Development of Parametric Power Generation and Distribution Subsystem Models at the Conceptual Aircraft Design Stage
Bibliographic record
Abstract
The ongoing efforts to reduce aviation related greenhouse gas emissions and fuel burn have led to advancements in power generation and distribution (PG&D) subsystem technology. Due to the absence of historical data, PG&D subsystem models must be created from first-order analysis without compromising crucial information on their characteristics. This paper demonstrates the development of parametric, physics-based subsystem models such as battery, electric motor, power distribution and management system, and propeller speed reduction unit for rapid and low-cost sizing, simulation and analysis at early design stages. A special focus was put on rechargeable battery technology and implementing a dynamic (rather than steady-state) discharge behavior into the propulsion architecture. A methodology to integrate the developed subsystem models was presented. A sample application was also provided to demonstrate the combined capabilities of the models. To this end, the models were applied within a sample parallel hybrid electric architecture using Dornier 328 as a test bed. The subsystem behaviors under varying power requirements were then analyzed. Finally, the importance of having more dimensionality at the subsystem level at early design stages was highlighted by comparing the results of two different architectural choices.
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 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".