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Title: Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

Abstract

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors,more » including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.« less

Authors:
; ; ; ; ; ; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1362002
Report Number(s):
PNNL-SA-109593
453060037
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: 10th European LS-Dyna Conference, June 15-17, 2015, Wurzburg, Germany
Country of Publication:
United States
Language:
English

Citation Formats

Stander, Nielen, Basudhar, Anirban, Basu, Ushnish, Gandikota, Imtiaz, Savic, Vesna, Sun, Xin, Choi, Kyoo Sil, Hu, Xiaohua, Pourboghrat, F., Park, Taejoon, Mapar, Aboozar, Kumar, Shavan, Ghassemi-Armaki, Hassan, and Abu-Farha, Fadi. Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®. United States: N. p., 2015. Web.
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Stander, Nielen, Basudhar, Anirban, Basu, Ushnish, Gandikota, Imtiaz, Savic, Vesna, Sun, Xin, Choi, Kyoo Sil, Hu, Xiaohua, Pourboghrat, F., Park, Taejoon, Mapar, Aboozar, Kumar, Shavan, Ghassemi-Armaki, Hassan, & Abu-Farha, Fadi. Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®. United States.
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Stander, Nielen, Basudhar, Anirban, Basu, Ushnish, Gandikota, Imtiaz, Savic, Vesna, Sun, Xin, Choi, Kyoo Sil, Hu, Xiaohua, Pourboghrat, F., Park, Taejoon, Mapar, Aboozar, Kumar, Shavan, Ghassemi-Armaki, Hassan, and Abu-Farha, Fadi. 2015. "Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®". United States.
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@article{osti_1362002,
title = {Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®},
author = {Stander, Nielen and Basudhar, Anirban and Basu, Ushnish and Gandikota, Imtiaz and Savic, Vesna and Sun, Xin and Choi, Kyoo Sil and Hu, Xiaohua and Pourboghrat, F. and Park, Taejoon and Mapar, Aboozar and Kumar, Shavan and Ghassemi-Armaki, Hassan and Abu-Farha, Fadi},
abstractNote = {Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.},
doi = {},
url = {https://www.osti.gov/biblio/1362002}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Sep 14 00:00:00 EDT 2015},
month = {Mon Sep 14 00:00:00 EDT 2015}
}
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