Exploring Analytical Methods for Expanding the AEDT Aircraft Fleet Database for Environmental Modeling

Abstract

Modeling the environmental effects of aviation accurately is crucial to their mitigation to ensure sustainable aviation growth. The Aviation Environmental Design Tool (AEDT) offers the capability to model and compute both an aircraft's operations as well as the associated environmental impact in terms of emissions and noise. AEDT relies on the aircraft noise and performance (ANP) data provided by aircraft manufacturers to support the calculation of aircraft trajectories and noise using aircraft performance information and noise-power-distance (NPD) relationships for specific aircraft/engine combinations. In the ANP/BADA (Base of Aircraft Data) workflow, the ANP performance data is also used in the calculation of emissions inventories and air quality dispersion. However, not all aircraft in the fleet are represented in the ANP database. When ANP data is not available for a specific target engine/airframe combination, AEDT uses a substitute aircraft from the ANP database to model the target aircraft by closely matching certification noise characteristics and other performance parameters. A problematic issue, however, is that the best substitute based on noise criteria does not always match the best substitute for emissions criteria. In addition, substitute aircraft do not capture the environmental benefits of newer aircraft with noise and emissions reduction technologies, resulting in overly conservative noise and emissions estimates. The goal of this research is to improve the accuracy of AEDT noise and emissions modeling of aircraft not currently in the ANP database. In the present work, the authors identify and review the aircraft not currently modeled in AEDT and collect information and necessary data to better understand their characteristics. Machine learning methods in the form of unsupervised clustering are utilized to group different aircraft types in terms of their size, age, technologies, and other engine/airframe parameters. The intent is to explore analytical methods to expand the AEDT fleet database to include noise, performance, and emissions data for aircraft not currently in the ANP database.