Probability based assessment of bridge exposed to extraordinary circumstances

Research output: Contribution to conferencePaper, not in proceeding

Abstract

Considerations of robustness for structural bridge systems subject to accidental circumstances are discussed in this paper. An overview of the framework for the assessment of structural robustness is given highlighting the various features vital to its implementation. The application of probabilistic risk based methodology for the investigation of system effects from rare exposure events is considered for a multi-span concrete bridge crossing multiple rail tracks as well as roads. Calculations are performed to ascertain and quantify these responses; this includes the investigation of impacts from derailed train traffic. The probability of such events occurring is estimated based on statistical data, an examination of subsequent propagating actions is carried out based on mechanical and structural considerations and the overall system response gauged. The potential consequences are then quantified and the corresponding risks associated with these events determined. Conclusions drawn here include the significance of utilizing probabilistic risk assessment methods and design strategies which reflect considerations of robustness of systems subject to rare exposure events with high con-sequences. Current design guidelines for accidental loading used for design of new bridges were also evaluated on the basis of the case study.

Details

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Building Technologies

Keywords

  • KstrStructural, robustness, risk, exposure, consequence, probability, rare, bridge
Original languageEnglish
Number of pages8
Publication statusSubmitted - 2011
Publication categoryResearch
Peer-reviewedYes
Event11th International Conference on Application of Statistics and Probability in Civil Engineering - Zurich, Switzerland
Duration: 2011 Aug 1 → …

Conference

Conference11th International Conference on Application of Statistics and Probability in Civil Engineering
CountrySwitzerland
CityZurich
Period2011/08/01 → …