Overlay of flexible pavements: an ANN approach

Gumansingh, S (2014) Overlay of flexible pavements: an ANN approach. BTech thesis.



The main problem in flexible pavement is deterioration due to traffic loading, material related factors and adverse climatic conditions. In order to avoid and mitigate such difficulties, a maintenance program should be carried out rather going for reconstruction. Most common method adopted in India is the use of an asphalt overlay on the old surface to increase the serviceability of the existing road, but designing an overlay is challenging given restricted boundary conditions that must be observed and designed for. Although, there is provided design code but difficulties in solving process such as accurate field data, error prone design curve reading, less accurate conversion formula for temperature variation, time consuming calculations make it complex and dull to be used for everyday purpose. Unavailability of design software leads to manual calculation which is prone to errors. This study presents an attempt to apply artificial neural network to recommend asphalt overlay thickness (HMA). Though noted common methods need time, reliable and some essential data to be able to start designing process but artificial intelligence especially artificial neural network is a method based on learning process which can find possible relation between input and output sample data and is able to predict the output without any time with founded relation quickly. Results of this study reveal that artificial neural network is appropriate for implementation in calculating flexible overlay thickness.

Item Type:Thesis (BTech)
Uncontrolled Keywords:Artificial Neural Network, Flexible pavement,Nondestructive testing, overlay design
Subjects:Engineering and Technology > Civil Engineering > Transportation Engineering
Divisions: Engineering and Technology > Department of Civil Engineering
ID Code:6190
Deposited By:Hemanta Biswal
Deposited On:28 Aug 2014 15:20
Last Modified:28 Aug 2014 15:20
Supervisor(s):Panda , M

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