Extending aircraft data for pollution models using public records
Extending Aircraft Coverage of the Poll Schumann Model Using Public Data
Machine Learning
Summary
Pollution models for aircraft need detailed information about the shape and engines of each plane, but this data is missing for many types. The authors show how to rebuild these missing details by using publicly available technical documents and engine databases. Their new estimates closely match published data, improving coverage from 68 to 90 aircraft types. Testing on real flight data shows the reconstructed data predicts fuel use nearly as well as the original. This means public sources can help fill gaps in pollution studies for many more aircraft.
What this means in practice
- •For aviation environmental analysts: Use publicly available documents to extend aircraft coverage for pollution dispersion modeling where data is incomplete.
- •For flight operations analysts: Improve fuel usage predictions for flight planning by incorporating reconstructed aircraft parameters from public technical data.
Authors
Gabriel Jarry, Ramon Dalmau, Philippe Very
Abstract
The Poll Schumann model requires airframe and engine parameters, but published tables cover only part of the fleet. Applications must obtain missing parameters, substitute another aircraft type or exclude unrepresented types. We reconstruct parameters using geometry from certification documents and manufacturer manuals, together with ICAO engine records. Published equations supply the physical parameters, regression estimates the propulsion efficiency scale. The inventory covers 90 type designators, including 22 absent from the direct pycontrails table and 18 without a listed substitute. Across 68 types, mean absolute percentage error (MAPE) against pycontrails was 7.38% for drag and 3.14% for design Mach. Across 66 types in 21 families, efficiency regression achieved 3.91% MAPE with the evaluated family excluded from input selection and fitting. On 100 recorded A320 flights, a type already represented in the published tables, cruise fuel flow MAPE for reconstructed and published parameter sets was 4.50% versus 4.68%, while mean absolute percentage error in integrated fuel over covered airborne intervals was 7.19% versus 6.82%. Public technical records can therefore extend Poll Schumann parameter coverage, with quantified agreement against published coefficients and comparable fuel prediction errors on the evaluated A320 flights.