{"title":"Crashworthiness Simulations with LS-DYNA Investigating the Effect of Strain Rate-Dependent Material Models","authors":"E. Ezgi Aytimur","doi":"10.1016/j.prostr.2025.06.094","DOIUrl":null,"url":null,"abstract":"<div><div>This study investigates the effect of using strain rate-dependent material models, specifically the Johnson-Cook, Cowper-Symonds and Elastic (non-strain rate effect) models, on crashworthiness simulations involving mild steel. The research examines the deformation, stress, deceleration and recovery coefficients of these models under single impact simulations conducted according to regulations of NHTSA. Ansys LS-DYNA version 13.1 was used for the simulation and material parameters were obtained from the study of Škrlec and Klemenc (2016) on mild steel E185. The results show various degrees of deformation where the Johnson-Cook model exhibits the lowest total deformation due to its ability to accurately capture strain rate sensitivity. Equivalent stress values show that the Johnson-Cook model has the highest stress, followed by the Cowper-Symonds and Elastic models. Deceleration values emphasize the superior prediction accuracy of the Johnson-Cook model, while restitution coefficients reveal differences in energy dissipation and recovery between the models. The findings emphasize the importance of selecting appropriate material models for collision simulations based on accuracy, computational efficiency and complexity tolerance. While the Johnson-Cook model offers improved prediction capabilities, it may require higher computational resources compared to simpler models such as the Elastic model. In conclusion, this study contributes to the understanding of material behaviour under dynamic loading conditions and provides insights for optimizing crash simulations to improve vehicle safety and structural integrity.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"68 ","pages":"Pages 540-546"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia Structural Integrity","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2452321625000952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigates the effect of using strain rate-dependent material models, specifically the Johnson-Cook, Cowper-Symonds and Elastic (non-strain rate effect) models, on crashworthiness simulations involving mild steel. The research examines the deformation, stress, deceleration and recovery coefficients of these models under single impact simulations conducted according to regulations of NHTSA. Ansys LS-DYNA version 13.1 was used for the simulation and material parameters were obtained from the study of Škrlec and Klemenc (2016) on mild steel E185. The results show various degrees of deformation where the Johnson-Cook model exhibits the lowest total deformation due to its ability to accurately capture strain rate sensitivity. Equivalent stress values show that the Johnson-Cook model has the highest stress, followed by the Cowper-Symonds and Elastic models. Deceleration values emphasize the superior prediction accuracy of the Johnson-Cook model, while restitution coefficients reveal differences in energy dissipation and recovery between the models. The findings emphasize the importance of selecting appropriate material models for collision simulations based on accuracy, computational efficiency and complexity tolerance. While the Johnson-Cook model offers improved prediction capabilities, it may require higher computational resources compared to simpler models such as the Elastic model. In conclusion, this study contributes to the understanding of material behaviour under dynamic loading conditions and provides insights for optimizing crash simulations to improve vehicle safety and structural integrity.