Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Dam Safety Reliability Analysis Based on Artificial Neural Network
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.
Dam Safety Reliability Analysis Based on Artificial Neural Network
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.
Dam Safety Reliability Analysis Based on Artificial Neural Network
Advanced Materials Research ; 255-260 ; 3620-3625
31.05.2011
6 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Dam Safety Reliability Analysis Based on Artificial Neural Network
| British Library Conference Proceedings | 2011
Loader Boom Reliability Analysis with Artificial Neural Network Method
| British Library Conference Proceedings | 2014
Loader Boom Reliability Analysis with Artificial Neural Network Method
| Tema Archiv | 2013
Reliability and performance-based design by artificial neural network
| Tema Archiv | 2007
Structural reliability analysis for implicit performance functions using artificial neural network
| British Library Online Contents | 2005