Directional effects of correlated wind and waves on the dynamic response of long-span sea-crossing bridges

Directional effects on the nonlinear response of vehicle-bridge system under correlated wind and waves

Long span sea-crossing bridges are often slender and sensitive to wind and wave loads. Nonlinear dynamic response analysis of the bridges under three-dimensional (3D) correlated wind and wave loads is performed in this study in consideration of both geometric and aerodynamic nonlinearities. An optimized C-vine copula is first used to construct a 3D joint probability distribution and environmental contour of mean wind speed, significant wave height and peak wave period. Multi-point fluctuating wind loads with Davenport coherence function and random wave loads with pile group effect are then determined using wind and wave spectra respectively. The nonlinear wind-wave-bridge system considering geometric and aerodynamic nonlinearities is solved by the Newmark-β method with the 3D correlated wind and wave parameters as an input. The proposed approach is finally applied to a real sea-crossing cable-stayed bridge with the measured wind and wave data. The results show that the nonlinear response of the bridge is higher than its linear response with the same input. The bridge response is significantly reduced if the 3D correlated wind and wave loads other than conventional uncorrelated wind and wave loads are considered.

Dynamic response of a sea-crossing cable-stayed suspension bridge under simultaneous wind and wave loadings induced by a landfall typhoon

Load distribution and dynamic response of multi-girder bridges with FRP decks

Rail–bridge coupling element of unequal lengths for analysing train–track–bridge interaction systems

Effects of aerodynamic parameters on the dynamic responses of road vehicles and bridges under cross winds

The sea-crossing railway bridge is exposed to a high risk of wind and wave, which threatens the safety of the bridge and railway. A wind–wave–vehicle–bridge dynamic analysis model for sea-crossing railway bridge under wind and wave loadings is developed by extending the previous wind–vehicle–bridge model. The developed wind–wave–vehicle–bridge model involves multipoint fluctuating wind field, irregular wave field, finite element model of the bridge, and mass–spring–damper model of the vehicle. The correlation between wind and wave is considered by an empirical curve derived based on field measurement. Static, buffeting, and self-excited wind forces on the bridge and vehicle are considered with coefficients obtained from wind tunnel tests. The wave forces on the bridge are calculated by Morison equation including stretching modification. The governing equations of the wind–wave–vehicle–bridge model are solved in time domain by Newmark-β method to compute the dynamic response of bridge and vehicle. The dynamic response of bridge and vehicle is compared and discussed in both wind–wave–vehicle–bridge and wind–vehicle–bridge model. The performance of bridge and vehicle are finally evaluated. Studies of dynamic response under correlated wind and wave are found to be imperative for assessment of structural and vehicle safety and driving comfort of sea-crossing railway bridge.

With emphasis on long-span bridges, the dynamic responses of bridges without considering random traffic flows were found to be different from actual situations. The introduction of a random traffic flow model provides a new approach for the random analysis of bridge structure responses under vehicle loads. In this paper, the finite element and intelligent ant colony optimization-back propagation neural network (ACO-BPNN) models were used to study the dynamic responses of long-span bridges. The computational model was also validated by an experimental test. To confirm the validity of the proposed ACO-BPNN model after parameter selection, it was compared with the traditional back propagation neural network (BPNN) model and the genetic algorithm-back propagation neural network (GA-BPNN) model. BPNN, GA-BPNN, and ACO-BPNN adopt the same network topology structure to predict the dynamic responses of the long-span bridge. When the ACO-BPNN model conducted the iteration to the 130th generation, a training error of 0.009 was found to be smaller than the set critical error. In this manner, the computational accuracy was increased, and the optimized time was reduced. In addition, only 0.4 hours were spent in using the proposed ACO-BPNN model to predict the dynamic response of the long-span bridge. In the case of the same computer performance, it took 4.5 h to use the finite element model to predict the dynamic response of the long-span bridge. The advantage of the proposed ACO-BPNN model in predicting the performance of large-scale complex structures such as long-span bridges was clearly found.

Fluid viscous dampers (FVDs) are widely used in long‐span suspension bridges for earthquake resistance. To analyze efficiently the influences of FVDs on the dynamic response of a suspension bridge under high‐intensity traffic flow, a bridge‐vehicle coupling method optimized by isoparametric mapping and improved binary search in this work was first developed and validated. Afterwards, the traffic flow was simulated on the basis of monitored weigh‐in‐motion data. The dynamic responses of bridge were analyzed by the proposed method under different FVD parameters. Results showed that FVDs could positively affect bridge dynamic response under traffic flow. The maximum accumulative longitudinal girder displacement, longitudinal girder displacement, and longitudinal pylon acceleration decreased substantially, whereas the midspan girder bending moment, pylon bending moment, longitudinal pylon displacement, and suspender force were less affected. The control efficiency of maximum longitudinal girder displacement and accumulative girder displacement reached 33.67% and 57.71%, longitudinal pylon acceleration and girder bending moment reached 31.51% and 7.14%, and the pylon longitudinal displacement, pylon bending moment, and suspender force were less than 3%. The increased damping coefficient and decreased velocity exponent can reduce the bridge dynamic response. However, when the velocity exponent was 0.1, an excessive damping coefficient brought little improvement and may lead to high‐intensity work under traffic flow, which will adversely affect component durability. The benefits of low velocity exponent also reduced when the damping coefficient was high enough, so if the velocity exponent has to be increased, the damping coefficient can be enlarged to fit with the velocity exponent. The installation of FVDs influences dynamic responses of bridge structures in daily operations and this issue warrants investigation. Thus, traffic load should be considered in FVD design because structural responses are perceptibly influenced by FVD parameters.

The dynamic responses of an asymmetrical arch railway bridge subjected to moving trains are experimentally and numerically investigated in this study. The strains, displacements and accelerations at critical sections of the bridge were measured at different speeds of trains. A three-dimensional finite element model of the bridge–vehicle coupling system was established to understand the measured dynamic responses and was validated against the experimental results. The numerical model was used to analyze the influence of asymmetry on the dynamic responses of the bridge and the safety and ride comfort of trains. The results indicate that the dynamic responses of the bridge increase with the train speed. Braking of the train has the largest impact on the vertical dynamic displacement of the bridge. The maximum dynamic strain is in the arch rib. The longer half arch demonstrated much larger counterforce and dynamic responses than those of the shorter half arch, while the symmetrical structures tend to exhibit good symmetry. The asymmetrical arrangement of the bridge reduces the structural stiffness.

Nonlinear vibration analysis of beam-like bridges with multiple breathing cracks under moving vehicle load

Simulation computation of vehicle-bridge coupling vibration and field experiment are carried out in a long-span continuous beam bridge of an intercity railway. And the effect of soil-structure interaction on the coupled vibration of continuous beam bridges and vehicles under high speed vehicle load was discussed in this paper. With BDAP V2.0(Bridge Dynamic Analysis Program), which is certificated by National Copyright Administration, the natural frequencies and dynamic responses of the bridge under vehicle load are calculated by using a more complex bridge FEM model(whole-pile model), which can take account of the interaction of lateral displacement and bending angle on group-piles. In order to assess the influence of soil-structure interaction on bridge dynamic response and evaluate the actual dynamic response of a long-span continuous beam high speed railway bridge, dynamic loading tests were made at the speed varying from 200km/h to 380km/h to get the vertical dynamic displacements in the mid-span and the lateral and vertical amplitude and acceleration of some typical points in the beam and pier. With a comparison of simulation computation results of different bridge FEM models and field experiment results, we can draw some conclusions, which is beneficial to research and design of long-span continuous beam bridges in high speed railway: Compared with commonly used consolidation model and equivalent-stiffness model, the dynamic response of the bridge with whole-pile model, especially the lateral dynamic response, varies a lot by considering soil-structure interaction. While the maximum dynamic accelerations get lower, the maximum lateral amplitudes become higher. And the results of field experiment show that with whole-pile model, a precise and reasonable simulation computation result can be gained because soil-structural interaction is also taken into account. For a high speed railway bridge located in soft ground with group-piles foundation, whole-pile model is proposed to analysis the coupled vibration of vehicle and bridge.

Effects of near-field ground motions and soil-structure interaction on dynamic response of a cable-stayed bridge

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalised cross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalisedcross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.