Crashworthiness of Traffic Light Steel Poles in Vehicle Collisions
Bibliographic record
Abstract
Vehicle crashworthiness focuses on the capability of a vehicle to protect its occupants in a collision. The Canadian Highway Bridge Design Code [2] does not provide design criteria for vehicle occupant safety except by field testing. The test-guided product development process is very costly and time-consuming. As an alternative, computer simulation tools are increasingly being used. The aim of this research is to contribute to the efficient design of traffic light poles by developing an experimentally calibrated, computer-based, finite-element model using LSDYNA [54], capable of predicting accurately their response when subjected to vehicle impact. The case of steel pole embedded directly in soil was proved to be strong enough to offer protection under service loading and vehicle impact. Side impact crashed proved to be more severe for the vehicle occupant as a result of the weak structural performance of the side doors of the vehicle. Based on this an innovative pole supported on a hard rubber base is introduced to improve crashworthiness.
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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) | 0.000 | 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) | 0.000 | 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".