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LEHKÝ, D.; NOVÁK, D.
Original Title
Probabilistic Inverse Analysis: Random Material Parameters of Reinforced Concrete Frame
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
The paper focuses on the statistical inverse analysis of material model parameters, where statistical moments of input parameters have to be indentified based on experimental data (histograms of response). Stratified simulation technique of Monte Carlo type combined with artifical neural network is efficiently used. The methodology is shown using the example of reinforced concrete frame solved by nonlinear fracture mechanics tool for objective failure modeling of structures with significant nonlinear effects. Means and standard deviations of fracture-mechanical parameters (like modulus of elasticity, fracture energy, etc.) are the subject of identification.
English abstract
Keywords
inverse analysis, concrete, nonlinear fracture mechanics, finite element method
Key words in English
Authors
Released
24.08.2005
Location
Lille, Francie
Book
Novel Applications of Neural Networks in Engineering
Pages from
147
Pages to
154
Pages count
8
BibTex
@inproceedings{BUT18369, author="David {Lehký} and Drahomír {Novák}", title="Probabilistic Inverse Analysis: Random Material Parameters of Reinforced Concrete Frame", booktitle="Novel Applications of Neural Networks in Engineering", year="2005", pages="147--154", address="Lille, Francie" }