Mechanical Property Test and Damage Evaluation Analysis of Steel Fiber Stainless-Steel Reinforced Concrete Beams (SFSRCBs) under Impact Load
Bibliographic record
Abstract
Abstract In this paper, the ultra-high drop hammer impact test system is adopted for the vertical impact experiment on six SFSRCBs with steel fiber volume fraction of 2.0% and build the relevant numerical model. The research variables mainly include impact energy, impact mass and cumulative impact mode. The results show that, under a single equal energy impact, with the increase of the impact speed, the crack distribution of the specimen gradually tends to the mid-span local position. Compared with the impact mass, the impact speed has a greater effect on the failure mode, deformation resistance and deformation recovery ability of SFSRCBs. When the total cumulative impact energy is the same as the single impact energy, then the overall damage of the specimen caused by high-mass low-velocity cumulative impact is less significant than that caused by low-mass high-velocity cumulative impact. Combined with the finite element analysis, the calculation formula of the maximum deflection of SFSRCB under impact load is obtained. Finally, the calculation method of the impact damage evaluation factor of SFSRCBs is proposed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.712 | 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".