Doctor of Philosophy, University of Akron, 2007, 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 op (open full item for complete abstract)
Committee: Pan Ernian (Advisor)
Subjects: Engineering, Civil