Date of Graduation

12-2020

Document Type

Thesis

Degree Name

Bachelor of Science in Civil Engineering

Degree Level

Undergraduate

Department

Civil Engineering

Advisor/Mentor

Braham, Andrew F.

Committee Member/Reader

Hernandez, Sarah

Committee Member/Second Reader

Heymsfield, Ernest

Committee Member/Third Reader

Murray, Cameron

Abstract

Gray scale image analysis is a powerful tool for testing asphalt concrete materials. From material composition to surface properties, gray scale analysis has shown evidence as a non-invasive way to obtain information from asphalt samples. Casillas et al. used a gray scale analysis to measure the Representative Volume Element of three asphalt sample geometries to understand the minimum size at which an asphalt sample is representative of a larger homogeneous mixture [1]. While the gray scale analysis used in this experiment yielded results, there were unknown factors in the image capturing process. Particularly, not much was known about the effect of varying the distance of asphalt samples from a camera or varying the sizes of asphalt samples on subsequent gray scale histograms. The purpose of this research was to quantify the effect of these two variables on a gray scale analysis and to understand the extent and significance of their impact. For each of the 12 samples analyzed and 34 histograms generated, it was discovered that for images that were captured closer to a camera, more pixels per intensity were captured for non-white intensities (#0 - #254). Secondly, it was discovered that sample geometry affected histograms when the area of images captured was not the same, meaning that the image capturing software generated histograms based on the image area captured rather than the sample geometry. Finally, over 75% of the pixels for this mix design fell between the range of intensities #30 - #160.

Keywords

Representative Volume Element (RVE); Nominal Maximum Aggregate Size (NMAS); Uniaxial; Indirect Tension (IDT); Torsion Bar; Dynamic Modulus Test

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