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dc.contributor.authorICASP14
dc.contributor.authorLeander, John
dc.date.accessioned2023-08-03T10:42:01Z
dc.date.available2023-08-03T10:42:01Z
dc.date.issued2023
dc.identifier.citationLeander, John, A code calibration for heavy special transports on railway bridges, 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland, 2023.
dc.descriptionPUBLISHED
dc.description.abstractThe current paper summarizes a code calibration project for heavy special transports on railway bridges. The basis is the Swedish code for assessing existing bridges, which has a safety format based on partial factors. Reliability-based models have been established for different bridge types and failure modes, covering the most common railway bridges and relations between permanent and variable loads. A sample of special transport vehicles from previous admission applications was considered and modelled with stochastic properties reflecting known axle loads and gross weights. Statistical data for stochastic variables were collected from the literature, but additional input had to be evaluated from recent measurements. The results include safety indices for the present partial factors and a suggestion for a reduced factor for vehicles with a known weight. With a target value of β = 3.7, applicable to existing bridges, the partial factor for vehicles can be reduced from 1.5 to 1.3.
dc.language.isoen
dc.relation.ispartofseries14th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP14)
dc.rightsY
dc.titleA code calibration for heavy special transports on railway bridges
dc.title.alternative14th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP14)
dc.typeConference Paper
dc.type.supercollectionscholarly_publications
dc.type.supercollectionrefereed_publications
dc.rights.ecaccessrightsopenAccess
dc.identifier.urihttp://hdl.handle.net/2262/103180


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    14th International Conference on Application of Statistics and Probability in Civil Engineering

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