Mixed convection in Bingham fluids: A comprehensive analysis of yielded and unyielded regions and their heat transfer implication using OpenFOAM
Bibliographic record
Abstract
Three-dimensional (3D) simulations of the laminar, incompressible, mixed convective flow of a Bingham viscoplastic fluid between two concentric cylinders of finite length are discussed here. Thermal exchange of a viscoplastic fluid is widely required; therefore, we aim to understand the characteristics of fluid flow and heat transfer in nonlinear fluids typically encountered in applications such as drilling. The simulations employ the regularized Papanastasiou constitutive model within the OpenFOAM framework, and results are validated against benchmark numerical and experimental data for Newtonian and Bingham plastic flows. The rheological behavior of four materials-heavy crude oil, Adriatic sea sediments, self-compacting cement and crushed glass is investigated to highlight the influence of cylinder rotation on the flow field. The thermophysical properties of these materials are considered constant, except density which obeys the Boussineq approximation. The flow characteristics, for instance, the streamlines pattern, the development of rigid/unyielded zones, viscosity distributions and strain-rate distributions, are analyzed. Heat transfer, which is quantified by the Nusselt number, showed a symmetric distribution with the highest values for heavy crude oil. The yielded region percentage (YRP) increases from 75% to 100% as the material yield stress decreases, with the unyielded zone expanding significantly at higher Bingham numbers, up to 50% for certain materials. This growth in the unyielded region impacts operational factors, such as pumping cost in drilling applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".