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A probabilistic model updating algorithm for fatigue damage detection in aluminum hull structures

Publication ,  Conference
Kurata, M; Kim, JH; Lynch, JP; Law, KH; Salvino, LW
Published in: ASME 2010 Conference on Smart Materials Adaptive Structures and Intelligent Systems Smasis 2010
January 1, 2010

The use of aluminum alloys in the design of naval structures offers the benefit of light-weight ships that can travel at high-speed. However, the use of aluminum poses a number of challenges for the naval engineering community including higher incidence of fatigue-related cracks. Early detection of fatigue induced cracks enhances maintenance of the ships and is critical for preventing the catastrophic failure of the hull. Furthermore, monitoring the integrity of the aluminum hull can provide valuable information for estimating the residual life of hull components. This paper presents a model-based damage detection methodology for fatigue assessment of hulls that are instrumented with a long-term hull monitoring system. At the core of the data driven damage detection approach is a Bayesian model updating algorithm enhanced with systematic enumeration and pruning of candidate solutions. The Bayesian model updating approach significantly reduce the computational effort by systematically narrowing the search space using errors functions constructed using the estimated modal properties associated with the condition of the structure. This study proposes the use of the Bayesian model updating technique to detect damage in an aluminum panel modeled using high-fidelity finite element models. The performance of the proposed damage detection method is tested through simulation of a progressively growing fatigue crack introduced in the vicinity of a welded stiffener element. An experimental study verifies the accuracy of the proposed damage detection method using an aluminum plate excited with a controlled excitation in the laboratory. Copyright © 2010 by ASME.

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Published In

ASME 2010 Conference on Smart Materials Adaptive Structures and Intelligent Systems Smasis 2010

DOI

Publication Date

January 1, 2010

Volume

2

Start / End Page

741 / 750
 

Citation

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Kurata, M., Kim, J. H., Lynch, J. P., Law, K. H., & Salvino, L. W. (2010). A probabilistic model updating algorithm for fatigue damage detection in aluminum hull structures. In ASME 2010 Conference on Smart Materials Adaptive Structures and Intelligent Systems Smasis 2010 (Vol. 2, pp. 741–750). https://doi.org/10.1115/smasis2010-3838
Kurata, M., J. H. Kim, J. P. Lynch, K. H. Law, and L. W. Salvino. “A probabilistic model updating algorithm for fatigue damage detection in aluminum hull structures.” In ASME 2010 Conference on Smart Materials Adaptive Structures and Intelligent Systems Smasis 2010, 2:741–50, 2010. https://doi.org/10.1115/smasis2010-3838.
Kurata M, Kim JH, Lynch JP, Law KH, Salvino LW. A probabilistic model updating algorithm for fatigue damage detection in aluminum hull structures. In: ASME 2010 Conference on Smart Materials Adaptive Structures and Intelligent Systems Smasis 2010. 2010. p. 741–50.
Kurata, M., et al. “A probabilistic model updating algorithm for fatigue damage detection in aluminum hull structures.” ASME 2010 Conference on Smart Materials Adaptive Structures and Intelligent Systems Smasis 2010, vol. 2, 2010, pp. 741–50. Scopus, doi:10.1115/smasis2010-3838.
Kurata M, Kim JH, Lynch JP, Law KH, Salvino LW. A probabilistic model updating algorithm for fatigue damage detection in aluminum hull structures. ASME 2010 Conference on Smart Materials Adaptive Structures and Intelligent Systems Smasis 2010. 2010. p. 741–750.

Published In

ASME 2010 Conference on Smart Materials Adaptive Structures and Intelligent Systems Smasis 2010

DOI

Publication Date

January 1, 2010

Volume

2

Start / End Page

741 / 750