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Erschienen in: Journal of Materials Engineering and Performance 8/2017

30.06.2017

Parameter Identification of GTN Model Using Response Surface Methodology for High-Strength Steel BR1500HS

verfasst von: Li-yong Wang, Le Li

Erschienen in: Journal of Materials Engineering and Performance | Ausgabe 8/2017

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Abstract

In order to investigate the damage evolution of ultra-high-strength steels at different temperatures, a series of the uniaxial tensile tests were carried out at different temperatures (20-800 °C) with a constant true strain rate (1 s−1). And then, two different deformation mechanisms were employed to describe the flow behaviors of BR1500HS. It is found that dynamic recrystallization (DRX) occurs during the deformation process at high temperatures (600-800 °C), while the tensile flow behaviors exhibit a very long work hardening period before a short flow softening stages without DRX at lower temperatures of 20-400 °C Furthermore, the Gurson-Tvergaard-Needleman (GTN) damage model was employed in this work to evaluate the ductile damage phenomena of BR1500HS. To determine the four vital parameters in GTN model, several numerical simulations were designed by central composite design and conducted by finite element simulation, and then the error evaluation functions (R) were established using four GTN parameters. Thereafter, the four parameters of GTN model were determined along with four minimum values of R by use of response surface methodology (RSM) and least square method. The results show that temperature affects the microvoid volume fraction significantly. Additionally, the parameters of GTN model were applied in the finite element simulation model and a comparison between the simulation results and the scanning electron microscopic observations was conducted.

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Metadaten
Titel
Parameter Identification of GTN Model Using Response Surface Methodology for High-Strength Steel BR1500HS
verfasst von
Li-yong Wang
Le Li
Publikationsdatum
30.06.2017
Verlag
Springer US
Erschienen in
Journal of Materials Engineering and Performance / Ausgabe 8/2017
Print ISSN: 1059-9495
Elektronische ISSN: 1544-1024
DOI
https://doi.org/10.1007/s11665-017-2806-4

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