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      Identification of Dynamic Vehicular Axle Loads: Theory and Simulations

      1 , 2
      Journal of Vibration and Control
      SAGE Publications

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          Abstract

          This paper presents a new method of identifying dynamic vehicular axle loads by directly using bridge measurements. To demonstrate how the proposed methodology works out, vehicle-bridge coupling equations are first established for numerical simulations. The developed vehicle-bridge coupled system contains only the modal properties of the bridge and the physical parameters of the vehicle. Using the superposition principle and influence surface concept, the dynamic interaction forces (i.e. the dynamic axle loads) can then be identified from the measured bridge responses. A series of simulations are carried out in which the effects of various factors such as bridge inertia force, measurement station, vehicle speed, traveling route, number of vehicles, road surface condition, and noise level have been investigated. The identified results show that the proposed method is able to identify dynamic axle loads with good accuracy, which can serve as a basis for dynamic bridge-weigh-in-motion. This paper also serves as a theoretical base for the companion paper in which the proposed method is applied to identify the dynamic axle loads of a real truck on an existing bridge.

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          Most cited references30

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          The description of road surface roughness

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            MOVING FORCE IDENTIFICATION: A TIME DOMAIN METHOD

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              Vehicle-Bridge Interaction Element for Dynamic Analysis

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                Author and article information

                Journal
                Journal of Vibration and Control
                Journal of Vibration and Control
                SAGE Publications
                1077-5463
                1741-2986
                December 2010
                May 26 2010
                December 2010
                : 16
                : 14
                : 2167-2194
                Affiliations
                [1 ]Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA
                [2 ]Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA ()
                Article
                10.1177/1077546309351221
                e6d2bd58-5b0e-43ae-a9c5-5ffd108ce86b
                © 2010

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

                History

                Quantitative & Systems biology,Biophysics
                Quantitative & Systems biology, Biophysics

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