Corrosion Modeling and Life Prediction Supporting Structural Prognostic Health Management

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,952.00
Award Year:
2006
Program:
SBIR
Phase:
Phase I
Contract:
FA8650-06-M-5022
Award Id:
78894
Agency Tracking Number:
F061-091-0460
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
200 Canal View Blvd, Rochester, NY, 14623
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
073955507
Principal Investigator:
Gregory Kacprzynski
Manager, Advanced Programs
(585) 424-1990
greg.kacprzynski@impact-tek.com
Business Contact:
Mark Redding
President
(585) 424-1990
mark.redding@impact-tek.com
Research Institute:
n/a
Abstract
Objective: Impact Technologies, in collaboration with Ohio State University (OSU) and with the support of Northrop Grumman Integrated Systems, propose to develop a novel framework for corrosion prognosis addressing corrosion initiation and differentiation physics of failure models, imperfect damage estimates and global to local electrochemical transfer functions. Using both new and historical data on aerospace aluminum alloys available at the OSU Fontana Corrosion Center, the research team will develop reasoning methods for capturing the influence of key microclimatic, metallurgical and electrochemical effects on corrosion initiation and failure mode differentiation. In addition, a Bayesian Inference tool will be developed to calibrate the physics-of-failure models as evidence from inspection becomes available so that the frequency of such inspections may be reduced or eliminated as the prognostic system is validated. Being fully aware of costs of corrosion inspections and limitations on obtaining microclimatic data, the team will report on the relative benefit of obtaining and tracking various data types within the constraints of planned autonomic logistics systems and provide suggested interface design specifications for a corrosion PHM module. Finally, a comprehensive software demonstration of the corrosion prognosis module will be developed and presented illustrating model-based damage predictions vs. experimental data.

* information listed above is at the time of submission.

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