Effect of crushable blockouts on a full-scale guardrail system
Bibliographic record
Abstract
Since the performance of the guardrail system depends in part on the compatibility of vehicle-to-roadside hardware, it is important to improve the interaction of the vehicle with the guardrail system by adding more compliance to the guardrail system. In this paper, a finite-element baseline model of a guardrail system consisting of a light truck (2000 kg) travelling at 100 km/h and striking a guardrail was developed in accordance with the NCHRP Report 350 guidelines for Test Level 3 safety performance. The model was validated through comparison to a full-scale test conducted by the Texas Transportation Institute. In order for the guardrail system to absorb more energy and offer better stability to the vehicle, a rigid wooden blockout was replaced by a new crushable blockout design that was evaluated at the component level. The new blockout was formed by three crash cans and triggered at the corner, then was implemented in the full-scale model. The results of the analysis indicate that the both models satisfy the requirements of NCHRP Report 350 for the Test 3-11 conditions and show that the crushable blockout offers better vehicle stability in terms of roll angle and vehicle deceleration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".