Split-Hopkinson Pressure Bar Test and Numerical Simulation of Steel Fiber-reinforced High-strength Concrete
Bibliographic record
Abstract
The fabrication and optimization of the shelter layer are critical to the performance of the protective works. The novel shelter layer made of steel fiber-reinforced high-strength concrete (SFRHSC) is much more advantageous than that of ordinary concrete. This paper carries out a split-Hopkinson pressure bar (SHPB) test on the steel fiber and high-strength concrete, two main components of the SFRHSC, aiming to disclose the failure features and dynamic compressive strength of the SFRHSC under dynamic conditions. Specifically, the SFRHSC specimens with 0 %, 0.5 % and 1.0 % of steel fiber were subjected to impact compression test under the air pressures of 0.7, 0.9 and 1.0MPa, respectively. In addition, the impact compression process was also numerically simulated on the finite-element software LS-DYNA. The research results show that: the increase in strain rate pushed up the dynamic compressive strength of the SFRHSC, that is, the failure degree of the specimen was greatly enhanced by the strain rate; under the air pressure of 0.7MPa, the specimen with 1.0 % of steel fiber had the highest dynamic compressive strength (180.9MPa), 22.6 % higher than that of the specimen with no steel fiber; the numerical simulation reproduced the one-dimensional (1D) propagation of the stress wave in the bars, which proves the hypothesis of 1D elastic stress wave, and restaged the impact compression process on the SFRHSC, outputting results similar to the test data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".