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dc.contributor.advisorStokoe, Kenneth H.en
dc.creatorNam, Boo Hyunen
dc.date.accessioned2012-12-17T18:52:35Zen
dc.date.available2012-12-17T18:52:35Zen
dc.date.issued2010-12en
dc.date.submittedDecember 2010en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2010-12-2538en
dc.descriptiontexten
dc.description.abstractA Rolling Dynamic Deflectometer (RDD) is a nondestructive testing device for determining continuous deflection profiles of pavements. Unlike discrete testing methods, the RDD performs continuous measurements. The ability to perform continuous measurements makes the RDD a powerful screening/evaluation tool for quickly characterizing large sections of pavement, with little danger of missing critical pavement features. RDD testing applications have involved pavement forensic investigations, delineations of areas to be repaired, selection of rehabilitation treatments, measurements of relative improvements due to the rehabilitation, and monitoring of changes with time (trafficking and environmental loading). However, the speed of RDD testing with the current rolling sensors is between 1 and 2 mph (1.6 to 3.2 km/hr). Improvements in testing speed and data analysis procedures would increase its usefulness in project-level studies as well as permit its used in some pavement network-level studies. A three-part study was carried out to further improve the RDD. The first part involved the development of speed-improved rolling sensors (referred as the third-generation rolling sensor). Key benefits of this new rolling sensor are: (1) increased testing speed up to 5 mph (8.0 km/hr), and (2) reduced level of rolling noise during RDD measurements. With this rolling sensor, the RDD can collect more deflection measurements at a speed of 3 to 5 mph (4.8 to 8.0 km/hr). Field trials using the first- and third-generation rolling sensors on both flexible and rigid pavements were performed to evaluate the performance of the third-generation rolling sensor. The second part of this study involved enhancements to the RDD data analysis procedure. An alternative data analysis method was developed for the third-generation rolling sensor. This new analysis method produces results at higher speeds that are comparable to the existing analysis method used for testing at 1 to 2 mph (1.6 to 3.2 km/hr). Key benefits of this analysis method that were not previously available are: (1) distance-based deflection profiles (report RDD deflections based on a selected distance interval), (2) improved-spatial resolution without sacrificing the filtering performance, and (3) analysis of the rolling noise characteristics and signal-to-noise and distortion ratios better characterize the deflection profiles and their accuracy. The third part of this study involved investigating the effects of parameters affecting RDD deflection measurements which include: (1) force level and operating frequency, (2) in-situ sensor calibration, (3) load-displacement curve, and (4) pavement temperature variations. These parameters need to be considered in testing and data analysis procedures of the RDD because small errors from these parameters can adversely influence calculations of the RDD deflections. Criteria are presented for selecting the best operating parameters for testing.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.subjectRolling Dynamic Deflectometeren
dc.subjectRolling sensoren
dc.subjectData analysis procedureen
dc.titleImproved testing and data analysis procedures for the Rolling Dynamic Deflectometeren
dc.date.updated2012-12-17T18:53:00Zen
dc.identifier.slug2152/ETD-UT-2010-12-2538en
dc.contributor.committeeMemberKallivokas, Loukasen
dc.contributor.committeeMemberProzzi, Jorgeen
dc.contributor.committeeMemberWilson, Clark R.en
dc.contributor.committeeMemberMurphy, Mikeen
dc.description.departmentCivil, Architectural, and Environmental Engineeringen
dc.type.genrethesisen
thesis.degree.departmentCivil, Architectural, and Environmental Engineeringen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen


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