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Research Papers

Structural Life Expectancy of Marine Vessels: Ultimate Strength, Corrosion, Fatigue, Fracture, and Systems

[+] Author and Article Information
Bilal M. Ayyub, David Webb

Center for Technology and Systems Management, Department of Civil and Environmental Engineering,
University of Maryland, College Park, MD 20742

Karl A. Stambaugh

Naval Architect, United States Coast Guard Surface Forces Logistics Center, Baltimore, MD 21226

Timothy A. McAllister

Naval Architect,
United States Coast Guard Surface Forces Logistics Center, Baltimore, MD 21226

Gilberto F. de Souza

Department of Mechatronics and Mechanical Systems Polytechnic School,
University of São Paulo, São Paulo 05508-900, Brazil

Manuscript received January 25, 2014; final manuscript received October 13, 2014; published online February 27, 2015. Assoc. Editor: James Lambert.

ASME J. Risk Uncertainty Part B 1(1), 011001 (Feb 27, 2015) (13 pages) Paper No: RISK-14-1001; doi: 10.1115/1.4026396 History: Received January 25, 2014; Accepted December 04, 2014; Online February 27, 2015

This paper provides a methodology for the structural reliability analysis of marine vessels based on failure modes of their hull girders, stiffened panels including buckling, fatigue, and fracture and corresponding life predictions at the component and system levels. Factors affecting structural integrity such as operational environment and structural response entail uncertainties requiring the use of probabilistic methods to estimate reliabilities associated with various alternatives being considered for design, maintenance, and repair. Variability of corrosion experienced on marine vessels is a specific example of factors affecting structural integrity requiring probabilistic methods. The Structural Life Assessment of Ship Hulls (SLASH) methodology developed in this paper produces time-dependent reliability functions for hull girders, stiffened panels, fatigue details, and fracture at the component and system levels. The methodology was implemented as a web-enabled, cloud-computing-based tool with a database for managing vessels analyzed with associated stations, components, details, and results, and users. Innovative numerical and simulation methods were developed for reliability predictions with the use of conditional expectation. Examples are provided to illustrate the computations.

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References

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Figures

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Fig. 1

Effects of corrosion on the buckling strength of a stiffened panel: (a) buckling capacity and corrosion area fraction and (b) percent of original strength and percent corrosion

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Fig. 3

Probability density functions of resistance S and load L [25]

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Fig. 4

Series system composed of three components

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Fig. 5

Effects of corrosion rate on panel reliability based on buckling strength

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Fig. 6

Effect of corrosion on probability of fatigue failure for a structural detail

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Fig. 7

Mean, median, standard deviation, and fitted crack depth (af) to the mean as functions of years of operation

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Fig. 8

Crack depth histograms as a function of years of operation: (a) After one year of operation, (b) after five years of operation, (c) after ten years of operation, and (d) after 15 years of operation

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Fig. 9

Fatigue reliability as a function of years of operation

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Fig. 10

SLASH ship database

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Fig. 11

SLASH ship definition tab

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Fig. 12

Example SLASH input screen

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Fig. 13

Example SLASH output

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