CFD Aided Ship Design and Helicopter Operation
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
In support of Canadian industrial and defence ship design and offshore helicopter operations, a series of Ship–Helicopter Operational Limits Analysis and Simulation (SHOLAS) projects are being conducted at the National Research Council Canada (NRC) in collaboration with Defence Research and Development Canada (DRDC). This study presents a brief overview of a Canadian in-house ship airwake simulation capability combining in-house high-fidelity wind-tunnel tests, full-scale sea trials, high-order computational fluid dynamics (CFD) tools, and realistic engineering-oriented flight simulators. This paper reports challenges and lessons learned during the course of the study, discusses the current capabilities and limitations of the CFD tools and the infrastructure required, and evaluates the gaps and barriers in industry adoption by focusing on how they could be overcome based on our current practice. After validating the CFD results of an updated version of a simplified frigate shape (SFS2) and the real-world Canadian Patrol Frigate (CPF), which are in reasonable agreement with the available in-house wind-tunnel and sea-trial data, the developed approach was recently applied to the design of an undisclosed Canadian ship. Among other applications, CFD airwake results were used with confidence as input to produce representative airwake features in industrial high-fidelity piloted flight simulators.
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 | 0.001 | 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 it