Bibliographic record
Abstract
Cette these porte sur l'animation d'un fluide a base de particules en utilisant un maillage dans un cadre d'infographie. De nouvelles facons d'animer un fluide dans son espace de simulation sont explorees. Cette animation se fait a travers la simulation, la visualisation d'un champ de vitesses et le rendu d'effets speciaux de fluide. Il s'agit d'une these par articles dans lequel trois articles ont ete realises. Les deux premiers ont dej a ete publies et le troisieme est en cours de publication. Le premier article porte sur une methode de simplification de la dynamique des fluides par des precalculs du champ de vitesses sur un maillage cubique du domaine de simulation. Plusieurs methodes de visualisation sont proposees, y compris avec des particules. Dans le second article, nous visualisons un champ de vitesses sur le maillage triangulaire d'une surface arbitraire. Des particules sont introduites dans le champ de vitesses afin de le visualiser, mais aussi afin de creer des rendus de liquide ou de fumee sur la surface. Le dernier article porte sur la simulation de gouttes d'eau sur une surface en temps reel. La simulation de la condensation de l'eau sur une surface de meme que la sueur ont pu etre traites comme des applications.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".