CN115455793A - High-rise structure complex component stress analysis method based on multi-scale model correction - Google Patents
High-rise structure complex component stress analysis method based on multi-scale model correction Download PDFInfo
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Abstract
The method comprises the steps of obtaining actual measurement data of dynamic and static force response of a corresponding test component in a high-rise structure and simulation data of the dynamic and static force response obtained by calculation based on an initial finite element model; constructing a multi-scale finite element model correction optimization function of the component according to the relative error between the measured data and the simulated data; correcting the initial finite element model by utilizing a multi-objective optimization algorithm; and finally, analyzing the stress change condition of the component under the action of the super wind load based on the corrected finite element model. The method can ensure the accuracy of the response of the simulated structure based on the corrected finite element model, and further confirm the safety of the high-rise actual structure under the action of the super wind load and the like.
Description
Technical Field
The application relates to the technical field of high-rise structure internal force analysis, in particular to a high-rise structure complex component stress analysis method based on multi-scale model correction.
Background
Under the action of a complex environment, a complex component in a high-rise structure is usually stressed complexly, the distribution and the change of the internal force of the component cannot be accurately reflected through numerical simulation, and although the local complex working state of a conversion structure can be directly reflected through real structural response obtained through actual monitoring of the structure, the local complex working state of the conversion structure is limited by the number of sensors, and complete response information cannot be obtained. It is therefore necessary to simulate the actual behaviour of the structure by means of a finite element model.
The finite element model of the structure is usually constructed by simplifying and assuming the geometric characteristics, material parameters, boundary conditions, and other conditions of the actual structure in the construction process according to the design drawing. However, due to uncertainty of the structure in the construction process, deviation often exists between the finite element model of the structure and the actual engineering structure. At this time, if the structural finite element model constructed by the method is directly used for stress change analysis under wind loads such as typhoon, a large error exists between simulated structural response and actual structural response, so that whether the actual structure is safe under super wind loads such as typhoon cannot be determined according to a simulated stress analysis result.
Disclosure of Invention
In view of this, the embodiment of the present application provides a method for analyzing stress of a complex member of a high-rise structure based on multi-scale model correction, which can ensure accuracy of structural response simulation based on a finite element model, so as to accurately analyze the safety problem of the high-rise structure.
In a first aspect, an embodiment of the present application provides a method for analyzing stress of a high-rise complex component based on multi-scale model correction, including:
acquiring actual measurement data of dynamic and static force response of a test component in a high-rise structure within a period of time;
calculating to obtain simulation data of dynamic and static responses of the test component through the initial finite element model of the test component;
determining a plurality of correction parameters in the initial finite element model according to the relative error between the actually measured data and the simulated data, and constructing a multi-scale finite element model correction optimization function related to the correction parameters;
solving the multi-scale finite element model correction optimization function by using a multi-objective optimization algorithm to obtain a correction value of each correction parameter, and correcting the initial finite element model by using the correction value to obtain a finite element correction model;
and analyzing and obtaining the stress change of the test component based on the effect of applying the ultra-large wind load by the finite element correction model.
In a second aspect, an embodiment of the present application further provides a system for analyzing safety of a high-rise complex component based on model modification, including:
the data acquisition unit comprises a plurality of strain sensors arranged on different strain measuring points on the testing component and acceleration sensors arranged on different floors and is used for acquiring the actual measurement data of the dynamic and static response of each testing component in a period of time;
the field control box is connected with the data acquisition unit and is used for sending the acquired actually measured data to the processor;
the processor is used for acquiring the measured data and calculating to obtain simulation data of dynamic and static response of the test component through an initial finite element model of the test component; determining a plurality of correction parameters in the initial finite element model according to the relative error magnitude between the measured data and the simulation data, and constructing a multi-scale finite element model correction optimization function related to the correction parameters;
the processor is further used for solving the multi-scale finite element model correction optimization function by using a multi-objective optimization algorithm to obtain a correction value of each correction parameter, and correcting the initial finite element model by using the correction value to obtain a finite element correction model; and analyzing and obtaining the stress change of the test component based on the effect of applying the ultra-large wind load by the finite element correction model.
In a third aspect, an embodiment of the present application further provides a terminal device, where the terminal device includes a processor and a memory, where the memory stores a computer program, and the processor is configured to execute the computer program to implement the above-mentioned method for analyzing stress of a high-rise complex component based on multi-scale model modification.
In a fourth aspect, an embodiment of the present application further provides a readable storage medium, which stores a computer program, where the computer program, when executed on a processor, implements the method for analyzing stress of a high-rise complex structural component based on multi-scale model modification.
The embodiment of the application has the following beneficial effects:
the stress analysis method of the high-rise structure complex component based on the multi-scale model modification comprises the steps of constructing a multi-scale finite element model modification optimization function of a test component by combining actual measurement data of dynamic and static response of corresponding components in a high-rise structure and simulation data of dynamic and static response obtained by calculating an initial finite element model of the test component; solving the optimization function by using a multi-objective optimization algorithm to obtain a modified value of the structural parameter, wherein the modified value is used for modifying the structural parameter of the initial finite element model; and finally, analyzing by using the corrected finite element model to obtain the stress change of the test member under the action of the applied wind load, wherein the stress change analysis result obtained at the moment can reflect the stress condition of the actual structure more truly. The method can ensure the accuracy of the simulation structure response based on the corrected finite element model, for example, the internal force change condition of the complex component under the action of the super-wind load such as typhoon in one fifty years can be further predicted, so that the safe use of the high-rise structure under the action of the super-wind load is ensured, and the like.
Drawings
To more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
FIG. 1 is a schematic flow chart illustrating a method for analyzing stress of a high-rise complex component based on multi-scale model modification according to an embodiment of the present application;
FIG. 2 is a diagram illustrating a stress simulation value of a finite element model according to an embodiment of the present application;
FIG. 3 is a flow chart illustrating a process of determining correction parameters of a finite element model according to an embodiment of the present application;
FIG. 4 is a flow chart illustrating the construction of a multi-scale finite element model modification optimization function according to an embodiment of the present application;
FIG. 5 is a schematic plan view of a structure monitoring object placed at level 69 of a practical high-level structure;
FIGS. 6 (a) and 6 (b) are diagrams illustrating, respectively, a simplified model of an overhanging truss selected as a test member and an actual field installation of a vibrating wire strain gauge arrangement in the actual high-rise structure of FIG. 4;
FIGS. 7 (a) and 7 (b) are diagrams illustrating, respectively, a simplified model of the actual high-rise structure of FIG. 4, selected as a node of the test member, and the actual installation in the field of the vibrating wire strain gauge arrangement;
FIG. 8 illustrates a strain data acquisition monitoring platform for the high-rise structural complex member of FIG. 4;
FIGS. 9 (a) and 9 (b) show east-west and north-south steady-state diagrams, respectively, of the high-level structure of FIG. 4;
fig. 10 (a) and 10 (b) respectively show stress clouds for two solid models of cantilever trusses selected from fig. 4;
FIGS. 11 (a) and 11 (b) show stress clouds for two selected node solid models of FIG. 4, respectively;
fig. 12 is a schematic structural diagram illustrating a security analysis system for a high-level structural complex component based on multi-scale model modification according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of the present application belong. The terms (such as those defined in commonly used dictionaries) should be interpreted as having a meaning that is consistent with their contextual meaning in the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in various embodiments.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
The high-rise structure in the application refers to a high-rise building with dozens of floors to hundreds of floors, such as Shenzhen's Ping's International finance center, jingji 100 building, dabaihui building, diwang building and the like. For such high-rise structure, there is basically no great influence under the action of small wind loads at ordinary times, however, if the high wind with strong wind power, such as typhoon in decades, is encountered, the safety problem of the structure needs to be considered. The stress analysis method of the high-rise structure complex component based on the multi-scale model correction is based on dynamic and static response data of an actually measured complex component, a structure multi-scale finite element correction mathematic problem is established, correction of the structure multi-scale finite element model is achieved through a multi-objective optimization algorithm, and finally, based on the corrected finite element model, the internal force change condition of the complex component is analyzed by applying the super-high wind load effect of the typhoon level and the like, and therefore the stress analysis method can be used for confirming the safety problem of the high-rise structure under the typhoon and the like. For example, when the stress would be less than the design strength of the structural material, then the structure can be confirmed to be safe.
In the application, the multi-scale modification of the finite element model of the structure is carried out from the whole and local responses of the structure, wherein the responses reflecting the whole and local responses of the structure can be divided into dynamic responses and static responses. For example, the dynamic response of a structure may include, but is not limited to, frequency and mode MAC values, etc., while the static response may include, but is not limited to, displacement, stress/strain, etc., of a structure. The actual dynamic and static force response of the structure can be obtained through a sensor arranged on the actual structure and a field test, the response simulation value of the structure is calculated through a finite element model of the structure, and then the corresponding response simulation values of the structure dynamic force and the static force are directly extracted from the structure model.
Please refer to fig. 1, which is a main flowchart of a method for analyzing stress of a high-rise complex component based on multi-scale model modification according to an embodiment of the present application. Exemplarily, the method for analyzing stress of the high-rise complex structural component based on the multi-scale model correction comprises steps S110 to S150:
s110, actual measurement data of dynamic and static responses of each test component in the high-rise structure in a period of time are obtained.
Exemplarily, some test members may be selected at corresponding floors of the high-rise structure, for example, the test members may include, but are not limited to, a conversion truss, a stress node, and the like, and each test member is provided with a plurality of strain measurement points, each strain measurement point is provided with a strain sensor, such as a vibrating wire strain gauge, and each strain sensor is used for acquiring an actual temperature stress at different positions of the test member in real time. By performing correlation analysis on temperature and stress, the present embodiment proposes a concept of a temperature stress coefficient, that is, a stress change value per unit temperature change. Specifically, a first-order linear regression analysis is performed on the temperature and stress of the normal strain measuring point, so that a corresponding temperature stress coefficient can be obtained.
For the dynamic response, in order to obtain the dynamic characteristics of the structure, a modal test may be performed by using a distributed synchronous acquisition method, for example, an acceleration monitor may be provided to obtain synchronous acceleration signals of different floors of the high-rise structure within a period of time, and then the synchronous acceleration signals may be analyzed and processed to obtain the natural frequency and the corresponding order mode of the structure. Thus, the measured data of the static and dynamic responses of the test member in the high-rise structure can be obtained.
And S120, calculating the initial finite element model of the test component to obtain simulation data of the dynamic and static force response of the test component.
The initial finite element model can be constructed according to relevant structural design parameters of the test component. In this embodiment, the simulation data of the dynamic and static response of the test component can be obtained by calculating the initial finite element model of the test component. The simulation data corresponds to the measured data and may include, for example, simulation values of temperature stress coefficients, natural frequency of vibration of the structure, and corresponding vibration modes.
Since the strain data acquired by the strain gauges installed on site is related to the arrangement position and the arrangement direction of the vibrating wire strain gauges, the analog value of the temperature stress coefficient needs to be determined in consideration of the arrangement position and the arrangement direction of the sensors. In consideration of the fact that the complex structural elements in the actual structure are multi-rod interactive and have complex geometric shapes, the entity units all adopt four-node tetrahedral units, and the grid shape of the four-node tetrahedral units is a trilateral grid.
For example, it is known that a vibrating wire strain gauge (i.e., a strain sensor) disposed on an actual structural member has a length L M And the length of the trilateral mesh on the finite element refinement model is L F Therefore, the number of elements n included in the range of the vibrating wire strain gauge is approximately:
n＝L M /L F ；
then, the node stresses of n +1 in the solid unit model are extracted along the arrangement direction of the vibrating wire strain gauges, the stress average value is calculated, and the stress average value is used as the simulation value of the actually measured stress.
In the formula, σ s The stress analog value is the stress analog value corresponding to the arrangement position of the vibrating wire strain gauge; sigma si Is a solid unit moduleStress value of the ith node in the model.
Therefore, the temperature stress coefficient analog value σ ΔT The expression of (a) is:
σ ΔT ＝σ s /ΔT；
in the formula, Δ T is a temperature change amount of the structural unit.
Exemplarily, initial finite element model construction is performed on each test component, and corresponding calculation is performed on the initial finite element model, so that simulated values of dynamic response and static response of each test component can be obtained.
S130, determining a plurality of correction parameters in the initial finite element model according to the relative error magnitude between the actual measurement data and the simulation data, and constructing a multi-scale finite element model correction optimization function related to the correction parameters.
Exemplarily, when the relative error between the measured data and the simulated data for calculating the structural response is large, if the relative error exceeds a preset error range threshold, it is determined that the initial finite element model needs to be modified. The error range threshold refers to a deviation range between an allowable actual value and an allowable analog value. When the range threshold is exceeded, a large error between the simulated value and the actual value is indicated.
Taking the temperature stress coefficient and the frequency of the structure as examples, when the obtained frequency and the temperature stress coefficient of the actual structure and the corresponding simulation value have large errors, it is determined that the finite element model which is initially established needs to be corrected.
In one embodiment, as shown in FIG. 3, the determining of the plurality of correction parameters in the initial finite element model may include the following steps S210-S230:
s210, 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.
For example, according to the relative error magnitude of each test point in the test components, a plurality of temperature stress coefficients with larger errors can be selected as a correction target of the finite element model. If the frequency of the structure has a large error, it can be used as another correction target. The number of correction targets is not particularly limited here.
S220, a plurality of material parameters related to each correction target and influencing the structural response are used as candidate correction parameters.
Analysis shows that the response error between the finite element model and the actual structure is mainly caused by material parameter error, structure error and order error. The structural error and the order error can be reduced as much as possible strictly according to the geometric dimension of the design drawing and reasonable meshing, so that the purpose of correcting the structural finite element is achieved by reducing the influence of the structural finite element model parameters on the structural response. In an exemplary embodiment, the material parameter having an influence on the structural response may be selected as the candidate correction parameter from all parameters related to the above correction targets.
And S230, performing significance analysis on each candidate correction parameter by a joint hypothesis testing method, and taking each candidate correction parameter with significance meeting preset conditions as a required correction parameter.
In general, there are many parameters affecting the structural response, and if the influence of all the parameters on the structural response is considered, the calculation scale and the correction difficulty are inevitably increased. Therefore, in the embodiment, a parameter which is sensitive to the influence of each structural response is selected from the alternative design parameters as the correction parameter. In order to judge the influence of each alternative design parameter on the structural response, a joint hypothesis test method, also called an F test method, is adopted to perform significance analysis on each alternative design parameter. It can be determined by an F-test whether all or part of the candidate design parameters are suitable for modifying the initial finite element model.
Exemplarily, the process of analyzing the significance level of each parameter using joint hypothesis testing is:
(1) The SST of each structural response is decomposed into SSB and SSE, and the expression is as follows:
in the formula, SST l Represents the sum of the squares of the total deviations of the ith structural response;
representing the sum of the squares of deviations of the ith structural response due to the jth correction parameter change; SSE l The square sum of the deviations of the ith structural response due to the test is shown; x is the number of li Represents the calculated value of the ith structural response in the ith experiment;
the sum of structural responses representing the same level of each factor; n represents the number of trials; k represents the number of repetitions of each factor at each level.
(2) Total deviation squared sum degree of freedom f of the ith response T And a degree of freedom f of a sum of squares of deviations caused by the ith candidate correction parameter i And the degree of freedom f of the sum of squares of deviations caused by experimental errors E Comprises the following steps:
f T ＝n-1；
f i ＝m i -1；
in the formula, m i The number of levels of the i-th candidate correction parameter is indicated.
(3) Using the sum of squares of deviations SSB divided by the degree of freedom f i The variance V can be obtained l i Using the sum of squared deviations SSE divided by the degree of freedom f E Can obtainVariance V l i . The specific expression form is as follows:
thus, the statistic F of the F-test is
F＝V l i /V l E 。
(4) After obtaining the statistical value F, the significance level α is set to obtain the threshold TH of the candidate parameter for screening. When F is larger than or equal to TH, the significance level of the correction parameter is higher, and the influence on the structural response is obvious. When F is less than or equal to TH, the significance level of the correction parameter is lower, and the influence on the structural response is not significant. Therefore, only parameters that have a significant influence on the structural response are retained as the finally required correction parameters.
For example, in one embodiment, the main factors influencing the structural response obtained by the above significance analysis are the elastic modulus, the density and the linear expansion coefficient of the material, so these three main factors are selected as the required correction parameters in this embodiment. It is understood that in practical applications, a smaller or larger number of material parameters capable of affecting the structure may be selected for modification according to practical requirements, and is not limited herein.
Then, after determining the final required modification parameters, a multi-scale finite element model modification optimization function based on the modification parameters can be further constructed. In one embodiment, as shown in FIG. 4, the construction of the multi-scale finite element model modified optimization function includes steps S310 to S340:
and S310, extracting sample points from the measured data and the simulation data according to a preset test design to obtain a preset number of parameter sample points. For example, the predetermined trial design may include, but is not limited to, a design for quadrature, a Box-Behnken Designs, a Latin hypercube design (LHS), and the like.
And S320, performing finite element model calculation by taking the preset number of parameter sample points as model structure parameters respectively to obtain dynamic and static response data of a plurality of groups of structures corresponding to the preset number of parameter sample points so as to establish a response surface model between each correction target and each correction parameter.
The basis of establishing a response surface model of the structure is to extract sample points in a multi-dimensional parameter space formed by significance parameters and obtain the structural response of each group of sample points through finite element analysis. For example, in one embodiment, a latin hypercube design is used, which is simple to operate and allows for rapid generation of sample sets. Therefore, the dynamic and static response data of the test components can be obtained by performing finite element model calculation by using the number of parameter sample points. Therefore, response surface models between the correction targets and the parameters can be established for different correction targets. The essence of the fitting of the response surface model is the process of obtaining a response surface function with better fitting degree by the input correction parameters and the output structural response.
It is noted that in order to ensure the accuracy and efficiency of the constructed response surface model, the response surface model needs to be constructed according to the characteristics of the structural response. For example, the function used to construct the response surface model may be a power function, a non-linear function, a polynomial function, or the like. The polynomial function is preferably used in this embodiment because it can easily model the relationship between the correction parameter and the structural response. In one embodiment, the second order polynomial is embodied in the form:
wherein y represents a response estimate; x is the number of i Representing a structural correction parameter; beta is a 0 Represents a constant term; beta is a i Representing the first order coefficient; beta is a ii ,β ij And m represents the number of correction parameters.
After the response surface model is obtained, in order to determine whether the reliability of the established response surface model meets the standard, the accuracy of the response surface model needs to be verified. For example, the judgment method may be a residual mean value method, an EISE test method, or an R 2 The inspection method and the relative root mean square error method. In this embodiment, theBy the use of R 2 The accuracy evaluation of the response surface model is carried out by a test method and a relative Root Mean Square Error (RMSE) method, wherein R 2 Values closer to 1 indicate better fit of the response surface model. The closer the RMSE is to 0, the higher the calculation accuracy is, the more the deviation between the estimated value and the true value of the structural response is.
S330, respectively establishing an error function of each correction target according to the actual measurement data and the simulation data.
Exemplarily, after the actual structural response and the simulated structural response of the dynamic and static forces are obtained and the correction targets are determined, the error functions of the dynamic response and the static response of the structure can be respectively established by using response measured data and simulated data corresponding to each correction target. For example, in one embodiment, the error functions for the dynamic and static responses established are:
in the formula (I), the compound is shown in the specification,
an error function representing the dynamic response of the structure,
an error function representing the static response of the structure,
and
respectively representing a dynamic response monitoring value and a static response monitoring value of an actual structure;
and
respectively representing a dynamic response simulation value and a static response simulation value of the structure finite element model; k and p represent the number of structural dynamic responses and the number of structural static responses, respectively.
And S340, constructing an expression of the modified optimization function of the multi-scale finite element model according to the response surface model and the error function of each modified target. The constraint condition of the optimization function comprises setting the value range of each correction parameter as a preset multiple of a reference value.
Because the sign of the calculated error function is uncertain, when the error is directly integrated, the error can be mutually offset. Therefore, the absolute value of the calculated error needs to be processed before the homogeneous data integration is performed. Therefore, according to the various error functions described above, the objective function for establishing the multi-scale model correction problem may be:
in the formula, J 1 A target correction function consisting of a structural dynamic response error function; j. the design is a square 2 Is a target correction function composed of a structural static response error function.
The finite element parameters mainly refer to elastic modulus, density and linear expansion coefficient, and in order to ensure that all the structural material parameters have actual physical significance, the variation range of each material parameter is set to be a preset multiple of a reference value, such as 0.8-1.2 times, and the like, and can be set according to actual requirements.
The multi-scale finite element model modification is actually to solve a multi-objective optimization problem with constraint conditions, and taking the above 0.8-1.2 times as an example, the expression of the obtained multi-scale finite element model modification optimization function is as follows:
wherein r represents the number of correction parameters, x 0r Indicating the reference value of the r-th material correction parameter.
It is understood that the values 0.8 and 1.2 in the above optimization function are only a preferred example, and any values near the reference value of the parameter, such as 0.75, 1.21, 1.25, etc., should be considered within the scope of the present application.
S140, solving the multi-scale finite element model correction optimization function by using a multi-objective optimization algorithm to obtain a correction value of each correction parameter, and correcting the initial finite element model by using the correction value to obtain a finite element correction model.
Since the problem of multi-scale model correction can be summarized as a multi-objective optimization problem with constraint conditions, each sub-target in each objective function has inconsistency in the optimization direction to cause conflict, a unique set of parameters cannot be found to optimize each sub-target simultaneously, and a pareto non-inferior solution set exists. In this embodiment, a pareto non-inferiority solution set is preferably solved by using a multi-objective particle swarm optimization (MOPSO) algorithm. The particle swarm optimization algorithm is characterized in that the positions of particles are updated in a mode of combining global update and individual update, and meanwhile, the particle swarm optimization algorithm has global optimization and local optimization capabilities. The particle swarm optimization algorithm has the advantages of easiness in implementation, high precision, high convergence speed and the like, and shows superiority in solving practical problems.
Exemplarily, after the optimization function is optimized and solved, a correction value of each correction parameter can be obtained, and further, by correcting the correction parameters, a corrected finite element model, that is, the above finite element correction model, can be obtained.
And S150, applying an ultra-large wind load effect based on the finite element correction model, and analyzing to obtain the stress change of the test component.
Exemplarily, by applying the super wind load effect such as typhoon in fifty years to the modified structure finite element model, a corresponding stress cloud chart can be obtained through analysis so as to reflect the stress change of the solid model under the load combination. It can be understood that the initially constructed finite element model is corrected by combining the dynamic and static response actual measurement data, so that the stress change result obtained by analyzing based on the corrected model is more accurate and more fit with the actual state of the actual high-rise structure.
Further optionally, safety verification problems and the like of the structure under some extreme environments are carried out based on the stress variation situation. For example, it is determined whether the maximum stress of the test member at that time exceeds the design strength of the structure, and if it is less than this, it is possible to confirm that the structure is safe under the applied super-wind load, otherwise there may be safety issues.
In order to verify the effectiveness of the stress analysis method of the high-rise structure complex component based on multi-scale model correction, the high-rise structure of the large Baihui plaza of Shenzhen is combined for security analysis. Under the action of temperature and wind load, the cantilever truss and the node have uncertainty in internal force and deformation. In order to research the internal force change of the cantilever truss and the node of the high-rise structure under the action of the environment, the system for synchronously acquiring and continuously monitoring the strain of the cantilever truss and the node of the high-rise structure in the grand assembly square is designed. Comprehensively considering the requirements of a construction stage and a long-term operation stage, analyzing the stress states of cantilever trusses and nodes of the grand assembly square according to an MIDAS finite element model established in the construction stage, comprehensively considering the problems of economic factors and the like, and finally selecting the cantilever trusses H1 and H2 and the nodes J1 and J2 as monitoring objects as shown in FIG. 5.
For the cantilever truss structure, in order to determine the arrangement position of the vibrating wire strain gauge on the cantilever truss, the cantilever truss is simplified, a simplified finite element model is established, the internal force distribution of the cantilever truss is analyzed, and the simplified cantilever truss model is shown in fig. 6 (a). Furthermore, based on the preliminary analysis result of the simplified model of the cantilever truss, in combination with the actual installation situation in the field, as shown in fig. 6 (b), a distribution diagram of the vibrating wire strain gauges of a single cantilever truss is designed. The statistics of the distribution of the measuring points of the single cantilever truss are shown in table 1.
TABLE 1 Single cantilever truss measurement Point distribution statistics
For the nodes, in order to determine the layout positions of the strain gauges on the nodes, the nodes are established into a simplified finite element model, and the internal force of the nodes is analyzed, wherein the simplified model is shown in fig. 7 (a). Furthermore, according to the results of the preliminary calculation of the node simplified model and the specific conditions in the field, as shown in fig. 7 (b), a distribution diagram of the single node vibrating wire strain gauge is designed. The strain measurement point distribution statistics for individual nodes are shown in table 2.
Therefore, according to the layout scheme of all strain measuring points, 3 strain collecting substations are arranged, and a collecting box of each collecting substation and a remote cloud platform control center are wirelessly transmitted to form a data collecting and monitoring platform, as shown in fig. 8. The system is composed of a cloud platform, a field control box, a data transmission module and a data acquisition unit, wherein the data acquisition unit is connected with each strain sensor and used for acquiring data. The cloud platform adopts an automatic data acquisition platform developed based on a MySQL database, and can store, visually display, analyze, export and the like data by using a front-end and back-end separation technology. Meanwhile, the temperature stress coefficient simulation values of the cantilever truss and the nodes can be obtained by calculating the initial finite element models of the cantilever truss and the nodes.
In order to obtain the structural dynamic characteristic parameters of the grand assembly square in operation, a modal test is performed on the grand assembly square in this embodiment, specifically, the acquisition of the structural synchronous acceleration signal can be realized by adopting an acceleration monitor, geoDAS software, and the like, and the synchronous acceleration signal is analyzed, so that the dynamic characteristic parameters of the structure of the grand assembly square, such as the natural vibration frequency, the vibration type, and the like, can be obtained.
In 7 months in 2021, modal tests were performed on the structure of the grand assembly square based on a distributed synchronous acquisition method. The monitoring instruments are respectively arranged on 9 layers, 19 layers, 35 layers, 54 layers and 71 layers of a main structure and 3 layers, 6 layers and a top layer of a top steel structure, a seismic monitoring instrument is respectively arranged at the corner of an outer frame of each floor along the X direction and the Y direction of the structure, 16 measuring points are arranged in total, the sampling time of each group of data is 10min, the sampling frequency is 100Hz, wherein a fixed reference point is arranged at a certain measuring point at the top of the steel frame, and other measuring points adopt a mobile monitoring instrument to obtain synchronous acceleration signals of different floors of the structure. By carrying out field modal test on the great deal square, the acceleration response time domain signal of the great deal square in the operation state can be obtained. Furthermore, the east-west steady-state diagram and the north-south steady-state diagram of the grand Baihui square, which are obtained by processing the acceleration signal by using the SSI-COV method, are shown in fig. 9 (a) and 9 (b), and the first 6-order modal frequencies of the structure are obtained. In addition, the relative vibration pattern value of each floor is calculated according to a covariance driven random subspace method, and a first six-order vibration pattern diagram can be obtained.
According to the structural natural vibration frequency and temperature stress coefficient simulation values calculated by the initial finite element model of the great-Baihui square, a large error exists between the structural natural vibration frequency and the temperature stress coefficient of the actual structure, wherein the relative error of the first 6-order frequency exceeds 8%, the relative error of the temperature stress coefficient of the cantilever truss and the node mostly exceeds 10%, and the maximum error of the temperature stress coefficient reaches 21.17%. Therefore, it is necessary to correct the initially established finite element model.
Because the influence of temperature on frequency is small, the influence of temperature on frequency is not considered, the large Baihui plaza is in Shenzhen city and is greatly influenced by typhoon, and the high-rise is dominant in the first order under the action of typhoon, so that the first 6-order frequency of the structure is selected as a correction target of the whole structure scale, and 3 temperature stress coefficients are respectively selected on each cantilever truss according to an error analysis result, and 10 temperature stress coefficients with large errors are selected on each node to serve as a correction target of the local scale.
Therefore, according to the measured data and the simulation data, error functions of correction targets, namely the structural frequency, the temperature stress coefficient of the cantilever truss and the temperature stress coefficient of the node can be constructed and obtained. Considering that the main factors influencing the structure are the elastic modulus, the density and the linear expansion coefficient of the material, the correction of the large-Baikal-square multi-scale finite element model is mainly realized by correcting the elastic modulus, the density and the linear expansion coefficient of the structural material. It should be noted that the present embodiment uses a total of 33 selected material attributes as candidate modification parameters for modifying the structure of the grand assembly square, and determines 20 required modification parameters through significance analysis. Setting the value range of the 20 correction parameters as 0.8-1.2 times of the initial value, and carrying out test design according to a Latin hypercube test method to obtain 300 groups of structural parameter sample points; the 300 groups of structural parameter sample points are respectively used as model parameters to carry out finite element model calculation, and the first 6-order frequency of the structure, the 6 temperature stress coefficient values of the cantilever truss and the 4 temperature stress coefficient values of the nodes corresponding to the 300 groups of sample points can be obtained through calculation, so that 300 groups of structural response values of each group of corresponding sample points are obtained. And establishing a response surface function model between the modified target and the parameters for different modified targets. By means of R 2 The true and estimated values of each corrected target are error-tested using a test method and a relative Root Mean Square Error (RMSE) method.
Therefore, according to the established response surface model and the error function of each correction target, the definition domain of each parameter is limited to be 0.8-1.2 times of the reference value, and the following multi-scale finite element model correction optimization functions of the large Baikui square can be constructed:
in the formula, J 1 Sub-target composed of frequency error function, J 2 Sub-target consisting of temperature stress coefficient error function of cantilever truss, J 3 Sub-targets composed of node temperature stress coefficient error functions; e i The ith elastic modulus is a parameter to be corrected; e 0i Setting the reference value of the parameter to be corrected of the ith elastic modulus; rho j The j density is a parameter to be corrected; rho 0j The reference value of the parameter to be corrected of the jth density is obtained; alpha (alpha) ("alpha") k The parameter to be corrected is the kth linear expansion coefficient; alpha (alpha) ("alpha") 0k Setting the reference value of the parameter to be corrected for the kth linear expansion coefficient; p E Correcting the number of parameters for the elastic modulus; p ρ Correcting the number of parameters for the density; p α The number of parameters is corrected for the linear expansion coefficient.
Then, a multi-target particle swarm optimization algorithm is adopted to solve the multi-target optimization function, multi-scale model correction of the large Baikui square is achieved, MOPSO parameter values are set to be 1000 of population scale, 1000 of non-dominated solution sets, 0.1 of variation probability and 1000 of maximum iteration times by combining with experience values, 982 sets of Pareto solutions are obtained after iterative calculation, the solution set which enables the maximum value of each sub-target to be minimized is selected as a parameter correction value in the Pareto solution set, and finally a set of correction parameters after multi-target particle swarm optimization are obtained. And finally, applying the correction parameters to the initial finite element model of the great-Baihui square, extracting 16 correction target simulation values of the model before and after correction, comparing the correction target simulation values with the measured values, calculating relative errors before and after correction, obtaining that the relative errors of the structure simulation frequency after correction are less than 5%, greatly improving the calculation precision of the natural vibration frequency, and checking the vibration mode MAC value, wherein the vibration mode MAC value exceeds 0.99. The relative errors of the temperature stress coefficients of the corrected model are all less than 10%, and the maximum relative error is reduced from 21.171% to 9.117%, so that the corrected model can accurately simulate the dynamic and static response of the structure.
And finally, carrying out corresponding load combination on the calculation result of the corrected finite element model by carrying out load action on the corrected finite element model Shi Jiafeng of the grand assembly square, and calculating and analyzing the stress change of the cantilever truss entity model under the load combination. Under the load combination of 1.2 dead load and 1.4 wind load, stress cloud charts of cantilever trusses H1 and H2 solid models are respectively shown in fig. 10 (a) and 10 (b), and maximum stress conditions of the cantilever trusses H1 and H2 are shown in table 3.
TABLE 3 maximum stress variation value of cantilever truss solid unit
By analyzing the node solid model, under the load combination of 1.2 dead load +1.4 wind load, the stress cloud charts of the node J1 and the node J2 solid model are respectively shown in fig. 11 (a) and fig. 11 (b). The solid models of nodes J1 and J2 are shown in Table 4 for the maximum stress case. The maximum stress of the node under the combined action of 1.2 constant load and 1.4 wind load is 235.50MPa, and the stress level is lower than 0.8 time of the yield strength of the used steel Q345B.
TABLE 5-4 maximum stress variation values of physical units of nodes
In conclusion, through the analysis on the cantilever truss and the cantilever node, the stress of the cantilever truss and the stress of the cantilever node are both less than 0.8 time of the yield strength of Q345B, so that the cantilever truss and the cantilever node can be shown to be safe under the action of typhoon.
The stress analysis method for the high-rise complex component based on the multi-scale model correction takes the high-rise structure in an operating state as a research object, constructs a multi-scale finite element correction data problem of the high-rise structure based on power and static response measured by a plurality of test components, performs significance analysis according to orthogonal test and F test to select parameters to be corrected, designs structure sample parameters by using an LHS method and the like, establishes a response surface model between the structure response and the correction parameters and verifies the model precision, and determines optimal structure parameters by combining a multi-objective particle swarm optimization algorithm to realize model correction. And finally, according to the modified structural finite element model, applying a wind load effect specified by a standard in fifty years to the structural finite element model, analyzing the internal force change condition of the complex component and the node, and realizing accurate verification of the safety of the high-rise structural complex component so as to ensure the safety of the structure.
Referring to fig. 12, based on the method of the foregoing embodiment, the present embodiment provides a stress analysis system 100 for a high-rise complex component based on multi-scale model modification, where exemplarily, the stress analysis system 100 includes:
the data acquisition unit 110 is connected with a plurality of strain sensors 101 arranged at different strain measuring points on a testing component in a high-rise structure and acceleration sensors 102 arranged at different floors, and is used for acquiring the measured data of the dynamic and static force response of the testing component in a period of time.
And the field control box 120 is connected with the data collector 110 and is used for sending the collected measured data to the processor 130. For example, the processor 130 may be a processor in a notebook computer directly on site, or may be a processor transmitted to a remote computer through a network module such as 3G/4G/5G, and the like, and the form and location where the processor 130 exists are not limited herein.
The processor 130 is configured to obtain the measured data, and obtain simulation data of dynamic and static responses of the test component through an initial finite element model calculation of the test component; and determining a plurality of correction parameters in the initial finite element model according to the relative error between the actually measured data and the simulated data, and constructing a multi-scale finite element model correction optimization function related to the plurality of correction parameters.
The processor 130 is further configured to solve the multi-scale finite element model modification optimization function by using a multi-objective optimization algorithm to obtain a modification value of each modification parameter, and modify the initial finite element model by using the modification value to obtain a finite element modification model; and analyzing and obtaining the stress change of the test component based on the effect of applying the ultra-large wind load by the finite element correction model.
It is understood that the system of the present embodiment corresponds to the method of the above embodiment, and the options in the above embodiment are also applicable to the present embodiment, so the description is not repeated here.
The application further provides a terminal device, such as a desktop computer, a notebook computer, a remote server, and the like, which exemplarily includes a processor and a memory, where the memory stores a computer program, and the processor executes the computer program, so that the terminal device executes the stress analysis method for the complex component with the high-rise structure based on the multi-scale model modification or the function of the processor in the stress analysis system.
The application also provides a readable storage medium for storing the computer program used in the terminal device.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, each functional module or unit in each embodiment of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a smart phone, a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application.
Claims (10)
1. A stress analysis method of a high-rise structure complex component based on multi-scale model correction is characterized by comprising the following steps:
acquiring actual measurement data of dynamic and static force response of a test component in a high-rise structure within a period of time;
calculating to obtain simulation data of dynamic and static response of the test component through the initial finite element model of the test component;
determining a plurality of correction parameters in the initial finite element model according to the relative error magnitude between the measured data and the simulation data, and constructing a multi-scale finite element model correction optimization function related to the correction parameters;
solving the multi-scale finite element model correction optimization function by using a multi-objective optimization algorithm to obtain a correction value of each correction parameter, and correcting the initial finite element model by using the correction value to obtain a finite element correction model;
and analyzing and obtaining the stress change of the test component based on the effect of applying the ultra-large wind load by the finite element correction model.
2. A force analysis method according to claim 1, wherein said determining a plurality of correction parameters in said initial finite element model comprises:
determining that the current response is a modified target of the initial finite element model when the relative error between the measured data and the simulated data of the same response exceeds an error range threshold;
taking as candidate modification parameters a plurality of material parameters affecting the structural response associated with each of said modification targets;
and carrying out significance analysis on each candidate correction parameter by a joint hypothesis testing method, and taking each candidate correction parameter with significance meeting preset conditions as a required correction parameter.
3. The force analysis method according to claim 2, wherein the correction target includes a temperature stress coefficient of the test member and a structural frequency of the high-rise structure;
the plurality of material parameters includes an elastic modulus, a density, and a linear expansion coefficient of the test member.
4. The force analysis method according to claim 3, wherein the test member is provided with a plurality of strain measurement points, and each strain measurement point is provided with a strain sensor; the acquiring of the measured data of the dynamic and static force response of the test component in the high-rise structure in a period of time comprises the following steps:
acquiring temperature stress coefficient actual values of different positions of the testing component through each strain sensor, and monitoring the structural response of the high-rise structure in a period of time based on a distributed synchronous acquisition system to obtain the actual structural frequency of the high-rise;
the acquisition of the simulation data of the dynamic and static force response of the test component comprises the following steps:
adopting a trilateral grid design for an initial finite element model of the test component, extracting a stress average value of corresponding nodes on a straight line where the strain sensors are actually arranged as a simulated temperature stress, and taking a ratio of the simulated temperature stress to the temperature variation of the structural unit as a temperature stress coefficient simulation value;
and carrying out modal analysis on the initial finite element model of the test component to obtain the frequency of the simulated structure.
5. A force analysis method according to claim 1, wherein the constructing a multi-scale finite element model modification optimization function relating to the plurality of modification parameters comprises:
according to a preset test design, sample points are extracted from the actual measurement data and the simulation data to obtain a preset number of parameter sample points;
respectively taking the preset number of parameter sample points as model structure parameters to carry out finite element model calculation, and obtaining dynamic and static response data of a plurality of groups of structures corresponding to the preset number of parameter sample points so as to establish a response surface model between each correction target and each correction parameter;
respectively establishing an error function of each correction target according to the measured data and the simulation data;
and constructing an expression of a correction optimization function of the multi-scale finite element model according to the response surface model and the error function of each correction target, wherein the constraint condition of the optimization function comprises setting the value range of each correction parameter as a preset multiple of a reference value.
6. The force analysis method according to claim 5, wherein the response surface model is constructed using a polynomial function and is represented by R 2 The testing method and the relative root-mean-square error method carry out precision verification on the constructed response surface model;
the preset test design adopts a Latin hypercube test design.
7. The force analysis method according to any one of claims 1 to 6, wherein the multi-objective optimization algorithm is a multi-objective particle swarm optimization algorithm.
8. A stress analysis system of a high-rise structure complex component based on multi-scale model correction is characterized by comprising:
the data acquisition unit is connected with a plurality of strain sensors arranged at different strain measuring points on the testing component and acceleration sensors arranged at different floors and is used for acquiring the actual measurement data of the dynamic and static response of each testing component in a period of time;
the field control box is connected with the data acquisition unit and is used for sending the acquired actually measured data to the processor;
the processor is used for acquiring the measured data and calculating to obtain simulation data of dynamic and static response of the test component through an initial finite element model of the test component; determining a plurality of correction parameters in the initial finite element model according to the relative error magnitude between the measured data and the simulation data, and constructing a multi-scale finite element model correction optimization function related to the correction parameters;
the processor is further used for solving the multi-scale finite element model correction optimization function by using a multi-objective optimization algorithm to obtain a correction value of each correction parameter, and correcting the initial finite element model by using the correction value to obtain a finite element correction model; and analyzing and obtaining the stress change of the test component based on the effect of applying the ultra-large wind load by the finite element correction model.
9. A terminal device, characterized in that the terminal device comprises a processor and a memory, the memory stores a computer program, and the processor is used for executing the computer program to implement the multi-scale model modification-based stress analysis method for a high-rise structural complex component according to any one of claims 1 to 7.
10. A readable storage medium, characterized in that it stores a computer program which, when executed on a processor, implements the multi-scale model modification-based high-rise structural complex member stress analysis method according to any one of claims 1 to 7.
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