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Optimal Empirical-Markovian approach for assessment of potential pavement rehabilitation strategies at the project level
An optimal Empirical-Markovian approach is presented for the assessment of potential rehabilitation strategies as applied to flexible pavement at the project level. A simplified empirical model is proposed to predict the heterogeneous transition probabilities associated with rehabilitated pavement b...
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Published in: | Road materials and pavement design 2018-04, Vol.19 (3), p.646-667 |
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description | An optimal Empirical-Markovian approach is presented for the assessment of potential rehabilitation strategies as applied to flexible pavement at the project level. A simplified empirical model is proposed to predict the heterogeneous transition probabilities associated with rehabilitated pavement based on the corresponding values associated with original pavement, future traffic loading, and modified structural capacity. Therefore, the performance of rehabilitated pavement can directly be controlled by the modified structural capacity. The modified structural capacity associated with a particular rehabilitation strategy is defined using the modified layer coefficients with the corresponding modified structural numbers are used in the empirical model to predict the relevant heterogeneous transition probabilities. These probabilities are then used to estimate the annual distress ratings (DRs) associated with each potential rehabilitation strategy for a specified analysis period. The optimal assessment of potential rehabilitation strategies is carried out using the cost-effectiveness ratio defined as the ratio of the life-cycle average DR to the life-cycle cost. The life-cycle cost can include cost items such as initial construction cost, routine maintenance cost, and major rehabilitation cost. The optimal rehabilitation strategy is the one associated with the highest cost-effectiveness ratio. The presented case study has indicated the effectiveness of the proposed optimal approach in developing and yielding dependable optimal rehabilitation strategies. |
doi_str_mv | 10.1080/14680629.2016.1267661 |
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A simplified empirical model is proposed to predict the heterogeneous transition probabilities associated with rehabilitated pavement based on the corresponding values associated with original pavement, future traffic loading, and modified structural capacity. Therefore, the performance of rehabilitated pavement can directly be controlled by the modified structural capacity. The modified structural capacity associated with a particular rehabilitation strategy is defined using the modified layer coefficients with the corresponding modified structural numbers are used in the empirical model to predict the relevant heterogeneous transition probabilities. These probabilities are then used to estimate the annual distress ratings (DRs) associated with each potential rehabilitation strategy for a specified analysis period. The optimal assessment of potential rehabilitation strategies is carried out using the cost-effectiveness ratio defined as the ratio of the life-cycle average DR to the life-cycle cost. The life-cycle cost can include cost items such as initial construction cost, routine maintenance cost, and major rehabilitation cost. The optimal rehabilitation strategy is the one associated with the highest cost-effectiveness ratio. The presented case study has indicated the effectiveness of the proposed optimal approach in developing and yielding dependable optimal rehabilitation strategies.</description><identifier>ISSN: 1468-0629</identifier><identifier>EISSN: 2164-7402</identifier><identifier>DOI: 10.1080/14680629.2016.1267661</identifier><language>eng</language><publisher>Abingdon: Taylor & Francis</publisher><subject>Construction costs ; Cost analysis ; Cycle ratio ; Empirical analysis ; flexible pavement ; heterogeneous Markov chains ; Life cycle costs ; Maintenance costs ; Markov processes ; Mathematical models ; pavement design ; pavement management ; pavement performance ; pavement rehabilitation ; Rehabilitation ; Strategy ; Traffic capacity ; Transition probabilities</subject><ispartof>Road materials and pavement design, 2018-04, Vol.19 (3), p.646-667</ispartof><rights>2016 Informa UK Limited, trading as Taylor & Francis Group 2016</rights><rights>2016 Informa UK Limited, trading as Taylor & Francis Group</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c366t-758f66ed4af2eb1b67e06965162d975db2fa0fc73df85420412269de660f8223</citedby><cites>FETCH-LOGICAL-c366t-758f66ed4af2eb1b67e06965162d975db2fa0fc73df85420412269de660f8223</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Abaza, Khaled A.</creatorcontrib><title>Optimal Empirical-Markovian approach for assessment of potential pavement rehabilitation strategies at the project level</title><title>Road materials and pavement design</title><description>An optimal Empirical-Markovian approach is presented for the assessment of potential rehabilitation strategies as applied to flexible pavement at the project level. A simplified empirical model is proposed to predict the heterogeneous transition probabilities associated with rehabilitated pavement based on the corresponding values associated with original pavement, future traffic loading, and modified structural capacity. Therefore, the performance of rehabilitated pavement can directly be controlled by the modified structural capacity. The modified structural capacity associated with a particular rehabilitation strategy is defined using the modified layer coefficients with the corresponding modified structural numbers are used in the empirical model to predict the relevant heterogeneous transition probabilities. These probabilities are then used to estimate the annual distress ratings (DRs) associated with each potential rehabilitation strategy for a specified analysis period. The optimal assessment of potential rehabilitation strategies is carried out using the cost-effectiveness ratio defined as the ratio of the life-cycle average DR to the life-cycle cost. The life-cycle cost can include cost items such as initial construction cost, routine maintenance cost, and major rehabilitation cost. The optimal rehabilitation strategy is the one associated with the highest cost-effectiveness ratio. The presented case study has indicated the effectiveness of the proposed optimal approach in developing and yielding dependable optimal rehabilitation strategies.</description><subject>Construction costs</subject><subject>Cost analysis</subject><subject>Cycle ratio</subject><subject>Empirical analysis</subject><subject>flexible pavement</subject><subject>heterogeneous Markov chains</subject><subject>Life cycle costs</subject><subject>Maintenance costs</subject><subject>Markov processes</subject><subject>Mathematical models</subject><subject>pavement design</subject><subject>pavement management</subject><subject>pavement performance</subject><subject>pavement rehabilitation</subject><subject>Rehabilitation</subject><subject>Strategy</subject><subject>Traffic capacity</subject><subject>Transition probabilities</subject><issn>1468-0629</issn><issn>2164-7402</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kE9PwzAMxSMEEtPgIyBF4tyRpK3b3kBo_JFAXLhHXuuwjK4pSRjs25OxccUXW9Z7z9aPsQspZlLU4koWUAtQzUwJCTOpoAKQR2yiJBRZVQh1zCY7TbYTnbLzEFYiVZ5LKOWEfb-M0a6x5_P1aL1tsc-e0b-7jcWB4zh6h-2SG-c5hkAhrGmI3Bk-upgmm4wjbuh362mJC9vbiNG6gYfoMdKbpcAx8rgknsJW1Ebe04b6M3ZisA90fuhT9no3f719yJ5e7h9vb56yNgeIWVXWBoC6Ao2ihVxARQKa9DqorqnKbqEMCtNWeWfqslCikEpB0xGAMLVS-ZRd7mPT8Y9PClGv3Kcf0kWthIC6VLKBpCr3qta7EDwZPfpExW-1FHqHWf9h1jvM-oA5-a73PjskRGv8cr7vdMRt77zxOLQ26Pz_iB8PZoXP</recordid><startdate>20180403</startdate><enddate>20180403</enddate><creator>Abaza, Khaled A.</creator><general>Taylor & Francis</general><general>Lavoisier</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20180403</creationdate><title>Optimal Empirical-Markovian approach for assessment of potential pavement rehabilitation strategies at the project level</title><author>Abaza, Khaled A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c366t-758f66ed4af2eb1b67e06965162d975db2fa0fc73df85420412269de660f8223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Construction costs</topic><topic>Cost analysis</topic><topic>Cycle ratio</topic><topic>Empirical analysis</topic><topic>flexible pavement</topic><topic>heterogeneous Markov chains</topic><topic>Life cycle costs</topic><topic>Maintenance costs</topic><topic>Markov processes</topic><topic>Mathematical models</topic><topic>pavement design</topic><topic>pavement management</topic><topic>pavement performance</topic><topic>pavement rehabilitation</topic><topic>Rehabilitation</topic><topic>Strategy</topic><topic>Traffic capacity</topic><topic>Transition probabilities</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Abaza, Khaled A.</creatorcontrib><collection>CrossRef</collection><jtitle>Road materials and pavement design</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Abaza, Khaled A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal Empirical-Markovian approach for assessment of potential pavement rehabilitation strategies at the project level</atitle><jtitle>Road materials and pavement design</jtitle><date>2018-04-03</date><risdate>2018</risdate><volume>19</volume><issue>3</issue><spage>646</spage><epage>667</epage><pages>646-667</pages><issn>1468-0629</issn><eissn>2164-7402</eissn><abstract>An optimal Empirical-Markovian approach is presented for the assessment of potential rehabilitation strategies as applied to flexible pavement at the project level. A simplified empirical model is proposed to predict the heterogeneous transition probabilities associated with rehabilitated pavement based on the corresponding values associated with original pavement, future traffic loading, and modified structural capacity. Therefore, the performance of rehabilitated pavement can directly be controlled by the modified structural capacity. The modified structural capacity associated with a particular rehabilitation strategy is defined using the modified layer coefficients with the corresponding modified structural numbers are used in the empirical model to predict the relevant heterogeneous transition probabilities. These probabilities are then used to estimate the annual distress ratings (DRs) associated with each potential rehabilitation strategy for a specified analysis period. The optimal assessment of potential rehabilitation strategies is carried out using the cost-effectiveness ratio defined as the ratio of the life-cycle average DR to the life-cycle cost. The life-cycle cost can include cost items such as initial construction cost, routine maintenance cost, and major rehabilitation cost. The optimal rehabilitation strategy is the one associated with the highest cost-effectiveness ratio. The presented case study has indicated the effectiveness of the proposed optimal approach in developing and yielding dependable optimal rehabilitation strategies.</abstract><cop>Abingdon</cop><pub>Taylor & Francis</pub><doi>10.1080/14680629.2016.1267661</doi><tpages>22</tpages></addata></record> |
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subjects | Construction costs Cost analysis Cycle ratio Empirical analysis flexible pavement heterogeneous Markov chains Life cycle costs Maintenance costs Markov processes Mathematical models pavement design pavement management pavement performance pavement rehabilitation Rehabilitation Strategy Traffic capacity Transition probabilities |
title | Optimal Empirical-Markovian approach for assessment of potential pavement rehabilitation strategies at the project level |
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