Detail publikace

A Comparison of Sensitivity Analyses of Prestressed Composite Bridge

Originální název

A Comparison of Sensitivity Analyses of Prestressed Composite Bridge

Anglický název

A Comparison of Sensitivity Analyses of Prestressed Composite Bridge

Jazyk

en

Originální abstrakt

Three sensitivity analysis methods are employed for proper selection of dominant random variables of prestressed composite bridge. The first one uses the non-parametric rank-order statistical correlation between the basic random variables and the structural response variable. The second method is neural network ensemble-based sensitivity analysis and the last one is sensitivity analysis in terms of coefficient of variation. All three methods were utilized and compared for the prestressed concrete bridge made of MPD girders. Such an information was used for proper set up of stochastic model and response surfaces and subsequent determination of selected uncertain design parameters followed by load-bearing capacity and reliability assessment.

Anglický abstrakt

Three sensitivity analysis methods are employed for proper selection of dominant random variables of prestressed composite bridge. The first one uses the non-parametric rank-order statistical correlation between the basic random variables and the structural response variable. The second method is neural network ensemble-based sensitivity analysis and the last one is sensitivity analysis in terms of coefficient of variation. All three methods were utilized and compared for the prestressed concrete bridge made of MPD girders. Such an information was used for proper set up of stochastic model and response surfaces and subsequent determination of selected uncertain design parameters followed by load-bearing capacity and reliability assessment.

BibTex


@inproceedings{BUT142570,
  author="David {Lehký} and Drahomír {Novák} and Martina {Šomodíková} and Lixia {Pan} and Maosen {Cao}",
  title="A Comparison of Sensitivity Analyses of Prestressed Composite Bridge",
  annote="Three sensitivity analysis methods are employed for proper selection of dominant random variables of prestressed composite bridge. The first one uses the non-parametric rank-order statistical correlation between the basic random variables and the structural response variable. The second method is neural network ensemble-based sensitivity analysis and the last one is sensitivity analysis in terms of coefficient of variation. All three methods were utilized and compared for the prestressed concrete bridge made of MPD girders. Such an information was used for proper set up of stochastic model and response surfaces and subsequent determination of selected uncertain design parameters followed by load-bearing capacity and reliability assessment.",
  booktitle="12th International Conference on Structural Safety & Reliability (ICOSSAR 2017)",
  chapter="142570",
  howpublished="electronic, physical medium",
  year="2017",
  month="august",
  pages="583--592",
  type="conference paper"
}