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Stochastic Characterization of Naval Aircraft Electromagnetic Vulnerability:…

Award Information

Agency:
Department of Defense
Branch:
Navy
Award ID:
85129
Program Year/Program:
2010 / STTR
Agency Tracking Number:
N08A-006-0263
Solicitation Year:
2008
Solicitation Topic Code:
N08-T006
Solicitation Number:
2008.A
Small Business Information
ANDRO Computational Solutions, LLC
Beeches Technical Campus 7902 Turin Road, Ste. 2-1 Rome, NY -
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 2010
Title: Stochastic Characterization of Naval Aircraft Electromagnetic Vulnerability: ElectroMagnetic Susceptibility Threshold Analysis Techniques by Estimatio
Agency / Branch: DOD / NAVY
Contract: N68335-10-C-0020
Award Amount: $499,962.00
 

Abstract:

The objective of this research is to advance technologies for accurately and reliably characterizing the distributed fields within Naval aircraft and the associated currents on avionic systems and their interconnecting cables in the operational electromagnetic (EM) environment. This includes computing the fields and currents within aircraft cockpits, cabins and equipment bays at/near metallic walls and interior surfaces to predict electromagnetic interference/vulnerability (EMI/V) for installed electronic equipments. Detailed guidelines, embodied in a decision-based expert system tool called EMSTATES, will be developed to direct the generation and analysis of avionics system enclosure/cavity models to supplement existing computational electromagnetics (CEM) tools and EMI/C simulation methodologies. A systematic approach is employed for classifying cavity problems using a taxonomy of susceptibility matched against certain modeling regimes (deterministic, statistical, hybrid). Detailed criteria are developed to select a deterministic method versus a statistical method to efficiently obtain a solution to facilitate weapon system performance risk assessments. Statistical methods are well suited in cases where there is a large degree of uncertainty due to the complexity of both the physical structures (i.e., system-to-system variability, variations in equipment designs and installations), and the chaotic nature of the EM sources, which can render even mature CEM codes by themselves an inefficient means of addressing the problem. Deterministic methods using analytical or numerical tools may be suitable in certain other situations. The required fidelity of aircraft geometry models becomes an important consideration here. The EMSTATES guidelines to be developed in this effort are anticipated to provide highly useful insights into the selection of the appropriate analysis method and the amount of model detail that will be necessary to reduce model/analysis uncertainty by computing bounds on the confidence. This approach will help alleviate the complexity of the computational modeling process and lead to solutions optimized for computational efficiency. New techniques for hybridizing (bridging) the deterministic and statistical domains will also be developed. The guidelines will derive from reverberation chamber, anechoic chamber and mode-stir measurement insights with EM field sampling statistics applied to the current problem. Demonstrations to validate and refine the capability will be performed for both simple models and for a realistic Navy avionics equipment installation. Emphasis will be on source frequencies below 2 GHz, as well as problems through 17 GHz. The belief is that the vast majority of the EMI/V problems we face -- perhaps as much as 95% -- can be worked with simplified methods, best practices handbooks, and current or updated specifications. Therefore, the immediate task is two-fold: (i) find that"vast majority"of the problems and (ii) develop the"simplified methods"for them. The first will be achieved through the taxonomy, supported by additional measurements and computations. Finding those 95% of"simple problems"leaves only 5% to work in detail. This means that the adopters and users of the EMSTATES technologies can increase productivity by nearly 20X as a result.

Principal Investigator:

Andrew Drozd
Chief Scientist
(315) 334-1163
adrozd@androcs.com

Business Contact:

Arnold Kloven
Chief Scientist
(315) 334-1163
akloven@androcs.com
Small Business Information at Submission:

ANDRO Computational Solutions, LLC
Beeches Technical Campus 7902 Turin Road, Ste. 2-1 Rome, NY 13440-

EIN/Tax ID: 043730066
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Research Institution Information:
Oklahoma State University
College of Engineering, Archit
201 Advanced Technology Resear
Stillwater, OK 74078-5012
Contact: Tim Schlais
Contact Phone: (405) 744-9500