Effects of Exhaust Positioning and Vehicle Operating Conditions on Rear Fascia Temperature
Bibliographic record
Abstract
<div>The ability to efficiently and accurately predict the thermal environment of vehicles is becoming increasingly important. Currently, in the design stage of an automobile, full-vehicle computational fluid dynamics (CFD) simulations are typically used to predict rear fascia temperatures. The plastic fascia can be damaged if excessively high temperatures are encountered, so this prediction is important. As the simulations are expensive, only what is intended to be a worst-case scenario is assessed. This does not allow for the best position of the exhaust to be determined, and it is also possible that the actual worst case is missed during the early design phase, requiring costly late-stage design changes. In this article, the dependence of the maximum fascia temperature on geometric (positioning of the exhaust) and nongeometric (vehicle operating condition) parameters is systematically investigated using CFD. A compact sport utility vehicle (C-SUV) is used for the investigation. The key outcomes are (1) The location and temperature of the hot spot on the fascia depends on whether there is significant impingement of the exhaust jet(s) or not; (2) the highest fascia temperature will occur at zero or near-zero vehicle speeds with a high engine load; and (3) for each of the four parameters which define the exhaust geometry, the best value is found for keeping the fascia temperature as low as possible. A single simulation of the worst load case can be used to find the absolute maximum temperature of the fascia, and the impact of the exhaust position can be used to guide the design changes if the initial design yields an unacceptably high fascia temperature.</div>
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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".