Implementation of Facility Models Using Neural Networks for Improved Control of Wind Tunnels

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9550-10-C-0150
Agency Tracking Number: F09B-T16-0214
Amount: $99,999.00
Phase: Phase I
Program: STTR
Awards Year: 2010
Solicitation Year: 2009
Solicitation Topic Code: AF09-BT16
Solicitation Number: 2009.B
Small Business Information
Innovative Technology Applications Co.,
PO Box 6971, Chesterfield, MO, 63006
DUNS: 126752018
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Mark Rennie
 Research Assistant Professor
 (574) 631-1695
 rrennie@nd.edu
Business Contact
 Alan Cain
Title: President
Phone: (314) 373-3311
Email: abcain@itacllc.com
Research Institution
 University of Notre Dame
 Shanda Wirt
 511 Main Building
Notre Dame, IN, 46556
 (574) 631-8710
 Nonprofit college or university
Abstract
Test facilities such as wind tunnels require stringent control of test parameters such as wind speed, temperature, pressure, etc., in order to satisfy the objectives of the simulation. Control of test facilities can be significantly improved using mathematical models for the facility behavior that are developed from physical principles. A shortcoming of mathematical control models is that they typically contain parameters that must be directly measured in order to match the performance of the actual facility. As a result, it is necessary to “tune” the mathematical models to match the actual facility response. Tuning of the mathematical models can be a very complex and time-intensive activity, particularly for complex facility operations requiring simultaneous control of multiple systems or actuators. The objective of the proposed research is to investigate methods of automating the data collection and analysis associated with tuning mathematical facility models, so that these activities are run simultaneously with regular facility operations and require minimal involvement of facility staff. BENEFIT: This program will result in improvements and automation in the operation of wind tunnel facilities that may be applied to government and industrial facilities.

* information listed above is at the time of submission.

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