Title :
Research on Ductility of Unbonded Partially Prestressed Concrete Beam with High Strength Based on Network Model
Author :
Hu Lili ; Wu Ke ; Liu Ming
Author_Institution :
Sch. of Civil Eng. & Archit., Chang´an Univ., Xi´an, China
Abstract :
In this paper, the neural network model is used to predict ductility of unbonded partially prestressed concrete beam with high strength. Meanwhile, kinds of ingredients of the beampsilas ductility are analyzed and it is obtained the curve between kinds of ingredients and displacement ductility ratio. The result indicates that displacement ductility ratio of the beam gradually reduces with unprestressed index, prestressed index, span depth ratio, and depth of section increased.
Keywords :
beams (structures); concrete; ductility; neural nets; ductility; high strength concrete beam; neural network model; unbonded partially prestressed concrete beam; Artificial neural networks; Civil engineering; Computer architecture; Computer networks; Concrete; Neural networks; Neurons; Predictive models; Structural beams; Valves; ductility; high strength concrete beam; neural network; prestressed;
Conference_Titel :
Engineering Computation, 2009. ICEC '09. International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-0-7695-3655-2
DOI :
10.1109/ICEC.2009.15
