Detail publikace

A comparison of sensitivity analyses for selected prestressed concrete structures

Originální název

A comparison of sensitivity analyses for selected prestressed concrete structures

Anglický název

A comparison of sensitivity analyses for selected prestressed concrete structures

Jazyk

en

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.

BibTex


@article{BUT149533,
  author="David {Lehký} and Lixia {Pan} and Drahomír {Novák} and Maosen {Cao} and Martina {Šomodíková} and Ondřej {Slowik}",
  title="A comparison of sensitivity analyses for selected prestressed concrete structures",
  annote="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.",
  chapter="149533",
  doi="10.1002/suco.201700291",
  howpublished="print",
  number="20",
  volume="2019",
  year="2019",
  month="february",
  pages="38--51",
  type="journal article in Web of Science"
}