Design and Development of a Computational Fluid Dynamics Software in the Context of a Capstone Project
Bibliographic record
Abstract
Polytechnique Montréal's Bachelor of Aerospace Engineering program integrates the Conceive-Design-Implement-Operate (CDIO) methodology through four integrative projects, one for each year of study. Final year students are asked to complete a capstone project. One of those proposed, the design of a tridimensional Euler-based Computational Fluid Dynamics (CFD) workflow, is detailed from technical as well as educational perspectives. To achieve the designated task, eleven students worked over two academic semesters and were guided by a professor and a lecturer. The project was initially divided in two phases to facilitate the learning curve: 1) the realization of a two-dimensional solver and 2) the development of a tridimensional program. The final software includes a Graphical User Interface (GUI), a geometry generator and a mesh partitioning algorithm, a second order solver and a post-processing module. Simulations on supercomputers with distributed memory parallelization was made possible through the use of MPI. Additional work, after the academic term, included the redaction of this conference paper, the correction of minor issues and a scalability assessment. Academic achievements and software performances are found to be in agreement with the motivations of a capstone project.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".