Implicit Runge-Kutta Time Integrators for Fluid-Structure Interactions
Bibliographic record
Abstract
This paper presents the application of high-order time integrators in the context of monolithic approach simulation of Fluid-Structure Interaction by the Finite Element Method. The numercial method relies on an ALE formulation satisfying the Geometric Conservation Law designed in such a way that the high order accuracy of the Implicit Runge-Kutta time integrator observed on fixed meshes is preserved on deforming meshes. The same integrator is used for both the flow and structural components. We also use coincidents nodes on the fluid structure interface, so that the interface loads, velocities and displacements are evaluated at the same place and at the same times. The formulation is applied to the analysis of the flow induced vibration of a flexible strip mounted on the wake side of a square obstacle placed in a uniform flow. Results compare favorably with previous works. Near optimal time accuracy is observed for 3 and 5 order Implicite Runge-Kutta time integrators (IRK). That’s why, while higher order IRK require more memory than the classical schemes, they are also much faster for a same accuracy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".