Cooling Inlet Aerodynamic Performance and System Resistance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<div class="htmlview paragraph">This report is a contribution to the understanding of inlet aerodynamics and cooling system resistance. A characterization of the performance capability of a vehicle front-end and underhood, called the ram curve, is introduced. It represents the pressure recovery/loss of the front-end subsystem - the inlet openings, underhood, and underbody. The mathematical representation, derived from several experimental investigations on vehicles and components, has four basic terms:</div> <div class="htmlview paragraph"> <ul class="list disc"> <li class="list-item"><div class="htmlview paragraph">Inlet ram pressure recovery; free-stream energy recovered when the vehicle is moving</div></li> <li class="list-item"><div class="htmlview paragraph">Basic inlet loss; inlet restriction when the vehicle is stationary</div></li> <li class="list-item"><div class="htmlview paragraph">Pressure loss of the engine bay</div></li> <li class="list-item"><div class="htmlview paragraph">Engine bay-exit pressure</div></li> </ul> </div> <div class="htmlview paragraph">Not surprisingly, the amount of frontal projection of radiator area through the grille, bumper and front-end structure (called projected inlet area), and flow uniformity play a major role in estimating inlet aerodynamic performance. One experimental investigation demonstrated that the ram curve is independent (essentially) of the fan/shroud system installed in the vehicle. Another experiment showed that the engine-bay pressure loss (which includes the interference of the underhood package on fan performance) might be small compared to the other resistances. The universal characteristic map of fan and system performance can be used to track airflow changes during early vehicle design tradeoff studies.</div>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it