Comparison between the predicted performance curve and the Markov Chain models for structural performance of infrastructure components

This paper compares the PPC model to a Markov Chain (MC) stochastic deterioration model. First, inspection data from the Société de Transport de Montréal (STM) is gathered and analyzed. Then Transition Probability Matrices (TPM) are developed, and, using Matlab, MC deterioration curves are developed...

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Main Authors: Semaan Nabil, Dib Youssef
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:MATEC Web of Conferences
Online Access:https://www.matec-conferences.org/articles/matecconf/pdf/2019/38/matecconf_cs18_08006.pdf
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spelling doaj-7a9d730898ec42c59e9b5f570f6402872021-02-02T04:06:49ZengEDP SciencesMATEC Web of Conferences2261-236X2019-01-012890800610.1051/matecconf/201928908006matecconf_cs18_08006Comparison between the predicted performance curve and the Markov Chain models for structural performance of infrastructure componentsSemaan Nabil0Dib Youssef1University Of Balamand, Civil and Environmental Engineering DepartmentUniversity Of Balamand, Math DepartmentThis paper compares the PPC model to a Markov Chain (MC) stochastic deterioration model. First, inspection data from the Société de Transport de Montréal (STM) is gathered and analyzed. Then Transition Probability Matrices (TPM) are developed, and, using Matlab, MC deterioration curves are developed. Comparison between MC and the PPC deterioration curves is performed for subway station walls and slabs. The comparison has shown that the useful service life can be as low as 2 years for components having many inspection history records, and very high as 30 years for components having very few inspection history records. The PPC model has always a higher useful service life estimate. Also, the MC has a ten times higher deterioration rate (0.2 per year) compared to the PPC model (0.02 per year). It can be concluded that the MC deterioration model requires a high amount of inspection data, and it is mathematically difficult to generate since most practicing managers and engineers have no background in Markov Chain modeling.https://www.matec-conferences.org/articles/matecconf/pdf/2019/38/matecconf_cs18_08006.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Semaan Nabil
Dib Youssef
spellingShingle Semaan Nabil
Dib Youssef
Comparison between the predicted performance curve and the Markov Chain models for structural performance of infrastructure components
MATEC Web of Conferences
author_facet Semaan Nabil
Dib Youssef
author_sort Semaan Nabil
title Comparison between the predicted performance curve and the Markov Chain models for structural performance of infrastructure components
title_short Comparison between the predicted performance curve and the Markov Chain models for structural performance of infrastructure components
title_full Comparison between the predicted performance curve and the Markov Chain models for structural performance of infrastructure components
title_fullStr Comparison between the predicted performance curve and the Markov Chain models for structural performance of infrastructure components
title_full_unstemmed Comparison between the predicted performance curve and the Markov Chain models for structural performance of infrastructure components
title_sort comparison between the predicted performance curve and the markov chain models for structural performance of infrastructure components
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2019-01-01
description This paper compares the PPC model to a Markov Chain (MC) stochastic deterioration model. First, inspection data from the Société de Transport de Montréal (STM) is gathered and analyzed. Then Transition Probability Matrices (TPM) are developed, and, using Matlab, MC deterioration curves are developed. Comparison between MC and the PPC deterioration curves is performed for subway station walls and slabs. The comparison has shown that the useful service life can be as low as 2 years for components having many inspection history records, and very high as 30 years for components having very few inspection history records. The PPC model has always a higher useful service life estimate. Also, the MC has a ten times higher deterioration rate (0.2 per year) compared to the PPC model (0.02 per year). It can be concluded that the MC deterioration model requires a high amount of inspection data, and it is mathematically difficult to generate since most practicing managers and engineers have no background in Markov Chain modeling.
url https://www.matec-conferences.org/articles/matecconf/pdf/2019/38/matecconf_cs18_08006.pdf
work_keys_str_mv AT semaannabil comparisonbetweenthepredictedperformancecurveandthemarkovchainmodelsforstructuralperformanceofinfrastructurecomponents
AT dibyoussef comparisonbetweenthepredictedperformancecurveandthemarkovchainmodelsforstructuralperformanceofinfrastructurecomponents
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