Uncertainty based aircraft derivative design for requirement changes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Aircraft manufacturers often consider producing multiple derivatives of aircraft to satisfy various market demands and technical changes while keeping development costs and time to a minimum. Many approaches have been proposed for carrying out derivative design. However, these approaches consider both the baseline design and derivatives together at the conceptual design stage using the entire set of design variables with an assumed set of expected requirements. These frozen requirements on derivative design cannot consider new demands from market changes. In this paper, a method is proposed that uses design optimisation for conceptual design of derivatives for existing aircraft that consider requirement changes. Furthermore, the Possibility-Based Design Optimisation (PBDO) method was implemented to consider uncertainty in the aircraft operation phase. The altitude range of aircraft operation was defined as an uncertain parameter to prevent violation of constraints in the entire operating envelope of the aircraft. The PBDO method yields a more conservative design than those obtained with deterministic design optimisation. In this paper, the proposed derivative design process was applied to the Expedition 350, a small piston engine powered aircraft produced by Found Aircraft, Canada. A derivative that changes the normally aspirated engine to a turbocharged engine for high-altitude operation was considered. An optimum configuration with the new engine was obtained while enhancing performance and stability characteristics. The proposed derivative design process can be implemented on the derivative design of other aircraft.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it