Reliability-based Inspection Planning with Application to Deck Structure Thickness Measurement of Corroded Aging Tankers.
dc.contributor.author | Guo, Jinting | en_US |
dc.date.accessioned | 2010-06-03T15:41:20Z | |
dc.date.available | NO_RESTRICTION | en_US |
dc.date.available | 2010-06-03T15:41:20Z | |
dc.date.issued | 2010 | en_US |
dc.date.submitted | en_US | |
dc.identifier.uri | https://hdl.handle.net/2027.42/75877 | |
dc.description.abstract | Structural inspection is a critical part of the ship structural integrity assessment. Corrosion, as a very pervasive type of structural degradation, can potentially lead to catastrophic failure or unanticipated out-of-service time. In order to mitigate the unfavorable consequences of age-related structural failure, a wisely planned inspection is needed. The current practice of calendar-based inspection of ship structures may cause either an unexpected stoppage during normal routine due to unpredicted structural failures or yield higher costs for unnecessary inspections. Therefore, a strategy to determine timely and effective inspection plans is highly desirable. Probabilistic tools have been used in ship structure analysis for years. Recently, there is revived interest in the reliability-based inspection planning of ship structures. This study is devoted to demonstrating a practical methodology and procedure that adopts a reliability-based approach in structural inspection planning of ship structures. Scheduling a gauging survey for deck panels of oil tankers is used to demonstrate the proposed procedure. This approach includes the derivation of explicit limit state functions for the ultimate strength failure of deck panels based on the equations stated in the International Association of Classification Societies’ Common Structure Rules for double hull oil tanker (2008), and quantifies the various types of uncertainties involved. A time-variant probabilistic corrosion model is derived based on the gauging data collected by the American Bureau of Shipping. Monte Carlo Simulation method with Latin Hypercube Sampling is used for calculating time-variant probability of ultimate strength failure is obtained. By comparing the calculated failure probabilities with the target reliability levels, the inspection intervals can then be determined. The reliability formulations derived in this study are applied to a case study in which the reliability assessment of the deck panels and associated inspection planning of a total of six oil tanker ship designs are carried out. Sensitivity analyses are also performed to investigate the relative contribution of each basic variable. The limitation of the proposed procedure is also discussed along with potential future work. | en_US |
dc.format.extent | 2714245 bytes | |
dc.format.extent | 1373 bytes | |
dc.format.mimetype | application/octet-stream | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | en_US |
dc.subject | Reliability-based Inspection | en_US |
dc.subject | Corrosion | en_US |
dc.subject | Ship Structural Degradation | en_US |
dc.subject | Aging Tankers | en_US |
dc.subject | Time-variant Failure Probability | en_US |
dc.title | Reliability-based Inspection Planning with Application to Deck Structure Thickness Measurement of Corroded Aging Tankers. | en_US |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | PhD | en_US |
dc.description.thesisdegreediscipline | Naval Architecture & Marine Engineering | en_US |
dc.description.thesisdegreegrantor | University of Michigan, Horace H. Rackham School of Graduate Studies | en_US |
dc.contributor.committeemember | Perakis, Anastassios N. | en_US |
dc.contributor.committeemember | Hansen, Will | en_US |
dc.contributor.committeemember | Vlahopoulos, Nickolas | en_US |
dc.contributor.committeemember | Wang, Ge | en_US |
dc.subject.hlbsecondlevel | Naval Architecture and Marine Engineering | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/75877/1/jtguo_1.pdf | |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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