Numerical Assessment of Reinforcing Details in Beam-Column Joints on Blast Resistance
Bibliographic record
Abstract
This numerical study investigated the effects of different reinforcing details in beam-column joints on the blast resistance of the joints. Due to increasing manmade and/or natural high rate accidents such as impacts and blasts, the resistance of critical civil and military infrastructure or buildings should be sufficiently obtained under those high rate catastrophic loads. The beam-column joint in buildings is one of critical parts influencing on the resistance of those buildings under extreme events such as earthquakes, impacts and blasts. Thus, the details of reinforcements in the joints should be well designed for enhancing the resistance of the joints under the events. Parameters numerically investigated in this study include diagonal, flexural, and shear reinforcing steel bars. The failure mechanism of the joints could be controlled by the level of tensile stress of reinforcing steel bars. Among various reinforcing details in the joints, diagonal reinforcement in the joints was found to be most effective for enhancing the resistance under blast loads. In addition, shear reinforcements also produced favourable effects on the blast resistance of beam-column joints.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".