Aerodynamic optimization of Laval nozzle flow with shocks: Numerical investigation of active/passive shock control via expansion fans
Bibliographic record
Abstract
Abstract Instantaneous ignition in the supersonic part of a 3‐D Laval nozzle realized by a well‐defined sudden temperature rise across a normal shock is the focus of the present study. Unfortunately, the divergence of the supersonic nozzle part is necessarily smooth. Therefore, the turbulent boundary layer ahead of the shock is thick and causes substantial shock/boundary layer interactions. The non‐homogeneous temperature increase across the shock, caused by the boundary layer thickening ahead of the shock and the resulting pre‐compression prevents the quasi 1‐D evolution of the flow downstream. Additionally, due to multiple boundary layer interactions the single shock disintegrates into a so called pseudo‐shock system; i.e., into a sequence of periodic weak compression and expansion regions. To avoid this drawback and to establish homogeneous thermodynamic conditions throughout the entire cross section and flow domain downstream of the shock we apply active and passive control techniques in the area of shock boundary layer interaction. The central idea of the control technique described below is compensation of the thickening of the boundary layer by quantitative appropriate inverse effects, i.e. by superimposing negative and positive pressure gradients in the near wall region close to the shock position. In a first approach the additional expansion fan is created by active suction slots in flow direction and through all sidewalls of the 3‐D nozzle. The resulting shock remains straight with exception of the near wall region. Suction creates an effective concave wall curvature. In supersonic flow the resulting local expansion tends to compensate the pre‐compression. Because suction in high temperature environment is difficult to realize, we alter the wall curvature to create a negative bump with the same effect on the effective wall curvature. Under these conditions a normal shock in the channel core could be established without active or passive suction. The paper compares these active/passive control techniques with the unmodified setup. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".