Publication detail

Fuzzy Sets Theory in Comparison with Stochastic Methods to Analyse Nonlinear Behaviour of a Steel Member under Compression

KALA, Zdeněk

Original Title

Fuzzy Sets Theory in Comparison with Stochastic Methods to Analyse Nonlinear Behaviour of a Steel Member under Compression

Type

journal article - other

Language

English

Original Abstract

The load-carrying capacity of the member with imperfections under axial compression is analysed in the present paper. The study is divided into two parts: (i) in the first one, the input parameters are considered to be random numbers (with distribution of probability functions obtained from experimental results and/or tolerance standard), while (ii) in the other one, the input parameters are considered to be fuzzy numbers (with membership functions). The load-carrying capacity was calculated by geometrical nonlinear solution of a beam by means of the finite element method. In the case (ii), the membership function was determined by applying the fuzzy sets, whereas in the case (i), the distribution probability function of load-carrying capacity was determined. For (i) stochastic solution, the numerical simulation Monte Carlo method was applied, whereas for (ii) fuzzy solution, the method of the so-called alfa cuts was applied. The design load-carrying capacity was determined according to the EC3 and EN1990 standards. The results of the fuzzy, stochastic and deterministic analyses are compared in the concluding part of the paper.

Keywords

fuzzy, stochastic, simulation, steel, beam

Authors

KALA, Zdeněk

RIV year

2005

Released

1. 1. 2005

Publisher

LANA

Location

Vilnius (Litva)

ISBN

1392-5113

Periodical

Nonlinear Analysis - Modelling and Control

Year of study

10

Number

1

State

Republic of Lithuania

Pages from

65

Pages to

75

Pages count

10

BibTex

@article{BUT42495,
  author="Zdeněk {Kala}",
  title="Fuzzy Sets Theory in Comparison with Stochastic Methods to Analyse Nonlinear Behaviour of a Steel Member under Compression",
  journal="Nonlinear Analysis - Modelling and Control",
  year="2005",
  volume="10",
  number="1",
  pages="65--75",
  issn="1392-5113"
}