Numerical Analysis of the Coupling Between the Flow Kinematics and the Fiber Orientation in Eulerian Simulations of Dilute Short Fiber Suspensions Flows
Bibliographic record
Abstract
Abstract This paper focuses on an accurate evaluation of short fibers suspensions models coupling the flow kinematics with the fiber orientation evolution. In coupled models the flow kinematics is usually solved using the finite element method, where the fiber orientation is introduced in the constitutive equation through its value in some points (nodes or integration points). In this paper we will compare in a simple steady shear flow, the exact solutions of the extra‐stresses associated with the fibers' presence with the numerical simulations obtained using both the method of characteristics and the discontinuous Galerkin's method to solve the equation governing the generalized gradient evolution, in order to avoid the introduction of any closure relation. The error introduced if a quadratic closure relation is considered in the constitutive equation will be also quantified.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".