Advanced Approaches to Characterizing Nonlinear Pavement System Responses

dc.contributor.author Ceylan, Halil
dc.contributor.author Gopalakrishnan, Kasthurirangan
dc.contributor.author Ceylan, Halil
dc.contributor.author Guclu, Alper
dc.contributor.department Civil, Construction and Environmental Engineering
dc.date 2018-02-14T17:30:33.000
dc.date.accessioned 2020-06-30T01:12:45Z
dc.date.available 2020-06-30T01:12:45Z
dc.date.copyright Mon Jan 01 00:00:00 UTC 2007
dc.date.embargo 2014-09-23
dc.date.issued 2007-12-01
dc.description.abstract <p>The use of falling weight deflectometer—based backcalculation techniques to determine pavement layer moduli is a cost-effective and widely used method for the structural evaluation of an existing pavement. The nonlinear stress-sensitive response of pavement geomaterials has been well established, and mechanistic-based pavement design can be improved by inclusion of these nonlinear material properties. To further the science of nonlinear backcalculation, the TRB Strength and Deformation Characteristics of Pavement Sections Committee has assembled four data sets that can be used to demonstrate the ability to derive stress-dependent moduli for pavement layers. In this study, validated artificial neural network (ANN)—based backcalculation-type flexible pavement analysis models were used to evaluate the TRB Nonlinear Pavement Analysis Project data sets. The Illi-Pave finite element (FE) model, considering nonlinear stress-dependent geomaterials characterization, was utilized to generate a solution database for developing the ANN-based structural models. Such use of ANN models enables the incorporation of needed sophistication in structural analysis, such as FE modeling with proper materials characterization, into routine practical design. This study illustrated the complexities associated with interpreting the backcalculated modulus values. In general, the predicted strains agreed reasonably well with the measured strain values, whereas the predicted stresses did not.</p>
dc.description.comments <p>This article is from <em>Transportation Research Record: Journal of the Transportation Research Board</em> 2005 (2007): 86-94, doi: <a href="http://dx.doi.org/10.3141/2005-10" target="_blank">10.3141/2005-10</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/ccee_pubs/20/
dc.identifier.articleid 1019
dc.identifier.contextkey 6153758
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath ccee_pubs/20
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/13848
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/ccee_pubs/20/2007_CeylanH_AdvancedApproachesCharacterizing.pdf|||Fri Jan 14 22:16:49 UTC 2022
dc.source.uri 10.3141/2005-10
dc.subject.disciplines Civil and Environmental Engineering
dc.subject.disciplines Construction Engineering and Management
dc.subject.keywords CNDE
dc.title Advanced Approaches to Characterizing Nonlinear Pavement System Responses
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 3cb73d77-de43-4880-939a-063f9cc6bdff
relation.isOrgUnitOfPublication 933e9c94-323c-4da9-9e8e-861692825f91
File
Original bundle
Now showing 1 - 1 of 1
Name:
2007_CeylanH_AdvancedApproachesCharacterizing.pdf
Size:
347.3 KB
Format:
Adobe Portable Document Format
Description:
Collections