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Scientific Papers

Evaluation of long-term performance of recycled aggregate base (RAB) layers and optimization of their design thicknesses

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Pages 1310-1329 | Received 13 Mar 2021, Accepted 26 Apr 2022, Published online: 10 May 2022
 

Abstract

To reduce the use of natural aggregates commonly used in base layers, constructing recycled aggregate base (RAB) layers has gained popularity. However, in the literature, there is limited information about the engineering properties of recycled concrete aggregate (RCA) materials with different gradations and the blends of RCA and recycled asphalt pavement (RAP) materials. There is also a lack of practice in using a mechanistic-empirical (ME) design method to optimize RAB layer thicknesses. In this study, several full-scale test cells were built with RAB and natural aggregate base layers, and the physical and engineering properties of the base layer aggregates were determined in the laboratory. For long-term performance evaluation of the cells built in the field, falling weight deflectometer (FWD) tests were performed, rutting measurements were taken, and soil temperature was monitored over a period of two years. An ME design procedure was used to optimize RAB layer thicknesses.

Acknowledgements

This study is a part of a project funded by the National Road Research Alliance (NRRA), a multi-state pooled fund. The authors would like to thank John Siekmeier, Dave Van Deusen, and Raul Velasquez of MnDOT for providing the field data. The authors would also like to thank Dr Soheil Nazarian and the Center for Transportation Infrastructure Systems at the University of Texas at El Paso (UTEP) for performing the resilient modulus (MR) and permanent deformation tests and sharing the data. The findings and opinions expressed in this study are solely those of the authors.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Declaration of interest statement

The authors declare no conflict of interest. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

This work was supported by National Road Research Alliance [grant number 1003320-2].

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