Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, dissertation, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

FAILURE PROBABILITY MODELING FOR PIPING SYSTEMS SUBJECT TO CORROSION UNDER INSULATION

MOKHTAR, AINUL AKMAR (2011) FAILURE PROBABILITY MODELING FOR PIPING SYSTEMS SUBJECT TO CORROSION UNDER INSULATION. PhD thesis, UTP.

[img]
Preview
PDF
Download (99Kb) | Preview
[img]
Preview
PDF
Download (427Kb) | Preview
[img]
Preview
PDF
Download (97Kb) | Preview
[img]
Preview
PDF
Download (210Kb) | Preview
[img]
Preview
PDF
Download (139Kb) | Preview
[img]
Preview
PDF
Download (58Kb) | Preview
[img]
Preview
PDF
Download (164Kb) | Preview
[img]
Preview
PDF
Download (1162Kb) | Preview
[img]
Preview
PDF
Download (336Kb) | Preview
[img]
Preview
PDF
Download (2230Kb) | Preview
[img]
Preview
PDF
Download (61Kb) | Preview
[img]
Preview
PDF
Download (8Kb) | Preview
[img]
Preview
PDF
Download (15Kb) | Preview
[img]
Preview
PDF
Download (149Kb) | Preview

Abstract

Corrosion under insulation (CUI) is found to be a major problem for insulated piping systems in refineries, petrochemical and gas processing plants. Since those pipes carry hydrocarbons or other dangerous process fluids, gradual thinning due to CUI may cause the pipes to leak, leading to a hazardous situation. Due to the nature of CUI which is hidden, the challenge is in the monitoring, detection and, hence, prediction of CUI. Also, due to scarcity of data, the current CUI inspection and maintenance strategy adopts the risk-based inspection (RBI) approach where the assessment of the probability of failure for CUI adopts either the qualitative or semi-quantitative methods. These approaches were highly subjective and to overcome this drawback, the quantitative approach is usually employed where this approach bases the failure probability estimates on historical failure data. This study presents a methodology for quantitatively estimating the probability of failure of piping systems subject to CUI based on the type of data available. In the absence of failure data and wall thickness data, logistic regression model was proposed by considering the inspection data as a binary data. When the wall thickness data is available, the probabilistic models, namely degradation analysis, structural reliability analysis and Markov chain model, were proposed. The study recommended that for the case where wall thickness data is minimal, a good model that can be used for quantitative risk assessment is the structural reliability analysis. If more wall thickness data is available, degradation analysis and Markov chain model are the potential models. This study also demonstrated that the logistic regression model is not applicable for quantitative risk assessment. In summary, the quantitative approach is necessary as a means for quantitatively establishing future reliability for piping systems subject to CUI. Even though applying the quantitative method is optional in the current RBI analysis, quantitative risk assessment is, in fact, now a required element of the maintenance optimization methodology.

Item Type: Thesis (PhD)
Subject: UNSPECIFIED
Divisions: Engineering > Mechanical
Depositing User: Users 5 not found.
Date Deposited: 05 Jun 2012 08:20
Last Modified: 25 Jan 2017 09:42
URI: http://utpedia.utp.edu.my/id/eprint/2775

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...