Detail publikace

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.

Originální název

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

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

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

Vydáno

28. 5. 2016

Místo

Shanghai, China

ISBN

978-7-5608-6303-0

Kniha

Structural Reliability and its Applications (APSSRA ´6)

Strany od

624

Strany do

629

Strany počet

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"
}