Insights for Modelling Turbulence in a Backward-Facing Step Flow in a Narrow Channel
Notice bibliographique
Résumé
Turbulent backward-facing step (BFS) flows in narrow channels apply to scenarios where the aspect ratio (channel width to depth ratio of the expanded channel) is less than 10.While such flows may be prevalent in practical cases such as compact cooling devices and turbine blade cooling channels with ribs, detailed experimental flow measurements are relatively expensive and rare [1,2].To facilitate parametric design at an amenable cost, it is imperative to employ appropriate tools that model the turbulent flow field.This is particularly important due to the complicated flow phenomena of the recirculation region, where flow separation is rampant and deterministic of the associated pressure differential cost of the flow system.However, current turbulent modelling tools are not sufficiently tuned for such a complex flow.This work is aimed at addressing this need.To that end, multicomponent velocity measurements of the flow field in the recirculation region of a narrow-channelled BFS are obtained and assessed to provide insights into how turbulence may be modelled.The experimental data is obtained using two-dimensional two-component high resolution particle image velocimetry.The measurements were conducted in an optically accessible channel, designed to simulate a closed BFS of step height h, aspect ratio 7.7 and expansion ratio 1.25.With the Reynolds number of the in-coming flow based on the maximum streamwise velocity and h at ~6200, turbulent flow in the channel was assured.Measurements across multiple spanwise planes of the recirculation region were subsequently obtained and evaluated.This was done to specifically study low and high-order moment turbulence statistics of the flow field relevant for turbulent modelling.The results show intricate and distinctive trends of the turbulent eddy viscosity, Prandtl mixing length, and coefficients of the Kolmogorov-Prandtl (K-P) expression for single and two-equation models.In the separated region, the eddy viscosity distributions in the wall-normal direction vary most with distance from the step up to 0.3h.The profiles are different from other flows.Notably, they deviate remarkably from that observed in a turbulent boundary layer (TBL) flow, with maximum values far exceeding it as well as that of a wide-channelled BFS flow [3].The mixing length profiles over the bottom wall are, on the other hand, similarly distributed in the streamwise direction.However, when assessed as a length scale in the K-P expression, the mixing length yields a coefficient that is not unity.The evaluation of planar estimates of the production and dissipation of energy yield coefficients of the K-P expression that are also non-uniform.They also suggest that underlying basis of a Smagorinsky-Lilly large eddy simulation model is inapplicable in the separated region of a narrow-channelled BFS flow.These results reveal that for narrow-channelled BFS flows, a single-equation turbulence model may be appropriately used to provide acceptable simulations.However, much more complex accounts of Reynolds stresses should be considered for accurate predictions of eddy viscosity-based turbulence models.
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».