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Laboratory Simulation of RAP Incorporated Mix in a Cold Region: An Artificial Intelligence-Based Approach

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Abstract

The use of reclaimed asphalt pavement (RAP) in road construction is expected to lead to a sustainable asphalt pavement system by reducing the environmental footprint as well as the cost in construction materials. However, the use of RAP in road construction results in a stiffer pavement and could cause the need for early rehabilitation than the traditional road management cycle. In this regard, a novel laboratory aging method is proposed where the new protocol, unlike the traditional simulation method, simulates the expected rehabilitation period. Here, different desired mixtures are aged five hours at 135 °C in the laboratory, while the corresponding mixtures are aged naturally and evaluated periodically for 30 months. The Bending Beam Rheometer (BBR) was used to evaluate the stiffness characteristics of the mixtures. Finally, the evaluation is carried out using an Artificial Intelligence-based approach, namely regression tree, by observing the minute details of stiffness and relaxation capacity instead of the traditional index value. It is observed that the samples aged in the laboratory for five hours at 135 °C simulate 2 years of field aging. The proposed accelerated laboratory procedure is expected to be a comparatively practical simulation procedure for RAP-incorporated mixture to achieve a two-year real-field aging condition for a cold region.

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Data Availability

Data are available from the corresponding author upon request.

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Acknowledgements

The authors express their sincere gratitude to the UDOT and United States Department of Transportation (USDOT) through the Mountain-Plains Consortium (MPC) for providing funds for this study (UDOT Contract: 16-8427).). The authors are also thankful to the Department of Civil and Environmental Engineering at the University of Utah.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, The University of Utah, 110 Central Campus Drive, Salt Lake City, UT, 84112, USA

    Abdullah Al Mamun, Pedro Romero & Abu Sufian Mohammad Asib

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  1. Abdullah Al Mamun
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Correspondence to Abdullah Al Mamun.

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Al Mamun, A., Romero, P. & Asib, A.S.M. Laboratory Simulation of RAP Incorporated Mix in a Cold Region: An Artificial Intelligence-Based Approach. Int. J. Pavement Res. Technol. (2023). https://doi.org/10.1007/s42947-023-00346-3

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