Bibliographic record
Abstract
The development of a quasi two-dimensional computational model for simulating the transient variations of bed topography profiles in alluvial river channels is reported. The formulation of the model is based on combining the longitudinal flow momentum with the continuity principle of the sediment bed load. The Engelund-Hansen formula is employed in estimating the total sediment bed load along the reach of a river channel. The lateral bed load contribution from the total load is calculated in the same way as in calculating the lateral secondary currents from the main flow velocities. The numerical scheme and the computational procedure used in the study are described in detail. The simulated bed level profiles are verified through comparisons with experimental and field measurements taken from case studies in the literature for different flow conditions, channel characteristics, and sediment properties. The correlation between flow discharge, bed load, boundary friction, and channel slope is discussed. On the basis of the reasonably good comparisons with field data, it may be deduced that the model can be used for predicting the bottom topography variations in river channels.Key words: meandering rivers, bottom topography, sediment transport, bed load, boundary roughness, field measurements, experimental data, computational modelling, finite difference method.
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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 | 0.000 | 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 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".