Reduced Order Modeling Methods for Aviation Noise Estimation

Ameya Behere; Dushhyanth Rajaram; Tejas G. Puranik; Michelle Kirby; Dimitri N. Mavris

doi:10.3390/su13031120

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Reduced Order Modeling Methods for Aviation Noise Estimation

Journal article

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Peer reviewed

Reduced Order Modeling Methods for Aviation Noise Estimation

Ameya Behere, Dushhyanth Rajaram, Tejas G. Puranik, Michelle Kirby and Dimitri N. Mavris

Sustainability (Basel, Switzerland), Vol.13(1120), p.1120

01/01/2021

DOI: https://doi.org/10.3390/su13031120

Handle:

https://hdl.handle.net/2376/109921

Appears in Aviation Sustainability Center (ASCENT)

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Abstract

air transportation

community noise

reduced order modeling

airports

A key enabler for sustainable growth of aviation is the mitigation of adverse environmental effects. One area of concern is community noise exposure at large hub airports serving growing population centers. Traditionally, community noise exposure is computed using noise contours around airports, which requires knowledge of a large dataset pertaining to the air traffic operations at the airport of interest. Due to the underlying variability in real-world aircraft operations, numerous assumptions need to be made which adversely affect the accuracy of the model. Reduced-Order Modeling (ROM) methods provide a new framework for the retention of a large number of these parameters, thus improving model speed and accuracy. In this work, a proper orthogonal decomposition in conjunction with a response surface methodology-based surrogate model is used to create a rapid noise assessment model. Validation is performed against results obtained from the aviation environmental design tool with quantitative error metrics and visual contour comparisons. Obtained results are encouraging and motivate further work in this area with other ROM methods. ROM based models for noise assessment expand the solution space for noise mitigation strategies which can be evaluated, and therefore can lead to novel solutions which cannot be found with traditional modeling methods.

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Title: Reduced Order Modeling Methods for Aviation Noise Estimation
Creators: Ameya Behere - Aerospace Systems Design Laboratory, Georgia Institute of Technology, Atlanta, GA 30332-0150, USA
Dushhyanth Rajaram - Aerospace Systems Design Laboratory, Georgia Institute of Technology, Atlanta, GA 30332-0150, USA
Tejas G. Puranik - Aerospace Systems Design Laboratory, Georgia Institute of Technology, Atlanta, GA 30332-0150, USA
Michelle Kirby - Aerospace Systems Design Laboratory, Georgia Institute of Technology, Atlanta, GA 30332-0150, USA
Dimitri N. Mavris - Aerospace Systems Design Laboratory, Georgia Institute of Technology, Atlanta, GA 30332-0150, USA
Publication Details: Sustainability (Basel, Switzerland), Vol.13(1120), p.1120
Academic Unit: Modeling Tools; Aviation Sustainability Center (ASCENT)
Publisher: MDPI AG
Grants: 13-C-AJFE-GT-054, Federal Aviation Administration (United States, Washington) - FAA
Identifiers: 99900567301301842
Language: English
Resource Type: Journal article