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author:

Aloisio, A. (Aloisio, A..) [1] | Quaranta, G. (Quaranta, G..) [2] | Contento, A. (Contento, A..) [3] | Rosso, M.M. (Rosso, M.M..) [4]

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Abstract:

The effect of vehicle braking can significantly amplify a bridge deflection compared to that induced by a vehicle moving at a constant speed. However, the magnitude of this amplification depends on vehicle bridge interaction (VBI) phenomena activated by the road roughness. The road roughness triggers the vehicle dynamics, thus magnifying the interaction between the vehicle and the bridge. This paper proposes a probabilistic model for the amplification factor. The amplification factor is associated with the vehicle’s hard braking by the mid-span of the bridge under different road roughness classes. The amplification factor, defined as the ratio between the maximum deflections corresponding to a vehicle braking and moving at a constant speed, is estimated as a function of the mass, velocity, natural frequency and damping of the vehicle. The VBI model is obtained by discretizing the coupled governing equations using the finite difference method. The vehicle is modelled as a two-degrees of freedom system corresponding to the bouncing and pitching motions. The computational efficiency of this model supported an expensive set of analyses, where the parameter values were selected using the Latin Hypercube sampling scheme. The model outputs have been validated against a middle-span bridge’s measured experimental displacement response under different scenarios. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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  • [ 1 ] [Aloisio A.]Department of Civil, Construction-Architectural and Environmental Engineering, Università degli Studi dell’Aquila, L’Aquila, Italy
  • [ 2 ] [Quaranta G.]Department of Structural and Geotechnical Engineering, Sapienza University of Rome, Rome, Italy
  • [ 3 ] [Contento A.]College of Civil Engineering, Fuzhou University, Fuzhou, China
  • [ 4 ] [Rosso M.M.]Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino, Turin, Italy

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ISSN: 2366-2557

Year: 2023

Volume: 433 LNCE

Page: 81-88

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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