Journal
ROAD MATERIALS AND PAVEMENT DESIGN
Volume 19, Issue 1, Pages 139-153Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/14680629.2016.1250665
Keywords
pavements; subgrade soils; resilient modulus; estimation; linear genetic programming
Ask authors/readers for more resources
The success of a flexible pavement design depends on the accuracy of determining the structural response of the pavement to dynamic loads, known as resilient modulus (M-R). This paper explores the potential of a branch of the computational intelligence techniques, namely linear genetic programming (LGP), for indirect estimation of the M-R of pavements subgrade soils. Furthermore, a pre-design model is proposed which characterises M-R factor in terms of subgrade soil properties and applied stress states utilising a selected database which comprises of several test results conducted on cohesive Ohio A-6 soils. In order to assess the degree of accuracy and reliability of the obtained model, various statistical criteria and verification study phases are conducted. Finally, better results of the obtained model in comparison with traditional models prove the robustness and capability of LGP approach for indirect estimation of M-R of pavement subgrade soils.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available