Acoustic Prediction/Measurement Tool

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NAS13-02018
Agency Tracking Number: 000226
Amount: $599,060.00
Phase: Phase II
Program: SBIR
Awards Year: 2002
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
AI Signal Research, Inc.
3411 Triana Blvd., Huntsville, AL, 35805
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Wade Dorland
 Senior Program Manager
 (256) 551-0008
 wdorland@aisignal.com
Business Contact
 Silvio D'Orazio
Title: Vice President
Phone: (256) 551-0008
Email: jjong@aisignal.com
Research Institution
N/A
Abstract
The proposed innovative analysis tool is driven by the need to integrate both analytical and experimental techniques when performing an experiment of spacecraft launch. When available, this tool provides an acoustic engineer access to both the experimental data being measured and analytical predictions that are derived from empirical models and a database. Thus, the proposed tool takes advantage of an existing database that includes pertinent extensive Computational Fluid Dynamics (CFD) data. As data are being recorded, the tool generates acoustic spectra at locations that are not part of the experimental setup to provide in-situ prediction. Furthermore, this high-level analysis tool improves the quality of the experimental data by detecting potential problems as the data is being taken; hence, the engineer can intervene in the process to eliminate anomalies or improve results. The analytical prediction tool, once calibrated, can be used to predict acoustic spectra during launch at various locations on and around the spacecraft. These acoustic load predictions can then be used for structural dynamic analysis. The proposed tool incorporates several input parameters that an analyst can change to simulate or eliminate perturbations in the experimental conditions. This flexibility helps determine the sensitivity of the measured experimental results to various parameters.

* information listed above is at the time of submission.

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