Grain shape effects in bed load sediment transport
Bibliographic record
Abstract
Predictions of bed load sediment flux are notoriously imprecise despite widespread occurrence and importance in contexts ranging from river restoration to planetary exploration. Natural variations in grain size, shape and density are possible sources of inaccuracy in sediment transport, as well as mixtures of different grain sizesand time-dependent bed structure. While many of these effects have been studied in depth, the effects of grain shape have rarely been quantified, even though shape has long been hypothesized to influence sediment transport.During bed load transport, the granular bed is sheared by the flow passing over it. Aspherical grains and rough surfaces generally increase the resistance to such shearing, enhancing frictional resistance, and reducing the efficiency of bed load transport. However, aspherical grains also experience higher fluid drag force than spherical grains of the same volume, enhancing transport efficiency under the same flow conditions. These two competing effects generally get stronger as grain shape deviates from spherical, making it challenging to predict the net effect of grain shape on sediment transport. We disentangle these competing effects by formulating a theory that accounts for the influence of grain shape on both fluid-grain and grain-grain interactions. It predicts that the onset and efficiency of transport depend on the average coefficients of drag and bulk friction of the transported grains. Because we use the average statistics of drag and friction to characterize the effect of grain shape, our approach is also applicable to materials like natural gravel that have many different shapes in the same sample.Using a series of flume experiments with different granular materials of distinct shapes, we show that grain shape can modify bed load transport rates by an amount comparable to the scatter in many sediment transport data sets. Our data also demonstrates that, although bed load transport of aspherical grains is generally inhibited by higher bulk friction and enhanced by higher fluid drag, these two effects do not simply cancel each other. This means that the effect of grain shape on sediment transport can be difficult to intuit from the appearance of grains, with the possibility for grain shape changes to lead to either a reduction or an enhancement of sediment transport efficiency.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".