Study on the dynamic mechanical properties and fractal characteristics of thermally-treated red sandstone under impact loading
Bibliographic record
Abstract
Abstract During deep unconventional resource extraction, high temperatures and dynamic loads exert a substantial impact on the stability of geotechnical structures. In this study, an improved Split Hopkinson Pressure Bar (SHPB) system was employed to conduct dynamic impact tests on high-temperature-treated red sandstone specimens at different impact velocities. A systematic analysis was carried out to investigate the effects of high temperature and impact velocity on the changes in dynamic mechanical properties and failure modes of the sandstone. Based on sieve test results, the size distribution of fragmented particles was quantified using fractal dimension analysis. Furthermore, by integrating thermal gravimetric analysis (TGA) and scanning electron microscopy (SEM), a clear correlation between the thermal damage evolution of sandstone and its microstructural degradation was established, thus providing novel insight into the dynamic failure mechanism. The results indicate that the dynamic mechanical properties of red sandstone show a significant temperature-dependent effect, following a decreasing trend described by a quadratic function. An increase in temperature significantly decreases the difference in dynamic strength of rocks under varying impact velocities. The particle size distribution of sandstone fragments displays statistical self-similarity, remaining unaffected by changes in temperature or loading velocity. At high loading rates, strain rate effects lead to a reduced influence of temperature on the fractal dimension. These findings offer valuable insights for the optimization of wellbore stability and enhancement of rock fragmentation efficiency.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".