Modèles d'écoulement à surface libre pour la simulation à long terme de la migration des systèmes méandriformes
Bibliographic record
Abstract
Over a long time, Meandering systems build sedimentary architectures composed of porous bodies scattered inside a volume of low-permeability sediments. These bodies may contain natural resources. In order to optimize their mining, it is essential to estimate the distribution and connectivity of such bodies. To this end, Mines ParisTech develops Flumy, a process-based model simulating the formation of these architectures. This thesis aims to improve the simulation of the migration in Flumy by taking into consideration the influence of the local slope.For this purpose, three distinct models were considered in conjunction, and compared. The first one (constant slope model), which constitutes the basis of the current Flumy version, was originally developed by [Ikeda 1981]. The second model (variable slope model), developed by [Lopez 2003], assigns to the free surface the slope of the surrounding topography. Finally, the last model (Saint-Venant model) has been derived from the variable slope model. Initially calculated under a known free surface, the mean flow in each cross-section is now obtained by solving the Saint-Venant equations over a known river bed. Each of those three models has been applied to the simulation of free meanders. Moreover, the constant-slope and variable slope models have been used to reproduce the confined meanders of two Canadian streams.The results point to a more realistic meanders development using the variable slope model than with the constant slope model. This improvement can particularly be observed in individual meanders, whose rate of extension decreases with the age. It is also noticeable in the overall river behavior, which self-confines in a meander belt. The specific morphology of the confined meanders is also better reproduced using the variable slope model than with the constant slope model. Lastly, though a lesser extent, the Saint-Venant model shows the same advantages than the variable slope model. In addition, it allows the construction of a physically meaningful free surface over a wide range of beds and, in doing so, resolves a limit of the variable slope model.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".