{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-1897"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-1897","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"An analytic hierarchy process and Markov chain based approach for condition rating and dynamic service life prediction of retaining walls","abstract":"Retaining walls are typically considered auxiliary assets within the global transportation asset management scheme. However, failure cases to this structure class have attracted more attention to retaining wall assets. The possibility of failure also helps validate Moving Ahead for Progress in the 21st Century (MAP-21) requirements that transportation agencies develop asset management plans. Consequently, this thesis represents the development of a framework that combines the Analytic Hierarchy Process (AHP) and Markov Chain to rate and predict the future condition of retaining walls respectively. Based on the Field Survey of candidate retaining walls, the research uses AHP for hierarchical configuration and pair-wise comparison of retaining wall elements (and sub-elements) – to generate relative weights. This process of relative weighting ultimately lends towards individual wall condition rating scores. This score, together with transition probabilities derived from historical condition data forms the basis of the dynamic service life prediction using the Markov chain.","abstract_html":"Retaining walls are typically considered auxiliary assets within the global transportation asset management scheme. However, failure cases to this structure class have attracted more attention to retaining wall assets. The possibility of failure also helps validate Moving Ahead for Progress in the 21st Century (MAP-21) requirements that transportation agencies develop asset management plans. Consequently, this thesis represents the development of a framework that combines the Analytic Hierarchy Process (AHP) and Markov Chain to rate and predict the future condition of retaining walls respectively. Based on the Field Survey of candidate retaining walls, the research uses AHP for hierarchical configuration and pair-wise comparison of retaining wall elements (and sub-elements) – to generate relative weights. This process of relative weighting ultimately lends towards individual wall condition rating scores. This score, together with transition probabilities derived from historical condition data forms the basis of the dynamic service life prediction using the Markov chain.","abstract_has_math":false,"creators":["Lawal, Abdulazeez"],"institution":"University of Tennessee at Chattanooga","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Wu, Weidong","Owino, Joseph; Fomunung, Ignatius; Onyango, Mbakisya","College of Engineering and Computer Science"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-02-10T08:00:00Z","date_published":"2022-02-10T08:00:00Z","updated_at":"2026-07-24T05:47:06Z","subjects":["Asset-liability management","Mathematical models","Retaining walls"],"languages":["English","eng"],"rights":[],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://scholar.utc.edu/theses/731","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Wu, Weidong","Owino, Joseph; Fomunung, Ignatius; Onyango, Mbakisya","College of Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Lawal, Abdulazeez"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-08-01T07:00:00Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-02-10T08:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"]},{"key":"dc:relation","label":"Dc Relation","values":["Masters Theses and Doctoral Dissertations"]},{"key":"dc:type","label":"Dc Type","values":["Masters theses","Text"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Asset-liability management","Mathematical models","Retaining walls"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholar.utc.edu/theses/731"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Dept. of Civil and Chemical Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."]},{"key":"dc:description.abstract","label":"Abstract","values":["Retaining walls are typically considered auxiliary assets within the global transportation asset management scheme. However, failure cases to this structure class have attracted more attention to retaining wall assets. The possibility of failure also helps validate Moving Ahead for Progress in the 21st Century (MAP-21) requirements that transportation agencies develop asset management plans. Consequently, this thesis represents the development of a framework that combines the Analytic Hierarchy Process (AHP) and Markov Chain to rate and predict the future condition of retaining walls respectively. Based on the Field Survey of candidate retaining walls, the research uses AHP for hierarchical configuration and pair-wise comparison of retaining wall elements (and sub-elements) – to generate relative weights. This process of relative weighting ultimately lends towards individual wall condition rating scores. This score, together with transition probabilities derived from historical condition data forms the basis of the dynamic service life prediction using the Markov chain."]},{"key":"dc:title","label":"Title","values":["An analytic hierarchy process and Markov chain based approach for condition rating and dynamic service life prediction of retaining walls"]}]}],"canonical_facts":{"dc:contributor":["Wu, Weidong","Owino, Joseph; Fomunung, Ignatius; Onyango, Mbakisya","College of Engineering and Computer Science"],"dc:creator":["Lawal, Abdulazeez"],"dc:date":["2021-08-01T07:00:00Z"],"dc:date.available":["2022-02-10T08:00:00Z"],"dc:description":["Dept. of Civil and Chemical Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."],"dc:description.abstract":["Retaining walls are typically considered auxiliary assets within the global transportation asset management scheme. However, failure cases to this structure class have attracted more attention to retaining wall assets. The possibility of failure also helps validate Moving Ahead for Progress in the 21st Century (MAP-21) requirements that transportation agencies develop asset management plans. Consequently, this thesis represents the development of a framework that combines the Analytic Hierarchy Process (AHP) and Markov Chain to rate and predict the future condition of retaining walls respectively. Based on the Field Survey of candidate retaining walls, the research uses AHP for hierarchical configuration and pair-wise comparison of retaining wall elements (and sub-elements) – to generate relative weights. This process of relative weighting ultimately lends towards individual wall condition rating scores. This score, together with transition probabilities derived from historical condition data forms the basis of the dynamic service life prediction using the Markov chain."],"dc:identifier":["https://scholar.utc.edu/theses/731"],"dc:language":["English","eng"],"dc:publisher":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"],"dc:relation":["Masters Theses and Doctoral Dissertations"],"dc:rights":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Asset-liability management","Mathematical models","Retaining walls"],"dc:title":["An analytic hierarchy process and Markov chain based approach for condition rating and dynamic service life prediction of retaining walls"],"dc:type":["Masters theses","Text"]},"updated_at":"2026-07-24T05:47:06Z"}