Velocity-induced post-elastic flow response of pavement: A finite element-based statistical investigation
Author Identifier (ORCID)
Sanjay Kumar Shukla: https://orcid.org/0000-0002-4685-5560
Abstract
In the present study, the implicit integration scheme using the Distributed LOAD (DLOAD) subroutine has been adopted in a finite element numerical model to forecast the behavior of pavement subjected to moving load. Statistical computation using the F-test, T-test, and chi-square methods was performed to forecast the displacement behavior of pavement. The results obtained using the finite element program show a non-monotonic increase in the post-elastic domain. Considering the vulnerability of pavement failure, the peak displacement values have been selected to obtain the Prob > F, Prob > |t|, dependency, and convergence for reproducibility using the novel empirical equation proposed in this work. The results were found in the 95% confidence and 95% prediction band for the set of selected velocities considered in this study. On a scale of 0 to 1, the dependency of statistical parameters was found in the range of 0.95 to 1, neglecting the one case where the dependence was 0.8. This issue was resolved by reduced chi-square and adjusted R-square with convergence of the data from 80 to 97.6%. Hence, it can be stated that the novel statistical computation model presented in this research work has the potential to predict the post-elastic response of the pavement-soil system and its uses in the design of pavements.
Document Type
Conference Proceeding
Date of Publication
1-1-2025
Volume
673 LNCE
Publication Title
Lecture Notes in Civil Engineering
Publisher
Springer
School
School of Engineering
Copyright
subscription content
First Page
69
Last Page
83
Comments
Kumar, Y., Trivedi, A., & Shukla, S. K. (2024). Velocity-induced post-elastic flow response of pavement: A finite element-based statistical investigation. In International Conference on Sustainable Infrastructure: Innovation, Opportunities and Challenges (pp. 69-83). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-96-8448-9_5