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dc.creatorWang, Kelvin
dc.creatorCross, Stephen
dc.creatorLi, Joshua
dc.date.accessioned2018-03-01T20:50:08Z
dc.date.available2018-03-01T20:50:08Z
dc.date.issued2013-12
dc.identifier.govdocFHWA-OK-13-10
dc.identifier.otherOklahoma Department of Transportation State Planning and Research item number 2235
dc.identifier.urihttps://hdl.handle.net/11244/54450
dc.description.abstractDistress prediction models, or transfer functions, are key components of the Pavement M-E Design and relevant analysis. The accuracy of such models depends on a successful process of calibration and subsequent validation of model coefficients in the transfer functions with independent data sets. In this project, data needs for distress models in Pavement ME Design are investigated for the state of Oklahoma. Based on past research work at Oklahoma Department of Transportation (ODOT), various Pavement ME Design inputs, historical cracking, rutting, and roughness data are gathered for selected ODOT segments and Long Term Pavement Performance (LTPP) sites. Pavement ME Design test runs are performed, and precision and bias levels of rutting, cracking, and roughness data sets in the historical ODOT databases are studied. Finally a workflow for Pavement ME Design prediction model calibration in Oklahoma is established to assist ODOT in implementing Pavement ME in the next decade in a production environment.
dc.format.extent116 pages
dc.format.extent4,211,692 bytes
dc.format.mediumapplication.pdf
dc.languageen_US
dc.relation.ispartofseriesNo
dc.relation.requiresAdobe Acrobat Reader
dc.relation.urihttps://rosap.ntl.bts.gov/view/dot/31444/dot_31444_DS1.pdf
dc.titleDISTRESS MODELING FOR DARWIN-ME (FHWA-OK-13-10 2235)
dc.typeTechnical Report
dc.description.versionFinal Report, October 2011-September 2013
dc.description.peerreviewNo
dc.type.materialtext
dc.subject.keywordsPavement ME design
dc.subject.keywordsdistress modeling
dc.contributor.sponsorOklahoma Department of Transportation. Materials and Research Division. Office of Research & Implementation


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