Simplified Fluid-Structure Model for Duckbill Valve Flow
Bibliographic record
Abstract
Duckbill valves (DBVs), made of a fabric reinforced layered rubber composite, are extensively used for nonreturn axial water flows with low back pressures. Fluid–structure interaction (FSI) is directly involved in the opening process of the DBV, with the opening depending on the pressure differential across the valve. In this paper, a simplified FSI model of the DBV is presented using a finite element method (FEM). The valve is modeled as a laminated thick shell structure with some simplifications to the boundary conditions. The pressure load acting on the shell surface of the DBV is a function of the variable valve cross-sectional area and determined, for preliminary analysis purposes, by using a simple potential flow model for the fluid mechanics. The hyperelasticity of the rubber and orthotropy of the fiber reinforcement, as well as large deflections of the DBV, are considered in the simulation. The valve is modeled as being closed when the upstream pressure is applied, and the transient opening process is tracked until a steady state opening is achieved. Several static cases of viscous flow passing through the deformed valve structure have also been carried out to compare the pressure and velocity fields of fluid flow with the corresponding pressure and velocity distribution predicted by the simplified model and to compare the hydraulic performance of the DBV predicted by both models.
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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 | 0.001 | 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) | 0.003 | 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".