Publication detail

Probabilistic Inverse Analysis: Random Material Parameters of Reinforced Concrete Frame

LEHKÝ, D. NOVÁK, D.

Original Title

Probabilistic Inverse Analysis: Random Material Parameters of Reinforced Concrete Frame

Type

conference paper

Language

English

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.

Keywords

inverse analysis, concrete, nonlinear fracture mechanics, finite element method

Authors

LEHKÝ, D.; NOVÁK, D.

RIV year

2005

Released

24. 8. 2005

Location

Lille, Francie

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"
}