Incorporating the Effectiveness of Preservation and Rehabilitation Techniques on Flexible Pavement Service Life Predictions Using Machine Learning Approach

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dc.authoridKAYA, ORHAN/0000-0001-6072-3882
dc.contributor.authorCitir, Nazik
dc.contributor.authorCeylan, Halil
dc.contributor.authorKim, Sunghwan
dc.contributor.authorKaya, Orhan
dc.date.accessioned2025-01-06T17:45:12Z
dc.date.available2025-01-06T17:45:12Z
dc.date.issued2021
dc.descriptionInternational Airfield and Highway Pavements Conference of the Transportation-and-Development-Institute (T and DI) of the American-Society-of-Civil-Engineers (ASCE) -- JUN 08-10, 2021 -- ELECTR NETWORK
dc.description.abstractA flexible pavement network may be exposed to traffic changes over time because of detours that may cause unusually high traffic loading on some parts of the pavement sections. Such sections, therefore, need to be preserved earlier than their expected service life. This study focuses on incorporating the effectiveness of preservation and rehabilitation techniques, e.g., functional thin overlay and structural asphalt overlay on flexible pavement service life predictions using a machine learning approach. The developed models are capable of estimating the current and future international roughness index (IRI) and of detecting performance recovery after application of preservation treatment, thereby forecasting the remaining service life. The traffic, pavement structural, and performance data were obtained from the pavement management information system (PMIS) of the Iowa Department of Transportation (DOT). This study describes realistic what-if scenarios considering various treatment techniques to provide a better understanding of the effectiveness of treatments on extending flexible pavement service life. Such outcomes will help facilitate better pavement preservation management strategies.
dc.description.sponsorshipAmer Soc Civil Engineers,Amer Soc Civil Engineers, Transportat & Dev Inst
dc.description.sponsorshipIowa Highway Research Board; Iowa County Engineers Service Bureau
dc.description.sponsorshipThe authors would like to thank the Iowa Highway Research Board and Iowa County Engineers Service Bureau for supporting this study. The authors also gratefully acknowledge the project technical advisory committee (TAC) members from Iowa County Engineers Association (ICEA), including Lee Bjerke, Zach Gunsolley, Todd Kinney, Mark Nahra, John Riherd, Brad Skinner, and Jacob Thorius for their guidance, support, and direction throughout the research. Special thanks are extended to Steve De Vries and Danny Waid, who developed the original concept of this study. The authors also sincerely acknowledge Brian P. Moore of ICEA for his guidance, support, and direction throughout the research.
dc.identifier.endpage377
dc.identifier.isbn978-0-7844-8351-0
dc.identifier.startpage365
dc.identifier.urihttps://hdl.handle.net/20.500.14669/3354
dc.identifier.wosWOS:000692658500033
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherAmer Soc Civil Engineers
dc.relation.ispartofAirfield and Highway Pavements 2021: Pavement Materials and Sustainability
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.titleIncorporating the Effectiveness of Preservation and Rehabilitation Techniques on Flexible Pavement Service Life Predictions Using Machine Learning Approach
dc.typeConference Object

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