DocumentCode :
3633357
Title :
Virtual reliability control of precast prestressed concrete elements using parameters identification and statistical simulation
Author :
Drahomir Novak;Zbynek Kersner;Jiri Dolezel;David Lehky
Author_Institution :
Brno University of Technology, Faculty of Civil Engineering, Czech Republic
fYear :
2009
Firstpage :
1778
Lastpage :
1781
Abstract :
An approach for statistical and reliability analyses of concrete structures is presented. It describes the virtual simulation used on the way from assessment of experimental results to reliability analysis. The whole approach is based on randomization of nonlinear fracture mechanics finite element analysis of concrete structures. Efficient techniques of both nonlinear numerical analysis of concrete structures and stochastic simulation methods of Monte Carlo type have been combined in order to offer an advanced tool for assessment of realistic behaviour of concrete structures. The stochastic response requires repeated analyses of the structure with stochastic input parameters, which reflects randomness and uncertainties in the input values. The procedure utilizes statistical simulation of Monte Carlo type also for preparation of training set of artificial neural network used for fracture mechanical parameters identification. The application of approach to virtual statistical simulation of shear capacity of precast prestressed concrete elements SPIROLL is presented. Design shear capacities calculated according to design codes and alternative procedures are compared with simulation of reality representing virtual reliability control of elements production.
Keywords :
"Concrete","Parameter estimation","Stochastic processes","Analytical models","Monte Carlo methods","Finite element methods","Numerical analysis","Uncertainty","Artificial neural networks","Production"
Publisher :
ieee
Conference_Titel :
Control Applications, (CCA) & Intelligent Control, (ISIC), 2009 IEEE
ISSN :
1085-1992
Print_ISBN :
978-1-4244-4601-8
Type :
conf
DOI :
10.1109/CCA.2009.5280995
Filename :
5280995
Link To Document :
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