Due to the gradual depletion in the conventional resources, searching for a more rational road construction approach aimed at reducing the dependence on imported materials while improving the quality and durability of the roads is necessary. A previous study carried out on a sample of Egyptian soil aimed at reducing the road construction cost, protect the environment and achieving sustainability. RoadCem, ground granulated blast furnace slag (GGBS), lime and ordinary Portland cement (OPC) were employed to stabilise the Egyptian clayey soil. The results revealed that the unconfined compressive strength (UCS) of the test soil increased while the free swelling percent (FSP) decreased with an increase in the total stabiliser and the curing period. This paper discusses attempts to reach optimum stabilization through: (1) Recognizing the relationship between the UCS/FSP of stabilized soil and the stabilization parameters using artificial neural network (ANN); and (2) Performing a backward optimization on the developed (ANN) model using general algorithm (GA) to meet practical design preferences. © 2012 WIT Press.
|Original language||English (US)|
|Title of host publication||Environmental Impact|
|Number of pages||10|
|State||Published - Jul 3 2012|
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The author would like to thank Dr. Ahmed El-hakim, Post Doctorate Fellow,AUC/KAUST, The American University in Cairo, Egypt, for his cooperation indevelopment of the neural network model.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.