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https://www.nationalacademies.org/trb/events

Advancing Pavement Design Inputs Through Improved R-Value Predictions

The objective of this research is to develop improved R-value prediction equations that enhance accuracy while remaining practical for Arizona Department of Transportation (ADOT) pavement design use. To achieve this objective, the project will: (1) Collect and compile available ADOT soil and R-value datasets from different Arizona regions, including measured R-values, soil classification, index properties, gradation data, project location, material source, and other routinely available laboratory or field information. (2) Perform regression and statistical analyses to evaluate the accuracy of the current ADOT R-value correlation and identify soil parameters that can improve prediction performance for Arizona materials. (3) Develop and validate enhanced R-value prediction equations using practical input parameters such as PI, percent passing the No. 200 sieve, gradation indices, USCS classification, and regional soil information where appropriate. (4) Provide implementation recommendations for ADOT, including recommended equations, input requirements, limitations, example calculations, and a simple calculation tool for use by Pavement Design and Geotechnical staff.