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dc.contributor.advisorProzzi, Jorge Alberto
dc.creatorZuniga Garcia, Natalia
dc.date.accessioned2017-06-30T22:12:48Z
dc.date.available2017-06-30T22:12:48Z
dc.date.issued2017-05
dc.date.submittedMay 2017
dc.identifierdoi:10.15781/T2VM4366C
dc.identifier.urihttp://hdl.handle.net/2152/47406
dc.description.abstractCurrent methodologies to measure road friction present several disadvantages that make them impractical for field data collection over large highway networks. Thus, it is important to study different ways to estimate surface friction characteristics based on other properties that are easier to measure. The main objective of this study was to analyze surface texture characteristics and to observe their influence on friction. A Line Laser Scanner (LLS) was implemented to make an improved characterization of the road texture which includes macro- and micro-texture description using different texture parameters. Field measurements of friction and texture were collected around Texas using different tests methods. The friction characterization tests included the British Pendulum test (BPT), the Dynamic Friction test (DFT), and the Micro GripTester. Thirty-six different pavement sections were evaluated, including different surface types such as hot-mix asphalt (HMA), surface treatment, and concrete sidewalk. Among the principal conclusions, it was found that there is not a unique relationship between texture and friction. The relationship between texture and friction is strong but it is different for each type of surface, thus, cross-sectional analysis cannot be utilized to quantify the relationship. Additionally, the prediction of friction measures obtained using the BPT and the DFT significantly improved when including information of both macro- and micro-texture into the prediction model. Therefore, a measure of micro-texture should be included into friction models based on texture. Finally, among the study of different texture parameters, the mean profile depth (MPD) was the most significant parameter for macro- and for micro-texture to explain the distinct friction measures.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectFriction
dc.subjectSkid resistance
dc.subjectMacro-texture
dc.subjectMicro-texture
dc.subjectLaser scanner
dc.subjectRoad pavements
dc.subjectMean profile depth
dc.subjectSignal processing
dc.titlePredicting friction with improved texture characterization
dc.typeThesis
dc.date.updated2017-06-30T22:12:48Z
dc.description.departmentCivil, Architectural, and Environmental Engineering
thesis.degree.departmentCivil, Architectural, and Environmental Engineering
thesis.degree.disciplineCivil Engineering
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelMasters
thesis.degree.nameMaster of Science in Engineering
dc.creator.orcid0000-0002-1538-3599
dc.type.materialtext


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