Numerical Simulation of the Interaction Between Fluid Flow and Elastic Flaps Oscillations
Bibliographic record
Abstract
Several numerical methods have been developed recently to solve problems including the interaction between viscous fluid flow and elastic solid structures. In this work, an in-house partitioned numerical solver is developed by using the open source C++ library OpenFOAM. Finite volume method is used to discretize the fluid flow problem on a moving mesh in an Arbitrary Lagrangian-Eulerian formulation and by using an adaptive time step. The structural elastic deformation is analyzed in a Lagrangian formulation using the St. Venant-Kirchhoff constitutive law. The solid structure is discretized by the finite volume method in an iterative segregated approach. The automatic mesh motion solver is based on Laplace smoothing equation with variable mesh diffusion. The strong coupling between the segregated solvers and the equilibrium on the fluid-structure interface are achieved by using an iterative implicit fixed-point algorithm with dynamic Aitken’s relaxation method. The solver is first validated on a benchmark largely used in the open literature. Then, a more complex case is studied including two elastic flaps immersed in a pulsatile fluid flow. The present solver predicts accurately the interaction between the complex flow structures generated by the flaps and the effect of the flaps oscillations on each other.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".