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dc.contributor.advisorMasad, Eyad
dc.creatorMcGahan, Jeremy
dc.date.accessioned2006-04-12T16:07:05Z
dc.date.available2006-04-12T16:07:05Z
dc.date.created2005-12
dc.date.issued2006-04-12
dc.identifier.urihttps://hdl.handle.net/1969.1/3351
dc.description.abstractThe physical characteristics of aggregates (form, angularity, and texture) are known to affect the performance of hot mix asphalt (HMA) pavements. Efforts to develop relationships between these aggregate characteristics and aggregate performance in HMA pavements have been limited in the past due to inherent inaccuracies in the methods used to measure these characteristics. The recently developed Aggregate Imaging System (AIMS) offers an opportunity to accurately measure aggregate shape characteristics allowing them to be properly related to asphalt performance. This research focused on relating the aggregate characteristics of form, angularity, and texture measured using AIMS to laboratory performance measurements on a wide variety of HMA mixes. The performance of these mixes was evaluated in three projects carried out by the Federal Highway Administration (FHWA) and the Texas Transportation Institute (TTI). During this research, a database of the volumetric, performance, and aggregate shape measurements for mixes used in these projects was created. Statistical analysis was conducted to correlate HMA performance parameters to volumetric and aggregate shape characteristics. The results show the dominant effect that aggregate shape properties have on HMA performance.en
dc.format.extent2991527 bytesen
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
dc.subjectnoneen
dc.titleThe development of correlations between HMA pavement performance and aggregate shape propertiesen
dc.typeBooken
dc.typeThesisen
thesis.degree.departmentCivil Engineeringen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberMartin, Amy
dc.contributor.committeeMemberSpiegelman, Cliff
dc.type.genreElectronic Thesisen
dc.type.materialtexten
dc.format.digitalOriginborn digitalen


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