Fractal dimensions of cohesive sediment during settling in steady state flow with different initial sediment concentrations
Bibliographic record
Abstract
Morphology of particle populations of cohesive sediment were examined during settling experiments in an annular flume with different initial sediment concentrations (200 and 350 mg/L) at constant bed shear stress (0.121 N/m2) using fractal dimensions. The area, longest axis, and perimeter of suspended solids were measured with light microscopy and an image-analysis system to determine three fractal dimensions (D, D1, D2). The ratio between the initial and steady state (time T = 300 min) sediment concentration was 0.54 for both experimental runs and is a function of bed shear stress, not the initial sediment concentration. The fractal dimension D changed from 1.32 at the start of the experiment to 1.36 at steady state, which represents an increase in shape irregularity of larger particles over time compared with smaller particles. At steady state, D1 and D2 were 1.19 and 1.66, respectively. Small increases in D1 and D2 over time indicated a change in morphology towards longer and more elongated particles. The D2 measurements in the present study indicate that differential sedimentation is the predominant flocculation mechanism of cohesive sediments in the flume settling experiments. Fractal dimensions of suspended solids were not significantly different at steady state as a function of initial sediment concentration.Key words: particle morphology, fractal dimensions, cohesive sediment, flocculation, deposition, annular flume.
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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 | 0.001 |
| 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".