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Estimating unconfined compressive behavior of HMA using soft computing

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Abstract

The mechanical properties of materials such as elastic tangential modulus (Et) and unconfined compressive strength (UCS) can be used to predict their performance during service life. This paper utilizes gene expression programming (GEP) as an alternative method to estimate the unconfined uniaxial compression properties of hot mix asphalt. Short-term static compression was used to evaluate modes of failure and stress–strain relationship of cylindrical and prismatic asphalt concrete specimens due to mixture types, specimen shape, height, temperature, binder type and testing orientation. The results show that cubic specimens tested parallel to the direction of compaction achieved higher compressive strength and peak strains than specimens tested to the perpendicular direction. Cylindrical specimens had greater elastic stiffness than prismatic specimens with similar aspect ratios. The GEP and multiple linear regression approaches for the assessment of UCS and Et concluded satisfactory outcomes. The coefficient of determination (R2) for USC-GEP was 0.887 and 0.908 and similarly Et-GEP of 0.785 and 0.648 was more significant than regression models. The models developed provide a cheap, simple and quick methodology of estimating the stress–strain properties of dense-graded asphalt concrete by eliminating the need for the compression test.

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Acknowledgement

The authors wish to thank the personnel in the Highway/Transportation laboratory of the Department of Civil and Environmental Engineering at the University of the West Indies for their assistance in executing the laboratory work and data collection for this manuscript.

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  1. Department of Civil and Environmental Engineering, University of the West Indies (UWI), Saint Augustine, Trinidad and Tobago

    Lee P. Leon & Indrajit Ray

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  1. Lee P. Leon
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  2. Indrajit Ray
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Correspondence to Lee P. Leon.

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Leon, L.P., Ray, I. Estimating unconfined compressive behavior of HMA using soft computing. Innov. Infrastruct. Solut. 6, 19 (2021). https://doi.org/10.1007/s41062-020-00386-9

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