SBIR/STTR Research Award

Reduced-Order Acoustic Prediction Tool for Ducted Fan Noise Sources Including Inflow Distortion and Turbulence Ingestion

Award identifier 998a9ea58c76e793b9746248eae160478274e248512c64ebfb3c66fee8b83defAwarding agency National Aeronautics and Space Administration

Award amount

$749,811

Program and phase

SBIR · Phase II

Award year

2019

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Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
Technology In Blacksburg Inc
Proposal award date
2019-08-13
Contract end date
2021-08-12
UEI
CLLECDWG5CK6
Solicitation number
SBIR_18_P2
Topic code
A1

Research abstract

In response to NASA SBIR topic A1.02, the team of Techsburg, AVEC, and aircraft developer Ampaire have begun implementation of a reduced-order acoustic prediction tool for ducted fan noise sources including inflow distortion and turbulence ingestion.nbsp; Named the ldquo;Installed Ducted-Fan Noise Modelrdquo; (IDFNM) and branching from Techsburg/AVECrsquo;s recognized collaborative work in noise modeling for pusher propellers for defense and commercial customers, this tool will offer early-stage design support for installed ducted fan-rotor propulsion systems by capturing the aerodynamic unsteady loading and noise sources resulting from inflow distortion and unsteadiness ndash; sources of significant importance for the emerging highly-integrated propulsion-airframe concepts such as boundary layer ingesting fans.nbsp; Phase I work positioned the team to use Ampairersquo;s first-generation, aero-efficient TailWind electric aircraft as a demonstrator for novel acoustic prediction tools. nbsp;Building on the Phase I upgrades to the existing NASA codebase V072, Phase II work will see targeted development of a reduced-order prediction tool for turbulence ingestion noise (TIN), a current technical gap in NASA/industry capability.nbsp; Leveraging extensive background in the field of turbulence ingestion from academic partners Drs. William Devenport and Nathan Alexander, this tool will derive inflow turbulence statistics by appropriate scaling of correlation functions as measured on four canonical geometries.nbsp; Combined with accepted blade response models and propagation via Greenrsquo;s function to the far-field, the result will be a first-of-its-kind prediction tool accessible at low computational cost.nbsp; Milestones throughout the work will see the acoustic prediction tool validated in the state-of-the-art anechoic wind tunnel at Virginia Tech.nbsp; nbsp;The deliverable of this Phase II work is the integrated low-order noise prediction softwarenbsp;quot;Installed Ducted-Fan Noise Modelrdquo; which ultimately will be commercialized.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

43 SBIR/STTR records share this UEI (1998–2025). Reported award amounts total $14,258,989. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration

Agency intelligence

National Aeronautics and Space Administration

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