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Signal recognition of fatigue crack growth in bridge structures connected to specimen behaviour

Signal recognition of fatigue crack growth in bridge structures connected to specimen behaviour Health monitoring in life and material sciences is involved fundamentally with the scaling of time and space variables. The use specificity, however, can differ widely with reference to ranges of the space and time scales even when the application is narrowed down to aeronautics and civil engineering structures. Reliable evaluation of the structural integrity depends on the connection between data acquisition and interpretation. The fulfillment of this link can vary from the most obvious to the very subtle. It is prudent that the effectiveness of the monitoring technology be identified with signal recognition. To this end, this work will be confined to the failure of bridge structural members by fatigue crack propagation, which is one of the primary concerns over the lifetime of the structure as the operational conditions and structural properties can change over a period of 100 years or less. Conventional fatigue crack growth methodology has been scrutinized in recent research in light of multiscaling where the crack growth rate da/dN data between the transition from region I to II are being re-visited. Experience has shown that cracks in the field are not always visible to the naked eye and yet they could be classified as macroscopic by conventional definitions which rely only on the crack-length parameter. In what follows, no a priori assumption will be made about the size scale of the crack but rather it can undergo transition from micro to macro or vice versa. The provision is made that a crack can be fully opened (τ = 0) or closed (τ = 1). Varying degree of crack surface tightness corresponds to 0 < τ < 1. Hence, the crack can be invisible to the naked eye (microscopic) at one time and visible (macroscopic) at another time depending on the alternating load. Fatigue cracks as a rule grow slowly and stably before they propagate unstably. An analytical model of this behaviour necessitates the dual scale feature that can describe the transition from micro to macro or in the reverse order. The same requirement applies to the sensing device that must be able to detect micro/macro displacement or strain under field conditions. The likelihood of micro/macro transition will be exhibited by existing fatigue crack growth data on 2024-T3 and 7075-T6 aluminum alloy from the aircraft industry where different mean stress levels and stress amplitudes were used. A similar transition of micro/macro effects are expected to occur in steel. When the crack surfaces are tightly in contact, the crack’s path would be affected by the material microstructure. This corresponds to relatively low mean applied fatigue load. The crack can be fully open and behave like a macrocrack when the mean stress is high. Because of the irregular nature of the material’s internal structure, no one simple fatigue crack damage model will likely describe the crack growth behaviour, even less for the damage caused by a cluster of cracks. The physical model must therefore possess the capability to switch from models to models as the combination of crack surface tightness changes with loading and the material microstructure. This possibility has been demonstrated in this work on the basis of the closed form solution for the micro/macro stress intensity factor that can be incorporated into a simple two-parameter crack growth rate model similar to the fourth power law that is presently limited to a fully opened macrocrack. A simple integration also applies to the micro/macro crack model such that crack length versus fatigue cycle relation can be obtained for different combinations of repeated loading, internal material structure, and specimen geometry as used in design. Corrections for environmental effects can be added if necessary. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bridge Structures IOS Press

Signal recognition of fatigue crack growth in bridge structures connected to specimen behaviour

Sih, G.C.
Bridge Structures , Volume 2 (3) – Jan 1, 2006
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Publisher
IOS Press
Copyright
Copyright © 2006 by IOS Press, Inc
ISSN
1573-2487
eISSN
1744-8999
DOI
10.1080/15732480600858366
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Abstract

Health monitoring in life and material sciences is involved fundamentally with the scaling of time and space variables. The use specificity, however, can differ widely with reference to ranges of the space and time scales even when the application is narrowed down to aeronautics and civil engineering structures. Reliable evaluation of the structural integrity depends on the connection between data acquisition and interpretation. The fulfillment of this link can vary from the most obvious to the very subtle. It is prudent that the effectiveness of the monitoring technology be identified with signal recognition. To this end, this work will be confined to the failure of bridge structural members by fatigue crack propagation, which is one of the primary concerns over the lifetime of the structure as the operational conditions and structural properties can change over a period of 100 years or less. Conventional fatigue crack growth methodology has been scrutinized in recent research in light of multiscaling where the crack growth rate da/dN data between the transition from region I to II are being re-visited. Experience has shown that cracks in the field are not always visible to the naked eye and yet they could be classified as macroscopic by conventional definitions which rely only on the crack-length parameter. In what follows, no a priori assumption will be made about the size scale of the crack but rather it can undergo transition from micro to macro or vice versa. The provision is made that a crack can be fully opened (τ = 0) or closed (τ = 1). Varying degree of crack surface tightness corresponds to 0 < τ < 1. Hence, the crack can be invisible to the naked eye (microscopic) at one time and visible (macroscopic) at another time depending on the alternating load. Fatigue cracks as a rule grow slowly and stably before they propagate unstably. An analytical model of this behaviour necessitates the dual scale feature that can describe the transition from micro to macro or in the reverse order. The same requirement applies to the sensing device that must be able to detect micro/macro displacement or strain under field conditions. The likelihood of micro/macro transition will be exhibited by existing fatigue crack growth data on 2024-T3 and 7075-T6 aluminum alloy from the aircraft industry where different mean stress levels and stress amplitudes were used. A similar transition of micro/macro effects are expected to occur in steel. When the crack surfaces are tightly in contact, the crack’s path would be affected by the material microstructure. This corresponds to relatively low mean applied fatigue load. The crack can be fully open and behave like a macrocrack when the mean stress is high. Because of the irregular nature of the material’s internal structure, no one simple fatigue crack damage model will likely describe the crack growth behaviour, even less for the damage caused by a cluster of cracks. The physical model must therefore possess the capability to switch from models to models as the combination of crack surface tightness changes with loading and the material microstructure. This possibility has been demonstrated in this work on the basis of the closed form solution for the micro/macro stress intensity factor that can be incorporated into a simple two-parameter crack growth rate model similar to the fourth power law that is presently limited to a fully opened macrocrack. A simple integration also applies to the micro/macro crack model such that crack length versus fatigue cycle relation can be obtained for different combinations of repeated loading, internal material structure, and specimen geometry as used in design. Corrections for environmental effects can be added if necessary.

Journal

Bridge Structures – IOS Press

Published: Jan 1, 2006

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