Analysis of surface erosion of cohesionless soils using a three-dimensional coupled computational fluid dynamics – discrete element method (CFD–DEM) model
Bibliographic record
Abstract
A fluid–solid interaction model has been implemented by coupling two numerical methods — computational fluid dynamics (CFD) and discrete element method (DEM) — that capture the mesoscale behaviors of the fluid–solid system. The model is first validated by comparing the results of simulations with two types of experiments: free settling of a single sphere in water and formation of angle of repose of particles under water, which show its capability in modeling the behaviors of both particle phase and fluid phase. The verified model is then used to study factors affecting the soil erodibility, where case studies are designed for soil particles deposited inside a pipe and subsequently subjected to water flow–induced surface erosion. Influencing factors for soil erodibility, including particle diameter and interparticle bond, are analyzed. For cohesionless soils without bond strength, the critical shear stress is found to be linearly related to particle size; while for soils with bond strength, simulation results show that interparticle bonding largely decelerates the erosion process and causes a much lower erosion rate. To further the understanding of soil surface erosion under turbulent flow, the “k–ε” turbulence model has been successfully implemented for the fluid phase. Comparison between the laminar model and the turbulence model shows turbulence significantly accelerates the erosion process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".