Implicit finite-volume scheme with anisotropic adaptive mesh re?nementfor predicting three-dimensional reactive laminar flows
Bibliographic record
Abstract
A novel anisotropic adaptive mesh refinement (AMR) algorithm is combined with a second-order accurate finite-volume spatial discretization scheme that incorporates low-Mach-number preconditioning for the prediction of three-dimensional (3D), axisymmetric laminar flames, both steady and unsteady, associated with premixed and non-premixed gaseous fuels, as described by the partial differential equations governing fully-compressible reactive flows of thermally perfect gaseous mixtures.The combined AMR and finitevolume approach permits the use of multi-block, body-fitted meshes consisting of hexahedral computational cells.Automatic, solutiondirected, anisotropic mesh adaptation as directed by physics-based refinement criteria is facilitated by using a binary-tree data structure, tracking the adaptive refinement history for each sub-domain as well as the block connectivity.The low-Mach-number local preconditioning is used to remove numerical stiffness and maintain solution accuracy at low Mach numbers.For unsteady flow prediction, a dualtime-stepping-like approach is used in conjunction with the low-Mach-number preconditioning and an implicit second-order backward discretization of physical time.The nonlinear algebraic equations arising from the spatial and temporal discretization procedures of the governing equations are solved by using an efficient parallel Newton-Krylov-Schwarz (NKS) algorithm in which a Jacobian-free inexact Newton method and preconditioned generalized minimal residual (GMRES) iterative linear-equation solution procedure are used.Block incomplete lower-upper (BILU) type local preconditioning is applied in conjunction with an additive Schwarz global preconditioner.The latter allows for a relatively straightforward and scalable parallel implementation of the algorithm on distributed-memory highperformance computing architectures.The proposed NKS, AMR, and finite-volume scheme is applied to the solution of both steady and unsteady, premixed and non-premixed, laminar methane-air flames in which the Cantera software package is used to represent both the detailed chemical kinetics and thermodynamic behaviour of the reactive gases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".