Innovative Capability to Quantify Fatigue Damage and Assessment of Endurance Limit in Spectrum Load Histories

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$79,933.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
N68335-11-C-0055
Award Id:
n/a
Agency Tracking Number:
N102-113-0597
Solicitation Year:
2010
Solicitation Topic Code:
N102-113
Solicitation Number:
2010.2
Small Business Information
1820 Ridge Avenue, Evanston, IL, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
088176961
Principal Investigator:
Herng-Jeng Jou
Director of Technology
(847) 425-8221
hjjou@questek.com
Business Contact:
Raymond Genellie
Vice President - Operatio
(847) 425-8211
rgenellie@questek.com
Research Institution:
Stub




Abstract
Flight-critical components in aircraft and helicopters experience complex service and loading conditions comprising of spectrum (variable amplitude) loading during their lifetime. Due to complex interaction of several life-limiting factors during spectrum loading, particularly, multiple fatigue damage mechanisms and microstructure sensitivity, development of analytical models to accurately predict fatigue damage and service life of the material/component in spectrum loading has been difficult. Additionally, highly conservative recommendations for component inspection and retirement schedule are subsequently adopted. In this effort, QuesTek proposes to combine its expertise in microstructure-sensitive fatigue modeling with Professor James Newman's expertise in fatigue crack growth and FASTRAN software development, to apply an innovative modeling scheme to accurately predict fatigue damage and service life during spectrum loading histories. The modeling strategies will be based on the mechanisms of small/short crack growth, with consideration of relevant microstructure features, during low amplitude cycles integrated with the well-established long crack growth law. The models will be integrated into FASTRAN to enable rapid transition into Navy applications. QuesTek intends to demonstrate the feasibility of this approach in Phase I through modeling and validation against existing data, and further refine and improve the analytical models utilizing a combined experimentation and numerical simulations in Phase II.

* information listed above is at the time of submission.

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