A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Case Studies of Asphalt Pavement Analysis/Design with Application of the Genetic Algorithm
Abstract The primary purpose of this study is to demonstrate the applicability of the genetic algorithm (GA) to solve nonlinear optimization problems encountered in asphalt pavement design. The fundamentals of the GA are briefly discussed, and four case studies are presented. The first case study is an example showing the backcalculation of layer moduli with deflection data from a falling weight deflectometer and a layered-elastic program. The second case study demonstrates how to construct the master curve, either from a mix flexural frequency sweep test or from a binder rheometer test, and how to apply that master curve in pavement design. The third case shows how to apply the GA to characterize the binder discrete relaxation spectrum with a generalized Maxwell solid model. The last case study illustrates how to apply the GA to define the mix fatigue damage process of a flexural controlled-deformation beam fatigue test and the permanent shear strain accumulation process of a controlled-load repetitive simple shear test with constant height using a three-stage Weibull approach, and how to apply the three-stage Weibull approach in predicting pavement performance. The results indicate that the GA is promising and successful in resolving the nonlinear optimization problem although the GA presents some difficulty in terms of computing efficiency in the case study of backcalulation of layer moduli.
Case Studies of Asphalt Pavement Analysis/Design with Application of the Genetic Algorithm
Abstract The primary purpose of this study is to demonstrate the applicability of the genetic algorithm (GA) to solve nonlinear optimization problems encountered in asphalt pavement design. The fundamentals of the GA are briefly discussed, and four case studies are presented. The first case study is an example showing the backcalculation of layer moduli with deflection data from a falling weight deflectometer and a layered-elastic program. The second case study demonstrates how to construct the master curve, either from a mix flexural frequency sweep test or from a binder rheometer test, and how to apply that master curve in pavement design. The third case shows how to apply the GA to characterize the binder discrete relaxation spectrum with a generalized Maxwell solid model. The last case study illustrates how to apply the GA to define the mix fatigue damage process of a flexural controlled-deformation beam fatigue test and the permanent shear strain accumulation process of a controlled-load repetitive simple shear test with constant height using a three-stage Weibull approach, and how to apply the three-stage Weibull approach in predicting pavement performance. The results indicate that the GA is promising and successful in resolving the nonlinear optimization problem although the GA presents some difficulty in terms of computing efficiency in the case study of backcalulation of layer moduli.
Case Studies of Asphalt Pavement Analysis/Design with Application of the Genetic Algorithm
Tsai, Bor-Wen (author) / Harvey, John T. (author) / Monismith, Carl L. (author)
2009-01-01
34 pages
Article/Chapter (Book)
Electronic Resource
English
Master Curve , Asphalt Concrete , Asphalt Binder , Stiffness Ratio , Fall Weight Deflectometer Computer Science , Artificial Intelligence (incl. Robotics) , Building Construction , Geoengineering, Foundations, Hydraulics , Appl.Mathematics/Computational Methods of Engineering , Engineering Economics, Organization, Logistics, Marketing
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