Elastic-plastic transition in high-strength structural alloys: A simulation approach with LS-DYNA

Abstract

The elastic-plastic transition in high-strength structural alloys is a critical phenomenon governing the mechanical performance of materials under various loading conditions. This study investigates the stress-strain behavior of high-strength alloys, including advanced high-strength steels (AHSS), titanium alloys (Ti-6Al-4V), and nickel-based superalloys (Inconel 718), through experimental testing and LS-DYNA finite element simulations. The primary objective is to develop and validate a computational model for predicting the elastic-plastic transition, considering strain hardening, strain rate sensitivity, and damage evolution. Quasi-static and high-strain-rate mechanical tests were conducted on tensile specimens following ASTM E8/E8M standards, while LS-DYNA simulations incorporated Johnson-Cook and Gurson-Tvergaard-Needleman (GTN) material models to replicate the observed deformation behavior.The results reveal a strong correlation (r = 0.9999) between experimental and simulated stress-strain curves, confirming the accuracy of LS-DYNA in modeling plastic deformation. The mean stress increased with strain rate, reaching 1000 MPa at 1000 s⁻¹, validating the strain-rate sensitivity of these alloys. Regression analysis showed a slope of 0.982 and a minimal standard error of 0.00013, demonstrating a near-ideal agreement between simulation and experimental data. Comparisons with past studies indicate that LS-DYNA extends previous modeling efforts by integrating high-strain-rate effects, improving predictive capability, and optimizing computational efficiency.The study concludes that LS-DYNA is a reliable tool for modeling the elastic-plastic transition in high-strength alloys, with applications in automotive safety, aerospace engineering, and structural health monitoring. Practical recommendations include integrating LS-DYNA into industrial material selection, manufacturing processes, and digital twin systems for real-time failure prediction and structural optimization. Future research should explore microstructural modeling, multi-physics simulations, and adaptive meshing techniques to further enhance computational accuracy and efficiency.