In order to assess the performance of concrete median barriers under vehicle crashes, a probability-based analysis approach was developed using computational techniques. Due to the inherent randomness in vehicle crashes, reliability analyses of these problems become more important for decision making in engineering design. Historically, the performance of median barrier systems has been relied on limited full-scale physical crash tests, and a prescriptive pass/fail method has been used. Improving the engineering practice to a probability-based approach is needed for transportation safety research. In this work, the parameters of a vehicular impact, such as the impact angle and the weight of vehicle were considered as random variables. A pickup truck meeting the specifications of the current crash standard was used and nonlinear finite element analyses were performed to calculate crash responses of the vehicle, including velocities and accelerations. To improve the computational efficiency of reliability analyses, explicit metamodels of crash responses were constructed using radial basis functions (RBFs). After explicit expressions of performance functions were obtained, the Monte Carlo simulations (MCS) approach was applied to determine the probability of exceedance, or failure probability. This proposed approach was shown to be very efficient, especially for problems involving expensive numerical simulations. In this study, various vehicular crash responses and limit values were selected and reliability analyses were conducted. The reliability analysis results obtained based on the RBF metamodels and MCS were found to provide useful information for assessment of concrete median barriers.


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    Title :

    A Probability-Based Approach for Assessment of Concrete Median Barriers


    Contributors:
    Wang, Qian (author) / Fang, Hongbing (author) / Yin, Hanfeng (author)

    Conference:

    International Conference on Transportation and Development 2018 ; 2018 ; Pittsburgh, Pennsylvania



    Publication date :

    2018-07-12




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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