects caused by the transformation enthalpy. For the steel 34CrNiMo6 an austenite grain growth model is parameterized and enhanced with a temperature-dependent activation energy to fit experimentally determined grain growth data. The grain growth model and the HTCs determined by RSO are combined into a numerical grain growth simulation for heating processes of large forging parts. Temperature trends of simulated heating processes using HTCs determined by RSO showed good agreement with experimental data and transferability of the HTCs to larger and more complex parts. The parameterized enhanced grain growth model was found to more accurately represent the measured data in the temperature range around 1100 °C than models from literature. Comparison of measured and calculated grain size evolution for temperatures in the range between 950 °C and 1100 °C revealed a very good agreement considering the uncertainties in grain size measurements and also a huge improvement compared to a conservative model. The grain growth simulation of the heating process of a large semi-finished crankshaft showed a significant difference in austenite grain size after the heating and before the forging process between core and near surface areas of above 100%. Consequently, either the optimization of the heating process or the consideration of the inhomogeneous grain size distribution for such parts are relevant for the subsequent thermomechanical treatment, as austenite grain size has an impact on both flow behavior and recrystallization kinetics.
KW - Grain growth
KW - Heat transfer coefficient
KW - Heating process
KW - Model parameterization
KW - Numerical simulation
KW - Tempering steel 34CrNiMo6
UR - http://www.scopus.com/inward/record.url?scp=84942162951&partnerID=8YFLogxK
U2 - 10.1016/j.jmatprotec.2015.09.015
DO - 10.1016/j.jmatprotec.2015.09.015
M3 - Article
AN - SCOPUS:84942162951
VL - 229
SP - 61
EP - 71
JO - Journal of Materials Processing Technology
JF - Journal of Materials Processing Technology
SN - 0924-0136
ER -