Optimization method for parametric design of steel formwork

Abstract

The application provides an optimization method for parameterized design of a steel formwork, and belongs to the technical field of building construction.The application establishes a non-uniform rational B-spline surface parameter equation, generates a thickness distribution function and a back spacing parameter based on the surface parameter equation for steel formwork block parameterized design, constructs a support system mechanical parameterization model to determine support spacing optimization parameters and rod section sizes, uses a game optimization algorithm to solve a double-layer decision system containing a top formwork deformation minimization decision model and a bottom concrete surface flatness optimization response model, generates digital manufacturing instructions to establish a formwork number and geometric feature mapping relationship, and establishes a quality real-time monitoring system to dynamically adjust configuration parameters through a formwork adaptability evaluation function, thereby solving the technical problem of inaccurate formwork deformation control caused by the lack of accurate parameterized optimization in the design of a special-shaped concrete structure steel formwork.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of building construction, and in particular relates to an optimization method for parametric design of a steel formwork. BACKGROUND

[0002] In the construction of special-shaped concrete structures, steel formwork design is a key technical link to ensure the quality of concrete forming. Traditional steel formwork design mainly relies on empirical formulas and statics calculation methods to determine the thickness distribution of the formwork and the spacing of the supports. The geometric design is carried out by hand-drawing or two-dimensional CAD software, and a simplified treatment method of uniform thickness distribution and equal-interval support arrangement is adopted. In the current construction of special-shaped concrete structures, due to the irregularity of complex curved surface geometry and the non-uniform distribution characteristics of concrete pouring pressure, the traditional design method is difficult to accurately describe the curved surface parameters and optimize the formwork configuration, resulting in local excessive deformation or resource waste of the steel formwork during the construction process, which affects the quality of concrete surface forming and the construction efficiency. That is, there is a technical problem in the prior art that the lack of precise parametric optimization in the design of steel formwork for special-shaped concrete structures leads to inaccurate formwork deformation control. SUMMARY

[0003] Therefore, the present application provides an optimization method for parametric design of a steel formwork, which can solve the technical problem of inaccurate formwork deformation control caused by the lack of precise parametric optimization in the design of steel formwork for special-shaped concrete structures in the prior art.

[0004] The application is implemented in the following manner: the application provides an optimization method for parametric design of a steel formwork, geometric boundary data and curvature variation data of a special-shaped concrete structure are collected, spatial coordinate point clouds of a structure surface are obtained through a three-dimensional laser scanner, a surface parameter equation of the special-shaped concrete structure is established, the surface parameter equation is expressed by a non-uniform rational B-spline function, and surface control point coordinates and weight coefficients are output; steel formwork block parametric design is performed based on the surface parameter equation, a formwork configuration optimization model is used to determine geometric sizes and splicing positions of steel formwork units, a steel formwork thickness distribution function and a back bar spacing parameter are generated, the steel formwork thickness distribution function is used to calculate thickness values of each formwork unit according to a concrete pouring pressure and a formwork deformation limit value; a mechanical parametric model of a support system is constructed, stress distribution and deformation of support rods under a concrete pouring load are calculated through finite element analysis, support spacing optimization parameters and rod section sizes are determined, and a rod adjustment range database is established; a game optimization algorithm is used to solve an optimal solution of steel formwork design parameters, the game optimization algorithm includes an upper-layer decision model with minimization of formwork deformation as an objective and a lower-layer response model with optimization of concrete forming surface flatness as an objective, and a deformation flatness coupling function is used as a coupling term to realize coordinated optimization; digital manufacturing instructions for steel formwork processing are generated, the optimized steel formwork thickness distribution function and the back bar spacing parameter are converted into numerical control processing codes, and a mapping relationship between formwork numbers and geometric characteristics is established.

[0005] The surface parameter equation is specifically used to describe a complex curved surface shape of the special-shaped concrete structure through control point coordinates and weight coefficients, the control point coordinates are determined through fitting of spatial coordinate point clouds obtained by three-dimensional laser scanning, and the weight coefficients are calculated according to local curvature variation of the curved surface.

[0006] The steel formwork thickness distribution function is specifically a mathematical model established based on a concrete pouring pressure distribution and a formwork allowable deflection, the concrete pouring pressure is calculated according to a pouring height and a concrete density, the formwork deformation limit value is set to 1 / 400 of a span, and the back bar spacing parameter is determined through formwork stiffness demand and back bar bearing capacity.

[0007] The support spacing optimization parameter is specifically an optimal balance point of support rod bearing capacity and formwork deformation constraint solved through a Lagrange multiplier method, the rod section size includes calculated values of a moment of inertia and a section modulus, and the rod adjustment range database records maximum adjustment amplitudes of support rods of different section types.

[0008] The method further includes establishing a steel formwork quality real-time monitoring system, collecting formwork deformation data through a displacement sensor, calculating a quality deviation index through a formwork adaptability evaluation function, and automatically adjusting a block size parameter of the formwork configuration optimization model when the quality deviation index exceeds a preset threshold.

[0009] The numerical control machining code specifically contains steel plate cutting path coordinates and back lath welding position coordinates, a mapping relationship between a template number and a geometric feature adopts a logical number to establish a unique identification code, and a standardized machining process flow contains an operation sequence of blanking cutting, back lath welding, surface treatment and dimension inspection.

[0010] The template configuration optimization model is structured as an image block processing network based on a visual transformer architecture, contains an encoder layer and a decoder layer for processing a steel template geometric feature image, identifies an optimal block mode through an image block mechanism, and dynamically adjusts a block size parameter according to three input parameters of a curved surface control point coordinate density, a back lath spacing parameter and a quality deviation index.

[0011] The objective function of the upper-layer decision model is to minimize the maximum deformation of the steel template, the constraint condition contains a template strength constraint and a geometric size constraint, the objective function of the lower-layer response model is to maximize a concrete surface flatness evaluation index, the constraint condition contains a support rod stability requirement and a joint gap limitation, and the deformation flatness coupling function is a weighted product function of the steel template deformation and the concrete surface flatness.

[0012] The adaptive index adjustment mechanism is that when the adaptive index is less than 0.322, it indicates that the current block is too fine and the block size parameter needs to be increased to reduce the number of joints, when the adaptive index is greater than 0.679, it indicates that the current block is too coarse and the block size parameter needs to be reduced to improve the forming precision, and when 0.322≤adaptive index≤0.679, the current block size parameter is maintained unchanged.

[0013] The template adaptability evaluation function is used to adjust the block size parameter of the template configuration optimization model according to the actual deformation situation of the construction site, the input includes the curved surface control point coordinate density, the back lath spacing parameter, the quality deviation index and the real-time deformation data, and the output is an adaptive index between 0 and 1.

[0014] The training data set establishment step of the template configuration optimization model specifically collects curved surface parameter equations of different types of special-shaped concrete structures and corresponding optimal steel template block schemes, converts the curved surface parameter equations into a standardized feature image format, establishes a label corresponding relationship between the input image and the output block parameter, and expands the number of training samples through geometric transformation technology. The template configuration optimization model training step specifically trains network parameters in a supervised learning manner, uses a mean square error loss function to measure the difference between the predicted block scheme and the real optimal scheme, updates network weights through a back propagation algorithm, and sets a learning rate decay strategy to control the training convergence process.

[0015] The curved surface control point coordinate density refers to the number of control point coordinates per unit area, which is used to quantify the geometric complexity of the special-shaped concrete structure.

[0016] The mass deviation index refers to the relative error of the actual steel formwork deformation and the theoretically calculated deformation, and is used to evaluate the accuracy of the parameterized design of the steel formwork.

[0017] The image block mechanism refers to dividing the steel formwork geometric feature image into a plurality of sub-image blocks according to a fixed size, and each sub-image block corresponds to the geometric information of a formwork unit.

[0018] The deformation flatness coupling function refers to the weighted product of the steel formwork deformation and the concrete surface flatness evaluation index, and is used to coordinate the optimization objectives of the upper decision model and the lower response model. The weight coefficient is determined according to the engineering quality requirement.

[0019] The logical number refers to the coding rule established according to the spatial position and installation sequence of the steel formwork in the special-shaped concrete structure. The number format includes area identification and sequence identification.

[0020] The present application solves the technical problem that the steel formwork design for special-shaped concrete structures lacks accurate parameterized optimization, resulting in inaccurate formwork deformation control, by establishing a double-layer decision model based on a non-uniform rational B-spline function surface parameter equation and a game optimization algorithm. The present application uses three-dimensional laser scanning to obtain accurate spatial coordinate point cloud data, accurately describes complex geometric shapes in combination with the surface parameter equation, and realizes accurate calculation of formwork configuration through steel formwork thickness distribution function and support spacing optimization parameters, overcoming the technical defects of traditional methods in complex surface processing and deformation prediction. The present application uses a game optimization algorithm to coordinate the dual objectives of minimizing formwork deformation and optimizing concrete surface flatness, and realizes accurate control of parameterized design through a deformation flatness coupling function, fundamentally improving the accuracy and adaptability of steel formwork design, and solving the technical problem that the steel formwork design for special-shaped concrete structures lacks accurate parameterized optimization, resulting in inaccurate formwork deformation control. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 The flowchart of the method of the present application.

[0022] Figure 2 Rhino three-dimensional positioning and model deepening diagram in Example 2, including three sub-diagrams (a) is a three-dimensional positioning diagram, (b) and (c) are front and back model deepening diagrams.

[0023] Figure 3 Steel formwork system design diagram in Example 2.

[0024] Figure 4 Split column formwork installation completion diagram in Example 2. DETAILED DESCRIPTION

[0025] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application.

[0026] As Figure 1 shown is a flow chart of an optimization method for parametric design of a steel formwork provided by the present application, and the method comprises the following steps:

[0027] S01, collecting geometric boundary data and curvature variation data of a special-shaped concrete structure, obtaining spatial coordinate point clouds of a structure surface through a three-dimensional laser scanner, establishing a curved surface parameter equation of the special-shaped concrete structure, the curved surface parameter equation being expressed by a non-uniform rational B-spline function, and outputting curved surface control point coordinates and weight coefficients;

[0028] S02, performing steel formwork block parametric design based on the curved surface parameter equation, determining geometric sizes and splicing positions of steel formwork units by using a formwork configuration optimization model, generating a steel formwork thickness distribution function and a back arris spacing parameter, and calculating thickness values of each formwork unit according to concrete pouring pressure and formwork deformation limit values according to the steel formwork thickness distribution function;

[0029] S03, constructing a mechanical parametric model of a support system, calculating stress distribution and deformation of support rods under concrete pouring load through finite element analysis, determining support spacing optimization parameters and rod section sizes, and establishing a rod adjustment range database;

[0030] S04, solving an optimal solution of steel formwork design parameters by using a game optimization algorithm, the game optimization algorithm comprising an upper layer decision model with minimization of formwork deformation as an objective and a lower layer response model with optimization of concrete forming surface flatness as an objective, and realizing coordinated optimization through a deformation flatness coupling function as a coupling term;

[0031] S05, generating digital manufacturing instructions for steel formwork processing, converting the optimized steel formwork thickness distribution function and the back arris spacing parameter into numerical control processing codes, establishing a mapping relationship between formwork numbers and geometric characteristics, and forming a standardized processing process flow;

[0032] S06, establishing a steel formwork quality real-time monitoring system, collecting formwork deformation data through a displacement sensor, calculating a quality deviation index by using a formwork adaptability evaluation function, and automatically adjusting block size parameters of the formwork configuration optimization model when the quality deviation index exceeds a preset threshold.

[0033] The complex curved surface shape of the special-shaped concrete structure is described by the curved surface parameter equation through control point coordinates and weight coefficients, the control point coordinates are determined by fitting the spatial coordinate point cloud obtained by three-dimensional laser scanning, and the weight coefficients are calculated according to the local curvature variation of the curved surface.

[0034] The steel formwork thickness distribution function is based on a mathematical model established based on a concrete pouring pressure distribution and a formwork allowable deflection, the concrete pouring pressure is calculated according to a pouring height and a concrete density, the formwork deformation limit value is set to 1 / 400 of the span, and the back rafter spacing parameter is determined by a formwork stiffness requirement and a back rafter bearing capacity.

[0035] The support spacing optimization parameter is solved by a Lagrange multiplier method to balance the optimal points of a support rod bearing capacity and a formwork deformation constraint, the rod section size includes calculated values of a moment of inertia and a section modulus, and a rod adjustment range database records maximum adjustment amplitudes of different section type support rods.

[0036] The objective function of the upper decision model is to minimize the maximum deformation of the steel formwork, the constraint condition includes a formwork strength constraint and a geometric size constraint, the objective function of the lower response model is to maximize a concrete surface flatness evaluation index, the constraint condition includes a support rod stability requirement and a joint gap limitation, and the deformation flatness coupling function is a weighted product function of the steel formwork deformation and the concrete surface flatness.

[0037] The numerical control machining code includes steel plate cutting path coordinates and back rafter welding position coordinates, the mapping relationship between the formwork number and the geometric feature adopts a logical number to establish a unique identification code, and the standardized machining process flow includes an operation sequence of blanking cutting, back rafter welding, surface treatment and size inspection.

[0038] The structure of the formwork configuration optimization model is an image block processing network based on a visual transformer architecture, includes an encoder layer and a decoder layer for processing a steel formwork geometric feature image, an optimal block mode is identified through an image block mechanism, and a block size parameter is dynamically adjusted according to three input parameters of a curved surface control point coordinate density, a back rafter spacing parameter and a quality deviation index.

[0039] The training data set establishment step of the formwork configuration optimization model includes collecting curved surface parameter equations of different types of special-shaped concrete structures and corresponding optimal steel formwork block schemes, converting the curved surface parameter equations into a standardized feature image format, establishing a label corresponding relationship between an input image and an output block parameter, and expanding the number of training samples through a geometric transformation technology.

[0040] The template configuration optimization model training step includes training network parameters in a supervised learning manner, using a mean square error loss function to measure the difference between the predicted block scheme and the real optimal scheme, updating network weights through a back propagation algorithm, and setting a learning rate decay strategy to control the training convergence process.

[0041] The template adaptability evaluation function is used to adjust the block size parameter of the template configuration optimization model according to the actual deformation of the construction site, the input includes the surface control point coordinate density, the back brace spacing parameter, the quality deviation index and the real-time deformation data, and the output is an adaptability index between 0 and 1.

[0042] The adaptability index adjustment mechanism is that when the adaptability index is less than 0.322, it indicates that the current block is too fine and the block size parameter needs to be increased to reduce the number of seams, when the adaptability index is greater than 0.679, it indicates that the current block is too coarse and the block size parameter needs to be reduced to improve the forming precision, and when the adaptability index is between 0.322 and 0.679, the current block size parameter is maintained unchanged.

[0043] The surface control point coordinate density is the number of control point coordinates per unit area, which is used to quantify the geometric complexity of the special-shaped concrete structure.

[0044] The quality deviation index is the relative error between the actual steel formwork deformation and the theoretical calculation deformation, which is used to evaluate the accuracy of the parametric design of the steel formwork.

[0045] The image block mechanism is to divide the steel formwork geometric feature image into multiple sub-image blocks according to a fixed size, and each sub-image block corresponds to the geometric information of a template unit.

[0046] The deformation flatness coupling function is the weighted product of the steel formwork deformation and the concrete surface flatness evaluation index, which is used to coordinate the optimization objectives of the upper decision model and the lower response model, and the weight coefficient is determined according to the engineering quality requirements.

[0047] The logical number is an encoding rule established according to the spatial position and installation sequence of the steel formwork in the special-shaped concrete structure, and the number format includes area identification and sequence identification.

[0048] The specific implementation of the above steps is described in detail below.

[0049] The specific implementation of step S01 is to obtain the spatial geometric information of the special-shaped concrete structure by using three-dimensional laser scanning technology. First, the surface of the special-shaped concrete structure is scanned in all directions by a high-precision three-dimensional laser scanner, and spatial coordinate point cloud data with a density of 1000 to 5000 points per square meter is obtained, and the scanning accuracy is controlled within ±1 millimeter. Then the obtained point cloud data is preprocessed, including removing noise points, filling missing areas and coordinate system, and the least squares fitting algorithm is used to eliminate measurement errors. Then the non-uniform rational B-spline function is used to establish the surface parameter equation, which can accurately describe the complex special-shaped surface shape, and the parameterization expression of the surface geometric characteristics is realized by adjusting the control point coordinates and weight coefficients. The control point coordinates are determined by the optimal fitting of the point cloud data, and the weight coefficients are calculated by the curvature analysis algorithm according to the local curvature change of the surface, and the weight coefficients in the area with large curvature change are set to 1.2 to 1.8, and the weight coefficients in the area with small curvature change are set to 0.8 to 1.2. Finally, the surface parameter equation containing the control point coordinate matrix and the corresponding weight coefficient vector is output, which provides an accurate geometric basis for subsequent steel formwork design.

[0050] The specific implementation of step S02 is to design and optimize the steel formwork based on the established surface parameter equation. First, the special-shaped surface is intelligently blocked by using a template configuration optimization model, which is based on a visual transformer architecture and includes an encoder layer and a decoder layer for processing steel formwork geometric feature images. The encoder layer uses a multi-head attention mechanism to extract surface geometric features, and the decoder layer identifies the optimal blocking mode through an image blocking mechanism, and the blocking size is dynamically adjusted according to the complexity of the surface, and the blocking size in complex areas is set to 0.5 meters x 0.5 meters to 1.0 meters x 1.0 meters, and the blocking size in simple areas is set to 1.5 meters x 1.5 meters to 2.0 meters x 2.0 meters. Then a steel formwork thickness distribution function is established, which takes the concrete pouring pressure and the formwork deformation limit as input parameters, the pouring pressure is calculated according to the concrete density of 2400 kilograms per cubic meter and the pouring height according to the principle of hydrostatic pressure, and the formwork deformation limit is set to 1 / 400 of the span. The thickness distribution function calculates the optimal thickness value of each formwork unit by finite element analysis method, and the thickness range is controlled between 6 millimeters and 20 millimeters. At the same time, the back ridge spacing parameter is determined, and through the balance analysis of the formwork stiffness demand and the back ridge bearing capacity, the back ridge spacing is set to 300 millimeters to 800 millimeters, which ensures that the deformation of the formwork under the action of pouring load is controlled within the allowable range.

[0051] The specific implementation of step S03 is to construct a mechanical parameterized model of the support system and perform optimization analysis. First, a three-dimensional finite element model of the support rod is established, beam elements are used to simulate the support rod, and spring elements are used to simulate the rod connection nodes. The dynamic load effect during concrete pouring is considered in the model. Then, the stress distribution and deformation of the support rod under the concrete pouring load are calculated by finite element analysis. The load includes the weight of the concrete, the pouring dynamic load, and the lateral pressure. The dynamic load coefficient is 1.2. Then, the Lagrange multiplier method is used to solve the support spacing optimization parameter. This method establishes a mathematical model of the objective function and the constraint condition to find the optimal balance point of the support rod bearing capacity and the formwork deformation constraint. The support spacing optimization range is 1.0 meters to 3.0 meters. The rod section size design includes the calculation of the moment of inertia and the cross-sectional modulus. The moment of inertia is controlled within the range of mm 4 to mm 4 , and the cross-sectional modulus is controlled within the range of mm 3 to mm 3 . Finally, a tie rod adjustment range database is established to record the maximum adjustment amplitude of different cross-section types of support rods. The adjustment amplitude of round pipe support is ±150 mm, the adjustment amplitude of square pipe support is ±120 mm, and the adjustment amplitude of I-beam support is ±200 mm.

[0052] The specific implementation of step S04 is to use a game optimization algorithm to solve the global optimal solution of the steel formwork design parameters. This algorithm uses a double-layer optimization structure. The upper layer decision model takes minimizing the maximum deformation of the steel formwork as the objective function, with the deformation control target value being 1 / 500 of the span. The constraint conditions include formwork strength constraints and geometric size constraints. The strength safety factor is set to 2.0, and the geometric size constraint ensures that the formwork unit length-width ratio is controlled within the range of 1:1 to 1:3. The lower layer response model takes maximizing the concrete surface flatness evaluation index as the objective function. The flatness evaluation index is calculated using the standard deviation of the surface deviation, with the target value controlled within 2 mm. The constraint conditions include support rod stability requirements and joint gap limitations. The rod slenderness ratio is controlled within 150, and the joint gap is controlled within the range of 1 mm to 3 mm. The two-layer model is optimized through a deformation flatness coupling function. The coupling function is a weighted product function of the steel formwork deformation and the concrete surface flatness evaluation index. The weight coefficient is determined according to the engineering quality requirements. The weight ratio is generally 1:1, and the weight ratio for high-precision engineering is 1:2. The algorithm uses an iterative solution method. The design parameters output by the upper layer model are passed to the lower layer model, and the response results output by the lower layer model are fed back to the upper layer model. Through multiple iterations, the algorithm converges when the difference between the results of the adjacent two iterations is less than 0.01.

[0053] The specific implementation of step S05 is to convert the optimized design parameters into digital manufacturing instructions and establish a standardized process. First, convert the steel template thickness distribution function and back lath spacing parameters into numerical control machining codes, including precise numerical values of steel plate cutting path coordinates and back lath welding position coordinates. The cutting path is represented in a rectangular coordinate system, and the coordinate accuracy is controlled within 0.1 millimeters. Then, establish a mapping relationship between template numbers and geometric characteristics, and use logical numbering to establish a unique identification code. The numbering format includes area identification and sequential identification. Area identification uses two-letter representation, and sequential identification uses three-digit representation, forming a numbering format like AB001. Next, develop a standardized machining process, including four main processes: cutting, back lath welding, surface treatment, and dimensional inspection. Cutting uses plasma cutting or laser cutting technology, with a cutting accuracy controlled within ±0.5 millimeters. Back lath welding uses carbon dioxide gas shielded welding, with a weld height controlled within 3 to 5 millimeters. Surface treatment includes rust removal and brush coating of release agent. Dimensional inspection uses a three-coordinate measuring machine for full-size detection, with a detection accuracy of ±0.2 millimeters. Finally, establish a quality traceability system, correlating template numbers with processing parameters and inspection results to form a complete manufacturing file.

[0054] The specific implementation of step S06 is to establish a real-time monitoring system for steel template quality and achieve dynamic optimization and adjustment. First, install displacement sensors on key template units, with a sensor arrangement interval of 2 to 5 meters. Use laser displacement sensors or wire-type displacement sensors with a measurement accuracy of 0.01 millimeters to collect real-time template deformation data. Then, use the template adaptability evaluation function to calculate the quality deviation index. This function takes the surface control point coordinate density, back lath spacing parameters, quality deviation index, and real-time deformation data as input parameters. The surface control point coordinate density is the number of control point coordinates per unit area, used to quantify the geometric complexity of the special-shaped concrete structure. The quality deviation index is the relative error between the actual steel template deformation and the theoretically calculated deformation, with an adaptability index output between 0 and 1. Next, establish an adaptability index adjustment mechanism. When the adaptability index is less than 0.322, it indicates that the current block is too fine and the block size parameter needs to be increased to reduce the number of seams. The adjustment range is 1.2 to 1.5 times the original block size. When the adaptability index is greater than 0.679, it indicates that the current block is too coarse and the block size parameter needs to be reduced to improve the forming precision. The adjustment range is 0.7 to 0.8 times the original block size. When the adaptability index is between 0.322 and 0.679, the current block size parameter remains unchanged. Finally, achieve closed-loop control. When the quality deviation index exceeds the preset threshold of 5%, automatically trigger parameter adjustment of the template configuration optimization model. Through the feedback control mechanism, continuously optimize the template design parameters to ensure that the construction quality is always within the design requirements.

[0055] The key technical ideas of the present application mainly embody in the following three aspects. The first key technical idea is the surface parameterization expression technology based on non-uniform rational B-spline function. This technology can accurately capture the local feature changes of the surface by establishing an accurate mathematical model to describe the complex geometry of the special-shaped concrete structure, compared with the traditional geometric modeling method, it has higher precision and stronger adaptability, can accurately capture the local feature changes of the surface, provides a reliable geometric basis for the accurate design of the steel formwork, effectively solves the problem of insufficient precision in traditional methods when dealing with complex special-shaped structures. The second key technical idea is the template configuration optimization technology based on the visual transformer architecture. This technology uses deep learning algorithm to realize intelligent block design of steel formwork, through multi-head attention mechanism and image block processing mechanism, it can automatically identify the optimal block scheme, compared with traditional manual design method, it has higher efficiency and better optimization effect, can significantly reduce the design time and improve the design quality. The third key technical idea is the double-layer game optimization algorithm. This algorithm can consider the template deformation control and concrete forming quality by establishing the coordinated optimization mechanism of the upper decision model and the lower response model, realize multi-objective collaborative optimization through deformation flatness coupling function, compared with traditional single-objective optimization method, it can obtain more balanced and comprehensive optimization results.

[0056] The synergistic effect of these three key technical ideas produces significant technical advantages. The accurate surface parameterization provides a reliable data basis for intelligent block design, the intelligent block design provides a reasonable design space for the game optimization algorithm, and the game optimization algorithm ensures the optimality of the overall design scheme. The three form a complete technical chain, compared with traditional steel formwork design methods, this collaborative technology system can improve the design precision, design efficiency and design quality, especially in dealing with complex special-shaped concrete structures, it shows obvious technical advantages, and provides a complete technical solution for intelligent design and manufacturing of steel formwork.

[0057] It should be noted that the present application also solves the following technical problems: the coordination and matching problem of steel formwork digital manufacturing and on-site construction. In the traditional steel formwork manufacturing process, the conversion of design drawings to machining instructions often depends on manual interpretation and experience, which is easy to cause manufacturing precision deviation and assembly error, leading to on-site installation difficulty and quality problems. The present application directly converts the optimized steel formwork thickness distribution function and back spacing parameters into numerical control machining code, establishes the logical mapping relationship between formwork number and geometric characteristics, forms a standardized machining process, realizes seamless connection from parameterized design to digital manufacturing. At the same time, the real-time monitoring system established by the present application can collect on-site formwork deformation data, calculate the quality deviation index through the formwork adaptability evaluation function, and automatically adjust the formwork configuration parameters when the deviation exceeds the threshold, realizing dynamic feedback optimization of design and manufacturing and on-site construction, ensuring the accurate matching and stable performance of the steel formwork system in actual engineering.

[0058] Specifically, the principle of the present application is that the present application can solve the technical problem of inaccurate deformation control of the steel formwork of the special-shaped concrete structure due to the lack of precise parameterized optimization in the design of the steel formwork. The root cause of the problem is that a complete parameterized design optimization system and an intelligent adjustment mechanism are established. First, the high-precision spatial coordinate point cloud of the surface of the special-shaped concrete structure is obtained by a three-dimensional laser scanner, and a non-uniform rational B-spline function is used to establish a surface parameter equation, which realizes accurate mathematical description of complex geometric shapes and provides an accurate geometric basis for subsequent parameterized design. Second, based on the surface parameter equation, a steel formwork thickness distribution function is established, the optimal thickness value of each formwork unit is calculated according to the concrete pouring pressure distribution and the formwork deformation limit value, and the accurate balance between the formwork bearing capacity and the deformation control is realized through the coordinated configuration of the support spacing optimization parameter and the rod section size. Third, a double-layer decision model is constructed using a game optimization algorithm. The upper layer decision model aims to minimize the formwork deformation, and the lower layer response model aims to optimize the flatness of the concrete surface. The two optimization objectives are coordinated and unified through a deformation flatness coupling function, ensuring the global optimality of the parameterized design scheme. Finally, a formwork configuration optimization model based on a visual transformer architecture is established. Through the image block mechanism, the optimal block mode is identified, and the dynamic adjustment and intelligent optimization of the design parameters are realized by combining the real-time monitoring system and the formwork adaptability evaluation function, ensuring the deformation control accuracy of the steel formwork in actual construction. Therefore, the technical scheme of the present application meets the logical requirements for solving the technical problem.

[0059] A specific embodiment 1 of the present application is provided below, and the specific implementation of each step in embodiment 1 is described in detail as follows.

[0060] The specific implementation of step S01 is to obtain the spatial geometric information of the special-shaped concrete structure using three-dimensional laser scanning technology and establish a surface parameter equation. First, the surface of the special-shaped concrete structure is scanned in all directions by a high-precision three-dimensional laser scanner, and the spatial coordinate point cloud data with a density of 1000 to 5000 points per square meter is obtained, with a scanning accuracy controlled within ±1 mm. Then, the obtained point cloud data is preprocessed, including removing noise points, filling missing areas, and aligning the coordinate system. The least squares fitting algorithm is used to eliminate measurement errors. The surface parameter equation of the special-shaped concrete structure is represented by a non-uniform rational B-spline function, which is specifically represented as follows:

[0061] ;

[0062] In the formula, is the three-dimensional coordinate of any point on the surface; is a parameter variable in the parameter domain, with a value range of 0 to 1; and are respectively direction and The B-spline basis function of the direction is calculated by using the Cox-de Boor recurrence formula. The order of the B-spline surface is usually 2 to 4. is the control point coordinate; is the weight coefficient of the corresponding control point; is the dimension of the control point grid. The specific expression of the surface control point coordinate density calculation formula is as follows:

[0063] ;

[0064] In the formula, is the surface control point coordinate density; is the total area of the surface.

[0065] The parameter acquisition method is: The point cloud data fitting method is adopted, including the following steps: step 1: grid division of the scanned point cloud data according to the spatial position; step 2: least square fitting of the point cloud data in each grid region to determine the three-dimensional coordinates of the control points. The curvature analysis method is adopted, including the following steps: step 1: calculation of the principal curvature of each control point of the surface; step 2: determination of the weight coefficient according to the degree of change of the principal curvature, the weight coefficient of the region with large curvature change is 1.2 to 1.8, and the weight coefficient of the region with small curvature change is 0.8 to 1.2.

[0066] The specific implementation of step S02 is based on the established surface parameter equation to design and optimize the steel formwork. First, the intelligent blocking of the special-shaped surface is carried out by using the formwork configuration optimization model, and the optimal blocking mode is identified by the image blocking mechanism based on the visual transformer architecture. Then, the steel formwork thickness distribution function is established, which is based on the mathematical model established by the concrete pouring pressure distribution and the allowable deflection of the formwork, and the specific expression is as follows:

[0067] ;

[0068] In the formula, is the thickness of the formwork unit at the coordinate ; is the concrete pouring pressure distribution function; is the span of the formwork unit; is the elastic modulus of the steel; is the maximum allowable deflection of the formwork; is the minimum thickness of the formwork.

[0069] The parameter acquisition method is: The hydrostatic pressure principle is used for calculation, and the specific expression is as follows:

[0070] ;

[0071] wherein, is the density of concrete, taking the value of 2400 kg / m3; is the acceleration of gravity, taking the value of 9.8 m / s2; is the pouring height at the coordinate ; is the pouring dynamic load, taking the value of 20% of the static load. is set to 1 / 400 of the span. is the elastic modulus of steel, taking the value of 206000 MPa. The back brace spacing parameter is determined by the formwork stiffness requirement and the back brace bearing capacity, and is specifically expressed as follows:

[0072] ;

[0073] wherein, is the back brace spacing; is the back brace sectional moment of inertia; is the allowable deflection of the back brace; is the distributed load acting on the back brace.

[0074] The specific implementation of step S03 is to construct a mechanical parameterized model of the support system and perform optimization analysis. First, a three-dimensional finite element model of the support rod is established, and then the stress distribution and deformation of the support rod under the concrete pouring load are calculated through finite element analysis. Then the Lagrange multiplier method is used to solve the support spacing optimization parameter. This method finds the optimal balance point of the bearing capacity of the support rod and the deformation constraint of the formwork by establishing a mathematical model of the objective function and the constraint condition, and is specifically expressed as follows:

[0075] ;

[0076] wherein, is the Lagrange function; is the support spacing design variable; is the objective function, indicating the total cost of the support system; is the constraint condition, indicating the formwork deformation constraint; is the Lagrange multiplier.

[0077] wherein, the parameter acquisition method is: obtained by cost analysis, including support rod material cost, labor cost and mechanical cost; obtained by finite element analysis, indicating the difference between the maximum deformation of the formwork and the allowable deformation. The rod section size design includes the calculation of the moment of inertia and the sectional modulus, and the moment of inertia is controlled to be mm to millimeters in the range of 0.5 to 1.5 millimeters, the cross-sectional modulus is controlled in the range of 0.5 to 1.5 millimeters. millimeters to millimeters in the range of 0.5 to 1.5 millimeters.

[0078] The specific implementation of step S04 is to use a game optimization algorithm to solve the global optimal solution of the steel formwork design parameters. The algorithm adopts a double-layer optimization structure. The upper-layer decision model takes the minimization of the maximum deformation of the steel formwork as the objective function, which is specifically expressed as follows:

[0079] ;

[0080] In the formula, is the upper-layer objective function; is the upper-layer decision variable, including the formwork thickness and the back lath spacing; is the lower-layer optimal response; is the deformation of the i-th formwork unit. The lower-layer response model takes the maximization of the concrete surface flatness evaluation index as the objective function, which is specifically expressed as follows:

[0081] ;

[0082] In the formula, is the lower-layer objective function; is the lower-layer decision variable, including the support spacing and the joint parameter; is the surface elevation deviation of the i-th measuring point; is the average elevation deviation; is the total number of measuring points. The two-layer models are coordinated and optimized through a deformation flatness coupling function, which is specifically expressed as follows:

[0083] ; In the formula,

[0084] is the deformation flatness coupling function; is the weight coefficient, which is determined according to the engineering quality requirements, generally for general engineering and for high-precision engineering.

[0085] The specific implementation of step S05 is the same as the foregoing, and will not be described in detail here.

[0086] The specific implementation of step S06 is to establish a real-time monitoring system for the quality of the steel formwork and realize dynamic optimization adjustment. First, install displacement sensors at key formwork units to collect formwork deformation data in real time. Then, use a formwork adaptability evaluation function to calculate the quality deviation index, which is specifically expressed as follows:​​

[0087] ;

[0088] wherein, is an adaptability index, with a value ranging from 0 to 1; is a weight coefficient, satisfying ; is the maximum design value of the density of the coordinates of the curved surface control points, with a value of 1000 points per square meter; is the maximum design value of the back corrugation spacing, with a value of 800 millimeters; is the maximum allowable value of the mass deviation index, with a value of 0.15; is the maximum allowable value of the real-time deformation data, with a value of 1 / 300 of the span.

[0089] wherein, the parameter acquisition method is: by counting the number of control points per unit area; obtained by using a relative error calculation method, specifically represented as follows:

[0090] ;

[0091] wherein, is the theoretical calculation deformation. Then, an adaptability index adjustment mechanism is established, when , the block size parameter is increased, with an adjustment coefficient of 1.2 to 1.5; when , the block size parameter is decreased, with an adjustment coefficient of 0.7 to 0.8; when , the current parameter is maintained unchanged.

[0092] It should be noted that the principle of the non-uniform rational B-spline function is based on the combination of spline function theory and rational function theory, and the function realizes accurate description of complex curved surfaces by introducing a weight coefficient. Compared with the traditional polynomial fitting method, the function has better local control and numerical stability, and can accurately capture the geometric feature changes of the special-shaped concrete structure, providing a high-precision geometric basis for subsequent steel formwork design, effectively solving the problems of insufficient precision and unstable calculation in traditional geometric modeling methods when dealing with complex curved surfaces. The principle of the steel formwork thickness distribution function is based on the bending theory in materials mechanics, and the relationship between the formwork thickness, load, span and material properties is derived according to the bending deformation formula of the beam by taking the concrete pouring pressure as a distributed load. The function can automatically calculate the optimal formwork thickness according to the load distribution at different positions, and compared with the traditional uniform thickness design method, it can realize the optimal allocation of material usage, ensuring the safety of the structure and improving the economy. The principle of the concrete pouring pressure distribution function The principle of the formula is based on the principle of fluid statics, considering the fluid properties of concrete and the dynamic effects in the pouring process, and the static pressure calculation results are corrected by introducing a dynamic load coefficient. This function can more accurately reflect the load state in the actual construction process, and improve the accuracy and safety of pressure calculation compared with the traditional method which only considers static load. The formula for calculating the spacing of back struts The principle of the formula is based on the continuous beam theory in structural mechanics, and the optimal spacing of back struts is determined by establishing the balance between the stiffness of back struts and the deformation of the formwork. This formula can optimize the use of back struts under the premise of meeting the deformation control requirements, and has stronger theoretical basis and better economy compared with the traditional empirical determination method. The Lagrange function The principle of the formula is based on the theory of constrained optimization, and the constrained optimization problem is transformed into an unconstrained optimization problem by introducing the Lagrange multiplier. This method can find the minimum value of the support system cost under the condition of meeting the deformation constraint of the formwork, and has higher efficiency and better optimization effect compared with the traditional trial-and-error design method. The upper objective function The principle of the formula is based on the concept of structural safety control, and the safety of the overall structure is ensured by minimizing the maximum deformation of the formwork system. This objective function can identify the weak links of the structure and optimize them, and has stronger safety protection ability compared with the traditional average deformation control method. The lower objective function The principle of the formula is based on the theory of concrete forming quality evaluation, and the forming quality of concrete is improved by maximizing the surface flatness evaluation index. This objective function uses the reciprocal of the standard deviation as the flatness index, which can effectively quantify the surface quality state, and has stronger objectivity and accuracy compared with the traditional qualitative evaluation method. The deformation flatness coupling function The principle of the formula is based on the theory of multi-objective optimization, and the coupling relationship between deformation control and quality control is established to realize the coordinated optimization of the two objectives. This function adjusts the importance of different objectives through weight coefficients, and can obtain more balanced and comprehensive optimization results compared with the traditional single-objective optimization method. The formwork adaptability evaluation function The principle of the formula is based on the fuzzy evaluation theory and real-time feedback control theory, and the adaptability level of formwork configuration is calculated by considering multiple influencing factors. This function can realize dynamic adjustment and optimization in the construction process, and has stronger self-adaptability and better construction adaptability compared with the traditional static design method. The quality deviation index The principle of the formula is based on the error analysis theory, and the relative error between actual deformation and theoretical deformation is calculated to evaluate the accuracy of the design scheme. This index can timely find the deviation between design and actual situation and trigger the adjustment mechanism, and has stronger preventability and timeliness compared with the traditional post-checking method.

[0093] To better understand and implement this invention, Example 2 of a specific application scenario is provided below: A technical team undertook the design of steel formwork for hyperbolic variable cross-section concrete bifurcated columns in a large transportation hub terminal building. The project includes 48 irregularly shaped bifurcated columns, each 12m high, with a bottom cross-section of 1.2m × 1.2m and two 0.8m × 0.6m cross-sections at the top, bifurcating at a 45° angle, resulting in complex surface variations. Traditional steel pipe reinforcement methods for this irregular structure suffer from difficulties in deformation control, excessive joints, and low construction efficiency. The technical team decided to use a parametric design optimization method for steel formwork to solve these technical challenges.

[0094] The technical team first performed step S01, using a FARO Focus3D X330 3D laser scanner to perform a 360-degree scan of the completed first test column. The scan point cloud density was set to 3200 points per square meter, with scanning accuracy controlled within ±0.8mm. The acquired raw point cloud data contained approximately 1.5 million spatial coordinate points. After noise reduction and coordinate system optimization, the effective point cloud data was 1.42 million points. The technical team used a least squares fitting algorithm to eliminate measurement errors and established the parametric equations for a non-uniform rational B-spline surface. Based on the analysis of local curvature changes in the surface, the bifurcated column was divided into three regions: the bottom cylindrical segment had small curvature changes, with a weighting coefficient of 0.9; the middle transition segment had larger curvature changes, with a weighting coefficient of 1.4; and the top bifurcated segment had the largest curvature changes, with a weighting coefficient of 1.7. The final output included the surface parametric equations containing the coordinates of 96 control points and their corresponding weighting coefficients, providing a precise geometric basis for subsequent steel formwork design.

[0095] Table 1 shows the key technical parameters for 3D laser scanning:

[0096] Table 1. Parameters of 3D Laser Scanning Technology

[0097]

[0098] Based on the established surface parametric equations, the technical team performed step S02 for the parameterized design of the steel formwork by segmentation. A formwork configuration optimization model based on a vision transformer architecture was adopted, which includes a 12-layer encoder and a 6-layer decoder. Dynamic segmentation was performed according to the complexity of the surface: the bottom cylindrical segment had relatively small curvature changes, and the segment size was set to 1.8m × 1.5m; the middle transition segment had complex geometry, and the segment size was set to 0.8m × 0.6m; the top bifurcated segment had the most complex shape, and the segment size was set to 0.6m × 0.5m. A steel formwork thickness distribution function was established, considering a concrete density of 2400 kg / m³. The maximum pouring height is 12 m, and the bottom pouring pressure is 282 kPa according to the calculation based on the principle of hydrostatic pressure. The deformation limit of the formwork is set to 1 / 400 of the span, and the thickness of each formwork unit is determined by finite element analysis calculation: 14 mm thick steel plate is used in the area with large pressure at the bottom, 10 mm thick steel plate is used in the transition area in the middle, and 8 mm thick steel plate is used in the top fork area. The spacing parameters of the back lath are determined according to the stiffness requirements of the formwork: the spacing of the back lath is 350 mm at the bottom, 400 mm in the middle, and 450 mm at the top.

[0099] When performing step S03 to build the support system mechanical parameterization model, the technical team establishes a three-dimensional finite element model, simulates 2400 support rods with BEAM188 beam elements, and simulates 480 connection nodes with COMBIN14 spring elements. Load analysis includes concrete dead weight of 288 kN, pouring dynamic load of 35 kN, and lateral pressure of 126 kN, and the dynamic load coefficient is 1.2. The stress distribution of the support rods is calculated by finite element analysis, and the maximum stress appears in the bottom main support rod, with a value of 145 MPa, and the safety factor is 1.8, which meets the design requirements. The support spacing is optimized by Lagrange multiplier method, and the support spacing in the bottom main column area is optimized to 1.2 m, and the support spacing in the forked cantilever area is optimized to 0.8 m. In the design of rod section, the moment of inertia of the main support rod is mm 4 , the cross-sectional modulus is mm 3 ; the moment of inertia of the secondary support rod is mm 4 , and the cross-sectional modulus is mm 3 . A database of rod adjustment range is established, and the adjustment range of round pipe support is ±140 mm, and the adjustment range of square pipe support is ±110 mm.

[0100] The support system mechanical parameters are shown in Table 2:

[0101] Table 2 Support system mechanical parameter table

[0102]

[0103] The technical team applies a game optimization algorithm to solve the optimal solution of the design parameters in step S04. The upper decision model takes minimizing the maximum deformation of the steel formwork as the target, and the deformation control target value is set to 1 / 500 of the span, i.e. 2.4 mm. In the constraint condition, the safety factor of the formwork strength is set to 2.0, and the geometric size constraint ensures that the length-width ratio of the formwork unit is controlled within the range of 1:1.2. The lower response model takes maximizing the flatness of the concrete surface as the target, and the flatness evaluation index is controlled within 1.8 mm. The constraint conditions include controlling the slenderness ratio of the rod within 140 and controlling the gap between the joints within 1.5 mm. The weight coefficient of the deformation flatness coupling function is determined to be 1:1.8 according to the quality requirements of the fair-faced concrete. The algorithm uses iterative solution, and after 23 iterations, the difference between the results of the adjacent two iterations is 0.008, which meets the convergence criterion. The optimized design parameters include: the number of formwork units is reduced to 186, the maximum deformation is controlled within 2.1 mm, and the flatness of the concrete surface reaches 1.6 mm, all of which meet the design requirements.

[0104] In step S05, the technical team converts the optimized design parameters into digital manufacturing instructions. The coordinate accuracy of the steel plate cutting path is controlled within 0.08 mm, and the coordinate of the back lath welding position is represented in a rectangular coordinate system. A formwork numbering system is established, and the regional identification is represented by AB, CD, and EF to represent the bottom, middle, and top three regions, and the sequential identification is represented by three digits, forming a complete number from AB001 to EF186. A standardized processing process is developed: the cutting of the blank is carried out by laser cutting process, and the cutting accuracy is ±0.4 mm; the back lath welding is carried out by gas shielded welding, and the weld height is controlled within 3.5 mm; the surface treatment includes shot blasting and brushing of the release agent; the size inspection is carried out by a three-coordinate measuring machine, and the detection accuracy is ±0.15 mm. The quality traceability system files all the processing parameters and inspection results of the 186 formworks.

[0105] Finally, step S06 is executed to establish a real-time quality monitoring system. Laser displacement sensors are installed on 24 key formwork units, with a layout interval of 3 m and a measurement accuracy of 0.008 mm. The formwork adaptability evaluation function takes the surface control point coordinate density of 33.6 points / m2, the back lath spacing parameter of 350-450 mm, the quality deviation index, and the real-time deformation data as inputs. During construction, the adaptability index is calculated in real time, and when the index is 0.286, it indicates that the block is too fine, and the block size parameter is automatically adjusted to 1.3 times of the original; when the index is 0.724, it indicates that the block is too coarse, and the parameter is adjusted to 0.75 times of the original; when the index is between 0.322 and 0.679, the parameter remains unchanged. The quality deviation index is monitored in real time, and the relative error between the actual deformation and the theoretical calculation value is controlled within 3.2%; when it exceeds the preset threshold of 5%, the parameter adjustment is automatically triggered.

[0106] The key quality monitoring indicators are shown in Table 3:​​

[0107] Table 3 Mass monitoring key indicator table

[0108]

[0109] Figure 2 The three-dimensional positioning and model deepening diagram based on Rhino software is shown, and the geometric characteristics and spatial positioning relationship of the hyperbolic variable cross-section bifurcated column are accurately expressed. Figure 3 The steel formwork system design drawing is shown, which includes the formwork block scheme and support system arrangement. Figure 4 The final effect of the bifurcated column formwork installation is shown, which verifies the accuracy of the parametric design.

[0110] Through the implementation of the parametric design optimization method of the steel formwork, the technical team successfully solved the construction problem of the hyperbolic variable cross-section concrete bifurcated column. Compared with the traditional steel pipe reinforcement method, this method has achieved significant improvement in many technical indicators: the formwork deformation amount is reduced from 3.6mm of the traditional method to 2.1mm, reducing by 17%; the concrete surface flatness is improved from 2.8mm of the traditional method to 1.6mm, improving by 18%; the formwork joint number is reduced from 312 of the traditional method to 186, reducing by 15%; the construction period is shortened from 45 days of the traditional method to 38 days, improving by 16%. The traditional method uses experience design and manual adjustment, and the formwork thickness and support spacing are often too conservative, resulting in material waste and low construction efficiency, and at the same time, due to the lack of accurate geometric control, deformation overrun and surface quality defects are prone to occur. This method realizes accurate design and intelligent control of the formwork system through parametric design and optimization algorithm, effectively solves the technical problems in the construction of special-shaped concrete structures, and provides reliable technical support for similar projects.

[0111] It should be noted that the variables involved in the present application are explained in detail as shown in Table 4.

[0112] Table 4 Variable explanation table

[0113]

[0114] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. An optimization method for parametric design of steel formworks, characterized by, The geometric boundary data and curvature change data of the special-shaped concrete structure are collected, the spatial coordinate point cloud of the structure surface is obtained through a three-dimensional laser scanner, a surface parameter equation of the special-shaped concrete structure is established, the surface parameter equation is expressed by a non-uniform rational B-spline function, and surface control point coordinates and weight coefficients are output; the steel formwork is divided into blocks for parameterized design based on the surface parameter equation, the geometric size and splicing position of the steel formwork unit are determined by using a formwork configuration optimization model, a steel formwork thickness distribution function and a back rafter spacing parameter are generated, the steel formwork thickness distribution function is used to calculate the thickness value of each formwork unit according to the concrete pouring pressure and the formwork deformation limit value; a mechanical parameterized model of the support system is constructed, the stress distribution and deformation of the support rods under the concrete pouring load are calculated through finite element analysis, the support spacing optimization parameter and the rod section size are determined, and a pull rod adjustment range database is established; the optimal solution of the steel formwork design parameter is solved by using a game optimization algorithm, the game optimization algorithm includes an upper decision model with the minimum formwork deformation as the target and a lower response model with the optimization of the concrete forming surface flatness as the target, and the deformation flatness coupling function is used as a coupling term to realize coordinated optimization; digital manufacturing instructions for steel formwork processing are generated, the optimized steel formwork thickness distribution function and the back rafter spacing parameter are converted into numerical control processing codes, and a mapping relationship between the formwork number and the geometric characteristics is established.

2. The method of claim 1, wherein, The surface parameter equation specifically describes the complex curved surface shape of the special-shaped concrete structure through control point coordinates and weight coefficients, the control point coordinates are determined by fitting the spatial coordinate point cloud obtained by three-dimensional laser scanning, and the weight coefficients are calculated according to the local curvature change of the curved surface.

3. The method of claim 2, wherein, The steel formwork thickness distribution function specifically establishes a mathematical model based on the concrete pouring pressure distribution and the allowable deflection of the formwork, the concrete pouring pressure is calculated according to the pouring height and the concrete density, the formwork deformation limit value is set to 1 / 400 of the span, and the back rafter spacing parameter is determined by the formwork stiffness requirement and the back rafter bearing capacity.

4. The method of claim 3, wherein, The support spacing optimization parameter specifically solves the optimal balance point of the support rod bearing capacity and the formwork deformation constraint by the Lagrange multiplier method, the rod section size includes the calculated values of the moment of inertia and the section modulus, and the pull rod adjustment range database records the maximum adjustment range of the support rod with different section types.

5. The method of claim 4, wherein, Further comprising: A steel form quality real-time monitoring system is established, form deformation data is collected by displacement sensors, a form adaptability evaluation function is used to calculate quality deviation indexes, and when the quality deviation indexes exceed preset threshold values, the block size parameters of the form configuration optimization model are automatically adjusted.

6. The method of claim 5, wherein, The numerical control machining code specifically includes steel plate cutting path coordinates and back lath welding position coordinates, a mapping relationship between form numbers and geometric features is established by using a logical number to form a unique identification code, and a standardized machining process flow includes the operation sequence of blanking, cutting, back lath welding, surface treatment and dimension inspection.

7. The method of claim 6, wherein, The form adaptability evaluation function is used to adjust the block size parameters of the form configuration optimization model according to actual deformation conditions at a construction site, the input includes curved surface control point coordinate density, back lath spacing parameters, quality deviation indexes and real-time deformation data, and the output is an adaptability index between 0 and 1.

8. The method of claim 7, wherein, When the adaptability index is <0.322, it indicates that the current block is too fine and the block size parameters need to be increased to reduce the number of seams, when the adaptability index is >0.679, it indicates that the current block is too coarse and the block size parameters need to be reduced to improve forming precision, and when 0.322≤adaptability index≤0.679, the current block size parameters remain unchanged.

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