Modelling of Hydrodynamic Forces on a Whirling Mixing Vessel Stirrer Including Fluid-Structure Interaction
Bibliographic record
Abstract
In this paper, a modeling approach for strongly coupled Fluid-Structure Interaction (FSI) simulations of a mixing vessel stirrer is presented and discussed. A finite-volume Computational Fluid Dynamics (CFD) model is used to calculate the mixer flow field while the structural dynamics of the stirrer is based on a 2-DOF damped spring-mass oscillator system. The time integration of the stirrer response is carried out using the Newmark method, and is applied in conjunction with the implicit time integration of the fluid governing equations. The solution methodology employs a transient rotorstator interface to handle frame change between the rotor system and the baffles. Furthermore, mesh adaption around the rotor system is applied using an Arbitrary Lagrangian Eulerian (ALE) treatment of the fluid governing equations. The fluid forces acting on the impeller are analyzed and a method is proposed for extracting the added mass, damping, and stiffness coefficients, which are of significance in rotordynamic analysis. The computational results for the average stirrer deflections are in close agreement with experimental data, and the trends in the extracted rotordynamic coefficients align with other previously reported data for turbomachinery.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 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 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".