CFD modeling of movement of geobag for riverbank erosion protectionstructures
Bibliographic record
Abstract
Many rivers suffer from riverbank erosion, which can lead to loss of soil properties, lands and infrastructure damage. Riverbank erosion can be avoided with erosion control structures. Since the 1970s, geobags (geotextile bags filled with sand) have been used as a fundamental element of revetment structures. The design of revetment structures needs a deep understanding of the hydraulic stability of geobags. Most research is focused on coastal applications characterized by wave loading. In contrast, current loading determines the geobag stability along riverbanks, which indicates a gap in knowledge of the stability of geobag in river studies, especially focusing on two failure modes, namely sliding and overturning. In addition, there are no CFD studies that considered the movement of the geobags. The aim of this study is to enhance the fundamental understanding of geobag stability using CFD modeling for river applications, which is accomplished by examining the movement of one submerged geobag. Studying the movement of geobag requires consideration of the shape of the bag since it affects its stability. Therefore, images of the submerged geobags are used for image processing. The edges and borders of one submerged geobag are determined, and the geometry is created by Ansys Space Claim. One sample bag is examined using the overset grid method and solved in Ansys Fluent. Six degrees of freedom (6DOF) solver is used to simulate the movement of geobag at the bottom of the channel. The 6DOF solver works with the forces and moments on the object to determine the translational and angular motion of the gravitational center of the object. Drag, inertia, buoyancy, lift and friction forces are the hydrodynamic forces acting on the submerged geobag, which affect the movement of the geobag. The numerical simulation result was validated with experimental observations. The experiments were conducted using a single submerged geobag at the bottom of the channel, with the flow being increased incrementally until the incipient motion was observed. The CFD results indicate that the overset mesh was able to model the movement of geobag at the bottom of the channel. Additionally, the forces and moments affecting the geobag are determined during its movement.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".