New Technology Automates Aggregate Analysis
The number of flat and elongated particles, for example, characterizes coarse aggregate shape. The angularity of gravel is determined by counting the number of particles with one or two crushed faces. Measuring the void percentage of an aggregate sample as it flows through a funnel assesses fine aggregate angularity.
A “National Cooperative Highway Research Program” study, described in Test Methods for Characterizing Aggregate Shape, Texture, and Angularity (NCHRP Report 555), evaluated emerging test methods for measuring aggregate characteristics. The analysis looked at factors such as accuracy, cost, ease of use, and readiness for implementation.
The study recommended Pine Instrument’s aggregate imaging system, or AIMS, for its ability to characterize both fine and coarse aggregates and its ease of use in central and field laboratories. The AIMS research prototype was developed in collaboration with NCHRP’s IDEA (Innovations Deserving Exploratory Analysis) program and the FHWA.
“AIMS allows the comparison of aggregates with a scientifically based system,” Meininger says. “It measures aggregates in a non-biased way.”
Researchers tested an AIMS prototype at the Texas Department of Transportation using FHWA’s mobile asphalt materials testing laboratory. The mobile lab demonstrated how AIMS can be used to classify aggregate stockpiles for form, angularity, and texture and its potential to replace aggregate consensus property test procedures for Superpave asphalt mix design with an automated, repeatable method that provides similar data, says Matthew Corrigan, mobile lab project manager.
The mobile lab has an ongoing project to collect AIMS data on a variety of aggregate sources used in asphalt pavements throughout the United States, Corrigan explains. Future plans call for linking AIMS aggregate data with asphalt pavement performance in the field and recommending which aggregate properties are the best indicators for long-life asphalt pavements.
The AIMS system works by capturing digital images of the particles in an aggregate sample, analyzing the sample, and providing a graphical output of characteristics. The system’s software uses a series of analysis algorithms that objectively quantify aggregate properties on both the macro scale, such as shape and angularity, and the micro scale, such as surface texture.
The system uses computer digital images to measure the shape and angularity of individual particles from their silhouette outline and focal depth, and the texture of coarse aggregates from the gray-scale images of aggregate surfaces. The system’s software allows characterization of the distribution of shape and angularity for correlation with performance in pavement layers.
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