Damping optimization method for damping cable of large-span cable-stayed bridge

Abstract

The invention belongs to the technical field of bridge engineering, and discloses a large-span cable-stayed bridge damping cable damping optimization method, which specifically comprises the following steps of: 1, establishing a bridge finite element model considering the temperature related characteristics of a damper, and according to a bridge design drawing, constructing a bridge finite element model; structural analysis software is adopted to construct a three-dimensional finite element model comprising a main beam, a bridge tower, an inclined damping cable, a support and a foundation. The mechanical parameters of the damper are defined as temperature related variables, the double-characteristic temperature is determined in combination with bridge site long-term meteorological data, and the influence of the temperature on the performance of the damper is accurately represented in cooperation with a viscosity-temperature characteristic curve with high fitting precision; through standardized dynamic response analysis and numerical optimization under the working condition of double extreme temperatures, the obtained optimal parameters can meet the requirements of extreme environments in summer and winter at the same time, and the problem of seasonal performance failure caused by traditional fixed parameter design is thoroughly solved; and then all-weather stable work of the damper is ensured through full-temperature-range multi-node verification.

Description

Technical Field

[0001] This invention belongs to the field of bridge engineering technology, specifically a method for optimizing the damping of shock-absorbing cables in long-span cable-stayed bridges. Background Technology

[0002] Long-span cable-stayed bridges, as key hubs in modern transportation infrastructure, are widely used in special landform areas such as rivers, lakes, seas, and canyons due to their advantages such as strong spanning capacity and adaptability to complex terrain. As the core device for suppressing the vibration of the cable-stayed bridge's damping cables and ensuring the long-term safety and durability of the structure, the quality of its optimized design directly affects the overall vibration resistance and service stability of the bridge.

[0003] In the current field of damping optimization for long-span cable-stayed bridges, relevant technical solutions have formed a certain application foundation, but there are still many key issues that are out of touch with actual engineering needs. Existing optimization methods generally set the damping coefficient of the damper to a fixed value, or determine the damping parameters only through simple theoretical estimation, failing to fully consider the core characteristic of the damping medium used in viscous dampers having significant temperature sensitivity. Long-span cable-stayed bridges often face environmental conditions with large seasonal temperature differences and frequent extreme temperatures at the bridge site. Temperature changes directly cause drastic fluctuations in the dynamic viscosity of the damping medium, which in turn causes the actual output damping force of the damper to deviate from the design value. At the same time, existing methods lack a systematic application of actual meteorological data at the bridge site, and the selection of characteristic temperatures relies heavily on empirical values. Instead of being based on scientific statistics from long-term measured data, the acquisition of viscosity-temperature characteristic curves often suffers from incomplete temperature point coverage and insufficient fitting accuracy, leading to inaccurate characterization of damper performance changes under temperature influence. Furthermore, existing optimization designs are mostly based on analysis under single temperature conditions, failing to consider the differences in structural dynamic response under extreme temperature scenarios such as high temperatures in summer and low temperatures in winter. This results in optimized damping parameters that can only meet performance requirements under specific temperature conditions. In practical applications, this can easily lead to the risk of dampers being too "soft" in summer and too "hard" in winter, failing to guarantee the stable vibration reduction effect of the damping system in all-weather environments. Ultimately, this results in a disconnect between optimization results and engineering realities, making it difficult to effectively address structural safety hazards caused by temperature changes. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of this invention is to provide an optimization method for damping of the shock-absorbing cables in long-span cable-stayed bridges to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for optimizing the damping of shock-absorbing cables in long-span cable-stayed bridges, the specific steps of which are as follows: Step 1: Establish a finite element model of the bridge considering the temperature-dependent characteristics of the damper. Based on the bridge design drawings, a three-dimensional finite element model including the main beam, bridge tower, inclined damping cables, supports, and foundations was constructed using structural analysis software. Each damping cable to be installed with a damper was accurately simulated in the model, and damper elements were established at the connection nodes between the damping cables and the main beam or bridge tower. An initial damping coefficient and velocity index were assigned to the damper element, and the mechanical performance parameters of the damper were explicitly defined as variables that change with temperature for subsequent temperature correction parameters. Step 2: Collect long-term meteorological observation data at the bridge site and determine the design characteristic temperature. Obtain raw data from meteorological monitoring stations at the bridge location for at least fifteen consecutive years, extract daily hourly temperature records from the raw data, and construct a long-term temperature database. Perform statistical analysis on the long-term temperature database, calculate the monthly average temperature of the hottest and coldest months of each year, select the highest average temperature of the hottest month of all years as the summer characteristic high temperature, and select the lowest average temperature of the coldest month of all years as the winter characteristic low temperature. The summer characteristic high temperature and the winter characteristic low temperature together constitute two characteristic temperature points for damping optimization. Step 3: Obtain the viscosity-temperature characteristic curve of the damping medium to be used. Based on the damper design scheme, the specific model of the viscous damping medium to be used is determined; through standard laboratory testing, the dynamic viscosity of this model of damping medium is measured at at least five different temperature points; using the data fitting method, a viscosity-temperature characteristic curve of the dynamic viscosity of the damping medium as a function of temperature is plotted, which fully characterizes the variation law of the medium viscosity from the characteristic low temperature of winter to the characteristic high temperature of summer. Step 4: Calculate the equivalent output performance parameters of the damper at the characteristic temperature. Substitute the specific values ​​of the summer characteristic high temperature and winter characteristic low temperature determined in step two into the viscosity-temperature characteristic curve obtained in step three, read and calculate the dynamic viscosity values ​​of the damping medium corresponding to the two characteristic temperature points; based on the mechanical principle and structural design drawings of the viscous damper, convert the dynamic viscosity values ​​of the medium at different temperatures into the actual output damping force of the damper body at the same operating speed, and then obtain two sets of equivalent damping coefficients of the damper under the summer characteristic high temperature condition and the winter characteristic low temperature condition; Step 5: Conduct comparative analysis of structural dynamic response under dual temperature conditions. Substitute the two sets of equivalent damping coefficients obtained in step four into the bridge finite element model established in step one to update the damper element parameters. First, simulate the characteristic high-temperature conditions of summer, apply the design wind load or seismic time history at the corresponding temperature to the bridge model, and conduct nonlinear dynamic time history analysis to obtain the displacement response, acceleration response and maximum vibration amplitude of the main beam key control points under this condition. Second, simulate the characteristic low-temperature conditions of winter, apply the corresponding load and conduct the same dynamic time history analysis to obtain another set of structural response results. Step Six: Optimize the damper design target parameters to meet dual-condition performance requirements. Structural response allowable limits are defined, including the maximum displacement limit of the main beam, the root mean square acceleration limit, and the maximum vibration amplitude limit of the damping cable. An optimization model is established using the design damping coefficient and velocity index of the damper as optimization variables. The constraint condition is that all structural response results obtained in step five under both summer high-temperature and winter low-temperature conditions do not exceed the corresponding allowable limits. The optimization objective is to maximize the margin of the most unfavorable structural response value relative to the limit in both conditions. A numerical optimization algorithm is used to solve the model, iteratively adjusting the damper design target parameters to finally obtain the optimal damper design target parameters that simultaneously meet the performance requirements under two extreme temperature environments. Step 7: Verify full-temperature-range performance and output design documents Set the optimal damper design target parameters obtained in step six as the damper reference design values; select at least five verification temperature points at 5°C intervals between the characteristic high temperature of summer and the characteristic low temperature of winter, repeat the process of steps four and five, calculate and analyze the structural response of the bridge at these intermediate temperature points using the same reference design value damper; after confirming that the structural response at all verification temperature points meets the requirements, compile a technical specification of the shock absorber cable damper that includes the optimal damper design target parameters and its performance description at the characteristic temperature, and complete the optimization design.

[0006] Preferably, the structural analysis software used in step one is a mainstream structural engineering analysis software such as ANSYS, ABAQUS, or MidasGen, and the meshing accuracy of the connection nodes of the damper element is not less than 2mm to ensure the accuracy of the transfer of the mechanical properties of the element.

[0007] Preferably, the original data from the meteorological monitoring station mentioned in step two must come from a formal monitoring station certified by the national meteorological department, and the data integrity must meet the requirement that the number of valid recording days per year is not less than 360 days. The monthly average temperature is calculated using the arithmetic mean method, and abnormal fluctuation data in the daily hourly records are removed.

[0008] Preferably, the five different temperature points mentioned in step three need to uniformly cover the range from the characteristic low temperature of winter to the characteristic high temperature of summer. The data fitting adopts the least squares method for curve fitting, and the goodness of fit R² is not less than 0.98.

[0009] Preferably, the conversion of the dynamic viscosity value of the medium in step four is based on the constitutive equation of the viscous damper, F=CV^α, where F is the output damping force of the damper, C is the damping coefficient, V is the operating speed, and α is the speed exponent. During the conversion process, the operating speed must be kept uniformly set to the rated design speed of the damper.

[0010] Preferably, in step five, the seismic time history should select three or more sets of natural or synthetic seismic waves that match the seismic parameters of the bridge site area, and the time step of the nonlinear dynamic time history analysis should not exceed 0.02s.

[0011] Preferably, the numerical optimization algorithm in step six is ​​a genetic algorithm, a particle swarm optimization algorithm, or a simulated annealing algorithm. The structural response redundancy calculation method is: redundancy = (allowable limit - worst response value) / allowable limit × 100%. The optimization iteration convergence criterion is set as the redundancy change in 10 consecutive iterations not exceeding 1%.

[0012] Preferably, the verification temperature points mentioned in step seven should include the characteristic low temperature of winter, the characteristic high temperature of summer, and at least three key temperature points in between; the technical specifications should clearly indicate the optimal design parameters, the equivalent damping coefficient at the characteristic temperature, the maximum output damping force, and the structural response verification conclusions over the entire temperature range, to ensure the integrity and feasibility of the design documents.

[0013] Preferably, the initial damping coefficient and velocity index of the damper in step one need to be set based on the reference parameter range provided by the damper manufacturer. The initial damping coefficient ranges from 100kN·s / m to 500kN·s / m, and the velocity index ranges from 0.3 to 0.7, to ensure that the initial parameters are within a reasonable design range.

[0014] The beneficial effects of this invention are as follows: By defining the damper's mechanical parameters as temperature-dependent variables and combining them with long-term meteorological data from the bridge site to determine dual-characteristic temperatures, along with a high-fitting-accuracy viscosity-temperature characteristic curve, the impact of temperature on damper performance is accurately characterized. Through standardized dynamic response analysis and numerical optimization under dual extreme temperature conditions, the optimal parameters obtained can simultaneously meet the requirements of extreme summer and winter environments, completely solving the seasonal performance failure problem caused by traditional fixed-parameter design. Furthermore, multi-node verification across the entire temperature range ensures the damper's stable operation in all weather conditions. Clear technical standards and parameter limits are defined for each stage, ensuring that the optimization process is standardized and repeatable, and the results are scientifically reliable, significantly improving the long-term applicability and safety of the vibration reduction system for long-span cable-stayed bridges. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] like Figure 1 As shown in the figure, this invention provides a method for optimizing the damping of the shock absorbers in a long-span cable-stayed bridge. The specific steps are as follows: Step 1: Establish a finite element model of the bridge considering the temperature-dependent characteristics of the damper. Based on the bridge design drawings, a three-dimensional finite element model including the main beam, bridge tower, inclined damping cables, supports, and foundations was constructed using structural analysis software. Each damping cable to be installed with a damper was accurately simulated in the model, and damper elements were established at the connection nodes between the damping cables and the main beam or bridge tower. An initial damping coefficient and velocity index were assigned to the damper element, and the mechanical performance parameters of the damper were explicitly defined as variables that change with temperature for subsequent temperature correction parameters. Step 2: Collect long-term meteorological observation data at the bridge site and determine the design characteristic temperature. Obtain raw data from meteorological monitoring stations at the bridge location for at least fifteen consecutive years, extract daily hourly temperature records from the raw data, and construct a long-term temperature database. Perform statistical analysis on the long-term temperature database, calculate the monthly average temperature of the hottest and coldest months of each year, select the highest average temperature of the hottest month of all years as the summer characteristic high temperature, and select the lowest average temperature of the coldest month of all years as the winter characteristic low temperature. The summer characteristic high temperature and the winter characteristic low temperature together constitute two characteristic temperature points for damping optimization. Step 3: Obtain the viscosity-temperature characteristic curve of the damping medium to be used. Based on the damper design scheme, the specific model of the viscous damping medium to be used is determined; through standard laboratory testing, the dynamic viscosity of this model of damping medium is measured at at least five different temperature points; using the data fitting method, a viscosity-temperature characteristic curve of the dynamic viscosity of the damping medium as a function of temperature is plotted, which fully characterizes the variation law of the medium viscosity from the characteristic low temperature of winter to the characteristic high temperature of summer. Step 4: Calculate the equivalent output performance parameters of the damper at the characteristic temperature. Substitute the specific values ​​of the summer characteristic high temperature and winter characteristic low temperature determined in step two into the viscosity-temperature characteristic curve obtained in step three, read and calculate the dynamic viscosity values ​​of the damping medium corresponding to the two characteristic temperature points; based on the mechanical principle and structural design drawings of the viscous damper, convert the dynamic viscosity values ​​of the medium at different temperatures into the actual output damping force of the damper body at the same operating speed, and then obtain two sets of equivalent damping coefficients of the damper under the summer characteristic high temperature condition and the winter characteristic low temperature condition; Step 5: Conduct comparative analysis of structural dynamic response under dual temperature conditions. Substitute the two sets of equivalent damping coefficients obtained in step four into the bridge finite element model established in step one to update the damper element parameters. First, simulate the characteristic high-temperature conditions of summer, apply the design wind load or seismic time history at the corresponding temperature to the bridge model, and conduct nonlinear dynamic time history analysis to obtain the displacement response, acceleration response and maximum vibration amplitude of the main beam key control points under this condition. Second, simulate the characteristic low-temperature conditions of winter, apply the corresponding load and conduct the same dynamic time history analysis to obtain another set of structural response results. Step Six: Optimize the damper design target parameters to meet dual-condition performance requirements. Structural response allowable limits are defined, including the maximum displacement limit of the main beam, the root mean square acceleration limit, and the maximum vibration amplitude limit of the damping cable. An optimization model is established using the design damping coefficient and velocity index of the damper as optimization variables. The constraint condition is that all structural response results obtained in step five under both summer high-temperature and winter low-temperature conditions do not exceed the corresponding allowable limits. The optimization objective is to maximize the margin of the most unfavorable structural response value relative to the limit in both conditions. A numerical optimization algorithm is used to solve the model, iteratively adjusting the damper design target parameters to finally obtain the optimal damper design target parameters that simultaneously meet the performance requirements under two extreme temperature environments. Step 7: Verify full-temperature-range performance and output design documents Set the optimal damper design target parameters obtained in step six as the damper reference design values; select at least five verification temperature points at 5°C intervals between the characteristic high temperature of summer and the characteristic low temperature of winter, repeat the process of steps four and five, calculate and analyze the structural response of the bridge at these intermediate temperature points using the same reference design value damper; after confirming that the structural response at all verification temperature points meets the requirements, compile a technical specification of the shock absorber cable damper that includes the optimal damper design target parameters and its performance description at the characteristic temperature, and complete the optimization design.

[0018] Based on the bridge design drawings, a three-dimensional finite element model was constructed using structural analysis software, including key components such as the main girder, bridge towers, inclined shock absorbers, and damper units. The mechanical performance parameters of the dampers were defined as temperature-dependent variables. Then, by collecting meteorological observation data from the bridge site for at least fifteen consecutive years, two key temperature points—characteristic high temperatures in summer and characteristic low temperatures in winter—were determined through statistical analysis. Subsequently, the viscosity-temperature characteristic curve of the proposed viscous damping medium was obtained through standard laboratory testing, and the equivalent damping coefficient of the damper under the two characteristic temperatures was calculated accordingly. Next, the two sets of equivalent damping coefficients were substituted into the finite element model to conduct structural dynamic response analysis under dual-temperature conditions, obtaining response data such as the displacement and acceleration of the main girder and the vibration amplitude of the shock absorbers. Finally, the damper design was used to... The damping coefficient and velocity index are used as optimization variables. The constraint is that the structural response under dual load conditions does not exceed the allowable limit. The objective is to maximize the margin of the most unfavorable structural response. The optimal design parameters are solved using a numerical optimization algorithm. Finally, performance verification is conducted at verification temperature points across the entire temperature range to ensure the damper meets usage requirements in all temperature intervals. A technical specification is then compiled to complete the design. This technical solution systematically covers the entire process from model construction, parameter acquisition, load analysis to optimization verification. It effectively solves the problem of the impact of temperature changes on damper performance, ensuring that the designed damper can adapt to extreme temperature environments and guaranteeing the long-term stable vibration reduction effect of the bridge structure. This provides comprehensive and reliable technical support for the practical application of this optimization design method.

[0019] In step one, mainstream structural engineering analysis software such as ANSYS, ABAQUS, or MidasGen are selected for structural analysis. The meshing accuracy of the connection nodes of the damper element is not less than 2mm to ensure the accuracy of the transfer of the mechanical properties of the element.

[0020] Limiting the mesh accuracy of the damper element connection nodes ensures the accuracy of the transmission of the damper element's mechanical properties and avoids deviations in subsequent temperature-related performance analysis and parameter optimization results due to non-standard model construction.

[0021] In step two, the original data from the meteorological monitoring station must come from a formal monitoring station certified by the national meteorological department. The data integrity must meet the requirement that the number of valid recording days per year is not less than 360 days. The monthly average temperature is calculated using the arithmetic mean method, and abnormal fluctuation data in the daily hourly records are removed.

[0022] By requiring data to come from officially certified monitoring sites, ensuring the number of valid records per year, and eliminating abnormal fluctuations, the accuracy and objectivity of calculations for summer high temperatures and winter low temperatures are ensured, thus avoiding the impact of unreliable temperature data on the rationality of damper temperature adaptability design.

[0023] In step three, the five different temperature points need to uniformly cover the range from the characteristic low temperature of winter to the characteristic high temperature of summer. The least squares method is used for curve fitting, and the goodness of fit R² is not less than 0.98.

[0024] By following standards in conducting tests, ensuring that temperature points uniformly cover the entire working range, and limiting the goodness of fit, the viscosity-temperature characteristic curve can truly and accurately characterize the change of the damping medium's viscosity with temperature.

[0025] In step four, the conversion of the dynamic viscosity of the medium is based on the constitutive equation of the viscous damper, F=CV^α, where F is the output damping force of the damper, C is the damping coefficient, V is the operating speed, and α is the speed exponent. During the conversion process, the operating speed must be kept at the design rated speed of the damper.

[0026] By clarifying the conversion method based on the constitutive equation of viscous dampers and unifying the actuation speed standard, the consistency and accuracy of the calculation of the equivalent damping coefficient at different temperatures are ensured, and the distortion of the dynamic response analysis results under dual-temperature conditions due to inconsistent conversion basis or parameters is avoided.

[0027] In step five, the ground motion time history must select three or more sets of natural or synthetic earthquake waves that match the ground motion parameters of the bridge site area, and the time step of the nonlinear dynamic time history analysis shall not exceed 0.02s.

[0028] By following the building structure load code to determine the wind load, selecting seismic waves that match the ground motion parameters of the bridge site and limiting the time step, the scientific nature and comparability of the dynamic response analysis under dual temperature conditions are ensured, and inaccurate structural response data are avoided due to improper load or analysis parameter settings.

[0029] In step six, the numerical optimization algorithm selected is genetic algorithm, particle swarm optimization algorithm or simulated annealing algorithm. The structural response redundancy calculation method is: redundancy = (allowable limit - worst response value) / allowable limit × 100%. The convergence criterion for optimization iteration is set as the redundancy change in 10 consecutive iterations not exceeding 1%.

[0030] To avoid issues such as divergence, slow convergence, or excessive iteration during the optimization process, a convergence criterion is set that the change in redundancy over 10 consecutive iterations does not exceed 1%. This criterion allows for precise determination of whether the optimization process has reached a stable state, thereby quickly locking in the optimal damper design target parameters and ensuring the optimization results.

[0031] In step seven, the verification temperature points must include the characteristic low temperature of winter, the characteristic high temperature of summer, and at least three key intermediate temperature points; the technical specifications must clearly indicate the optimal design parameters, the equivalent damping coefficient at the characteristic temperature, the maximum output damping force, and the structural response verification conclusions over the entire temperature range, to ensure the integrity and feasibility of the design documents.

[0032] By reasonably setting verification temperature points covering the entire operating temperature range, the performance of the damper can be fully verified at characteristic low temperatures in winter, characteristic high temperatures in summer, and intermediate transition temperatures, thus avoiding performance failures in local temperature ranges.

[0033] In step one, the initial damping coefficient and velocity index of the damper need to be set based on the reference parameter range provided by the damper manufacturer. The initial damping coefficient should be in the range of 100kN·s / m to 500kN·s / m, and the velocity index should be in the range of 0.3 to 0.7, to ensure that the initial parameters are within the reasonable design range.

[0034] By limiting the reasonable range of initial damping coefficient and velocity exponent of the damper, problems such as difficulty in convergence of optimization iteration and excessive number of iterations caused by the initial parameters deviating from the reasonable design range can be effectively avoided.

[0035] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0036] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for damping optimization of a large-span cable-stayed bridge, characterized in that, The specific steps are as follows: Step one: Establish a bridge finite element model considering the temperature-dependent characteristics of dampers According to the bridge design drawings, a three-dimensional finite element model is constructed using structural analysis software, including the main girder, tower, inclined damping cable, support and foundation. In the model, each damping cable to be installed is accurately simulated, and a damper unit is established at the connection node of the damping cable and the main girder or tower. The initial damping coefficient and velocity exponent are assigned to the damper unit, and the mechanical properties of the damper are defined as variables that change with temperature, which are used to input the temperature correction parameters in the subsequent steps. Step two: Collect long-term weather observation data at the bridge site and determine the design characteristic temperature Obtain at least fifteen years of continuous original data from the weather monitoring station at the bridge site, extract the daily hourly air temperature records from the original data, and construct a long-term air temperature database. Perform statistical analysis on the long-term air temperature database to calculate the monthly average temperature of the hottest month and the coldest month in each year, respectively. Select the highest value of the average temperature of the hottest month in all years as the summer characteristic high temperature, and select the lowest value of the average temperature of the coldest month in all years as the winter characteristic low temperature. The summer characteristic high temperature and the winter characteristic low temperature together constitute the two characteristic temperature points for damper optimization. Step three: Obtain the viscosity-temperature characteristic relationship curve of the damping medium to be used According to the damper design scheme, determine the specific model of the viscous damping medium to be used. Measure the dynamic viscosity values of the damper medium at least at five different temperature points through standard laboratory tests. Use data fitting methods to draw the viscosity-temperature characteristic relationship curve of the damper medium, which fully represents the variation of the medium viscosity from the winter characteristic low temperature to the summer characteristic high temperature. Step four: Calculate the equivalent output performance parameters of the damper at the characteristic temperatures Substitute the summer characteristic high temperature and the winter characteristic low temperature determined in step two into the viscosity-temperature characteristic relationship curve obtained in step three to read and calculate the dynamic viscosity values of the damping medium at the two characteristic temperature points. According to the mechanical principles of viscous dampers and the structural design drawings, convert the dynamic viscosity values of the medium at different temperatures into the actual output damping force of the damper entity at the same actuation speed, and then obtain two sets of equivalent damping coefficients of the damper under the summer characteristic high temperature and the winter characteristic low temperature conditions. Step five: Perform comparative analysis of structural dynamic responses under double temperature conditions Substitute the two sets of equivalent damping coefficients obtained in step four into the bridge finite element model established in step one to update the damper unit parameters. First, simulate the summer characteristic high temperature condition, apply the corresponding temperature design wind load or seismic time history to the bridge model, and perform nonlinear dynamic time history analysis to obtain the displacement response, acceleration response of the main girder key control points, and the maximum vibration amplitude of the damping cable under this condition. Second, simulate the winter characteristic low temperature condition, apply the corresponding load and perform the same dynamic time history analysis to obtain another set of structural response results. Step six: Optimize the damper design target parameters to meet the performance of double conditions The definition structure response limit value includes the maximum displacement limit value of the main beam, the acceleration root mean square limit value, and the maximum vibration amplitude limit value of the damping cable; the design damping coefficient and the velocity index of the damper are taken as the optimization variables to establish an optimization model, the constraint condition is that all the structure response results under the summer high temperature working condition and the winter low temperature working condition obtained in step five are not more than the corresponding allowable limit value, and the optimization target is to maximize the surplus degree of the most unfavorable value of the structure response relative to the limit value in the two working conditions; The numerical optimization algorithm is used to solve the model, and the damper design target parameters are iteratively adjusted, so that the optimal damper design target parameters which meet the performance requirements under two extreme temperature environments are finally obtained; Step seven: Perform full temperature range working performance verification and output design file The optimal damper design target parameters obtained in step six are set as the damper reference design values; at least five verification temperature points are selected at intervals of 5℃ between the summer characteristic high temperature and the winter characteristic low temperature, the processes of steps four and five are repeated, the structure responses of the bridge at these intermediate temperature points using the same reference design value damper are calculated and analyzed; after confirming that the structure responses at all verification temperature points meet the requirements, a damping cable damper technical specification including the optimal damper design target parameters and the performance description at the characteristic temperature is prepared, and the optimization design is completed.

2. The damping optimization method for a large-span cable-stayed bridge seismic cable according to claim 1, characterized in that: The structure analysis software in step one is selected from mainstream structural engineering analysis software such as ANSYS, ABAQUS or MidasGen, and the connection node grid division precision of the damper unit is not less than 2mm, which ensures the accuracy of the transmission of the mechanical properties of the unit.

3. The damping optimization method for a large-span cable-stayed bridge seismic cable according to claim 1, characterized in that: The raw data of the meteorological monitoring station in step two should come from a regular monitoring station certified by the national meteorological department, and the data integrity should meet the requirement of not less than 360 days of valid records per year, the monthly average temperature is calculated by the arithmetic average method, and the abnormal fluctuation data in the single-day hourly record is excluded.

4. The damping optimization method for a large-span cable-stayed bridge seismic cable according to claim 1, characterized in that: The five different temperature points in step three should uniformly cover the interval from the winter characteristic low temperature to the summer characteristic high temperature, the data fitting is performed by curve fitting using the least squares method, and the goodness of fit R² is not less than 0.

98.

5. The damping optimization method for a large-span cable-stayed bridge seismic cable according to claim 1, characterized in that: In step four, the medium dynamic viscosity value conversion is based on the constitutive equation of the viscous damper F=CV^α, where F is the damper output damping force, C is the damping coefficient, V is the actuation speed, and α is the velocity index. The actuation speed is uniformly set as the rated speed of the damper during the conversion process.

6. The damping optimization method for a large-span cable-stayed bridge seismic cable according to claim 1, characterized in that: In step five, the seismic time history should select 3 groups or more of natural seismic waves or artificially synthesized seismic waves matched with the seismic parameters of the bridge site area, and the time step of the nonlinear dynamic time history analysis is not more than 0.02s.

7. The method of claim 1, wherein: In step six, the numerical optimization algorithm is selected from genetic algorithm, particle swarm optimization algorithm or simulated annealing algorithm, the structure response surplus degree calculation method is: surplus degree=(allowable limit value-most unfavorable response value) / allowable limit value×100%, and the optimization iteration convergence criterion is set as the change amount of the surplus degree of 10 consecutive iterations not more than 1%.

8. The damping optimization method for a large-span cable-stayed bridge seismic cable according to claim 1, characterized in that: The verification temperature points in step seven should include the low temperature in winter, the high temperature in summer and at least three key temperature points in between. The technical specification should clearly mark the optimal design parameters, equivalent damping coefficient at the characteristic temperature, maximum output damping force and the structural response verification conclusion in the full temperature range, to ensure the completeness and implementability of the design document.

9. The damping optimization method for a large-span cable-stayed bridge seismic cable according to claim 1, characterized in that: The initial damping coefficient and velocity index in step one should be set based on the reference parameter range provided by the damper manufacturer. The initial damping coefficient value range is 100 kN·s / m~500 kN·s / m, and the velocity index value range is 0.3~0.7, to ensure that the initial parameters are in a reasonable design interval.

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