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Extracting More from Dynamic Modulus Data Using Split-Plot Repeated Measures Analysis

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Dynamic modulus testing and the development of master curves is an essential test used to characterize asphalt mixes. The dynamic modulus values are used in the mechanisitic-emprical pavement design guide… Click to show full abstract

Dynamic modulus testing and the development of master curves is an essential test used to characterize asphalt mixes. The dynamic modulus values are used in the mechanisitic-emprical pavement design guide that is being implemented by many state agencies. To compare dynamic modulus values, most researchers use master curves to analyze the values; however, the log-log scale of the master curve masks the differences between the mixes, requiring the use of an appropriate and reliable statistical data analysis approach to make accurate comparisons between mixes. In this paper, a full experimental plan is designed to investigate the effect of three different factors on the dynamic modulus, namely (1) type of mix: hot mix asphalt versus warm mix asphalt, (2) impact of reheating, and (3) moisture conditioning of specimens. An open-access statistical software package, “R,” is used for the analysis. The data showed that the type of mix and moisture conditioning were statistically significant factors. The statistical analyses presented in this paper begin with a simplified approach and then become increasingly comprehensive. The simplified approach considers a single temperature and frequency only. A more encompassing approach, with the aid of split-plot repeated measures (SPRM) analysis, is then performed in which each of the three factors is considered separately. This is followed by a full analysis on the entire data set that takes into account the interaction between all factors. The benefits of performing a full analysis in lieu of a simplified analysis are highlighted and a detailed interpretation of the results is given.

Keywords: dynamic modulus; split plot; analysis; plot repeated; approach; repeated measures

Journal Title: Journal of Testing and Evaluation
Year Published: 2017

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