Thermodynamically consistent damage evolution model coupled with rate-dependent crystal plasticity: Application to high-strength low alloy steel at various strain rates
Bibliographic record
Abstract
• Experimental characterization of HSLA steel is conducted. • Rate sensitive damage evolution model is proposed. • Thermodynamic framework is developed to capture internal temperature rise. • Thermodynamically consistent rate-dependent crystal plasticity damage model is developed and validated. • Stress-strain response and internal temperature changes are successfully predicted. High-strength low-alloy (HSLA) steels demonstrate superior strength and load-bearing capacity compared to traditional plain carbon steel. However, these steels are susceptible to microstructural damage even at intermediate strain rates, which can compromise their performance in automotive application. This research aims to investigate the stress-strain response, internal temperature rise, and damage evolution in HSLA steels under quasi-static and intermediate strain rates. The initial microstructure of two different grades of HSLA steels, HR340 and HR550, are characterized using Electron Backscatter Diffraction (EBSD) data. During uniaxial tensile tests at various strain rates, a high-speed infrared thermal camera is utilized to capture the rise of the instantaneous surface temperature within the gauge section of the specimens. A new, thermodynamically consistent rate-dependent crystal plasticity formulation is developed. The damage evolution is governed by a thermodynamic driving force that accounts for various effects (i.e., temperature, void nucleation, and void growth). A power-law based damage formulation is proposed to account for the effects of strain rates and internal temperature rise on the damage evolution. The constitutive model is implemented into a crystal plasticity (CP) formulation to study the effects of damage, temperature and texture evolution on localized deformation in HSLA steel. The constitutive model is calibrated using experimental stress-strain data and temperature evolution measurements at different strain rates. The new model not only accurately predicts the softening/post-necking behaviour and failure of HR340 and HR550 but also accurately captures temperature variations in the material, aligning well with experimental results. The texture evolution prediction by the developed model also demonstrated good agreement with experimentally observed texture evolution at different strain rates. This study highlights the significant influence of strain rate and internal temperature rise on the damage, dislocation density evolution and microstructural behavior of HSLA steels. The model serves as a robust physics-based foundation for future investigative studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".