Protection from Ignition Sources Due to Lightning, EMI and Wire Harness Shorts for Aircraft Fuel Tank Gauging Systems
Bibliographic record
Abstract
The investigation that followed the TWA 800 tragedy has revealed the probability that the center wing fuel tank exploded and caused structural failure that led to the aircraft plunging into the ocean. Examination of wiring from that aircraft and other Boeing 747 aircraft of similar age has uncovered the existence of wiring insulation faults. These faults have been found inside the tanks between powered leads and ground surfaces, and outside the tanks between Fuel Quantity Indicating System wiring and other wiring. The Boeing series of aircraft have in the past been designed with the FQIS wiring routed together with other wiring such as power leads. Thus, wire harness insulation failures could result in the FQIS wiring being exposed to voltages that might provide an ignition source in the tank. EMI from neighboring wires and lightning may also be present. Fuel gauging systems have not in the past been designed for these contingencies. Smiths Industries has developed a Transient Suppression Unit that is installed in the FQIS wiring at the tank wall which filters out any dangerous electrical transients from entering the fuel tank, while allowing the Smiths digital fuel gauging system to function normally.
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".