PhD Defense by Cibi Pranav P.S.

Event Details
  • Date/Time:
    • Monday May 24, 2021
      1:00 pm - 3:00 pm
  • Location: Atlanta, GA
  • Phone:
  • URL: Bluejeans
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Summary Sentence: Characterization and Modeling Deterioration of High Friction Surface Treatment

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Ph.D. Thesis Defense Announcement

Characterization and Modeling Deterioration of High Friction Surface Treatment



Cibi Pranav P.S.



Dr. Yi-Chang (James) Tsai (CEE)


Committee Members:

Dr. Iris Tien (CEE), Dr. Yong K. Cho (CEE), Dr. Adjo A. Amekudzi-Kennedy (CEE), Dr. Ghassan AlRegib (ECE), Dr. Michael Heitzman (NCAT, Alabama)


Date & Time: May 24, 2021, 1 p.m. - 4 p.m. EST


High Friction Surface Treatment (HFST) is used to improve friction on curved roadways, especially on curves that have a high friction demand and history of roadway departure crashes; and it has generated a positive impact on highway safety. The significant concern is that HFST friction deteriorates significantly and rapidly at the end of service life due to loss of aggregates, creating unsafe driving conditions. The objectives of this research study are 1) to analyze the temporal and spatial friction deterioration performance at HFST sites, 2) to characterize aggregate loss using 2D image and 3D texture to correlate and predict friction, and 3) to develop a comprehensive framework and an implementation guide to systematically manage HFST friction throughout its life cycle activities.
In this research, the long-term friction performance and key factors affecting the friction deterioration (material, truck loading, roadway curve geometry, driving speed, spatial locations within the curve site) were analyzed based on 3-year friction data collected using Dynamic Friction Tester (DFT) on 30 Georgia Friction Improvement Surface Treatment (FIST) sites including calcined bauxite and phonolite aggregates. Results from Georgia FIST sites show calcined bauxite aggregates' friction performed very well while phonolite aggregates' friction dropped significantly (40%), and the curve radius and deviation angle have a strong impact on long-term friction deterioration.
To characterize aggregate loss, 2D images and surface texture were collected on HFST sections at National Center for Asphalt Technology (NCAT) Test Track. Friction tests were performed using the DFT (measured at 60 kph). The surface texture was measured by means of a Circular Texture Meter and a high-resolution 3D pavement scanning system (LS-40). Four key aggregate loss characteristics based on visual appearance and texture change were identified. Texture parameters related to the height, shape, and density of surface asperities were used to quantitatively characterize aggregate loss. Aggregate loss area acquired from 2D images and texture parameters acquired from 3D sensing system were correlated to friction. Results show strong correlation between the HFST friction coefficient and a) HFST aggregate loss percentage area and b) height-, shape- based macrotexture parameters. In addition, a friction prediction model was developed to predict friction using macro and micro texture parameters obtained from the 3D sensing system. The developed friction prediction model showed satisfactory R-squared (almost 0.8) when predicting HFST friction. This research opens new perspectives for the use of low-cost visual inspection, 2D imaging, and 3D laser scanning technologies to monitor HFST friction deterioration.
Finally, a comprehensive framework and roadmap is proposed based on a national survey, literature review, and research findings to enable transportation agencies to systematically manage HFST throughout its lifecycle activities safely and cost-effectively.  Using this comprehensive framework, an implementation guide including sampling and testing strategies, optimal monitoring frequencies, and trigger criteria to take maintenance actions is developed for GDOT to cost-effectively monitor and manage friction performance and safety of network-level FIST sites in Georgia. 

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Phd Defense
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Apr 1, 2021 - 1:59pm
  • Last Updated: Apr 12, 2021 - 11:47am