Deshpande, Vighnesh Prakash (2008-08). Accounting for the effects of rehabilitation actions on the reliability of flexible pavements: performance modeling and optimization. Master's Thesis. Thesis uri icon

abstract

  • A performance model and a reliability-based optimization model for flexible pavements that accounts for the effects of rehabilitation actions are developed. The developed performance model can be effectively implemented in all the applications that require the reliability (performance) of pavements, before and after the rehabilitation actions. The response surface methodology in conjunction with Monte Carlo simulation is used to evaluate pavement fragilities. To provide more flexibility, the parametric regression model that expresses fragilities in terms of decision variables is developed. Developed fragilities are used as performance measures in a reliability-based optimization model. Three decision policies for rehabilitation actions are formulated and evaluated using a genetic algorithm. The multi-objective genetic algorithm is used for obtaining optimal trade-off between performance and cost. To illustrate the developed model, a numerical study is presented. The developed performance model describes well the behavior of flexible pavement before as well as after rehabilitation actions. The sensitivity measures suggest that the reliability of flexible pavements before and after rehabilitation actions can effectively be improved by providing an asphalt layer as thick as possible in the initial design and improving the subgrade stiffness. The importance measures suggest that the asphalt layer modulus at the time of rehabilitation actions represent the principal uncertainty for the performance after rehabilitation actions. Statistical validation of the developed response model shows that the response surface methodology can be efficiently used to describe pavement responses. The results for parametric regression model indicate that the developed regression models are able to express the fragilities in terms of decision variables. Numerical illustration for optimization shows that the cost minimization and reliability maximization formulations can be efficiently used in determining optimal rehabilitation policies. Pareto optimal solutions obtained from multi-objective genetic algorithm can be used to obtain trade-off between cost and performance and avoid possible conflict between two decision policies.
  • A performance model and a reliability-based optimization model for flexible pavements
    that accounts for the effects of rehabilitation actions are developed. The developed
    performance model can be effectively implemented in all the applications that require
    the reliability (performance) of pavements, before and after the rehabilitation actions.
    The response surface methodology in conjunction with Monte Carlo simulation is used
    to evaluate pavement fragilities. To provide more flexibility, the parametric regression
    model that expresses fragilities in terms of decision variables is developed. Developed
    fragilities are used as performance measures in a reliability-based optimization model.
    Three decision policies for rehabilitation actions are formulated and evaluated using a
    genetic algorithm. The multi-objective genetic algorithm is used for obtaining optimal
    trade-off between performance and cost.
    To illustrate the developed model, a numerical study is presented. The developed
    performance model describes well the behavior of flexible pavement before as well as
    after rehabilitation actions. The sensitivity measures suggest that the reliability of
    flexible pavements before and after rehabilitation actions can effectively be improved by providing an asphalt layer as thick as possible in the initial design and improving the
    subgrade stiffness. The importance measures suggest that the asphalt layer modulus at
    the time of rehabilitation actions represent the principal uncertainty for the performance
    after rehabilitation actions. Statistical validation of the developed response model shows
    that the response surface methodology can be efficiently used to describe pavement
    responses. The results for parametric regression model indicate that the developed
    regression models are able to express the fragilities in terms of decision variables.
    Numerical illustration for optimization shows that the cost minimization and reliability
    maximization formulations can be efficiently used in determining optimal rehabilitation
    policies. Pareto optimal solutions obtained from multi-objective genetic algorithm can be
    used to obtain trade-off between cost and performance and avoid possible conflict
    between two decision policies.

publication date

  • August 2008