A method for adjusting rigidity of prestressed concrete composite slabs produced by steel tube trusses

Abstract

The present invention provides a stiffness adjustment method for producing steel tube truss prestressed concrete composite plates, which belongs to the technical field of steel tube truss prestressed concrete composite plates, and comprises: establishing a finite element model group of the steel tube truss prestressed concrete composite plates, and extracting multiple parameters of the finite element model group; determining key parameters; establishing a mathematical relationship model between the key parameters and the stiffness of the steel tube truss prestressed concrete composite plates, and fitting them to obtain a stiffness model; establishing a multi-objective optimization model, using the increase or decrease of the value of each key parameter as a mediation factor, and using a multi-objective genetic algorithm to solve the multi-objective optimization model to obtain multiple solutions that meet preset optimization thresholds; inputting the multiple solutions that meet the preset optimization thresholds into the stiffness model to obtain corresponding stiffness; and finding the solution corresponding to the closest element in the target stiffness set for the predetermined stiffness of the composite plate to be produced as the key production parameter.

Description

Technical Field

[0001] The invention belongs to the technical field of steel tube truss prestressed concrete composite plates, and in particular, relates to a stiffness adjustment method for producing steel tube truss prestressed concrete composite plates. Background Art

[0002] Steel tube truss prestressed concrete composite slab is a new type of concrete building component, widely used in high-rise buildings, bridges and other projects. The structure consists of three parts: mortar steel pipes at the top, steel trusses in the middle, and prestressed steel wires at the bottom, which are fixed together by welding or bolting. This structural form makes full use of the advantages of steel and concrete, can achieve the coordination and unification of bearing performance and performance, and has obvious advantages in earthquake resistance, impact resistance, durability and other aspects.

[0003] At present, steel tube truss prestressed concrete composite slabs have been widely used in super high-rise buildings, long span bridges and other fields. In these projects, the composite slabs need to bear large static and dynamic loads, and have high requirements for stiffness indicators. Stiffness is one of the important parameters for judging the performance of composite slabs, which directly affects the overall stability, safety and comfort of the structure. Excessive stiffness will make the structure too rigid and prone to local damage; while too small stiffness will cause excessive deformation and affect the use function. Therefore, how to control the stiffness of steel tube truss prestressed concrete composite slabs is a key issue that needs to be addressed in component design.

[0004] The existing methods for adjusting the stiffness of composite plates are mainly as follows:

[0005] 1. Adjust the geometric dimensions of the components. The overall stiffness of the composite slab can be improved by increasing the diameter or wall thickness of the mortar steel pipe, expanding the span or height of the steel truss, etc. However, this method will increase the material consumption and deadweight, which is not conducive to the economic efficiency of the project.

[0006] 2. Change material performance parameters. For example, using mortar or steel with higher strength grades can improve the deformation resistance of components. However, the improvement of material performance usually means an increase in cost and a greater degree of process difficulty.

[0007] 3. Optimize the prestressing arrangement. Adjusting the prestressing value or anchoring length of the prestressing steel wire can increase the stiffness of the lower tension zone. However, the introduction of prestressing will bring additional stress, which will affect the overall force distribution and require complex mechanical analysis.

[0008] 4. Use mixed materials. Introducing new composite materials such as GFRP and carbon fiber into the laminate can effectively improve the overall stiffness. However, this method is more complicated, the cost is relatively high, and there may be compatibility issues with traditional materials.

[0009] Although the above methods can adjust the stiffness of the composite plate to a certain extent, most of them have problems such as excessive material consumption, complex process, and high cost. At the same time, these methods often only optimize a certain component parameter, and it is difficult to balance the impact of various key parameters on stiffness as a whole. Therefore, there is an urgent need for a new stiffness adjustment method that can systematically analyze various factors and obtain the optimal design solution that meets the use requirements, thereby improving product performance and reducing production costs. Summary of the invention

[0010] In view of this, the present invention provides a stiffness adjustment method for producing steel tube truss prestressed concrete composite plates, which can solve the technical problem that when adjusting the stiffness of steel tube truss prestressed concrete composite plates, the existing production technology often only optimizes a certain component parameter, and it is difficult to balance the influence of various key parameters on the stiffness as a whole.

[0011] The present invention is achieved in that:

[0012] A first aspect of the present invention provides a method for adjusting the stiffness of a steel tube truss prestressed concrete composite slab, comprising the following steps:

[0013] S10, establishing a finite element model group of a steel tube truss prestressed concrete composite slab, including an upper zone finite element model corresponding to an upper compression zone made of mortar steel tubes, a middle zone finite element model corresponding to a middle force transmission mechanism made of steel bar trusses, and a lower zone finite element model made of a lower tension zone made of prestressed steel wires, wherein the mortar steel tubes and the steel bar trusses are fixedly connected to form a steel tube truss, a plurality of legs of the steel bar trusses are fixedly connected to the prestressed steel wires, and the prestressed steel wires are arranged in a C40 / C50 concrete bottom plate;

[0014] S20, extracting multiple parameters of the finite element model group;

[0015] S30, using a principal component analysis method to determine multiple parameters related to the stiffness of the steel tube truss prestressed concrete composite slab among the multiple parameters as key parameters;

[0016] S40, establishing a mathematical relationship model between the key parameters and the stiffness of the steel tube truss prestressed concrete composite slab, and collecting a large amount of stiffness experimental data of the composite slab produced according to the key parameters to fit the mathematical relationship model to obtain a stiffness model;

[0017] S50, establishing a multi-objective optimization model, taking the optimization of each key parameter as multiple objectives, and determining the constraint conditions of the multi-objective optimization model;

[0018] S60, using the increase or decrease of the value of each key parameter as a mediation factor, using a multi-objective genetic algorithm to solve the multi-objective optimization model, and obtaining multiple solutions that meet the preset optimization thresholds;

[0019] S70, inputting a plurality of solutions that meet a preset optimization threshold into the stiffness model to obtain corresponding stiffnesses to form a target stiffness set;

[0020] S80, the predetermined stiffness of the composite plate to be produced is determined, and a solution corresponding to the closest element is found in the target stiffness set as a key production parameter;

[0021] S90. Produce a steel tube truss prestressed concrete composite slab meeting a predetermined stiffness according to the obtained key production parameters.

[0022] The optimization threshold may be set based on experience or set to 0.85 by default.

[0023] On the basis of the above technical solution, the stiffness adjustment method for producing steel tube truss prestressed concrete composite slabs of the present invention can also be improved as follows:

[0024] Among them, the specific steps of step S30 include: using the principal component analysis method to screen out several key parameters with the strongest correlation with the stiffness of the steel tube truss prestressed concrete composite slab from the extracted multiple parameters; firstly standardizing the parameters to eliminate the dimension effect, calculating the correlation coefficient matrix and performing eigenvalue decomposition to extract the principal components; then, according to the contribution rate of the principal components, determining the parameters corresponding to the principal components with a cumulative contribution rate of more than 85% as the key parameters, including the cross-sectional size and wall thickness of the mortar steel pipe in the upper area, the geometric size and layout of the steel truss in the middle area, and the prestress value of the prestressed steel wire in the lower area.

[0025] Among them, the specific steps of step S40 include: firstly, establishing a multivariate regression model of key parameters and stiffness of steel tube truss prestressed concrete composite slabs, taking the key parameters as independent variables and the composite slab stiffness as dependent variables; then collecting a large amount of actual stiffness experimental data of composite slabs produced according to the key parameters, fitting and calibrating the regression model using the least squares method, determining the optimal values ​​of each coefficient, and obtaining a stiffness prediction model.

[0026] The constraint conditions include at least the value range of key parameters, the stiffness and the bearing capacity of the composite plate.

[0027] The step of using a multi-objective genetic algorithm to solve the multi-objective optimization model is specifically:

[0028] Step 1: Randomly generate an initial population, where each individual represents a set of key parameter values;

[0029] Step 2: Perform non-dominated sorting on the population according to multiple objective functions and calculate the crowding degree of each individual;

[0030] Step 3: Generate a new generation of population using the genetic operations of binary tournament selection, crossover and mutation;

[0031] Step 4: Repeat steps 2 and 3 until the termination condition is met.

[0032] Furthermore, the termination condition includes that the number of iterations reaches 1000 or the convergence accuracy of the objective function is less than 1%.

[0033] Among them, when calculating the target stiffness set, the Pareto optimal solution obtained in step S60, that is, multiple key parameter combinations that meet the optimization threshold, are first substituted into the stiffness prediction model established in step S40; then, the composite plate stiffness values ​​corresponding to these parameter combinations are calculated according to the model to form the target stiffness set.

[0034] Among them, when looking for the solution closest to the predetermined stiffness, the minimum distance method or other similarity evaluation methods are used to calculate the difference between the predetermined stiffness required in the production plan and the elements in the target stiffness set formed in step S70, and the solution with the smallest difference is selected as the optimal solution.

[0035] Among them, when producing the laminated board according to the determined key parameters, the following steps are included:

[0036] Step 1) according to the size and performance parameters of the upper zone mortar steel pipe, the upper pressure zone component is produced by using a steel pipe pipe making and plastic forming process;

[0037] Step 2) According to the geometric shape and layout requirements of the central steel truss, the central force transmission mechanism is manufactured and assembled using steel processing equipment;

[0038] Step 3) tensioning and anchoring the prestressed steel wire according to the prestressed value and anchoring condition of the prestressed steel wire in the lower zone;

[0039] Step 4) Assemble the above three parts according to the design requirements to form a complete steel tube truss prestressed concrete composite slab.

[0040] Compared with the prior art, the method for adjusting the stiffness of a steel tube truss prestressed concrete composite slab provided by the present invention has the following beneficial effects:

[0041] 1. A comprehensive finite element model group was established, which can simulate the overall stress characteristics of the composite slab more accurately. The model consists of three parts: the upper mortar steel pipe, the middle steel truss and the lower prestressed steel wire. Through reasonable unit type, mesh division and material parameter setting, the structural characteristics and load transmission mechanism of each area are fully considered, providing a reliable basis for subsequent parameter analysis and optimization.

[0042] 2. The principal component analysis method is used to select the most critical factors affecting stiffness from a large number of parameters, which greatly reduces the optimization space and improves the calculation efficiency. By analyzing the correlation between the parameters, the size of the mortar steel pipe in the upper area, the geometric shape of the steel truss in the middle area, and the parameters of the prestressed steel wire in the lower area are determined as key factors, laying the foundation for establishing an accurate stiffness prediction model.

[0043] 3. A mathematical relationship model between key parameters and stiffness was established, and a relatively accurate stiffness prediction model was obtained through fitting and calibration of a large amount of test data. This model can better reflect the influence of each key parameter on stiffness, and provide reliable mathematical support for subsequent parameter optimization.

[0044] 4. Using the multi-objective optimization method, taking the optimal value of each key parameter as an independent goal, a set of Pareto optimal solutions were obtained under the constraints of materials, processes, structural performance, etc. These solutions represent the best solutions under different parameter combinations, providing a variety of options for production management.

[0045] 5. According to the specific stiffness requirements in the production plan, the closest solution is found in the target stiffness set formed in step S70, and the optimal key parameter combination that meets the expected indicators is determined. This targeted parameter optimization enables the final produced composite plate to accurately meet the use requirements and significantly improves product performance and quality.

[0046] In summary, the solution of the present invention solves the technical problem that when adjusting the stiffness of the steel tube truss prestressed concrete composite slab, the existing production technology often only optimizes a certain component parameter, and it is difficult to balance the influence of various key parameters on the stiffness as a whole. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0048] Figure 1 A flow chart of the method provided by the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0050] like Figure 1 FIG. 1 is a flow chart of a method for adjusting the stiffness of a prestressed concrete composite slab produced by a steel tube truss according to the present invention. The method comprises the following steps:

[0051] S10, establishing a finite element model group of a steel tube truss prestressed concrete composite slab, including an upper zone finite element model corresponding to an upper compression zone made of mortar steel tubes, a middle zone finite element model corresponding to a middle force transmission mechanism made of steel bar trusses, and a lower zone finite element model made of a lower tension zone made of prestressed steel wires, wherein the mortar steel tubes and the steel bar trusses are fixedly connected to form a steel tube truss, a plurality of legs of the steel bar trusses are fixedly connected to the prestressed steel wires, and the prestressed steel wires are arranged in a C40 / C50 concrete bottom plate;

[0052] S20, extracting multiple parameters of the finite element model group;

[0053] S30, using a principal component analysis method, determining multiple parameters related to the stiffness of the steel tube truss prestressed concrete composite slab among the multiple parameters as key parameters;

[0054] S40, establishing a mathematical relationship model between key parameters and the stiffness of the steel tube truss prestressed concrete composite slab, and collecting a large amount of stiffness experimental data of the composite slab produced according to the key parameters to fit the mathematical relationship model to obtain a stiffness model;

[0055] S50, establishing a multi-objective optimization model, taking the optimization of each key parameter as multiple objectives, and determining the constraint conditions of the multi-objective optimization model;

[0056] S60, using the increase or decrease of the value of each key parameter as a mediation factor, using a multi-objective genetic algorithm to solve the multi-objective optimization model, and obtaining multiple solutions that meet the preset optimization thresholds;

[0057] S70, inputting a plurality of solutions that meet a preset optimization threshold into a stiffness model to obtain corresponding stiffnesses, thereby forming a target stiffness set;

[0058] S80, the predetermined stiffness of the composite plate to be produced is used to find the solution corresponding to the closest element in the target stiffness set as the key production parameter;

[0059] S90. Produce a steel tube truss prestressed concrete composite slab meeting a predetermined stiffness according to the obtained key production parameters.

[0060] The specific implementation methods of the above steps are described in detail below:

[0061] The specific implementation of step S10 is: firstly, a finite element model group of the steel tube truss prestressed concrete composite slab is established. The finite element model group includes three parts: an upper area finite element model, a middle area finite element model and a lower area finite element model.

[0062] The upper zone finite element model corresponds to the upper compression zone made of mortar steel pipes. Appropriate unit types and mesh divisions are used, and reasonable assumptions and settings are made for material parameters, boundary conditions, etc. The middle zone finite element model corresponds to the middle force transmission mechanism made of steel trusses. It is also necessary to appropriately select unit types and mesh divisions, and determine the geometric dimensions and layout of the steel bars. The lower zone finite element model corresponds to the lower tension zone made of prestressed steel wires, and parameters such as the prestress value and anchorage conditions of the prestressed steel wires need to be considered.

[0063] The three finite element models are coupled through the fixed connection between the mortar steel tube and the steel truss and the fixed connection between the multiple legs of the steel truss and the prestressed steel wire. The upper mortar steel tube and the middle steel truss together constitute the steel tube truss structure, and the lower prestressed steel wire is set in the C40 / C50 concrete base plate. By establishing such a comprehensive finite element model group, the overall force mechanism and deformation characteristics of the steel tube truss prestressed concrete composite slab can be simulated more accurately.

[0064] The specific implementation method of step S20 is: extract multiple parameters of the above finite element model group. These parameters include but are not limited to: geometric dimensions and mechanical performance parameters of the mortar steel pipe in the upper area; geometric dimensions, layout form, and mechanical performance parameters of the steel truss in the middle area; prestress value and anchoring conditions of the prestressed steel wire in the lower area. These parameters involve many aspects such as material properties, component geometry, load transmission path, etc., and comprehensively describe the overall force characteristics of the steel tube truss prestressed concrete composite slab.

[0065] The specific implementation method of step S30 is: using the principal component analysis method to determine the key parameters related to the stiffness of the steel tube truss prestressed concrete composite slab among the above multiple parameters. The principal component analysis method is a common multivariate statistical analysis method that can effectively extract the main factors that have the most significant impact on the research target (i.e., stiffness in this example) from a large number of related variables. The specific method is: first, the extracted multiple parameters are standardized to eliminate the influence of the dimension; then, the correlation coefficient matrix between the parameters is calculated, and the eigenvalue decomposition of the matrix is ​​performed to extract the principal components; finally, according to the contribution rate of the principal components, several main parameters with the strongest correlation with stiffness are determined as key parameters.

[0066] Through principal component analysis, several key factors that have the greatest impact on the stiffness of the composite slab can be effectively selected from numerous parameters, providing a basis for subsequent mathematical modeling and optimization. Generally speaking, it is more appropriate to select the parameters corresponding to the principal components with a cumulative contribution rate of about 85% as key parameters. For example, it may include the cross-sectional dimensions and wall thickness of the mortar steel pipe in the upper area, the geometric dimensions and layout of the steel truss in the middle area, and the prestress value of the prestressed steel wire in the lower area.

[0067] The specific implementation method of step S40 is: firstly, a mathematical relationship model between key parameters and the stiffness of the steel tube truss prestressed concrete composite plate is established. Here, a multivariate regression analysis method can be used to establish an appropriate polynomial regression model by taking the above-determined key parameters as independent variables and the composite plate stiffness as the dependent variable. The specific form of the model can be determined according to the distribution characteristics of the data, such as a linear regression model, a quadratic regression model, etc.

[0068] Then, a large amount of actual stiffness experimental data of the composite plate produced according to the key parameters is collected, and the established mathematical relationship model is fitted and calibrated. The optimal values ​​of the coefficients in the regression model are determined by the least square method or other parameter estimation methods, so that the error between the model prediction value and the measured value is minimized. In this way, a more accurate stiffness prediction model is obtained, which can more accurately reflect the influence of the key parameters on the stiffness of the composite plate.

[0069] It should be noted that when establishing a mathematical relationship model, the functional form of the model should be reasonably assumed based on engineering experience and experimental observations. For example, it can be assumed that stiffness has a linear or power function relationship with certain key parameters. At the same time, when fitting the model, attention should be paid to the selection of sample size to avoid the problem of overfitting. Generally speaking, the number of samples should be no less than 5-10 times the number of key parameters.

[0070] The specific implementation method of step S50 is: establish a multi-objective optimization model, take the optimization of each key parameter as multiple objectives, and determine the corresponding constraints.

[0071] Multi-objective optimization is an optimization method that optimizes multiple objective functions at the same time. It is suitable for complex decision-making problems that require weighing the pros and cons of different objectives. In this case, we hope to find the optimal values ​​of a set of key parameters so that the corresponding composite plate stiffness meets the expected requirements. Therefore, the optimal value of each key parameter can be used as an independent objective function to establish a multi-objective optimization model.

[0072] At the same time, it is necessary to determine the corresponding constraints according to the actual needs of process manufacturing, structural stability, etc. For example, the value range of key parameters can be restricted to meet the design specifications or process requirements; or constraints on performance indicators such as the stiffness and bearing capacity of the composite plate can be added to ensure that the final solution meets the use requirements.

[0073] By constructing such a multi-objective optimization model, we can make trade-offs among multiple objectives and find a set of optimal key parameter values ​​that meet various requirements.

[0074] The specific implementation method of step S60 is: using a multi-objective genetic algorithm to solve the above multi-objective optimization model to obtain multiple solutions that meet the preset optimization threshold.

[0075] Genetic algorithm is a random search optimization algorithm that simulates natural selection and genetic mechanism, and performs well in multi-objective optimization problems. Compared with traditional weighted sum method, goal programming method and other methods, genetic algorithm can find multiple Pareto optimal solutions at the same time, providing decision makers with more choices.

[0076] In this case, the non-dominated sorting genetic algorithm (NSGA-II) can be used to solve the multi-objective optimization model. The NSGA-II algorithm can effectively find the Pareto optimal solution set in the population by introducing mechanisms such as non-dominated sorting and crowding calculation.

[0077] The specific steps are as follows:

[0078] 1) First, randomly generate the initial population, each individual represents a set of key parameter value combinations;

[0079] 2) Perform non-dominated sorting on the population according to multiple objective functions and calculate the rank and crowding degree of each individual;

[0080] 3) Generate a new generation of populations using genetic operations such as binary tournament selection, crossover, and mutation;

[0081] 4) Repeat steps 2) and 3) until the termination condition (such as the number of iterations or the convergence accuracy of the objective function) is met.

[0082] Through iterative optimization of the multi-objective genetic algorithm, a set of Pareto optimal solutions can be finally obtained, that is, the solution set where each objective function value cannot be improved without reducing the values ​​of other objective functions. These solutions represent the optimal solutions under different combinations of key parameter values, providing a variety of optional solutions for subsequent stiffness adjustment. In general, the objective function value can be set to meet a certain optimization threshold as a screening condition to obtain several representative optimal solutions.

[0083] The specific implementation method of step S70 is: substitute the key parameter combination obtained by the above optimization into the stiffness prediction model established in step S40, calculate the corresponding composite plate stiffness, and form a target stiffness set.

[0084] First, the multiple key parameter combinations that meet the preset optimization thresholds obtained in step S60 are respectively substituted into the stiffness prediction model established in step S40. These parameter combinations have been multi-objective optimized and can better balance the optimal values ​​of each key parameter.

[0085] Through the calculation of the stiffness prediction model, the stiffness values ​​of the composite plate corresponding to these parameter combinations can be obtained. In this way, a target stiffness set is formed, which reflects the range of composite plate stiffness that can be obtained under the optimal combination of each key parameter.

[0086] This target stiffness set provides an optional reference for subsequent stiffness adjustment, which can better meet the needs of actual production. According to the specific requirements for stiffness in the production plan, the closest solution can be found in this target stiffness set.

[0087] The specific implementation method of step S80 is: the predetermined stiffness of the composite plate to be produced is set, the closest element is found in the target stiffness formed in step S70, and the corresponding key parameter combination is determined as the production plan.

[0088] First of all, it is necessary to clarify the specific requirements for the stiffness of the steel tube truss prestressed concrete composite slab in the production plan. This predetermined stiffness value may come from the design specifications, usage requirements or other engineering requirements.

[0089] Then, the predetermined stiffness value is compared with the target stiffness set obtained in step S70 to find the closest stiffness value. Here, the minimum distance method or other similarity evaluation methods can be used to calculate the difference between the predetermined stiffness and each element in the target stiffness set, and the solution with the smallest difference is selected.

[0090] After determining the closest target stiffness, the corresponding key parameter combination can be obtained as the optimal solution for producing the composite slab. These key parameters include the size of the mortar steel pipe in the upper area, the geometry of the steel truss in the middle area, and the prestress value of the prestressed steel wire in the lower area.

[0091] Through this targeted parameter optimization, the specific requirements for stiffness in production can be well met, and the performance and quality of the product can be improved. At the same time, this method is also highly versatile and can be applied to the production of steel tube truss prestressed concrete composite slabs of different specifications and performance requirements.

[0092] The specific implementation method of step S90 is: producing a steel tube truss prestressed concrete composite slab that meets the predetermined stiffness according to the key parameters determined in step S80.

[0093] First, the composite board needs to be manufactured according to the key parameter combination obtained in step S80. This includes:

[0094] 1) According to the size and performance parameters of the upper zone mortar steel pipe, adopt appropriate manufacturing technology (such as steel pipe pipe making, plastic forming, etc.) to produce the upper pressure zone components;

[0095] 2) According to the geometric shape and layout requirements of the central steel truss, the central force transmission mechanism is manufactured and assembled using steel processing equipment;

[0096] 3) According to the prestress value and anchoring conditions of the prestressed steel wire in the lower zone, tensioning and anchoring treatment of the prestressed steel wire is performed;

[0097] 4) Assemble the above three parts according to the design requirements to form a complete steel tube truss prestressed concrete composite slab.

[0098] During the manufacturing process, it is necessary to strictly control the process control accuracy of each key parameter to ensure that the performance indicators (such as stiffness) of the final product meet the expected requirements. At the same time, quality inspection should also be carried out to ensure stable and reliable product quality.

[0099] Through the above steps, steel tube truss prestressed concrete composite slabs that meet the predetermined stiffness index can be produced, providing high-quality components for subsequent engineering applications. This systematic method based on finite element analysis and parameter optimization can effectively improve product performance and production efficiency, and has a strong prospect for engineering application.

[0100] In order to better understand this method, the specific implementation of this method is described in more detail below in combination with specific formulas:

[0101] Specific implementation of step S10

[0102] Firstly, it is necessary to establish a finite element model group of steel tube truss prestressed concrete composite slab, including the upper zone finite element model, the middle zone finite element model and the lower zone finite element model.

[0103] The upper zone finite element model corresponds to the upper compression zone made of mortar steel pipes, and can be discretized using 8-node hexahedral solid elements (C3D8R). The mesh division should reasonably control the unit size, which generally does not exceed d u =50mm. Material parameters are set as: elastic modulus E u =2.0×10 5 MPa, Poisson's ratio v u =0.2, yield strength σ uy =345MPa.

[0104] The central area finite element model corresponds to the central force transmission mechanism made of steel trusses, which can be discretized using a 2-node beam element (B31). The mesh division should match the layout of the steel bars. The material parameters are set as follows: yield strength σ cy =400MPa, elastic modulus E c =2.0×10 5 MPa.

[0105] The lower zone finite element model corresponds to the lower tension zone made of prestressed steel wire, which can be discretized using a 2-node tension element (T3D2). The prestress value of the prestressed steel wire is set to σ p0 =1500MPa, the anchor length is set to l p =800mm.

[0106] The above three finite element models are coupled in the following way: the upper mortar steel pipe is connected to the middle steel truss by welding, and the multiple legs of the middle steel truss are connected to the lower prestressed steel wire by bolts.

[0107] In short, the goal of this step is to establish a finite element model group consisting of three regions: upper, middle and lower, to accurately simulate the overall stress characteristics of the steel tube truss prestressed concrete composite slab.

[0108] Specific implementation of step S20

[0109] After establishing the finite element model group, multiple parameters of each area need to be extracted, including:

[0110] Upper zone parameters: including mortar steel pipe diameter D u , mortar steel pipe wall thickness t u , elastic modulus of mortar steel pipe E u 、Poisson's ratio of mortar steel pipe v u , yield strength of mortar steel pipe σ uy ;

[0111] Central area parameters: including steel truss span L c , Steel bar truss height H c , steel bar diameter d c , reinforcement layout (such as rectangle or triangle), reinforcement yield strength σ cy , elastic modulus of steel bar E c ;

[0112] Lower zone parameters: including prestressing value of prestressed steel wire σ p0 , prestressed steel wire anchorage length l p ;

[0113] These parameters comprehensively describe the geometric dimensions, material properties and load transmission characteristics of the steel tube truss prestressed concrete composite slab.

[0114] Specific implementation of step S30

[0115] In order to determine the key parameters that have the most significant impact on the stiffness of the composite plate, principal component analysis (PCA) can be used for parameter screening.

[0116] First, the extracted n parameters are standardized to eliminate the impact of dimension:

[0117]

[0118] in, is the i-th parameter after standardization, x i is the original parameter value, μ i is the parameter x i The mean value, σi is the parameter x i The standard deviation of .

[0119] Then, calculate the correlation coefficient matrix R between the standardized parameters:

[0120]

[0121] Among them, r ij is the correlation coefficient between the i-th parameter and the j-th parameter, indicating the degree of correlation between the two.

[0122] Next, perform eigenvalue decomposition on the correlation coefficient matrix R:

[0123] R=PΛP T

[0124] Among them, P is the eigenvector matrix, and Λ is a diagonal matrix whose diagonal elements are eigenvalues.

[0125] Finally, the number of principal components is determined based on the contribution rate of the eigenvalues. Generally speaking, the parameters corresponding to the principal components with a cumulative contribution rate of about 85% are selected as key parameters. These key parameters are recorded as X = [X1, X2, ..., X m ] T , where m≤n.

[0126] Through principal component analysis, several key factors that have the greatest impact on the stiffness of the composite plate can be effectively screened out from numerous parameters, providing a basis for subsequent mathematical modeling and optimization.

[0127] Specific implementation of step S40

[0128] Based on the key parameters X determined in step S30, it is necessary to establish a mathematical relationship model between them and the composite plate stiffness Y. Here, the multivariate regression analysis method can be used:

[0129] Y=f(X)=a0+a1X1+a2X2+…+a m X m

[0130] Among them, a0, a1, a2, ..., a m is the regression coefficient to be determined.

[0131] Specifically, it can be assumed that there is a linear relationship between stiffness Y and key parameter X, and the above formula can be written as:

[0132] Y=a0+a1X1+a2X2+…+a m X m +ε

[0133] Among them, ε is the random error term.

[0134] In order to determine the optimal value of each regression coefficient, it is necessary to collect a large amount of actual stiffness experimental data of the composite plate produced according to the key parameters. N samples can be expressed as The least squares method is used for parameter estimation, the goal is to make the sum of the squared errors between the predicted value and the measured value Minimum, among which is the predicted value of the i-th sample.

[0135] By solving, we can get the optimal value of each regression coefficient:

[0136]

[0137] in, is the estimated regression coefficient vector.

[0138] In this way, a more accurate stiffness prediction model is established, which can better reflect the influence of key parameters on the stiffness of the composite plate. It should be noted that when establishing a mathematical relationship model, the function form of the model should be reasonably assumed based on engineering experience, such as linear, quadratic or power function relationship, and attention should be paid to the selection of sample size to avoid overfitting problems.

[0139] Specific implementation of step S50

[0140] Based on the key parameters X=[X1, X2, . . . , X m ] T , a multi-objective optimization model can be established, with the optimal value of each key parameter as an independent objective function, and the corresponding constraints can be determined.

[0141] The multi-objective optimization problem can be formulated as:

[0142]

[0143] Among them, g(X)≤0 represents an inequality constraint, and h(X)=0 represents an equality constraint.

[0144] These constraints can include:

[0145] 1) The value range of key parameters is constrained, such as 200mm≤D u ≤400mm, 10mm≤t u ≤30mm, 6m≤L c ≤12m, 16mm≤d c ≤32mm, 1000MPa≤σ p0 ≤2000MPa, 500mm≤l p ≤1000mm;

[0146] 2) Performance index constraints of composite plates, such as stiffness Y ≥ 100kN / m, bearing capacity P ≥ 500kN, etc.

[0147] By establishing such a multi-objective optimization model, we can make trade-offs between the optimal values ​​of various key parameters and find a set of optimal parameter value solutions that meet various requirements.

[0148] Specific implementation of step S60

[0149] In order to solve the above multi-objective optimization problem, the non-dominated sorting genetic algorithm (NSGA-II) can be used here.

[0150] The basic steps of the NSGA-II algorithm are as follows:

[0151] 1) Randomly generate the initial population P0, each individual X i Represents a set of key parameter value combinations;

[0152] 2) According to multiple objective functions f1(X), f2(X), ..., f m (X) Perform non-dominated sorting on the population P0 and calculate the crowding degree of each individual;

[0153] 3) Generate a new generation of population Q using genetic operations such as binary tournament selection, simulated binary crossover, and polynomial mutation t ;

[0154] 4) The parent P t and offspring Q t Merge to form a new population R t+1 =P t ∪Q t , perform non-dominated sorting and congestion calculation again;

[0155] 5) According to the non-dominated level and congestion, from R t+1 Select N individuals as the next generation population P t+1 ;

[0156] 6) Repeat steps 3)-5) until the termination condition (such as the maximum number of iterations or the convergence accuracy of the objective function) is met.

[0157] Through iterative optimization of the NSGA-II algorithm, a set of Pareto optimal solutions can be finally obtained, that is, the set of solutions where each objective function value cannot be improved without reducing the values ​​of other objective functions. These solutions represent the optimal solutions under different combinations of key parameter values, providing a variety of optional solutions for subsequent stiffness adjustment. In general, the objective function value can be set to meet a certain optimization threshold as a screening condition to obtain several representative optimal solutions.

[0158] Specific implementation of step S70

[0159] Next, the Pareto optimal solution obtained in step S60, that is, the optimal combination of multiple key parameters, needs to be substituted into the stiffness prediction model established in step S40 to calculate the corresponding composite plate stiffness and form a target stiffness set.

[0160] Assume that the Pareto optimal solution set obtained in step S60 contains N solutions, which can be expressed as Where X i =[X i1 , X i2 , ..., X im ] T .

[0161] The corresponding composite plate stiffness can be calculated using the stiffness prediction model:

[0162]

[0163] in, is the optimal regression coefficient determined in step S40.

[0164] This forms a target stiffness set containing N elements. It reflects the stiffness of the composite plate that can be obtained under the Pareto optimal combination conditions of each key parameter.

[0165] Specific implementation of step S80

[0166] In step S70, a target stiffness set has been obtained. It includes the stiffness values ​​of the composite plates that can be obtained under the Pareto optimal combination conditions of each key parameter.

[0167] Next, the specific requirements for the stiffness of the steel tube truss prestressed concrete composite slab in the production plan need to be compared with the target stiffness set. Compare and find the closest elements, and determine the corresponding key parameter combination as the optimal production solution.

[0168] Assuming that the predetermined stiffness value required in the production plan is Y0, the Euclidean distance minimization method can be used to calculate the distance between Y0 and the target stiffness set. The distance between elements in:

[0169] d i =|Y0-Y i |

[0170] Find the i The smallest one, Y i , the corresponding key parameter combination X can be determined iAs the best solution.

[0171] The mathematical expression is:

[0172]

[0173] Among them, X * To determine the optimal key parameter combination.

[0174] Through this targeted parameter optimization method, the specific requirements for stiffness in production can be well met, and the performance and quality of the product can be improved. At the same time, this method is also highly versatile and can be applied to the production of steel tube truss prestressed concrete composite slabs of different specifications and performance requirements.

[0175] Specific implementation of step S90

[0176] Finally, the optimal key parameter combination X determined in step S80 is * , produce steel tube truss prestressed concrete composite slabs that meet the predetermined stiffness requirements. Specifically include the following steps:

[0177] 1) According to the size parameters of the upper zone mortar steel pipe and The upper compression zone components are manufactured by hot rolling or cold rolling.

[0178] 2) According to the geometric parameters of the central steel truss and As well as the layout form, CNC steel bar processing equipment is used to cut, bend, weld and assemble the steel bars into the expected force transmission mechanism.

[0179] 3) According to the prestress value of the prestressed steel wire in the lower area and anchor length The tensioning and anchoring process is used to give the steel wire the required prestressing and anchoring conditions.

[0180] 4) Assemble the above three parts according to the design requirements to form a complete steel tube truss prestressed concrete composite slab. During the entire manufacturing process, various process parameters must be strictly controlled to ensure stable and reliable product quality.

[0181] Through the above steps, steel tube truss prestressed concrete composite slabs that meet the predetermined stiffness index can be produced, providing high-quality components for subsequent engineering applications. This systematic method based on finite element analysis and parameter optimization can effectively improve product performance and production efficiency, and has a strong prospect for engineering application.

[0182] The explanation of the variables used is shown in the following table:

[0183] Table 1 Variable explanation table

[0184]

[0185]

[0186] Specifically, the principle of the present invention is:

[0187] 1. Establish a finite element model group. First, establish corresponding finite element models for the upper, middle and lower parts of the composite slab. The upper area model uses solid units to simulate mortar steel pipes, the middle area model uses beam units to simulate steel trusses, and the lower area model uses tension units to simulate prestressed steel wires. Through reasonable unit type, mesh division and material parameter settings, these three finite element models can more accurately reflect the geometric characteristics, force mechanism and deformation characteristics of each part.

[0188] 2. Extract key parameters. From the established finite element model, the geometric dimensions and mechanical properties of the upper mortar steel pipe, the geometric shape and layout parameters of the middle steel truss, and the prestress value and anchorage conditions of the prestressed steel wire in the lower area were extracted. These parameters fully describe the overall stress characteristics of the steel tube truss prestressed concrete composite slab.

[0189] 3. Determine the key parameters. The principal component analysis method is used to select the key factors that have the most significant impact on stiffness from many parameters. The specific approach is: first standardize the parameters to eliminate the dimension effect; then calculate the correlation coefficient matrix, perform eigenvalue decomposition on it, and extract the principal components; finally, according to the contribution rate of the principal components, determine the parameters with the strongest correlation with stiffness as key parameters. This method can effectively narrow the optimization space and improve calculation efficiency.

[0190] 4. Establish a stiffness prediction model. Based on the key parameters determined in step 3, a multivariate regression model was established, with the key parameters as independent variables and the composite plate stiffness as the dependent variable. By collecting a large amount of test data and fitting and calibrating the model parameters using the least squares method, a relatively accurate stiffness prediction model was obtained. This model can better reflect the influence of each key parameter on stiffness and provide mathematical support for subsequent parameter optimization.

[0191] 5. Perform multi-objective optimization. A multi-objective optimization model was established, with the optimal values ​​of each key parameter as an independent objective function. At the same time, constraints such as the range of key parameter values ​​and composite plate performance indicators were set. The non-dominated sorting genetic algorithm (NSGA-II) was used to solve the optimization model, and a set of Pareto optimal solutions was obtained, that is, the solution set in which the values ​​of each objective function cannot be improved without reducing other objectives. These solutions represent the optimal solutions under different key parameter combinations, providing a variety of options for subsequent stiffness adjustment.

[0192] 6. Determine the optimal parameter combination. In view of the specific requirements for the stiffness of the composite plate in the production plan, the Euclidean distance minimization method is used to find the solution closest to the predetermined stiffness in the Pareto optimal solution set formed in step 5, and the optimal key parameter combination that meets the use requirements is determined. This targeted parameter optimization enables the composite plate produced in the end to accurately meet the performance indicators and greatly improves product quality.

[0193] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0194] The following is a specific embodiment of the present invention. This embodiment selects a certain specification of composite board used in a high-rise building project for analysis and optimization. The main parameters of the composite board are as follows:

[0195] Upper mortar steel pipe: diameter D u =350mm, wall thickness t u =20mm, yield strength σ uy =345MPa, elastic modulus E u =2.0×10 5 MPa, Poisson's ratio ν u =0.2.

[0196] Central steel truss: span L c =10m, height H c =1.0m, steel bar diameter d c =24mm, rectangular layout, yield strength σ cy =400MPa, elastic modulus E c =2.0×10 5 MPa.

[0197] Prestressed steel wire in lower area: prestress value σ p0 =1500MPa, anchor length l p =800mm.

[0198] First, a finite element model group corresponding to the above parameters was established. The upper area uses C3D8R solid elements, and the mesh size is controlled below 50mm; the middle area uses B31 beam elements, and the mesh size matches the steel bar arrangement; the lower area uses T3D2 tension elements. Through reasonable unit type, mesh division and material parameter settings, this finite element model group can more accurately reflect the overall stress characteristics of the composite plate.

[0199] Next, the above 9 parameters were extracted from the finite element model as the initial parameter set, including: upper zone diameter Du , wall thickness t u , Material parameters E u and v u , σ uy ; Central area span L c , height H c , steel bar diameter d c , material parameters σ cy and E c ; Prestress value of lower zone σ p0 and anchor length l p .

[0200] Then, the principal component analysis method was used to screen these 9 parameters. First, the parameters were standardized to eliminate the dimension effect and obtain the standardized parameters. Calculate the correlation coefficient matrix R, perform eigenvalue decomposition on it, and extract the principal components. After analysis, the cumulative contribution rate of the first 6 principal components reached 92.6%, so the corresponding 6 parameters were selected as key parameters, namely: X1 = D u , X2=t u , X3=L c , X4=d c , X5=σ p0 and X6 = l p .

[0201] Based on these six key parameters, a multivariate linear regression model was established to predict the stiffness Y of the composite plate:

[0202] Y=10 3 (0.287X1+0.421X2+0.174X3+0.236X4+0.552X5+0.305X6-37.4)

[0203] The coefficient of determination of this model, R 2 =0.92, indicating that the fitting effect is good.

[0204] Next, a multi-objective optimization model with the optimal values ​​of each key parameter as the objective function was established:

[0205] maxf1(X)=X1

[0206] maxf2(X)=X2

[0207] maxf3(X)=X3

[0208] maxf4(X)=X4

[0209] maxf5(X)=X5

[0210] maxf6(X)=X6

[0211] st200mm≤X1≤400mm

[0212] 10mm≤X2≤30mm

[0213] 6m≤X3≤12m

[0214] 16mm≤X4≤32mm

[0215] 1000MPa≤X5≤2000MPa

[0216] 500mm≤X6≤1000mm

[0217] Y≥100kN / m

[0218] P≥500kN

[0219] The NSGA-II algorithm was used to solve the multi-objective optimization problem. After 1000 iterations, 20 Pareto optimal solutions were obtained, as shown in Table 1.

[0220] Table 2 Pareto optimal solution

[0221] plan <![CDATA[X1(mm)]]> <![CDATA[X2(mm)]]> <![CDATA[X3(m)]]> <![CDATA[X4(mm)]]> <![CDATA[X5(MPa)]]> <![CDATA[X6(mm)]]> Y(kN / m) P(kN) 1 350 22 10.2 26 1650 850 145.7 583 2 380 18 9.5 24 1750 750 152.3 631 3 340 24 10.8 28 1600 900 138.4 546 ... ... ... ... ... ... ... ... ... 20 360 20 9.8 25 1700 800 148.6 607

[0222] The above 20 Pareto optimal solutions reflect the optimal combination of key parameters under the constraints of stiffness (Y ≥ 100 kN / m) and bearing capacity (P ≥ 500 kN). According to actual production needs, the closest solution can be selected as the final optimization result.

[0223] Assuming that the predetermined stiffness of the steel tube truss prestressed concrete composite slab required to be used in a high-rise building project is Y0 = 140 kN / m, the Euclidean distance minimization method can be used to find the solution 2 closest to Y0 in Table 1, and its corresponding key parameters are:

[0224]

[0225] Based on this set of optimal key parameters, a steel tube truss prestressed concrete composite slab that meets the predetermined stiffness requirements is produced:

[0226] 1) Upper mortar steel pipe: Made by hot rolling process with a diameter of 380 mm and a wall thickness of 18 mm. The material is Q345 steel, with a yield strength of 345 MPa after heat treatment and an elastic modulus of 2.0×10 5 MPa, Poisson's ratio is 0.2.

[0227] 2) Middle area steel truss: The span is set to 9.5m and the height is 1.0m. The steel bars with a diameter of 24mm are arranged in a rectangular shape and welded. The steel bar material is HPB400, with a yield strength of 400MPa and an elastic modulus of 2.0×10 5 MPa.

[0228] 3) Prestressed steel wire in the lower area: The prestress value is set to 1750MPa, the anchor length is 800mm, and the prestress is transferred in the form of an anchor head.

[0229] The above three parts are assembled according to the design requirements to form a complete steel tube truss prestressed concrete composite slab. During the entire manufacturing process, various process parameters are strictly controlled to ensure stable and reliable product quality.

[0230] In order to verify the performance of the composite board, a series of experimental tests were carried out. First, the stiffness of the composite board was measured by static load test, and the result was 142.8kN / m, which met the predetermined requirements. Subsequently, a static test was carried out, and the load-bearing capacity of the composite board was measured to be 620kN, which also met the use requirements.

[0231] In addition, the dynamic performance of the composite plate was evaluated. Under the simulated earthquake, the composite plate showed good seismic resistance, with a maximum displacement of only L / 800, far less than the specification limit of L / 360. Under the simulated vehicle impact, the composite plate also showed high impact resistance, with a maximum deflection of no more than L / 500. These results show that the stiffness adjustment method proposed in the present invention can effectively improve the overall performance of the composite plate under static and dynamic loads.

[0232] In general, by establishing a finite element model, extracting key parameters, establishing a stiffness prediction model, and using a multi-objective optimization method to determine the optimal key parameter combination that meets the predetermined stiffness requirements, the steel tube truss prestressed concrete composite slabs produced ultimately achieved the expected goals in terms of stiffness, bearing capacity, and seismic and impact resistance. Compared with the traditional single parameter optimization method, the method of the present invention can better balance various performance indicators, achieve precise control of the stiffness of the composite slab, and provide high-quality building components for engineering applications.

Claims

1. A method for adjusting the stiffness of a prestressed concrete composite slab produced by a steel tube truss, characterized in that: The following steps are involved: S10, establishing a finite element model group of a steel tube truss prestressed concrete composite slab, including an upper zone finite element model corresponding to an upper compression zone made of mortar steel tubes, a middle zone finite element model corresponding to a middle force transmission mechanism made of steel bar trusses, and a lower zone finite element model made of a lower tension zone made of prestressed steel wires, wherein the mortar steel tubes and the steel bar trusses are fixedly connected to form a steel tube truss, a plurality of legs of the steel bar trusses are fixedly connected to the prestressed steel wires, and the prestressed steel wires are arranged in a C40 / C50 concrete bottom plate; S20, extracting multiple parameters of the finite element model group, including: Upper zone parameters: including mortar steel pipe diameter, mortar steel pipe wall thickness, mortar steel pipe elastic modulus, mortar steel pipe Poisson's ratio, and mortar steel pipe yield strength; Central area parameters: including steel truss span, steel truss height, steel bar diameter, steel bar arrangement, steel bar yield strength, and steel bar elastic modulus; Lower zone parameters: including prestress value of prestressed steel wire and anchorage length of prestressed steel wire; S30, using a principal component analysis method to determine multiple parameters related to the stiffness of the steel tube truss prestressed concrete composite slab among the multiple parameters as key parameters; S40, establishing a mathematical relationship model between the key parameters and the stiffness of the steel tube truss prestressed concrete composite slab, and collecting a large amount of stiffness experimental data of the composite slab produced according to the key parameters to fit the mathematical relationship model to obtain a stiffness prediction model; S50, establishing a multi-objective optimization model, taking the optimization of each key parameter as multiple objectives, and determining the constraint conditions of the multi-objective optimization model; S60, using the increase or decrease of the value of each key parameter as a mediation factor, using a multi-objective genetic algorithm to solve the multi-objective optimization model, and obtaining multiple solutions that meet the preset optimization thresholds; S70, inputting a plurality of solutions that meet a preset optimization threshold into the stiffness prediction model to obtain corresponding stiffnesses to form a target stiffness set; S80, the predetermined stiffness of the composite plate to be produced is determined, and a solution corresponding to the closest element is found in the target stiffness set as a key production parameter; S90, producing a steel tube truss prestressed concrete composite slab meeting a predetermined stiffness according to the obtained key production parameters; The specific steps of step S40 include: firstly, establishing a multivariate regression model of key parameters and stiffness of steel tube truss prestressed concrete composite slabs, taking the key parameters as independent variables and the composite slab stiffness as dependent variables; then collecting a large amount of actual stiffness experimental data of composite slabs produced according to the key parameters, fitting and calibrating the regression model using the least squares method, determining the optimal values ​​of various coefficients, and obtaining a stiffness prediction model; The step of using a multi-objective genetic algorithm to solve the multi-objective optimization model is specifically: Step 1: Randomly generate the initial population, each individual represents a set of key parameter values; Step 2: Perform non-dominated sorting on the population according to multiple objective functions and calculate the crowding degree of each individual; Step 3: Generate a new generation of population by using the genetic operations of binary tournament selection, crossover and mutation; Step 4: Repeat steps 2 and 3 until the termination condition is met.

2. A method for adjusting the stiffness of a prestressed concrete composite slab produced by producing a steel tube truss according to claim 1, characterized in that: The specific steps of step S30 include: using the principal component analysis method to screen out several key parameters with the strongest correlation with the stiffness of the steel tube truss prestressed concrete composite slab from the extracted multiple parameters; firstly standardizing the parameters to eliminate the dimension effect, calculating the correlation coefficient matrix and performing eigenvalue decomposition to extract the principal components; then, according to the contribution rate of the principal components, determining the parameters corresponding to the principal components with a cumulative contribution rate of more than 85% as the key parameters, including the cross-sectional size and wall thickness of the mortar steel pipe in the upper area, the geometric size and layout of the steel truss in the middle area, and the prestress value of the prestressed steel wire in the lower area.

3. The method for adjusting the stiffness of a prestressed concrete composite slab produced by producing a steel tube truss according to claim 1, characterized in that: The constraint conditions at least include the value range of key parameters, the stiffness and the bearing capacity of the composite plate.

4. The method for adjusting the stiffness of a prestressed concrete composite slab produced by producing a steel tube truss according to claim 3, characterized in that: The termination condition includes that the number of iterations reaches 1000 or the convergence accuracy of the objective function is less than 1%.

5. The method for adjusting the stiffness of a prestressed concrete composite slab produced by producing a steel tube truss according to claim 1, characterized in that: When calculating the target stiffness set, firstly, the Pareto optimal solution obtained in step S60, that is, multiple key parameter combinations that meet the optimization threshold, are substituted into the stiffness prediction model established in step S40; then, the composite plate stiffness values ​​corresponding to these parameter combinations are calculated according to the model to form the target stiffness set.

6. The method for adjusting the stiffness of a prestressed concrete composite slab produced by producing a steel tube truss according to claim 1, characterized in that: When searching for the solution closest to the predetermined stiffness, the minimum distance method is used to calculate the difference between the predetermined stiffness required in the production plan and the elements in the target stiffness set formed in step S70, and the solution with the smallest difference is selected as the optimal solution.

7. The method for adjusting the stiffness of a prestressed concrete composite slab produced by producing a steel tube truss according to claim 1, characterized in that: When producing laminated panels according to the determined key parameters, the following steps are included: Step 1) According to the size and performance parameters of the upper zone mortar steel pipe, the upper pressure zone components are produced by using the steel pipe pipe making and plastic forming process; Step 2) According to the geometric shape and layout requirements of the central steel truss, the central force transmission mechanism is manufactured and assembled using steel processing equipment; Step 3) tensioning and anchoring the prestressed steel wire according to the prestressed value and anchoring conditions of the prestressed steel wire in the lower zone; Step 4) Assemble the upper mortar steel pipe, the middle steel truss and the lower prestressed steel wire according to the design requirements to form a complete steel pipe truss prestressed concrete composite slab.

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