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Backcalculation of Pavement Moduli Using Genetic Algorithms

Alkasawneh, Wael Mohammad
http://rave.ohiolink.edu/etdc/view?acc_num=akron1176831189

Abstract Details

2007, Doctor of Philosophy, University of Akron, Civil Engineering.
The static elastic moduli of pavement layers can be considered to be among the most controversial physical properties in pavement engineering. In addition, pavement analysis using the static elastic moduli of the constituting layers is widely known and accepted by engineers and practitioners due to its simplicity. Nondestructive tests are commonly performed on existing pavements to measure the surface deflections, which in turn are used to backcalculate the elastic moduli of the pavement layers. However, the accuracy of the backcalculated moduli is dependent on the backcalculation procedure and the associated seed moduli. None of the existing classical backcalculation methods can find the “actual” pavement moduli due to the theoretical limitations of the existing methods. These limitations include the convergence to local optima due to the use of seed moduli, which in turn lead to erroneous pavement moduli. The genetic algorithms can be used to optimize the search domain of the backcalculated moduli to avoid the premature convergence to local optima. The use of genetic algorithms in pavement engineering is new and no guidelines or thorough investigations have been carried out to address all the aspects and challenges associated with the backcalculation procedure using the genetic algorithms. This study can be considered as the first comprehensive work that deals with all aspects of both pavement and genetic algorithms and how to merge them. In addition, this work can be considered as the first state of the art work on the backcalculation of pavement moduli using genetic algorithms. In this study, the use of genetic algorithms has been studied thoroughly to address all the important parameters and operators that affect the backcalculation process. In addition, recommendations and findings regarding all the details needed to carry out the backcalculation process were identified and discussed thoroughly. New novel methods to study the interaction between the genetic operators and parameters and their effect on the backcalculation process were developed. Recommendations regarding the genetic operators as well as the genetic parameters were presented throughout the work. In addition, the AASHTO recommended ranges of pavement moduli were modified based on the study results to suit the GAs backcalculation process. On the other hand, a new novel method was developed to automate the backcalculation process. The automation of the backcalculation process was aimed at reducing the number of inputs needed to carry out the backcalculation process and to make it more appealing to be used in practice. A new Dynamic Parameterless Genetic Algorithm (DPGA) was developed as part of this work. The new DPGA can be extended to many other applications of genetic algorithms including robotics and optimizations. A new program (BackGenetic3d) was developed based on the novel MultiSmart3D program developed by the Computation and Simulation Group at the University of Akron. The new program is the first in the world that can backcalculate the pavement moduli of pavement systems with any arbitrary number of layers, loading conditions, and loading configurations. Existing classical programs use backcalculation procedures that lead to local optima and limited to a maximum of 5 pavement layers and one loading circle with uniform pressure.
Pan Ernian (Advisor)
275 p.
Engineering, Civil
Genetic Algorithms; Pavement; Backcalculation; Falling Weight Deflectometer

Recommended Citations

Citations

  • Alkasawneh, W. M. (2007). Backcalculation of Pavement Moduli Using Genetic Algorithms [Doctoral dissertation, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1176831189

    APA Style (7th edition)

  • Alkasawneh, Wael. Backcalculation of Pavement Moduli Using Genetic Algorithms. 2007. University of Akron, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=akron1176831189.

    MLA Style (8th edition)

  • Alkasawneh, Wael. "Backcalculation of Pavement Moduli Using Genetic Algorithms." Doctoral dissertation, University of Akron, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=akron1176831189

    Chicago Manual of Style (17th edition)

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© 2007, all rights reserved.
This open access ETD is published by University of Akron and OhioLINK.