The UOIT Automotive Centre of Excellence - Climatic Test Facility
Bibliographic record
Abstract
The University of Ontario Institute of Technology (UOIT) is the home of the General Motors of Canada Automotive Centre of Excellence (ACE), a university owned and operated facility that is funded by the university and the provincial and federal governments of Canada. As such, ACE is available to all automotive manufacturers (OEM's), Tier 1 suppliers, university researchers, or any other industry requiring the need for independent research and development test capability. A large climatic wind tunnel is the signature feature of ACE, which also includes climatic chambers (one of which is a high feature chamber), a climatic 4-post shaker test cell and a hemi-anechoic chamber equipped with a multi-axis shaker table. Some key design features of the climatic wind tunnel include a variable nozzle geometry (from 7 m₂ to 13 m₂), a chassis dynamometer inserted in an 11.7 meter turntable, a boundary layer control system and circuit acoustic treatment for low background noise levels. The climatic wind tunnel performance envelope covers wind speeds up to 250 km/h, temperature range from -40°C to +60°C, relative humidity from 5% to 95%, and the test section is equipped for solar, rain and snow simulation. This paper provides an introduction to the ACE facility and presents the results of the aerodynamic commissioning program. The climatic performance and flow quality test results of the wind tunnel are given, as well as the climatic performance for each chamber.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.145 | 0.092 |
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".