Bibliographic record
Abstract
This paper deals with the development and the applications of a computational transient model of the VINCI cryogenic expander cycle upper stage rocket engine, tested in the frame of the FLPP Expander Demonstration Program managed by the European Space Agency (ESA). Snecma has been developing a transient system model of the VINCI engine since the beginning of the engine development, and the constant use of transient simulation was one of the major factors contributing to the success of the first two VINCI engines test campaigns. Simulation results have been found to be in good agreement with the measurements from the very first tests. The model accurately predicts the engine global behavior during start-up and shutdown, as well as the engine steady-state performance, and it also describes correctly the transient behavior of complex subsystems such as the combustion chamber or the turbopumps. This paper provides an overview of the physical content of the VINCI engine transient model. Simulation results from the model are compared with engine test data, and the model representativeness is discussed in detail. A focus is made on highly unsteady phenomena, such as valve maneuverings, and their effects on the whole engine behavior. I. Introduction HIS paper deals with the development and the applications of a computational transient model of the VINCI rocket engine. The VINCI is a cryogenic expander cycle engine, basis of a demonstration program preparing an application on the European launchers, in the frame of the European Space Agency (ESA) Future Launcher Preparatory Program (FLPP). The VINCI development in 200 5 and 2006 was conducted in the frame of the predevelopment of a cryogenic upper stage, under contract from the Centre National d’Etudes Spatiales (CNES), the French Space Agency, on behalf of ESA. The Space Engines Division of Snec ma in Vernon, France, acting as a prime contractor, is in charge in particular of the engine overall system design and integration. Snecma has been developing a transient system model of the VINCI engine since the beginning of the engine development, in order to predict its behavior during start-up and shutdown transients, as well as during potential failure scenarios. This model can also be used to identify possible undesirable unsteady effects that may occur during the engine transient operation phases, and to assess the consequences of any design changes. The constant use of tran sient system simulation has been one of the major success factors of the first two VINCI engines test campaigns that took place from May to July 2005 (M1 engine) and from November 2005 to February 2006 (M2 engine). During a test campaign, the model was used on a systematic basis in order to perform risk analysis for the subsequent tests, and to gain a physical knowledge of the engine behavior complementary to the one coming from raw measurements. Thanks to the intensive modeling work done at Snec ma, and to the experience gained from subsystem and component tests, simulation results were found to be in good agreement with measurements. A fairly good agreement was obtained from the very first tests, despite the fact that the VINCI engine is the first cryogenic expander cycle engine ever built and tested in Western Europe. The model accurately predicts the engine global behavior during start-up and shutdown, as well as the engine steady-state performance, and it also describes correctly the transient behavior of complex subsystems such as the combustion chamber or the turbopumps. This publication provides an overview of the physical content of the VINCI engine transient model, including the modeling process of the different subsystems. Simulation results from the model are compared with engine test data, and the model representativeness is discussed in detail. A focus is made on highly unsteady phenomena, such as valve maneuverings, and their effects on the whole engine behavior.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".