Accepted manuscript
Noise Model Validation using Real World Operations Data
AIAA AVIATION 2021 FORUM
AIAA Aviation Forum
Handle:
https://hdl.handle.net/2376/120335
Appears in Aviation Sustainability Center (ASCENT)
Abstract
View Video Presentation: https://doi.org/10.2514/6.2021-2136.vid
The mitigation of aviation environmental effects is one of the key enablers to sustainable aviation growth. In order to perform mitigation efforts, however, it is required that the effects themselves be modeled with a high level of accuracy. The Aviation Environmental Design Tool (AEDT) offers the capability to model aircraft performance, fuel burn, emissions, and noise. Efforts are ongoing for improving the fidelity of modeling accuracy of AEDT by improving the assumptions used within AEDT to model various real-world effects. In this paper, the overall sensitivity of noise metric predictions to varying assumptions within AEDT is explored and quantified. This is achieved with the utilization of multiple types of real-world data including detailed flight performance characteristics from airline flight data records, noise monitoring data obtained from stations around one specific airport, and historical weather data. The paper provides a quantification of the overall accuracy of AEDT at its highest level of fidelity and also the sensitivity of noise predictions to various assumptions. The outcomes are expected to provide best practice recommendations and help users prioritize and more accurately quantify community noise exposure using AEDT.
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Details
- Title
- Noise Model Validation using Real World Operations Data
- Creators
- Ana B. Gabrielian - Georgia Institute of TechnologyTejas G. Puranik - Georgia Institute of TechnologyMayank V. Bendarkar - Georgia Institute of TechnologyMichelle Kirby - Georgia Institute of TechnologyDimitri Mavris - Georgia Institute of TechnologyDylan Monteiro
- Publication Details
- AIAA AVIATION 2021 FORUM
- Conference
- AIAA Aviation Forum
- Academic Unit
- Aviation Sustainability Center (ASCENT); Noise
- Grants
- 13-C-AJFE-GT-061, Federal Aviation Administration (United States, Washington) - FAA
- Identifiers
- 99900620470201842
- Language
- English
- Resource Type
- Accepted manuscript