In the inner-city area, the maximum vehicle weight of heavy transport vehicles is often enforced to lower limit values compared to the main road network. In the case of the inner city of Amsterdam, yearly permits are required for vehicles heavier than 7.5 ton and special limited time permits for vehicles heavier than 30 ton. Currently, load models for assessment and design are derived with traffic load data for the main road network. To prevent unnecessary costs and material use in redesign or renovation of existing bridges in these areas, it is necessary to consider realistic traffic loads. Data regarding the properties of observable transport vehicles in inner-city areas is consequently limited, thus making modeling of the traffic load and load effect in these areas difficult. This can be problematic when a safety assessment of transport infrastructure needs to be performed. Here, we use a Weigh-In-Motion dataset from a measurement station in the outskirts of the city of Amsterdam, along with data from cameras set up in the inner city to create a database of vehicles that is representative for the enforced zone area. We then computationally simulate the traffic load effect and use a Bayesian inference approach to fit distribution functions to the simulated load effect. Consequently, we perform a reliability analysis to calibrate the characteristic values of EN 1991-2 Load Models LM1 and LM2 so that they reflect the reliability requirements prescribed by NEN 8700, which is the normative document in the Netherlands for the assessment of existing structures.


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    Title :

    Reliability-Based Calibration of EN 1991-2 Traffic Load Models for Inner-City Areas


    Additional title:

    Lecture Notes in Civil Engineering



    Conference:

    International Probabilistic Workshop ; 2024 ; Guimarães, Portugal May 08, 2024 - May 10, 2024



    Publication date :

    2024-07-06


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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