Project Number: 054
Category: Tools
Project 54 builds on the prior research by the Georgia Institute of Technology (GT) on project 45 and project 36. Project 45’s focus was improving the modeling assumptions within the FAA’s AEDT Aircraft Performance Module (APM) as compared to real world flight data, whereas project 36’s focus was conducting verification and validation of AEDT’s future service pack releases of new features. Project 54 continues these two research thrusts.
First, accurate modeling of aircraft performance is a key factor in estimating aircraft noise, combustion products, and fuel burn. Within the AEDT, many assumptions are made for aircraft performance modeling with respect to aircraft weight and departure procedure, coupled with aircraft departure typically being modeled by assuming that full rated takeoff power/thrust is used. As operations around airports continue to evolve, there is a need to examine those assumptions and to improve the modeling accuracy with flight data. In recent years, flight data are increasingly being used to enhance models and bring model estimation even closer to reality. Research is needed to build on prior work with a view to develop a robust set of recommendations for improved estimation processes for takeoff weight, reduced thrust takeoffs, and departure profiles within AEDT.
Second, the verification and validation applied in this project comprehensively assesses the accuracy, functionality, and capabilities of AEDT during the development process. The major purposes of this effort are as follows:
- Contribute to the external understanding of AEDT
- Demonstrate and evaluate AEDT’s capability and fidelity (ability to represent reality)
- Help AEDT users to understand the sensitivities of output responses to variations in input parameters/assumptions
- Identify gaps in functionality
- Identify high-priority areas for further research and development
Annual Reports
Participants
Lead Investigators
Program Managers
Publications
- Takeoff Ground Roll Analysis of Real-World Operations for Improved Noise Modeling
- A Reduced Order Modeling Methodology for the Parametric Estimation and Optimization of Aviation Noise
- Data-Driven Analysis of Departure Procedures for Aviation Noise Mitigation
- Reduced Order Modeling Methods for Aviation Noise Estimation
- Data-driven Approach to Environmental Impact Assessment of Real-World Operations
- Uncertainty Quantification Analysis of the Aviation Environmental Design Tool in Emission Inventory and Air Quality Modeling
- Parametric Uncertainty Quantification of Aviation Environmental Design Tool