Optimized Rigid Side Underride Protection Device Designs for Tractor-Trailers and Straight Trucks
Bibliographic record
Abstract
This work describes the design and testing of side underride protection devices (SUPD) for tractor-trailers and straight trucks. Its goal is to reduce the incompatibility between small passenger cars and these large vehicles during side collisions. The purpose of these crash attenuating guards is to minimize occupant injury and passenger compartment intrusion. The methods presented utilize a regulation previously created and published for testing the effectiveness of these devices based on the principles of a force application device already implemented in the Canadian rear underride guard regulation. Topology and multi-objective optimization design processes are outlined using a proposed design road map to create the most feasible SUPD. The test vehicle in question is a 2010 Toyota Yaris which represents the 1100C class of vehicle from the Manual for Assessing Safety Hardware (MASH). Since the tractor-trailers and straight trucks utilize different structural components, separate concepts must be generated to accommodate each individual application. The LS-DYNA software package is employed for the creation of the devices, the simulations and the optimization. The guards are tested and their performance is evaluated in order to examine their benefits during collisions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".