Force Analysis Method for Complex Components of High-Rise Structures Based on Multi-Scale Model Correction

Abstract

The present application provides a method for analyzing the force on complex components of high-rise structures based on multi-scale model correction. This method obtains the measured data of the static and dynamic force responses of corresponding test components in high-rise structures and the simulated data of the static and dynamic force responses calculated based on the initial finite element model; constructs a multi-scale finite element model correction and optimization function according to the relative error between the measured data and the simulated data; uses a multi-objective optimization algorithm to realize the correction of the initial finite element model; finally, analyzes the stress change of the component under the action of super strong wind loads based on the corrected finite element model. This method can ensure the accuracy of simulating the structural response based on the corrected finite element model, and further confirm the safety of the actual high-rise structure under the action of super strong wind loads, etc.

Description

Technical Field

[0001] This application relates to the technical field of internal force analysis of high-rise structures, and particularly to a method for analyzing the forces on complex components of high-rise structures based on multi-scale model correction. Background Art

[0002] Under the action of complex environments, the complex components in high-rise structures usually have complex forces. Numerical simulations cannot accurately reflect the internal force distribution and changes of the components. Although the real structural responses obtained through actual monitoring of the structure can directly reflect the local complex working state of the transfer structure, due to the limitation of the number of sensors, complete response information cannot be obtained. Therefore, it is necessary to simulate the actual behavior of the structure through a finite element model.

[0003] The structural finite element model is usually constructed by simplifying and assuming the geometric characteristics, material parameters, boundary conditions, and other conditions of the actual structure during the establishment process according to the design drawings. However, due to the uncertainties during the construction process of the structure, there are often deviations between the structural finite element model and the actual engineering structure. At this time, if the structural finite element model constructed by the above method is directly used for stress change analysis under wind loads such as typhoons, there will be a large error between the simulated structural response and the actual structural response. Therefore, it is impossible to determine whether the actual structure is safe under ultra-high wind loads such as typhoons based on the simulated force analysis results, etc. Summary of the Invention

[0004] In view of this, the embodiments of this application provide a method for analyzing the forces on complex components of high-rise structures based on multi-scale model correction, which can ensure the accuracy of simulating the structural response based on the finite element model, thereby accurately analyzing the safety issues of high-rise structures, etc.

[0005] In a first aspect, the embodiments of this application provide a method for analyzing the forces on complex components of high-rise structures based on multi-scale model correction, including:

[0006] Obtain the measured data of the dynamic and static force responses of the test components in the high-rise structure over a period of time;

[0007] Calculate the simulated data of the dynamic and static force responses of the test components through the initial finite element model of the test components;

[0008] Determine multiple correction parameters in the initial finite element model according to the relative error between the measured data and the simulated data, and construct a multi-scale finite element model correction and optimization function related to the multiple correction parameters;

[0009] Solve the multi-scale finite element model correction optimization function by using a multi-objective optimization algorithm to obtain the correction values of each of the correction parameters, and use the correction values to correct the initial finite element model to obtain a finite element corrected model;

[0010] Apply an ultra-high wind load based on the finite element corrected model, and analyze and obtain the stress change of the test component.

[0011] In a second aspect, an embodiment of the present application further provides a safety analysis system for high-rise complex components based on model correction, including:

[0012] A data collector, including a plurality of strain sensors for setting at different strain measurement points on the test component and acceleration sensors for setting on different floors, and is used to collect the measured data of the dynamic and static force responses of each of the test components within a period of time;

[0013] A field control box, connected to the data collector, and is used to send the collected measured data to a processor;

[0014] The processor is used to obtain the measured data, and calculate and obtain the simulated data of the dynamic and static force responses of the test component through the initial finite element model of the test component; and, determine a plurality of correction parameters in the initial finite element model according to the relative error between the measured data and the simulated data, and construct a multi-scale finite element model correction optimization function related to the plurality of correction parameters;

[0015] The processor is further used to solve the multi-scale finite element model correction optimization function by using a multi-objective optimization algorithm to obtain the correction values of each of the correction parameters, and use the correction values to correct the initial finite element model to obtain a finite element corrected model; apply an ultra-high wind load based on the finite element corrected model, and analyze and obtain the stress change of the test component.

[0016] In a third aspect, an embodiment of the present application further provides a terminal device, the terminal device includes a processor and a memory, the memory stores a computer program, and the processor is used to execute the computer program to implement the above-mentioned method for analyzing the force of complex components of a high-rise structure based on multi-scale model correction.

[0017] In a fourth aspect, an embodiment of the present application further provides a readable storage medium, which stores a computer program, and when the computer program is executed on a processor, the above-mentioned method for analyzing the force of complex components of a high-rise structure based on multi-scale model correction is implemented.

[0018] The embodiments of the present application have the following beneficial effects:

[0019] The stress analysis method for complex components of high-rise structures based on multi-scale model correction in the embodiments of the present application constructs a multi-scale finite element model correction and optimization function by combining the measured data of the static and dynamic force responses of the corresponding components in the high-rise structure and the simulated data of the static and dynamic force responses obtained from the initial finite element model calculation of the test component; and uses a multi-objective optimization algorithm to solve the optimization function to obtain the corrected values of the structural parameters for correcting the structural parameters of the initial finite element model; finally, the stress change of the test component under the action of the applied wind load is analyzed by using the corrected finite element model, and the obtained stress change analysis result can more truly reflect the stress condition of the actual structure. This method can ensure the accuracy of simulating the structural response based on the corrected finite element model. For example, it can further predict the internal force change of complex components under extreme wind loads such as typhoons once in 50 years, so as to ensure the safe use of high-rise structures under extreme wind loads, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 The flowchart of the stress analysis method for complex components of high-rise structures based on multi-scale model correction in the embodiments of the present application is shown;

[0022] Figure 2 The schematic diagram of calculating the stress simulation value of the finite element model in the embodiments of the present application is shown;

[0023] Figure 3 The flowchart of determining the correction parameters of the finite element model in the embodiments of the present application is shown;

[0024] Figure 4 The flowchart of constructing the multi-scale finite element model correction and optimization function in the embodiments of the present application is shown;

[0025] Figure 5 The plan view of setting the structural monitoring object on the 69th floor of an actual high-rise structure is shown;

[0026] Figures 6(a) and 6(b) respectively show Figure 4 the simplified model of the cantilever truss selected as the test component and the on-site actual installation diagram of the vibrating wire strain gauge in the actual high-rise structure;

[0027] Figures 7(a) and 7(b) respectively showFigure 4 The simplified model of the node selected as the test component in the actual high-rise structure and the on-site actual installation diagram of the vibrating wire strain gauge setting;

[0028] Figure 8 shows the Figure 4 strain data acquisition and monitoring platform for complex components of high-rise structures;

[0029] Figure 9 (a) and Figure 9 (b) respectively show the Figure 4 east-west steady-state diagram and north-south steady-state diagram of the high-rise structure;

[0030] Figure 10 (a) and Figure 10 (b) respectively show the Figure 4 stress nephograms of two selected cantilever truss solid models in;

[0031] Figure 11 (a) and Figure 11 (b) respectively show the Figure 4 stress nephograms of two selected node solid models in;

[0032] Figure 12 shows the structural schematic diagram of the safety analysis system for complex components of high-rise structures based on multi-scale model updating in the embodiments of the present application. Detailed implementation manners

[0033] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments.

[0034] Unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which various embodiments of the present application belong. The terms (such as those defined in a commonly used dictionary) will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized meaning or an overly formal meaning, unless clearly defined in various embodiments of the present application.

[0035] Next, some embodiments of the present application will be described in detail in conjunction with the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0036] The high-rise structure in this application refers to a high-rise building with dozens to hundreds of floors. For such a high-rise structure, it has little impact under some relatively small wind loads in normal times. However, if it encounters strong winds, such as typhoons that occur once in several decades, the structural safety issues need to be considered. The method for analyzing the forces on complex components of a high-rise structure based on multi-scale model correction proposed in this application is based on the dynamic and static response data of the measured complex components, establishes a mathematical problem for correcting the multi-scale finite element of the structure, and realizes the correction of the multi-scale finite element model of the structure through a multi-objective optimization algorithm. Finally, based on the corrected finite element model, by applying ultra-high wind loads such as typhoon levels, the internal force changes of complex components are analyzed, and then it can be used to confirm the safety issues of the high-rise structure under typhoons. For example, when the stress is less than the design strength of the structural material, it can be confirmed that the structure is safe.

[0037] In this application, the multi-scale correction of the structural finite element model is carried out from the overall and local responses of the structure. Among them, the responses reflecting the overall and local structure can be divided into dynamic responses and static responses. For example, the dynamic responses of the structure can include, but are not limited to, frequency and mode MAC values, etc., while the static responses can include, but are not limited to, the displacement, stress / strain of the structure, etc. Among them, the actual dynamic and static responses of the structure can be obtained through sensors installed on the actual structure and field tests, while the response simulation values of the structure are calculated by the structural finite element model, and then the corresponding dynamic and static response simulation values of the structure are directly extracted on the structural model.

[0038] Please refer to Figure 1 , which is a schematic diagram of the main process of the method for analyzing the forces on complex components of a high-rise structure based on multi-scale model correction proposed in an embodiment of this application. Demonstratively, the method for analyzing the forces on complex components of a high-rise structure based on multi-scale model correction includes steps S110 to S150:

[0039] S110, obtain the measured data of the dynamic and static responses of each test component in the high-rise structure within a period of time.

[0040] Demonstratively, some test components can be selected at the corresponding floors of the high-rise structure. For example, the test components can include, but are not limited to, transfer trusses and force-bearing nodes, etc. And a plurality of strain measurement points are respectively arranged on each test component, and a strain sensor, such as a vibrating wire strain gauge, etc., is arranged on each strain measurement point. Each strain sensor is respectively used to collect the actual temperature stress at different positions of the test component in real time. Through the correlation analysis of temperature and stress, this embodiment proposes the concept of temperature stress coefficient, that is, the stress change value when the temperature changes by a unit. Specifically, through the first-order linear regression analysis of the temperature and stress of the normal strain measurement points, the corresponding temperature stress coefficient can be obtained.

[0041] For the dynamic response, in order to obtain the dynamic characteristics of the structure, a distributed synchronous acquisition method can be adopted for modal testing. For example, the synchronous acceleration signals of different floors of the high-rise structure can be obtained by setting acceleration monitors, etc. Then, by analyzing and processing the synchronous acceleration signals, the natural vibration frequency of the structure and the corresponding vibration modes can be obtained. Thus, the measured data of the static and dynamic responses of the test components in the high-rise structure can be obtained.

[0042] S120, the simulated data of the static and dynamic responses of the test component are obtained by calculating the initial finite element model of the test component.

[0043] Among them, the initial finite element model can be constructed according to the relevant structural design parameters of the test component. In this embodiment, by calculating the initial finite element model of the test component, the simulated data of the static and dynamic responses of the test component can be obtained. The simulated data corresponds to the measured data. For example, it can include the simulated values of the temperature stress coefficient, the natural vibration frequency of the structure, and the corresponding vibration modes, etc.

[0044] Since the stress data obtained by the strain gauges installed on site is related to the layout position and direction of the vibrating wire strain gauges, the simulated value of the temperature stress coefficient needs to be determined by considering the layout position and direction of the sensors. Considering that there are many multi-bar interactions and complex geometric shapes in the parts of various complex components in the actual structure, four-node tetrahedral elements are used for the solid elements, and the mesh shape is a triangular mesh. In this embodiment, the average stress of the corresponding nodes on the straight line where the actually installed strain sensors are located is extracted as the stress simulation value, as Figure 2 shown, and then the ratio of the simulated temperature stress to the temperature change of the structural unit is used as the simulated value of the temperature stress coefficient, so as to ensure the accuracy of the obtained simulated value, etc.

[0045] For example, it is known that the length of the vibrating wire strain gauge (i.e., strain sensor) installed on the actual structural component is L M , and the length of the triangular mesh on the constructed refined finite element model is L F , therefore, the number of elements n included in the vibrating wire strain gauge is approximately:

[0046] ;

[0047] Then, along the layout direction of the vibrating wire strain gauge, the stresses of n + 1 nodes on the solid element model are extracted, and the average stress is calculated, and this average stress is used as the simulated value of the measured stress.

[0048] ;

[0049] In the formula, is the stress simulation value corresponding to the layout position of the vibrating wire strain gauge; is the stress value of the i-th node in the solid element model.

[0050] Therefore, the simulated value of the temperature stress coefficient has the following expression:

[0051] ;

[0052] wherein, is the temperature change of the structural element.

[0053] Exemplarily, by separately constructing the initial finite element model for each test component and performing corresponding calculations on the initial finite element model, the simulated values of the dynamic response and static response of each test component can be obtained.

[0054] S130. Determine a plurality of correction parameters in the initial finite element model according to the relative error between the measured data and the simulated data, and construct a multi-scale finite element model correction and optimization function related to the plurality of correction parameters.

[0055] Exemplarily, when the relative error between the measured data and the simulated data of the structural response is large, such as exceeding the preset error range threshold, it is determined that the initial finite element model needs to be corrected. Among them, the error range threshold refers to the allowable deviation range between the actual value and the simulated value. When exceeding this range threshold, it indicates that there is a large error between the simulated value and the actual value.

[0056] Taking the above temperature stress coefficient and the frequency of the structure as an example, when there are large errors between the obtained frequency and temperature stress coefficient of the actual structure and the corresponding simulated values, it is determined that the initially established finite element model needs to be corrected.

[0057] In one implementation manner, as Figure 3 shown, when determining a plurality of correction parameters in the initial finite element model, the following steps S210 to S230 may be included:

[0058] S210. When the relative error between the measured data and the simulated data of the same response exceeds the error range threshold, determine that the current response is a correction target of the initial finite element model.

[0059] For example, according to the relative error magnitudes of each test point in these test components, a plurality of temperature stress coefficients with large errors can be selected as a correction target of the finite element model. If there is also a large error in the frequency of the structure, it can also be used as another correction target, etc. The number of correction targets is not specifically limited here.

[0060] S220, take multiple material parameters that affect the structural response related to each correction target as alternative correction parameters.

[0061] Through analysis, it is known that the response error between the finite element model and the actual structure is mainly caused by material parameter error, structural error, and order error. Among them, the structural error and order error can be minimized as much as possible according to the geometric dimensions of the design drawings and reasonable mesh division. Therefore, in this embodiment, the influence of the structural finite element model parameters on the structural response will be reduced to achieve the purpose of structural finite element correction. Demonstratively, among all the parameters related to the above correction targets, select the material parameters that affect the structural response as alternative correction parameters.

[0062] S230, perform significance analysis on each alternative correction parameter through the joint hypothesis testing method, and take each alternative correction parameter whose significance meets the preset conditions as the required correction parameter.

[0063] Generally, there are many parameters that affect the structural response. If the influence of all parameters on the structural response is considered, it will inevitably increase the calculation scale and correction difficulty. Therefore, in this embodiment, the parameters that are more sensitive to each structural response will be selected from the alternative design parameters as correction parameters. To judge the influence size of each alternative design parameter on the structural response, this article uses the joint hypothesis testing method, also called the F-test method, to perform significance analysis on each alternative design parameter. Through the F-test, it can be judged whether all or part of the alternative design parameters are suitable for correcting the initial finite element model.

[0064] Demonstratively, the process of using the joint hypothesis testing to analyze the significance level of each parameter is as follows:

[0065] (1) Decompose the SST of each structural response into SSB and SSE , and its expression is:

[0066] ;

[0067] ;

[0068] ;

[0069] In the formula, represents the total sum of squared deviations of the l th structural response; represents the sum of squared deviations of the l th structural response caused by the change of the j th correction parameter; represents the sum of squared deviations of the l th structural response caused by the test; denotes the calculated value of the l th structural response in the i th trial; denotes the sum of the structural responses at the same level of each factor; n denotes the number of trials; k denotes the number of repetitions of each factor at each level.

[0070] (2) The degrees of freedom of the total sum of squared deviations of the l th response, the degrees of freedom of the sum of squared deviations caused by the th and i th alternative correction parameters, and the degrees of freedom of the sum of squared deviations caused by the experimental error are:

[0071] ;

[0072] ;

[0073] ;

[0074] wherein, denotes the number of levels of the i th alternative correction parameter.

[0075] (3) Dividing the sum of squared deviations SSB by the degrees of freedom can obtain the variance , and dividing the sum of squared deviations SSE by the degrees of freedom can obtain the variance . The specific expression is:

[0076] ;

[0077] Therefore, the statistic F of the F-test is

[0078] .

[0079] (4) After obtaining the statistical value F , set the significance level to obtain the threshold TH for screening alternative parameters. When F ≥ TH , the significance level of the correction parameter is relatively high and the influence on the structural response is significant. When F ≤ TH , the significance level of the correction parameter is relatively low and the influence on the structural response is not significant. Therefore, only retain the parameters that have a significant influence on the structural response as the final required correction parameters.

[0080] ​For example, in one embodiment, through the above-mentioned significance analysis, the main factors affecting the structural response are found to be the elastic modulus, density, and linear expansion coefficient of the material. Therefore, in this embodiment, these three main factors will be selected as the required correction parameters. It can be understood that in actual applications, fewer or more material parameters that can affect the structure can also be selected for correction according to actual needs, which is not limited here.

[0081] Then, after determining the finally required correction parameters, a multi-scale finite element model correction and optimization function based on these correction parameters can be further constructed. In one embodiment, as Figure 4 shown, the construction of this multi-scale finite element model correction and optimization function includes steps S310 to S340:

[0082] S310, sample points are extracted from the measured data and the simulated data according to a preset experimental design to obtain a preset number of parameter sample points. For example, the preset experimental design may include, but is not limited to, orthogonal design, Box-Behnken Designs design, Latin Hypercube Sampling (LHS), etc.

[0083] S320, respectively use the preset number of parameter sample points as model structure parameters to perform finite element model calculations to obtain multiple sets of static and dynamic response data of the structure corresponding to the preset number of parameter sample points, so as to establish a response surface model between each correction target and the correction parameters.

[0084] The basis for establishing the response surface model of the structure is to extract sample points in the multi-dimensional parameter space composed of significant parameters and obtain the structural responses of each group of sample points through finite element analysis. For example, in one embodiment, Latin Hypercube Sampling is adopted, which is simple to operate and can quickly generate sample groups. Then, using these numbers of parameter sample points for finite element model calculations, the static and dynamic response data of these test components can be obtained. Thus, a response surface model between different correction targets and parameters can be established. Among them, the essence of the fitting of the response surface model is the process of obtaining a response surface function with a better fitting degree from the input correction parameters and the output structural responses.

[0085] It should be noted that in order to ensure the accuracy and efficiency of the constructed response surface model, it is necessary to construct the response surface model according to the characteristics of the structural response. For example, the function used to construct the response surface model can be a power function, a non-linear function, a polynomial function, etc. In this embodiment, a polynomial function is preferably adopted because it can more easily simulate the relationship between the correction parameters and the structural response. In one embodiment, the specific expression form of the second-order polynomial is:

[0086] ;

[0087] In the formula, y represents the response estimated value; represents the structure correction parameter; represents the constant term; represents the coefficient of the first-order term; , are the constant terms of the quadratic term respectively, m represents the number of correction parameters.

[0088] After obtaining the response surface model, in order to judge whether the reliability of the established response surface model meets the standard, its accuracy also needs to be verified. For example, the judgment methods can include the residual mean method, the EISE test method, R 2 the test method, and the relative root mean square error method, etc. In this embodiment, the R 2 test method and the relative root mean square error (RMSE) method will be used to evaluate the accuracy of the response surface model. Among them, R 2 the closer the

[0089] S330, establish the error function of each correction target according to the measured data and the simulated data respectively.

[0090] Exemplarily, after obtaining the actual structural response and the simulated structural response of the static and dynamic forces and determining the correction target, the error functions of the dynamic response and the static response of the structure can be established by using the measured data and the simulated data corresponding to each correction target respectively. For example, in one implementation, the established error functions of the dynamic response and the static response are respectively:

[0091] ;

[0092] ;

[0093] In the formula, represents the error function of the structural dynamic response, represents the error function of the structural static response, and respectively represent the monitored values of the dynamic response and the static response of the actual structure; and respectively represent the simulated values of the dynamic response and the static response of the structural finite element model; k and p respectively represent the number of structural dynamic responses and the number of structural static responses.

[0094] S340. Based on the response surface model and the error functions of each correction target, an expression of the multi-scale finite element model correction optimization function is constructed. Among them, the constraint conditions of the optimization function include setting the value range of each correction parameter to a preset multiple of the reference value.

[0095] Since the positive and negative signs of the calculated error functions are uncertain, when directly integrating the errors, the situation where the errors cancel each other out will occur. Therefore, before integrating the same type of data, it is necessary to take the absolute value of the calculated errors. Thus, according to the above various error functions, the objective function for the multi-scale model correction problem can be:

[0096] ;

[0097] ;

[0098] In the formula, is the objective correction function composed of the structural dynamic response error function; is the objective correction function composed of the structural static response error function.

[0099] Among them, the finite element parameters mainly refer to the elastic modulus, density, and linear expansion coefficient. To ensure that the structural material parameters have actual physical meanings, the change range of each material parameter is set to a preset multiple of the reference value, such as 0.8 - 1.2 times, etc., and can be specifically set according to actual needs.

[0100] The multi-scale finite element model correction is actually to solve a multi-objective optimization problem with constraint conditions. Taking the above 0.8 - 1.2 times as an example, the expression of the multi-scale finite element model correction optimization function obtained is:

[0101] ;

[0102] In the formula, r represents the number of correction parameters, represents the r th reference value of the material correction parameter.

[0103] It can be understood that the numerical values 0.8 and 1.2 in the above optimization function are only a preferred example. As long as the values are taken near the reference value of the parameter, such as 0.75, 1.21, 1.25, etc., they should all be within the protection scope of this application.

[0104] S140. Use the multi-objective optimization algorithm to solve the multi-scale finite element model correction optimization function, obtain the correction values of each correction parameter, and use the correction values to correct the initial finite element model to obtain the finite element corrected model.

[0105] Since the above-mentioned multi-scale model correction problem can be reduced to a multi-objective optimization problem with constraints, there are conflicts due to the inconsistency of each sub-objective in each objective function in the optimization direction, and it is impossible to find a unique set of parameters that makes each sub-objective optimal at the same time. Instead, there is a Pareto non-dominated solution set. In this embodiment, the Pareto non-dominated solution set will be preferentially solved by using the multi-objective particle swarm optimization algorithm (MOPSO). Among them, the unique feature of the particle swarm optimization algorithm lies mainly in that it updates the position of the particles by combining global update and individual update, and has both global optimization and local optimization capabilities. The particle swarm optimization algorithm has the advantages of easy implementation, high accuracy, fast convergence, etc., and has shown its superiority in solving practical problems.

[0106] Exemplarily, after optimizing and solving the optimization function, the correction values of each correction parameter can be obtained. Furthermore, by correcting these correction parameters, a corrected finite element model can be obtained, that is, the above-mentioned finite element correction model.

[0107] S150, based on the finite element correction model, apply the action of super strong wind load, and analyze the stress change of the test member.

[0108] Exemplarily, by applying super strong wind loads such as typhoons once in 50 years to the corrected structural finite element model, the corresponding stress nephogram can be analyzed to reflect the stress change of the physical model under the load combination. It can be understood that by combining the measured data of the static and dynamic responses to correct the initially constructed finite element model, the stress change results analyzed based on the corrected model can be made more accurate and more in line with the true state of the actual high-rise structure, etc.

[0109] Further optionally, based on the stress change situation, verify the safety of the structure in some extreme environments, etc. For example, judge whether the maximum stress of the test member at this time exceeds the design strength of the structure. If it is less, it can be confirmed that the structure is safe under the action of the applied super strong wind load. Otherwise, there may be safety problems.

[0110] To verify the effectiveness of the stress analysis method for complex components of high-rise structures based on multi-scale model correction in this application, the safety analysis of a certain high-rise structure will be carried out below. The high-rise structure is subjected to the action of temperature and wind loads during the operation state, and there are uncertainties in the internal forces and deformations of the cantilever truss and joints. In order to study the internal force changes of the cantilever truss and joints of the high-rise structure under environmental actions, a continuous online monitoring system for synchronous strain acquisition of the cantilever truss and joints of the high-rise structure is designed. Considering the needs of the construction stage and the long-term operation stage, based on the MIDAS finite element model established in the construction stage, the stress states of the cantilever truss and joints of the high-rise structure are analyzed. Considering economic factors and other issues, finally, the cantilever trusses H1 and H2, and the joints J1 and J2 are selected as the monitoring objects, as Figure 5 shown.

[0111] For the cantilever truss structure, to determine the layout positions of vibrating wire strain gauges on the cantilever truss, the cantilever truss is simplified, a simplified finite element model is established, and the internal force distribution of the cantilever truss is analyzed. The simplified model of the cantilever truss is shown in Figure 6(a). Furthermore, based on the preliminary analysis results of the simplified model of the cantilever truss and combined with the actual on-site installation conditions, as shown in Figure 6(b), the distribution diagram of vibrating wire strain gauges for a single cantilever truss is designed. The statistical distribution of measuring points for a single cantilever truss is shown in Table 1.

[0112] Table 1 Statistical distribution of measuring points for a single cantilever truss

[0113]

[0114] For the joint, to determine the layout positions of strain gauges on the joint, a simplified finite element model of the joint is established, and the internal force of the joint is analyzed. Its simplified model is shown in Figure 7(a). Furthermore, based on the preliminary calculation results of the simplified model of the joint and combined with the specific on-site conditions, as shown in Figure 7(b), the distribution diagram of vibrating wire strain gauges for a single joint is designed. The statistical distribution of strain measuring points for a single joint is shown in Table 2.

[0115]

[0116] Therefore, according to the layout schemes of all strain measuring points, 3 strain acquisition sub-stations are set up. The acquisition boxes of each acquisition sub-station are wirelessly transmitted to the remote cloud platform control center to form a data acquisition and monitoring platform, as Figure 8As shown in the figure. This system consists of a cloud platform, a field control box, a data transmission module, and a data collector. Among them, the data collector is connected to each strain sensor and is used to collect data. The cloud platform adopts an automated data collection platform developed based on the MySQL database and uses the front-end and back-end separation technology, which can store, visually display, analyze, and export data. At the same time, by calculating the initial finite element models of the cantilever truss and each node above, the simulated values of the temperature stress coefficients of the cantilever truss and the nodes can be obtained.

[0117] In order to obtain the structural dynamic characteristic parameters of this high-rise structure during operation, in this embodiment, a modal test is carried out on this high-rise structure. Specifically, an acceleration monitor and GeoDAS software can be used to obtain the synchronous acceleration signals of the structure, and by analyzing the synchronous acceleration signals, the dynamic characteristic parameters such as the natural vibration frequency and vibration mode of this high-rise structure can be obtained.

[0118] In July 2021, a modal test was carried out on this high-rise structure based on the distributed synchronous acquisition method. Among them, the monitors are respectively arranged on the 9th, 19th, 35th, 54th, 71st floors of the main structure, the 3rd, 6th floors and the top floor of the top steel structure. An earthquake monitor is arranged in the X and Y directions of the structure at the outer frame corner points of each floor, and a total of 16 measuring points are arranged. The sampling duration of each group of data is 10 min, and the sampling frequency is 100 Hz. Among them, the fixed reference point is set at a certain measuring point on the top of the steel frame, and a mobile monitor is used for other measuring points to obtain the synchronous acceleration signals of different floors of the structure. By carrying out a field modal test on this high-rise structure, the acceleration response time-domain signal of this high-rise structure under the operating state can be obtained. Furthermore, the east-west and north-south steady-state diagrams of this high-rise structure obtained by processing the acceleration signals using the SSI-COV method are shown in Figures 9(a) and 9(b), and the first 6-order modal frequencies of the structure are obtained. In addition, according to the calculation of the relative vibration mode values of each floor using the covariance-driven stochastic subspace method, the vibration mode diagrams of the first six orders can be obtained.

[0119] According to the natural vibration frequencies and the simulated values of the temperature stress coefficients calculated from the initial finite element model of this high-rise structure, it is found that there are large errors between them and the frequencies and temperature stress coefficients of the actual structure. Among them, the relative errors of the first 6-order frequencies all exceed 8%, and most of the relative errors of the temperature stress coefficients of the cantilever truss and the nodes exceed 10%, and the maximum error of the temperature stress coefficient reaches 21.17%. Therefore, it is very necessary to correct the initially established finite element model.

[0120] Since the influence of temperature on frequency is relatively small, the influence of temperature on frequency is not considered. Moreover, this high-rise structure is located in Shenzhen and is greatly affected by typhoons. The first order dominates under the action of typhoons. Therefore, the first 6 natural frequencies of the structure are selected as the correction targets for the overall structural scale. According to the error analysis results, 3 temperature stress coefficients are selected on each cantilever truss and 2 temperature stress coefficients are selected on each node, a total of 10 temperature stress coefficients with larger errors are used as the correction targets for the local scale.

[0121] Thus, based on the measured data and the simulated data, the error functions of the correction targets such as the natural frequencies of the structure, the temperature stress coefficients of the cantilever trusses and the nodes can be constructed. Considering that the main factors affecting the structure are the elastic modulus, density and linear expansion coefficient of the material, here the multi-scale finite element model of the high-rise structure is mainly corrected by modifying the elastic modulus, density and linear expansion coefficient of the structural material. It should be noted that in this embodiment, a total of 33 material properties are selected as the alternative correction parameters for the correction of the high-rise structure, and 20 correction parameters required are determined through significance analysis. The value ranges of these 20 correction parameters are set to 0.8 - 1.2 times the initial values. According to the Latin hypercube test method, the experimental design is carried out to obtain 300 sets of structural parameter sample points; these 300 sets of structural parameter sample points are respectively used as model parameters for finite element model calculation. Through calculation, the first 6 natural frequencies of the structure, 6 temperature stress coefficients of the cantilever trusses and 4 temperature stress coefficients of the nodes corresponding to the 300 sets of sample points can be obtained, and 300 sets of structural response values corresponding to each set of sample points are obtained. Response surface function models between the correction targets and the parameters are established for different correction targets. Using the 2 R test method and the relative root mean square error method (RMSE) to conduct error tests on the true values and estimated values of each correction target.

[0122] Therefore, according to the established response surface model and the error functions of each correction target, with the domain of each parameter limited to 0.8 - 1.2 times the reference value, the following multi-scale finite element model correction and optimization function of the high-rise structure can be constructed:

[0123] ;

[0124] In the formula, is the sub-target composed of the frequency error function, is the sub-target composed of the temperature stress coefficient error function of the cantilever truss, is the sub-target composed of the temperature stress coefficient error function of the node; is the i th elastic modulus parameter to be corrected; is the reference value of the i th elastic modulus parameter to be corrected; is the jA density parameter to be corrected; is the j benchmark value of the density parameter to be corrected; is the k linear expansion coefficient parameter to be corrected; is the k benchmark value of the linear expansion coefficient parameter to be corrected; is the number of elastic modulus correction parameters; is the number of density correction parameters; is the number of linear expansion coefficient correction parameters.

[0125] Next, the multi-objective particle swarm optimization algorithm is used to solve the multi-objective optimization function constructed above to realize the multi-scale model correction of the high-rise structure. Combining with empirical values, the MOPSO parameter values are set as population size 1000, non-dominated solution set 1000, mutation probability 0.1, and maximum iteration number 1000. After iterative calculation, 982 groups of Pareto solutions are obtained. Select the group of solutions that minimizes the maximum value of each sub-objective in the Pareto solution set as the parameter correction value, and finally obtain a group of correction parameters optimized by the multi-objective particle swarm. Finally, apply the correction parameters to the initial finite element model of the high-rise structure, extract the simulated values of 16 correction objectives of the model before and after correction and compare them with the measured values, calculate the relative error before and after correction, and obtain that the relative error of the simulated frequency of the corrected structure is less than 5%, and the calculation accuracy of the natural vibration frequency has been greatly improved. The MAC values of the vibration modes are checked, and the MAC values of the vibration modes all exceed 0.99. The relative error of the temperature stress coefficient of the corrected model is less than 10%, and the maximum relative error is reduced from 21.171% to 9.117%. Therefore, it is considered that the corrected model can accurately simulate the dynamic and static responses of the structure.

[0126] Finally, by applying wind load to the finite element model of the corrected high-rise structure, the calculation results of the corrected finite element model are combined with corresponding loads, and the stress changes of the cantilever truss solid model under the load combination are calculated and analyzed. Under the load combination of 1.2 dead load + 1.4 wind load, the stress nephograms of the cantilever truss solid models H1 and H2 are shown in Figures 10(a) and 10(b) respectively, and the maximum stress conditions of the cantilever trusses H1 and H2 are shown in Table 3.

[0127] Table 3 Maximum stress change values of the cantilever truss solid elements

[0128]

[0129] By analyzing the node entity model, under the load combination of 1.2 dead load + 1.4 wind load, the stress nephograms of the node entity models of J1 and J2 are shown in Figures 11(a) and 11(b) respectively. The maximum stresses of the node entity models of J1 and J2 in the maximum stress condition are shown in Table 4. The maximum stress of the calculation result of the node under the action of the 1.2 dead load + 1.4 wind load combination is 235.50 MPa, and the stress level is lower than 0.8 times the yield strength of the used steel Q345B.

[0130] Table 5-4 Maximum stress change values of node entity elements

[0131]

[0132] In summary, through the above analysis of the cantilever truss and nodes, the stresses of the cantilever truss and nodes are both less than 0.8 times the yield strength of Q345B. Therefore, it can be shown that the cantilever truss and nodes are safe under typhoon action.

[0133] The method for analyzing the forces on complex components of high-rise structures based on multi-scale model correction in the embodiments of the present application takes the high-rise structure in the operating state as the research object, constructs the multi-scale finite element correction data problem of the high-rise structure based on the measured dynamic and static responses of multiple test components, selects the parameters to be corrected through significance analysis according to orthogonal experiments and F-tests, designs the structural sample parameters by using methods such as the LHS method, establishes a response surface model between the structural response and the correction parameters and verifies the model accuracy, and also combines the multi-objective particle swarm optimization algorithm to determine the optimal structural parameters to achieve model correction. Finally, according to the corrected structural finite element model, apply the wind load with a return period of 50 years specified by the code, and analyze the internal force changes of the complex components and nodes, so as to accurately verify the safety of the complex components of the high-rise structure and ensure the safety of the structure.

[0134] Please refer to Figure 12 , based on the method of the above embodiments, this embodiment proposes a system 100 for analyzing the forces on complex components of high-rise structures based on multi-scale model correction. Exemplarily, the force analysis system 100 includes:

[0135] A data collector 110, connected to a plurality of strain sensors 101 arranged at different strain measurement points on the test components in the high-rise structure and acceleration sensors 102 arranged on different floors, for collecting the measured data of the dynamic and static responses of the test components over a period of time.

[0136] The on-site control box 120 is connected to the data collector 110 and is used to send the collected measured data to the processor 130. For example, the processor 130 may refer to the processor in a directly-on-site laptop computer, or may be a processor sent to a remote computer through network modules such as 3G / 4G / 5G. Here, the form and location of the processor 130 are not limited.

[0137] The processor 130 is used to obtain the measured data and calculate the simulated data of the dynamic and static force responses of the test component through the initial finite element model of the test component; and, according to the relative error between the measured data and the simulated data, determine multiple correction parameters in the initial finite element model, and construct a multi-scale finite element model correction and optimization function related to the multiple correction parameters.

[0138] The processor 130 is further used to solve the multi-scale finite element model correction and optimization function by using a multi-objective optimization algorithm, obtain the correction values of each correction parameter, and correct the initial finite element model by using the correction values to obtain a finite element correction model; based on the finite element correction model, apply an ultra-high wind load, and analyze the stress change of the test component.

[0139] It can be understood that the system in this embodiment corresponds to the method in the above embodiment, and the optional items in the above embodiment are also applicable to this embodiment, so they will not be repeated here.

[0140] The present application also provides a terminal device, such as a desktop computer, a notebook, a remote server, etc. Exemplarily, the terminal device includes a processor and a memory. Among them, the memory stores a computer program, and the processor runs the computer program to enable the terminal device to execute the above-mentioned method for analyzing the force on complex components of a high-rise structure based on multi-scale model correction or the functions of the processor in the above-mentioned force analysis system.

[0141] The present application also provides a readable storage medium for storing the computer program used in the above terminal device.

[0142] In several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and structure diagrams in the accompanying drawings show the possible architectures, functions, and operations of devices, methods, and computer program products according to multiple embodiments of this application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the part of the module, program segment, or code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in an alternative implementation, the functions marked in the blocks can occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the structure diagram and / or flowchart, as well as the combination of blocks in the structure diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0143] In addition, each functional module or unit in various embodiments of this application can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0144] If the above-mentioned functions are implemented in the form of software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0145] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered by the protection scope of this application.

Claims

1. A method for analyzing the force of complex components in high-rise structures based on multi-scale model correction, characterized in that Including: Obtaining the measured data of the dynamic and static force responses of the test component in the high-rise structure over a period of time; Calculating the simulated data of the dynamic and static force responses of the test component through the initial finite element model of the test component; Determining multiple correction parameters in the initial finite element model according to the relative error between the measured data and the simulated data, and constructing a multi-scale finite element model correction and optimization function related to the multiple correction parameters; Using a multi-objective optimization algorithm to solve the multi-scale finite element model correction and optimization function, obtaining the corrected values of each correction parameter, and using the corrected values to correct the initial finite element model to obtain a finite element corrected model; Based on the finite element corrected model, applying an ultra-high wind load, and analyzing the stress change of the test component; Among them, determining the multiple correction parameters in the initial finite element model includes: When the relative error between the measured data and the simulated data of the same response exceeds the error range threshold, determining the current response as a correction target of the initial finite element model; taking multiple material parameters that affect the structural response related to each correction target as alternative correction parameters; performing significance analysis on each alternative correction parameter through a joint hypothesis testing method, and taking each alternative correction parameter whose significance meets the preset conditions as the required correction parameter; the correction targets include the temperature stress coefficient of the test component and the structural frequency of the high-rise structure; Among them, the multi-scale finite element model correction and optimization function includes: ； Wherein, is a sub-goal composed of a frequency error function, is a sub-goal composed of a temperature stress coefficient error function of a cantilever truss, is a sub-goal composed of a temperature stress coefficient error function of a node; is the i th elastic modulus parameter to be corrected; is the reference value of the i th elastic modulus parameter to be corrected; is the j th density parameter to be corrected; is the reference value of the j th density parameter to be corrected; is the k th linear expansion coefficient parameter to be corrected; is the reference value of the k th linear expansion coefficient parameter to be corrected; is the number of elastic modulus correction parameters; is the number of density correction parameters; is the number of linear expansion coefficient correction parameters.

2. The force analysis method according to claim 1, wherein The multiple material parameters include the elastic modulus, density, and linear expansion coefficient of the test component.

3. The force analysis method according to claim 2, wherein A plurality of strain measurement points are provided on the test component, and a strain sensor is arranged at each strain measurement point; obtaining the measured data of the dynamic and static force responses of the test component in the high-rise structure over a period of time includes: Collecting the actual values of the temperature stress coefficients at different positions of the test component through each strain sensor, and monitoring the structural response of the high-rise structure over a period of time based on a distributed synchronous acquisition system to obtain the actual structural frequency of the high-rise; Obtaining the simulated data of the dynamic and static force responses of the test component includes: Adopting a triangular grid design for the initial finite element model of the test component, extracting the average stress of the corresponding nodes on the straight line where the actually arranged strain sensors are located as the simulated temperature stress, and using the ratio of the simulated temperature stress to the temperature change amount of the structural unit as the simulated value of the temperature stress coefficient; Performing a modal analysis on the initial finite element model of the test component to obtain the simulated structural frequency.

4. The force analysis method according to claim 1, characterized in that, Constructing a multi-scale finite element model correction and optimization function related to the multiple correction parameters includes: Sampling sample points from the measured data and the simulated data according to a preset experimental design to obtain a preset number of parameter sample points; Taking the preset number of parameter sample points as model structure parameters respectively to perform finite element model calculations, obtaining multiple groups of dynamic and static force response data of the structures corresponding to the preset number of parameter sample points, so as to establish a response surface model between each correction target and the correction parameters; An error function for each correction target is established according to the measured data and the simulated data respectively. According to the response surface model and the error functions of each correction target, an expression of the multi-scale finite element model correction optimization function is constructed, wherein the constraint conditions of the optimization function include setting the value range of each correction parameter to a preset multiple of the reference value.

5. The force analysis method according to claim 4, characterized in that The response surface model is constructed using a polynomial function, and the accuracy of the constructed response surface model is verified by the R 2 -test method and the relative root mean square error method; The preset experimental design adopts the Latin hypercube experimental design.

6. The force analysis method according to any one of claims 1 to 5, characterized in that The multi-objective optimization algorithm is a multi-objective particle swarm optimization algorithm.

7. A force analysis system for complex components of high-rise structures based on multi-scale model correction, characterized in that, It includes: A data collector, connected to a plurality of strain sensors arranged at different strain measurement points on the test member and acceleration sensors used to be arranged on different floors, for collecting the measured data of the dynamic and static force responses of each test member within a period of time. A field control box, connected to the data collector, for sending the collected measured data to the processor. The processor is used to obtain the measured data and calculate the simulated data of the dynamic and static force responses of the test member through the initial finite element model of the test member. And, according to the relative error magnitude between the measured data and the simulated data, determine multiple correction parameters in the initial finite element model, and construct a multi-scale finite element model correction optimization function related to the multiple correction parameters. The processor is further used to solve the multi-scale finite element model correction optimization function by using a multi-objective optimization algorithm, obtain the correction value of each correction parameter, and correct the initial finite element model by using the correction value to obtain a finite element corrected model. Based on the finite element corrected model, apply an ultra-high wind load, and analyze the stress change of the test member. Among them, determining multiple correction parameters in the initial finite element model includes: When the relative error between the measured data and the simulated data of the same response exceeds the error range threshold, determine the current response as a correction target of the initial finite element model; use multiple material parameters affecting the structural response related to each correction target as alternative correction parameters; perform significance analysis on each alternative correction parameter by the joint hypothesis testing method, and use each alternative correction parameter whose significance meets the preset conditions as the required correction parameter; the correction targets include the temperature stress coefficient of the test member and the structural frequency of the high-rise structure. Among them, the multi-scale finite element model correction optimization function includes: ； In the formula, is the sub-goal composed of the frequency error function, is the sub-goal composed of the temperature stress coefficient error function of the cantilever truss, is the sub-goal composed of the temperature stress coefficient error function of the node; is the i th elastic modulus parameter to be corrected; is the reference value of the i th elastic modulus parameter to be corrected; is the j th density parameter to be corrected; is the reference value of the j th density parameter to be corrected; is the k th linear expansion coefficient parameter to be corrected; is the reference value of the k th linear expansion coefficient parameter to be corrected; is the number of elastic modulus correction parameters; is the number of density correction parameters; is the number of linear expansion coefficient correction parameters.

8. A terminal device, characterized in that, The terminal device includes a processor and a memory, the memory stores a computer program, and the processor is used to execute the computer program to implement the method for analyzing the force on complex members of a high-rise structure based on multi-scale model correction according to any one of claims 1-6.

9. A readable storage medium, characterized in that, It stores a computer program, and when the computer program is executed on the processor, it implements the method for analyzing the force on complex members of a high-rise structure based on multi-scale model correction according to any one of claims 1-6.

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