Detail publikace

Study on reliability of prestressed concrete bridge using ANN-based inverse method

Originální název

Study on reliability of prestressed concrete bridge using ANN-based inverse method

Anglický název

Study on reliability of prestressed concrete bridge using ANN-based inverse method

Jazyk

en

Originální abstrakt

The paper describes an application of artificial neural network-based inverse reliability method for reliability-based design of selected parameters of the concrete bridge. The design reliability level is determined using a fully probabilistic approach. The analysed structure is a single-span concrete bridge made of precast MPD3 and MPD4 girders post-tensioned by longitudinal as well as transversal tendons. According to diagnostic survey the bridge exhibits a spatial variability of deterioration which brings uncertainty into actual values of concrete strength in transverse joints and of actual loss of pre-stressing. Mean value and coefficient of variation of these two variables were considered as the design parameters with the aim of finding their critical values corresponding to desired reliability level and load-bearing capacity. Here, various load levels together with several values of mean tensile strength were considered.

Anglický abstrakt

The paper describes an application of artificial neural network-based inverse reliability method for reliability-based design of selected parameters of the concrete bridge. The design reliability level is determined using a fully probabilistic approach. The analysed structure is a single-span concrete bridge made of precast MPD3 and MPD4 girders post-tensioned by longitudinal as well as transversal tendons. According to diagnostic survey the bridge exhibits a spatial variability of deterioration which brings uncertainty into actual values of concrete strength in transverse joints and of actual loss of pre-stressing. Mean value and coefficient of variation of these two variables were considered as the design parameters with the aim of finding their critical values corresponding to desired reliability level and load-bearing capacity. Here, various load levels together with several values of mean tensile strength were considered.

BibTex


@inproceedings{BUT155480,
  author="Martin {Lipowczan} and David {Lehký} and Martina {Šomodíková} and Drahomír {Novák}",
  title="Study on reliability of prestressed concrete bridge using ANN-based inverse method",
  annote="The paper describes an application of artificial neural network-based inverse reliability method for reliability-based design of selected parameters of the concrete bridge. The design reliability level is determined using a fully probabilistic approach. The analysed structure is a single-span concrete bridge made of precast MPD3 and MPD4 girders post-tensioned by longitudinal as well as transversal tendons. According to diagnostic survey the bridge exhibits a spatial variability of deterioration which brings uncertainty into actual values of concrete strength in transverse joints and of actual loss of pre-stressing. Mean value and coefficient of variation of these two variables were considered as the design parameters with the aim of finding their critical values corresponding to desired reliability level and load-bearing capacity. Here, various load levels together with several values of mean tensile strength were considered.",
  address="Wilhelm Ernst & Sohn",
  booktitle="16th International Probabilistic Workshop",
  chapter="155480",
  doi="10.1002/best.201800059",
  howpublished="online",
  institution="Wilhelm Ernst & Sohn",
  number="S2",
  year="2018",
  month="september",
  pages="1--6",
  publisher="Wilhelm Ernst & Sohn",
  type="conference paper"
}