Detail publikačního výsledku

A comparison of sensitivity analyses for selected prestressed concrete structures

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

Originální název

A comparison of sensitivity analyses for selected prestressed concrete structures

Anglický název

A comparison of sensitivity analyses for selected prestressed concrete structures

Druh

Článek WoS

Originální abstrakt

Three sensitivity analysis methods are employed to achieve the optimum selection of the dominant random variables of selected concrete structures. The first of these methods uses the nonparametric rank‐order statistical correlation between the basic random input variables and the structural response output variable. The second is neural network ensemble‐based sensitivity analysis and the last of them is sensitivity analysis in terms of coefficient of variation. All of the methods were utilized and compared for two selected concrete structures: a prestressed concrete bridge made of MPD girders, and T‐shaped prestressed concrete roof girder. The obtained information was used to set up a stochastic model and response surfaces in an optimum manner and was employed in the subsequent determination of selected uncertain design parameters followed by load‐bearing capacity and reliability assessment.

Anglický abstrakt

Three sensitivity analysis methods are employed to achieve the optimum selection of the dominant random variables of selected concrete structures. The first of these methods uses the nonparametric rank‐order statistical correlation between the basic random input variables and the structural response output variable. The second is neural network ensemble‐based sensitivity analysis and the last of them is sensitivity analysis in terms of coefficient of variation. All of the methods were utilized and compared for two selected concrete structures: a prestressed concrete bridge made of MPD girders, and T‐shaped prestressed concrete roof girder. The obtained information was used to set up a stochastic model and response surfaces in an optimum manner and was employed in the subsequent determination of selected uncertain design parameters followed by load‐bearing capacity and reliability assessment.

Klíčová slova

Artificial neural network, prestressed concrete, sensitivity analysis, structural reliability, surrogate modeling

Klíčová slova v angličtině

Artificial neural network, prestressed concrete, sensitivity analysis, structural reliability, surrogate modeling

Autoři

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

Rok RIV

2019

Vydáno

01.02.2019

Nakladatel

ERNST & SOHN, ROTHERSTRASSE 21, BERLIN, DEUTSCHLAND 10245, GERMANY

Místo

Berlin

ISSN

1464-4177

Periodikum

Structural Concrete

Svazek

20

Číslo

1

Stát

Spolková republika Německo

Strany od

38

Strany do

51

Strany počet

14

URL

https://onlinelibrary.wiley.com/doi/abs/10.1002/suco.201700291

Plný text v Digitální knihovně

http://hdl.handle.net/

BibTex

@article{BUT149533,
  author="David {Lehký} and Lixia {Pan} and Drahomír {Novák} and Maosen {Cao} and Martina {Sadílková Šomodíková} and Ondřej {Slowik}",
  title="A comparison of sensitivity analyses for selected prestressed concrete structures",
  journal="Structural Concrete",
  year="2019",
  volume="20",
  number="1",
  pages="38--51",
  doi="10.1002/suco.201700291",
  issn="1464-4177",
  url="https://onlinelibrary.wiley.com/doi/abs/10.1002/suco.201700291"
}