Numerical Study of Turbulent Rotating Flow in a Tesla Disc Pump
Bibliographic record
Abstract
The advantages of Tesla’s bladeless turbine over the conventional bladed turbine — such as an easier manufacturing process; low cost; low noise; the ability to operate with different working fluids, including Newtonian and non-Newtonian fluids; and single phase or multi-phase systems [1] — keep the design development of this device a subject of ongoing research. The first design of the Tesla turbine was presented by N. Tesla in 1913 [2]. In the 60s and 70s, a number of research groups built the Tesla device to investigate its performance (power, torque, efficiency) [3]–[6]. At the present time, the efficient design of the Tesla device is still a focus of experimental and numerical research studies [7]–[13]. In this work, the computational fluid dynamics (CFD) simulations are performed to study three-dimensional turbulent compressible flow between the two corotating discs. The wide gap between the discs results in a Reynolds number of 1656, which is calculated based on the disc gap and the rotational speed of the discs. The CO2 gas is used as a working fluid. The simulations are performed using the commercial CFD software (STAR-CCM+, SIEMENS PLM). In this study, we determined the inlet and outlet boundary conditions together with the rotational speed of the discs that make the device work as a pump. The realizable k–ε turbulence model was used. The performance parameters of the pump were assessed by considering the dimensionless flow coefficient and efficiency.
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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 | 0.000 |
| 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)
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".