Sensitivities of Aircraft Acoustic Metrics to Engine Design Variables for Multidisciplinary Optimization

Voet, Laurens J. A.; Prakash, Prashanth; Speth, Raymond; Sabnis, Jayant; Tan, Choon S; Barrett, Steven R.H.; Massachusetts Institute of Technology; United States. Federal Aviation Administration. Center of Excellence for Alternative Jet Fuels and Environment

doi:10.2514/1.J061411

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Sensitivities of Aircraft Acoustic Metrics to Engine Design Variables for Multidisciplinary Optimization

2022-05-01
By Voet, Laurens J. A. ; Prakash, Prashanth ; Speth, Raymond ; ...

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Creators:

Voet, Laurens J. A. ; Prakash, Prashanth ; Speth, Raymond ; Sabnis, Jayant ; Tan, Choon S ; ... More +

Voet, Laurens J. A. ; Prakash, Prashanth ; Speth, Raymond ; Sabnis, Jayant ; Tan, Choon S ; Barrett, Steven R.H. Less -
Corporate Creators:

Massachusetts Institute of Technology ; United States. Federal Aviation Administration. Center of Excellence for Alternative Jet Fuels and Environment

Massachusetts Institute of Technology ; United States. Federal Aviation Administration. Center of Excellence for Alternative Jet Fuels and Environment Less -
Corporate Contributors:

United States. Department of Transportation. Federal Aviation Administration. Office of Environment and Energy
Subject/TRT Terms:

[+]

Aircraft Aircraft Operations Airplanes ASCENT Design Engines Intake Valves Supersonic Aircraft Wings (Aircraft)
Publication/ Report Number:

1.J061411
DOI:

https://doi.org/10.2514/1.J061411
Resource Type:

Journal Article
Geographical Coverage:

United States
Corporate Publisher:

American Institute of Aeronautics and Astronautics
Abstract:

Aircraft environmental performance metrics including fuel burn, takeoff and landing noise, and gaseous emissions are increasingly driving the design and optimization of modern aircraft engines. Gradient-based methods can significantly reduce the computational resources required during their multidisciplinary optimizations. However, current state-of-the art noise modeling tools do not allow for effective computation of sensitivities of acoustic metrics with respect to engine design and control variables, and therefore cannot be easily integrated into multidisciplinary optimization tools. This paper presents the utility of the python Noise Assessment tool (known as pyNA): an aircraft noise estimation model providing sensitivities of acoustic metrics, enabling multidisciplinary optimization and optimal control of engines for low-noise aircraft. The model is used to assess the trades of environmental performance metrics in the clean-sheet engine design for the NASA supersonic technology concept airplane. For the engine examined, if the fan diameter is allowed to change while technology levels are held constant, the takeoff noise levels and emissions are found to be most sensitive to the design fan pressure ratio. For an engine with a fixed fan diameter, takeoff noise levels are found to be insensitive to design variables; whereas nitrogen oxide emissions and cruise thrust-specific fuel consumption are most sensitive to the engine fan and high-pressure compressor pressure ratios.
Content Notes:

This research was funded by the Federal Aviation Administration (FAA) Office of Environment and Energy through the FAA Center of Excellence for Alternative Jet Fuels and the Environment (ASCENT), and Project 47 through FAA Award No. 13-C-AJFEMIT.

NTL provides this record to document USDOT's funding of this research.

This is a copyrighted article published by the American Institute of Aeronautics and Astronautics (AIAA). This item may be behind a paywall, and you may have to seek interlibrary loan through your local library.
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PDF
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13-C-AJFF-MIT-52, 59, 74
Collection(s):

Federal Aviation Administration
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urn:sha256:e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855
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Sensitivities of Aircraft Acoustic Metrics to Engine Design Variables for Multidisciplinary Optimization

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