Entropy-Adjoint p-Adaptive Discontinuous Galerkin Method for the Under-Resolved Simulation of Turbulent Flows
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Bibliographic record
Abstract
This paper presents an approach to mesh adaptation suitable for scale-resolving simulations. The methodology is based on the entropy-adjoint approach, which corresponds to a standard output-based adjoint method with the output functional targeting areas of spurious generation of entropy. The method shows several advantages over standard output-based error estimation: 1) it is computationally inexpensive; 2) it does not require the solution of a fine-space adjoint problem; and 3) it is nonlinearly stable with respect to the primal solution for chaotic dynamic systems. In addition, the work reports on the parallel efficiency of the solver, which has been optimized through a multiconstraint domain decomposition algorithm available within the Metis 5.0 library. The reliability, accuracy, and efficiency of the approach are assessed by computing three test cases: the two-dimensional, laminar, chaotic flow around a square at ; and the implicit large-eddy simulation of the flow past a circular cylinder at and past a square cylinder at . The results show a significant reduction in the number of degrees of freedom with respect to uniform order refinement with a good agreement with experimental data.
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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 | 0.000 |
| 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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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