Publication result detail

Utilization of Artificial Neural Network Based Response Surface Method for Reliability Analysis of Structures

LEHKÝ, D.; ŠOMODÍKOVÁ, M.

Original Title

Utilization of Artificial Neural Network Based Response Surface Method for Reliability Analysis of Structures

English Title

Utilization of Artificial Neural Network Based Response Surface Method for Reliability Analysis of Structures

Type

Abstract

Original Abstract

The key step of the reliability and lifetime assessment of structures is the determination of reliability level, described by failure probability or reliability index. Some of the simulation or approximation techniques can be used for this purpose. In case of large structures analyzed using the nonlinear finite element method, it is necessary to develop more efficient procedures, reducing the number of evaluations of original limit state function to a minimum. Here, artificial neural network based response surface method in combination with small-sample simulation technique Latin Hypercube Sampling is utilized for the approximation of a limit state function. Thanks to ability of artificial neural network to generalize it is efficient to fit limit state function with a sufficiently small number of simulations.

English abstract

The key step of the reliability and lifetime assessment of structures is the determination of reliability level, described by failure probability or reliability index. Some of the simulation or approximation techniques can be used for this purpose. In case of large structures analyzed using the nonlinear finite element method, it is necessary to develop more efficient procedures, reducing the number of evaluations of original limit state function to a minimum. Here, artificial neural network based response surface method in combination with small-sample simulation technique Latin Hypercube Sampling is utilized for the approximation of a limit state function. Thanks to ability of artificial neural network to generalize it is efficient to fit limit state function with a sufficiently small number of simulations.

Keywords

artificial neural network, Latin hypercube sampling, load bearing capacity, probability of failure, reliability index

Key words in English

artificial neural network, Latin hypercube sampling, load bearing capacity, probability of failure, reliability index

Authors

LEHKÝ, D.; ŠOMODÍKOVÁ, M.

RIV year

2016

Released

11.05.2015

Publisher

Náprstek, J. & Fischer, C.

Location

Svratka, Česká republika

ISBN

978-80-86246-42-0

Book

Engineering Mechanics 2015 – 21st International Conference: Extended Abstracts, May 11–14, 2015, Svratka, Czech Republic

Pages from

182

Pages to

183

Pages count

2

BibTex

@misc{BUT120743,
  author="David {Lehký} and Martina {Sadílková Šomodíková}",
  title="Utilization of Artificial Neural Network Based Response Surface Method for Reliability Analysis of Structures",
  booktitle="Engineering Mechanics 2015 – 21st International Conference: Extended Abstracts, May 11–14, 2015, Svratka, Czech Republic",
  year="2015",
  pages="182--183",
  publisher="Náprstek, J. & Fischer, C.",
  address="Svratka, Česká republika",
  isbn="978-80-86246-42-0",
  note="Abstract"
}