Bibliographic record
Abstract
This thesis demonstrates a Life Cycle Analysis (LCA) framework tailored for sustainable aviation and engineering design.Sustainable aviation encompasses electrified technology, alternative fuels, and sustainable aviation fuel (SAF); however, this thesis focuses on electrified propulsion.This LCA framework is designed to compare two scenarios, and validated using two case studies that rely on well-defined datasets from the ground transportation industry.Two case studies are conducted: the first evaluates the environmental benefits of retrofitting a Piper Archer LX airframe with a fully electric propulsion system, compared to continued operation with an internal combustion engine; the second analyzes the life cycle impacts of the same propulsion system during overhaul, comparing an electrified solution to a conventional combustion engine.The use of NMC811 Li-ion battery chemistry is identified as the most environmentally beneficial option using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI) impact assessment method.However, the Intergovernmental Panel on Climate Change (IPCC) impact assessment method finds that the electrified retrofits present a higher risk of global warming potential and temperature change potential than their respective base case.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".