Publication result detail

Soft Computing and Stochastic Optimization Approaches for Uncertain Design Parameters Determination of Post-Tensioned Composite Bridge

LEHKÝ, D.; NOVÁK, D.; SLOWIK, O.; ŠOMODÍKOVÁ, M.; CAO, M.

Original Title

Soft Computing and Stochastic Optimization Approaches for Uncertain Design Parameters Determination of Post-Tensioned Composite Bridge

English Title

Soft Computing and Stochastic Optimization Approaches for Uncertain Design Parameters Determination of Post-Tensioned Composite Bridge

Type

Paper in proceedings (conference paper)

Original Abstract

To achieve desired level of reliability in limit state design is generally not an easy task, especially when probabilistic analysis including detailed description of uncertainties is utilized. In general, engineering design belongs to the category of inverse problems with the aim to determine selected design parameters. Inn the paper two alternative approaches are employed for finding design parameters of a single-span post-tensioned composite bridge. The first approach is based on utilization of artificial neural network in combination with small-sample simulation technique and genetic algorithms. The second approach considers inverse problem as reliability-based optimization task using small-sample double-loop method.

English abstract

To achieve desired level of reliability in limit state design is generally not an easy task, especially when probabilistic analysis including detailed description of uncertainties is utilized. In general, engineering design belongs to the category of inverse problems with the aim to determine selected design parameters. Inn the paper two alternative approaches are employed for finding design parameters of a single-span post-tensioned composite bridge. The first approach is based on utilization of artificial neural network in combination with small-sample simulation technique and genetic algorithms. The second approach considers inverse problem as reliability-based optimization task using small-sample double-loop method.

Keywords

Reliability-based design, inverse analysis, artificial neural network, double-loop optimization, post-tensioned bridge, reliability index, latin hypercube sampling

Key words in English

Reliability-based design, inverse analysis, artificial neural network, double-loop optimization, post-tensioned bridge, reliability index, latin hypercube sampling

Authors

LEHKÝ, D.; NOVÁK, D.; SLOWIK, O.; ŠOMODÍKOVÁ, M.; CAO, M.

RIV year

2017

Released

28.05.2016

Location

Shanghai, China

ISBN

978-7-5608-6303-0

Book

Structural Reliability and its Applications (APSSRA ´6)

Pages from

624

Pages to

629

Pages count

6

BibTex

@inproceedings{BUT128479,
  author="David {Lehký} and Drahomír {Novák} and Ondřej {Slowik} and Martina {Sadílková Šomodíková} and Maosen {Cao}",
  title="Soft Computing and Stochastic Optimization Approaches for Uncertain Design Parameters Determination of Post-Tensioned Composite Bridge",
  booktitle="Structural Reliability and its Applications (APSSRA ´6)",
  year="2016",
  pages="624--629",
  address="Shanghai, China",
  isbn="978-7-5608-6303-0"
}