Development of Pavement Performance and Remaining Service Life Prediction Tools for Iowa Jointed Plain Concrete Pavement Systems

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dc.authoridKAYA, ORHAN/0000-0001-6072-3882
dc.authoridCitir, Nazik/0000-0001-5163-7421
dc.contributor.authorKaya, Orhan
dc.contributor.authorCitir, Nazik
dc.contributor.authorCeylan, Halil
dc.contributor.authorKim, Sunghwan
dc.contributor.authorWaid, Danny R.
dc.date.accessioned2025-01-06T17:44:09Z
dc.date.available2025-01-06T17:44:09Z
dc.date.issued2023
dc.description.abstractMoving Ahead for Progress in the Twenty-First Century (MAP-21) requires US state highway agencies (SHA) to utilize performance-based approaches in their pavement management decision-making processes, and use of a remaining service life (RSL) model would be one of such performance-based approaches for facilitating the pavement management decision-making process for SHAs. In this study, statistical and artificial neural network (ANN)-based pavement performance and RSL models were developed for Iowa jointed plain concrete pavement systems (JPCP) using actual pavement structural, traffic, construction history, and pavement performance records obtained from the Iowa Department of Transportation pavement-management information system database. While both models were found to be potentially useful for project and network level performance and RSL predictions, statistical and ANN-based models were respectively found to be more suitable for project and network level analysis. Using these models, efficient Microsoft Excel-based automation tools were created to predict future performance of a JPCP section and estimate RSL values based on predicted future performance and threshold limits for the performance indicators. Consequence analysis was also conducted to investigate the impact of traffic and preservation treatment (diamond grinding) on the RSL of a JPCP. The tool, also capable of estimating realistic pavement pretreatment and posttreatment performance and RSL, could be successfully used as part of performance-based pavement management strategies and helping decision-makers make better-informed pavement management decisions to properly allocate agency resource expenditures. Moreover, this study provides a better understanding of RSL and the factors that influence both the project and network level RSL.
dc.description.sponsorshipIowa Highway Research Board; Iowa County Engineers Service Bureau; Iowa Highway Research Board (IHRB) [TR-740]
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 members from the 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 study. 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. The authors would like to express their sincere gratitude to Mark Murphy from the Iowa Department Office of Analytics for his full support during data collection and processing models and tools. The authors would also like to sincerely thank other research team members from Iowa State University's Program for Sustainable Pavement Engineering and Research (PROSPER) at InTrans for their assistance. The contents of this paper reflect the views of the authors who are responsible for the facts and accuracy of the data presented within. The contents do not necessarily reflect the official views and policies of the Iowa Highway Research Board, the Iowa Department of Transportation, or Iowa State University. This paper does not constitute a standard, specification, or regulation. This study was funded by the Iowa Highway Research Board (IHRB) through research project TR-740, Development of Iowa Pavement Analysis Technique (IPAT).
dc.identifier.doi10.1061/JPEODX.PVENG-1160
dc.identifier.issn2573-5438
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85145185578
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1061/JPEODX.PVENG-1160
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2955
dc.identifier.volume149
dc.identifier.wosWOS:000914663800019
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherAsce-Amer Soc Civil Engineers
dc.relation.ispartofJournal of Transportation Engineering Part B-Pavements
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectRemaining service life (RSL)
dc.subjectJointed plain concrete pavements (JPCP)
dc.subjectPavement performance models
dc.titleDevelopment of Pavement Performance and Remaining Service Life Prediction Tools for Iowa Jointed Plain Concrete Pavement Systems
dc.typeArticle

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