Investigation of a Multiflow Ejector Equipped with Variable-Length Links for Thrust Vector Control Using Euler’s Methodology
Bibliographic record
Abstract
The coordinated operation of multiple jet devices enhances the efficiency of technological processes and thrust vector control systems, enabling the resolution of various practical challenges. Traditional jet control systems regulate the thrust vector in the direction from +20° to −20° in a 3D space. For the first time, this study considers, from a general perspective, the conditions under which the thrust vector angle can vary from +180° to −180° in any direction within a complete geometric sphere, including thrust reversal. Conceptual design using computational fluid dynamics (CFD) techniques considers kinematic schemes with variable lengths and flexible links. This study demonstrates the technical feasibility of controlled energy distribution through multidirectional ejector channels, including the maintenance of constant pressure at the nozzle apparatus inlet. Potential modernization strategies for the Laval nozzle incorporating a rotary diffuser were examined. The research outcomes are patented and aimed at developing a digital twin of the jet system for training artificial intelligence based on the philosophy of science and technology and Euler’s methodology within interdisciplinary works. The findings are primarily applicable to research and development efforts focused on creating energy-efficient oil and gas production systems. Furthermore, the research results can be applied to the development of advanced maneuverable unmanned vehicles and robotics for various purposes.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".