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Improving the Physics of Applied Reverberation Models

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-13-P-1168
Agency Tracking Number: N13A-026-0045
Amount: $79,989.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N13A-T026
Solicitation Number: 2013.A
Timeline
Solicitation Year: 2013
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-07-01
Award End Date (Contract End Date): 2014-04-30
Small Business Information
5860 Trinity Parkway Suite 200
Centreville, VA -
United States
DUNS: 135121148
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Rob Blanchard
 Principal Investigator
 (703) 968-6127
 rblanchard@adaptivemethods.com
Business Contact
 Judy Barhorst
Title: Director of Contracts
Phone: (703) 968-6110
Email: jbarhorst@adaptivemethods.com
Research Institution
 APL University of Washington
 Lynette Arias
 
1013 NE 40th Street
Seattle, WA 98105-
United States

 (206) 543-4043
 Nonprofit College or University
Abstract

We propose to enhance the capability of ASTRAL/ASPM by adding to it a treatment of several physical phenomena. Several methods enabling these new features have been developed and tested in recent years and are mature enough for transition. Efforts will be made to ensure the enhancement will not come with significant loss of efficiency. The Phase I effort consists of incorporating into ASTRAL/ASPM the surface loss model TOTLOS, which takes into account surface forward scattering in its effect on both propagation and reverberation. A Phase I Option is also proposed and consists of developing a strategy for incorporating more physically-based bottom loss models into ASPM reverberation modeling, testing the strategy for a specific environment, and comparing the results to the current bottom loss models used in ASPM as well as parabolic equation and mode codes. Potential Phase II efforts include: (a) incorporate tested models, where appropriate, into ASPM; (b) use ONR TREX13 data sets along with full environmental inputs, to evaluate the improved version of ASTRAL/ASPM, and demonstrate its efficacy; (c) test the resulting code on other data sets, including those of NAVO; (d) help guide the ASPM enhancements through the OAML process.

* Information listed above is at the time of submission. *

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