Comparative Life Cycle Assessment (LCA) in the Aerospace Industry Regarding Aviation Seat Frame Options
Bibliographic record
Abstract
The aerospace industry is actively seeking sustainable solutions within the aviation sector to mitigate greenhouse gas (GHG) emissions driven by increasing population demands. This study presents the first environmental life cycle assessment (LCA) of economy-class seating frames, comparing conventional alloy steel with lightweight alternative materials, including magnesium alloy, aluminum alloy, and titanium. Seat frames account for an aircraft’s total weight, making them a critical component for innovation toward more sustainable solutions. Using SolidWorks V3.1, economy-class seat frames were designed and evaluated through a cradle-to-grave assessment of a functional unit (FU) representing the interior of a single aircraft. The analysis was conducted using SimaPro V8.4.0 with the Ecoinvent V3.10 database. The total GHG emissions associated with seat frames composed of alloy steel, titanium, aluminum alloy, and magnesium alloy were 208 kt CO2 equivalent (eq.), 120 kt CO2 eq, 71.1 kt CO2 eq, and 44.9 kt CO2 eq per FU, respectively. This study identifies alloy steel and titanium to be the most sustainable seat frame materials relative to other considered materials for commercial aircrafts.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".