Paper Title:
Dam Safety Reliability Analysis Based on Artificial Neural Network
  Abstract

There are many factors, such as climate, flood, material, geology, structure, management, to influence dam safety. So dam safety evaluation, involving many fields, is very complicated, and very difficult to establish mathematic model for assessment. Artificial Neural Network (ANN) has many obvious advantages to deal with these problems influenced by multi-factor, consequently is widely used in engineering fields. This paper considered water level, temperature, main factors influencing dam deformation, as random variables, employed ANN and statistical model to establish performance function of dam hidden trouble deformation and abnormal deformation. Then reliability theory was used to analyze dam safety reliability and sensitivity. The results show that temperature has great effect on probability of dam hidden trouble deformation and abnormal deformation than reservoir water level, due to great variability of temperature. Change of Reliability index of dam is contrary to reservoir water level. Temperature, especially average temperature in 10 days and 5 days, has great effect on sensitivity of reliability index than water level.

  Info
Periodical
Advanced Materials Research (Volumes 255-260)
Edited by
Jingying Zhao
Pages
3620-3625
DOI
10.4028/www.scientific.net/AMR.255-260.3620
Citation
H. Wei, H. S. Yang, L. Wu, Y. Gui, "Dam Safety Reliability Analysis Based on Artificial Neural Network", Advanced Materials Research, Vols. 255-260, pp. 3620-3625, 2011
Online since
May 2011
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Price
$32.00
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