| Wind-induced buffeting is one of the damages of long-span bridges,which easily causes fatigue damages of suspension bridge structure and has serious effects on the safety of suspension bridge and driving comfortableness.With the wide application of suspension bridge,wind-induced buffeting control has became one of the key scientific issues that are urgent to make a deep study in civil engineering.Multi-tuned mass damper?MTMD?is often used as a mechanical vibration damper for long span structures because of its good vibration reduction performance.At present,majority of researches on MTMD are based on simplified models and optimize parameter by manifesting the vibration reduction index.However,the simplified model is unable to accurately simulate the structures in actual projects due to complex members and connection modes of suspension bridge as well as its strong non-linearity.Based on the above research background,this paper takes a long-span suspension bridge as example and accurately simulate the suspension bridge and MTMD by using the finite element software ANSYS.In addition,it does research into the simulation of pulsating wind and the vibration reduction optimization of MTMD.Specific contents are as follows:?1?Three methods are introduced to optimize the traditional harmonic synthesis method.In this paper,the traditional method is optimized by interpolation fitting in spectral density matrix decomposition.At the same time,three optimization methods are compared,among which the efficiency and accuracy of cubic spline interpolation are relatively prominent.Compared with traditional harmonic synthesis method,the simulation time of the cubic spline interpolation method is reduced by 95%and its errors only reach 5.8×10-5when there are 40 simulation points,which has fleet and effective simulation on wind field.The improved harmonic synthesis method is used to simulate the wind field.?2?The models of bridge and damper are established in this paper.ANSYS is employed to establish the bridge and conduct modal analysis.Compared with other literatures,the top five modes of the two models are consistent with each other and their maximum error of frequency is only 2.9%,which proves the reliability of the model in this paper.?3?Sensitivity of MTMD parameters is analyzed in this paper.The TMD number,mass,frequency band width,center frequency ratio and damping ratio are used in time-history analysis as variables.The sensitivity of vibration reduction rate was learn from the results.?4?Optimized algorithm is verified in this paper.At the beginning,The design variables are obtained by uniform design.Then,the program written by Python is used to call ANSYS to realize batch operation of the design variables.Finally,the function of RBF neural network approximation structure is used to call the genetic algorithm.The test precision of the network shows that obtained neural network has a good generalization ability because it is of high fitting precision under the condition of finite group variables and the maximum fitting error is only 2.5%.Moreover,the evolutionary process demonstrates that the new improved genetic algorithm can achieve rapid convergence and ensure the diversity of parameter combinations.?5?Two-parameter co-optimization of MTMD is performed in this paper.Taking the Xihoumen Bridge as the engineering background,this paper firstly analyzes the sensitivity of ANSYS model to determine the parameter optimization interval of MTMD and obtain the structural damping rate by time-history analysis for each group parameter of finite element model.Next,the RBF neural network is applied to fit the relationship between the parameters and the damping rate.In the end,the genetic algorithm is employed to call the trained RBF neural network for optimizing the parameters,which gives the final optimization scheme and damping rate. |
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