The present study aims to demonstrate the performance assessment of flexible pavement structure in probabilistic framework with due consideration of spatial variability modeling of input parameter.
The analysis incorporates mechanistic–empirical approach in which numerical analysis with spatial variability modeling of input parameters, Monte Carlo simulations (MCS) and First Order Reliability Method (FORM) are combined together for the reliability analysis of the flexible pavement. Random field concept along with Cholesky decomposition technique is used for the spatial variability modeling of the input parameter and implemented in commercially available finite difference code FLAC for the numerical analysis of pavement structure.
Results of the reliability analysis, with spatial variability modeling of input parameter, are compared with the corresponding results obtained without considering spatial variability of parameters. Analyzing a particular three-layered flexible pavement structure, it is demonstrated that spatial variability modeling of input parameter provides more realistic treatment to property variations in space and influences the response of the pavement structure, as well as its performance assessment.
Research is based on reliability analysis approach, which can also be used in decision-making for quality control and flexible pavement design in a given environment of uncertainty and extent of spatially varying input parameters in a space.
The authors thank Dr Sumanta Haldar, Associate Professor, IIT Bhubaneshwar, for providing them support and guidance on the development of FISH code in spatial variability modeling process using FLAC and Prof G.L. Sivakumar Babu, Professor, IISc Bangalore, for providing them with the facilities for using FLAC code.
Srivastava, A., Srivastava, D.K. and Misra, A.K. (2019), "Spatial variability modeling and reliability analysis of flexible pavement through mechanistic–empirical model", Journal of Engineering, Design and Technology, Vol. 17 No. 6, pp. 1129-1145. https://doi.org/10.1108/JEDT-02-2019-0038Download as .RIS
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