NASA SBIR 2019-I Solicitation

Proposal Summary


PROPOSAL NUMBER:
 19-1- A1.02-2701
SUBTOPIC TITLE:
 Quiet Performance - Airframe Noise Reduction
PROPOSAL TITLE:
 High-Resolution Source Characterization and Modeling for Efficient Prediction of Propulsion-Airframe Aeroacoustics
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
ATA Engineering, Inc.
13290 Evening Creek Drive South, Suite 250
San Diego, CA 92128- 4695
(858) 480-2000

Principal Investigator (Name, E-mail, Mail Address, City/State/Zip, Phone)

Name:
Parthiv Shah
E-mail:
parthiv.shah@ata-e.com
Address:
13290 Evening Creek Drive South, Suite 250 San Diego, CA 92128 - 4695
Phone:
(858) 480-2101

Business Official (Name, E-mail, Mail Address, City/State/Zip, Phone)

Name:
Joshua Davis
E-mail:
jdavis@ata-e.com
Address:
13290 Evening Creek Drive South, Suite 250 San Diego, CA 92128 - 4695
Phone:
(858) 480-2028
Estimated Technology Readiness Level (TRL) :
Begin: 2
End: 3
Technical Abstract (Limit 2000 characters, approximately 200 words)

Community noise reduction is a critical focus of NASA ARMD, which is studying highly integrated airframe/propulsion systems such as the hybrid wing body (HWB) and the quiet supersonic technology (QueSST) demonstrator. Relative to conventional aircraft, these systems have closer coupling between sound generation and propagation, creating challenges for noise prediction but also opportunities for shielding. ATA Engineering, in collaboration with the University of California, Irvine, proposes to develop methods to efficiently characterize and ultimately predict aircraft noise associated with such propulsion airframe aeroacoustics (PAA).

The methods will utilize near-field surface source models that are informed by high-spatial-resolution, fixed receiver and continuous-scan array acoustic measurements. In Phase I, the team will apply such measurements to canonical experiments and propulsion simulators (e.g, fan or jet exhaust noise) using fixed and scanning sensors to define stochastic source models. These models will support improved acoustic shielding predictions by directly detecting the mechanisms that propagate sound to the far field and using this information to define surface-based source models to predict noise shielding/scattering of integrated propulsion-airframe configurations using boundary element methods (BEM).

Phase II will involve creating a database of surface-based engine source models based on both experiments and CFD to apply the models to an acoustic design and optimization trade study. Additionally, the team will pursue direct measurement of high-resolution source surface models for use in multi-fidelity noise prediction frameworks such as NASA’s ANOPP/ANOPP2. The expected outcome is a novel, efficient means to quantify community noise from integrated airframe-propulsion systems containing significant PAA. This capability will allow NASA and industry to perform acoustic design and optimization of configurations like HWB and QueSST.

Potential NASA Applications (Limit 1500 characters, approximately 150 words)

The technology enables BEM prediction of far-field acoustics using surface-based sources, enhancing capabilities in two ARMD Strategic Thrusts: Innovations in Commercial Supersonic Aircraft (#2), where a critical theme is “jet and high speed fan/inlet acoustics with airframe interactions,” and Ultra Efficient Commercial Vehicles (#3), where “propulsion noise shielding” is needed for “revolutionary” vehicles. NASA laboratories and wind tunnels could use the tools for studying PAA.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)

Several commercial and defense applications will benefit from improved PAA prediction. Paramount is certification of commercial supersonic aircraft, which are expected to eventually reach fleets of to 350 business and 1700 civil aircraft. Continued improvement of noise performance for the rapidly growing fleet of subsonic commercial aircraft is also a potential application of the technology.

Duration: 6

Form Generated on 06/16/2019 23:26:48