Assessment of optimum settlement of structure adjacent urban tunnel by using neural network methods

Autor: Ali Kashfi, Shahram Pourakbar, Mohammad Azadi
Rok vydání: 2013
Předmět:
Zdroj: Tunnelling and Underground Space Technology. 37:1-9
ISSN: 0886-7798
DOI: 10.1016/j.tust.2013.03.002
Popis: Currently with the spread of tunnel constructions in cities, the proximity of other structures being built close to these tunnels have now become an important subject. Studying the rate of settlement of structures built in the vicinity of these tunnels could be an importance as well. The distance between tunnels and buildings is an important factor which can also be taken to account. Considering some of the parameters in place, favorable results can be achieved in having tunnels and other structures in the close proximity of each other. In this paper, the settlement of structures with different scenarios has been studied. The proximity of structures and their orientation in comparison with the location of the tunnels has also been a part of this study. Through the Finite Element Method (FEM), and with the use of Neural Network (NN), a various settlement situations have been studied. Using NN on the analysis of the FEM outcome and consideration of the vertical and horizontal distances between the tunnels and constructions with the number of their stories and the diameter of tunnel, relation between the settlements of constructions in any given direction will be immerge. In the study of this matter, the use of methods such as NN and genetic algorithms has not been reported. Using NN to evaluate the results can help to optimize the construction and implementation of underground structures.
Databáze: OpenAIRE
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