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    Microtexture Characterization of Bulk-Aggregate Samples for Application in High-Friction Surface Treatments

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    JMCEE7.MTENG-18766.pdf (4.448Mb)
    Date
    2025
    Author
    Kyle Maeger
    Adam Biehl
    Prasad Rangaraju
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    Abstract
    High-friction surface treatments can improve roadway safety by increasing the pavement friction. Macrotexture and microtexture are primary contributors to pavement friction. Macrotexture has established protocols for measurement, but no standardized methodologies exist for direct microtexture measurement. Additionally, there is a need for standard laboratory methods for assessment of aggregate microtexture for friction applications. This study developed and assessed a novel laboratory test to directly measure the microtexture of bulk aggregate samples using high-resolution laser scanning. Five abrasion resistant aggregates were evaluated at various gradations. Laser profiles were filtered to isolate microtexture band wavelengths. Spatial (micro-MPD, micro-RMS, micro-Ra), statistical (micro-Rsk, micro-Rku), and frequency domain [Log(power spectral density slope and intercept)] parameters were evaluated for repeatability and ability to distinguish among aggregates at various gradations. The effects of Los Angeles abrasion (LAA) and microdeval (MD) abrasion on the microtexture were also assessed. Acceptably repeatable microtexture measures were produced by the test method. ANOVA showed a significant effect of gradation on microtexture parameters. The laboratory methods were able to adequately predict texture on high friction surface treatment (HFST) samples made from the same aggregate at equivalent gradation under particular conditions. MD resulted in a decrease in microtexture depth, while LAA had no statistically significant effect. Similarly, MD led to a decrease in British pendulum test friction for all aggregates while the LAA produced mixed results indicating the advantages of MD over LAA in simulating friction and texture loss due to traffic abrasion. Once calibrated, regression models of the microtexture parameters showed acceptable modeling coefficients with a logarithmic fit of micro-MPD providing the highest R2 of 0.81. In comparison with macrotexture parameters from the same profiles, microtexture was a superior predictor of friction. The laboratory method developed can augment currently relied upon aggregate quality measures such as abrasion resistance to aid in the selection of suitable HFST aggregates.
    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4309766
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