Simulink-Based Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV)
Bibliographic record
Abstract
The Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV) is a Simulink-based approach to providing an engineering quality desktop simulation capability for finding trim solutions, extracting linear models for vehicle analysis and control law development, and generating open-loop and closed-loop time history responses for control system evaluation. It represents a useful level of maturity rather than a finished product. The layout is hierarchical and supports concurrent component development and validation, with support from the Concurrent Versions System (CVS) software management tool. Real Time Workshop (RTW) is used to generate pre-compiled code for substantial component modules, and templates permit switching seamlessly between original Simulink and code compiled for various platforms. Two previous limitations are addressed. Turn around time for incorporating tabular model components was improved through auto-generation of required Simulink diagrams based on data received in XML format. The layout was modified to exploit a Simulink "compile once, evaluate multiple times" capability for zero elapsed time for use in trimming and linearizing. Trim is achieved through a Graphical User Interface (GUI) with a narrow, script definable interface to the vehicle model which facilitates incorporating new models.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".