{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/84095"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/84095","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Data-Driven Railway Track Deterioration Modeling for Predictive Maintenance","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Ghofrani, Faeze; 0000-0002-8972-6072"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["He, Qing","Civil, Structural and Environmental Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-06-21T15:47:53Z","date_published":"2022-06-21T15:47:53Z","updated_at":"2026-07-27T19:05:30Z","subjects":["civil engineering","transportation"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/84095","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["He, Qing","Civil, Structural and Environmental Engineering"]},{"key":"dc:creator","label":"Author","values":["Ghofrani, Faeze; 0000-0002-8972-6072"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-06-21T15:47:53Z","2020"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["civil engineering","transportation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/84095"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","Railroad track is a very complex system that involves many interactions, and thus, generates many potential areas where a defect can occur. According to the existing literature, defects appearing on the rail track could be either of a geometry or structural type. Track structural defects (which is referred to as rail defects) indicate ill-conditioned structural parameters. Rail defects can grow in size through the regular rail operations and might lead to complete rail breakage when unnoticed. These events are known as service failures. As a practice of responsive track maintenance, when railroads notice a defect with size over the threshold value, they will take the rail segment out of service. However, due to the intrinsic features of a rail segment, as well the complex interactions between the factors related to the environment, traffic, infrastructure, etc. it is still probable for defects to appear later in the same location. Moreover, despite the effective inspection strategies developed by the railroad, service failures occur in rail track network because of the growth of an undetected defect or the defect that is initiated after an inspection...The main objective of this dissertation is to build and evaluate data-driven risk prediction models for occurrences of rail defects and service failures. The developed models will enlighten the effect of different factors affecting track failures. At the same time the provided analytical models can help railroads on predictive maintenance and capital planning decisions. The dissertation consists of five major components.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Data-Driven Railway Track Deterioration Modeling for Predictive Maintenance"]}]}],"canonical_facts":{"dc:contributor":["He, Qing","Civil, Structural and Environmental Engineering"],"dc:creator":["Ghofrani, Faeze; 0000-0002-8972-6072"],"dc:date":["2022-06-21T15:47:53Z","2020"],"dc:description":["Ph.D.","Railroad track is a very complex system that involves many interactions, and thus, generates many potential areas where a defect can occur. According to the existing literature, defects appearing on the rail track could be either of a geometry or structural type. Track structural defects (which is referred to as rail defects) indicate ill-conditioned structural parameters. Rail defects can grow in size through the regular rail operations and might lead to complete rail breakage when unnoticed. These events are known as service failures. As a practice of responsive track maintenance, when railroads notice a defect with size over the threshold value, they will take the rail segment out of service. However, due to the intrinsic features of a rail segment, as well the complex interactions between the factors related to the environment, traffic, infrastructure, etc. it is still probable for defects to appear later in the same location. Moreover, despite the effective inspection strategies developed by the railroad, service failures occur in rail track network because of the growth of an undetected defect or the defect that is initiated after an inspection...The main objective of this dissertation is to build and evaluate data-driven risk prediction models for occurrences of rail defects and service failures. The developed models will enlighten the effect of different factors affecting track failures. At the same time the provided analytical models can help railroads on predictive maintenance and capital planning decisions. The dissertation consists of five major components.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/84095"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["civil engineering","transportation"],"dc:title":["Data-Driven Railway Track Deterioration Modeling for Predictive Maintenance"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:30Z"}