Computational Study on the Influence of jet on Reduction of Drag Over Cone Flare Bodies in Hypersonic Turbulent Flow
Bibliographic record
Abstract
Recently, Nhypersonic research activities around the universe have been in major focus because of the milestone developments in hypersonic reentry vehicles, orbital transfer vehicles, reusable launch vehicles and space recovery experimental modules. One of the major problems in hypersonic flight is drag and with the tremendous progress in computational powers it can be analysed. In this work, the effects of counter flow jet on reduction of drag around two blunt cone flare bodies in the hypersonic turbulent flow are investigated through a numerical study. Flow field around the blunt bodies is calculated numerically for the free stream Mach number of 6.5. Numerical solutions of Navier-Stokes equation and energy equation governing the turbulent flow of compressible fluid are obtained by adopting Finite Volume Method (FVM) through an industry standard CFD code, FLUENT 6.3.26 package. Shear Stress Transport (SST) model was used in the computation of pressure drag, skin friction drag and total drag for both the absence of jet and the presence of jet cases for both the configuration. Contours of Mach number are presented to describe the flow patterns. It is clear that the reduction of drag was greatly influenced by the jet conditions and body shapes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".