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Probabilistic numerical evaluation of dynamic load allowance factors in steel modular bridges using a vehicle-bridge interaction model
Highlights Probabilistic approach to numerically evaluate dynamic allowance factors IM. Vehicle-bridge interaction method to analyze the coupling system. Stochastic generation of different pavement irregularity types in modular bridges. Deterministic evaluation of IM factors may lead to unreliable results. Probabilistic evaluation of IM factors can lead to important material savings.
Abstract A reliable evaluation of dynamic amplification effects is crucial in bridge design in order to achieve safer and economical solutions. In engineering practice, these effects are commonly taken into account through dynamic load allowance factors (IM) specified by the codes. However, some codes allow the calculation of these IM factors through more advanced dynamic analysis in order to achieve more realistic results. Therefore, a methodology to numerically evaluate the IM in bridges is described. The methodology is based on a vehicle-bridge interaction model that can take into account any configuration of pavement irregularities. A case study consisting of two modular steel bridges is presented. In order to reach a comprehensive characterization of the IM factors, a probabilistic analysis is conducted, taking into consideration the stochastic generation of random irregularity profiles based on pavement roughness and experimentally measured manufacturing imperfections, as well as a wide range of vehicle speeds. The results obtained in this study demonstrate the advantages of performing a probabilistic numerical evaluation of the IM factor in comparison to the use of pre-defined factors proposed by design codes. The consideration of IM factors based on probabilistic assessments can lead to relevant material savings in the design of steel modular bridges.
Probabilistic numerical evaluation of dynamic load allowance factors in steel modular bridges using a vehicle-bridge interaction model
Highlights Probabilistic approach to numerically evaluate dynamic allowance factors IM. Vehicle-bridge interaction method to analyze the coupling system. Stochastic generation of different pavement irregularity types in modular bridges. Deterministic evaluation of IM factors may lead to unreliable results. Probabilistic evaluation of IM factors can lead to important material savings.
Abstract A reliable evaluation of dynamic amplification effects is crucial in bridge design in order to achieve safer and economical solutions. In engineering practice, these effects are commonly taken into account through dynamic load allowance factors (IM) specified by the codes. However, some codes allow the calculation of these IM factors through more advanced dynamic analysis in order to achieve more realistic results. Therefore, a methodology to numerically evaluate the IM in bridges is described. The methodology is based on a vehicle-bridge interaction model that can take into account any configuration of pavement irregularities. A case study consisting of two modular steel bridges is presented. In order to reach a comprehensive characterization of the IM factors, a probabilistic analysis is conducted, taking into consideration the stochastic generation of random irregularity profiles based on pavement roughness and experimentally measured manufacturing imperfections, as well as a wide range of vehicle speeds. The results obtained in this study demonstrate the advantages of performing a probabilistic numerical evaluation of the IM factor in comparison to the use of pre-defined factors proposed by design codes. The consideration of IM factors based on probabilistic assessments can lead to relevant material savings in the design of steel modular bridges.
Probabilistic numerical evaluation of dynamic load allowance factors in steel modular bridges using a vehicle-bridge interaction model
Montenegro, P.A. (author) / Castro, J.M. (author) / Calçada, R. (author) / Soares, J.M. (author) / Coelho, H. (author) / Pacheco, P. (author)
Engineering Structures ; 226
2020-09-08
Article (Journal)
Electronic Resource
English
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