الفهرس | Only 14 pages are availabe for public view |
Abstract The Highway construction acceptance procedure must be designed to encourage the control of Materials and Construction (M&C) variables that present most strongly long-term performance. Therefore, many highway agencies moved away from the oldest types of Specifications (Method-type and End-result specifications) to develop Performance-related Specifications (PRS). PRS consider the long–term performance and the Life Cycle Cost (LCC) of the pavement and relate them to the M&C variables. Reward or punishment assessed for the contractor is based on comparing LCC of as-constructed to as-designed pavements. To ensure the quality of the as-constructed pavement, the M&C variables can be optimized using optimization methods to select the optimum values for M&C variables to achieve optimum performance. The aim of this research is selecting the optimum values of M&C to maximize the pavement performance of as-constructed pavement. In this research, the finite element method represents the behavior of the pavement materials and evaluate the pavement response (horizontal tensile strain εt at the bottom of the asphalt layer and vertical compressive strains εc at the top of the subgrade soil) using the nonlinear elastic orthotropic axisymmetric finite element model with the help of Ansys. The anticipated performance of as-constructed pavement depends mainly on the M&C variables that the contractor used. A case study was developed to verify the optimization process. Genetic Algorithms method is selected as it can deal with multiple variables and can be applied to achieve any fitness function so the contractor can find the optimum solutions without performance loses. Also, a computer program structured into several subroutines and modules was developed to demonstrate the sensitive case study. V-model of verification and validation is applied to this computer program to investigate its capability of satisfying the required specification and standards. |