Method for improving bearing performance of flat and corrugated steel plate shear wall based on parameter optimization

Abstract

The application belongs to the technical field of building structure engineering, and particularly relates to a bearing performance improvement method of flat and corrugated steel plate shear wall based on parameter optimization. First, a structured parameter configuration set is constructed by defining and inputting multiple key parameters of the shear wall. Then, a finite element model is automatically established based on the parameter set, and eigenvalue buckling analysis and nonlinear hysteretic analysis are performed in parallel to obtain comprehensive performance indicators such as stability, bearing capacity, ductility and energy dissipation. Finally, a multi-objective optimization model is established with wave amplitude to wavelength ratio and corrugated inclination as design variables, and the optimal parameter matching interval is determined through collaborative optimization, and the shear wall construction detail drawing is automatically generated. The application realizes the full-process automation from parameter input to performance optimization and drawing generation, and systematically and collaboratively improves the bearing, deformation and energy dissipation capacity of the shear wall, overcoming the limitations of traditional experience-dependent and single-objective design.

Description

Technical Field

[0001] This invention relates to the field of building structural engineering technology, specifically to a method for improving the load-bearing performance of flat and corrugated steel plate shear walls based on parameter optimization. Background Technology

[0002] In the field of building structural engineering, there is a continuous pursuit of high efficiency and lightweight lateral force resisting systems. Flat and corrugated steel plate shear walls, as a structural form that combines high load-bearing capacity and good energy dissipation capability, are subject to complex influences from various parameters such as corrugation geometry, component dimensions, and connection details. With the development of computational mechanics and optimization theory, systematically adjusting key design parameters to synergistically improve their comprehensive performance in terms of load-bearing capacity, deformation, and energy dissipation has become an important research direction for achieving refined structural design.

[0003] In existing technologies, the design of flat and corrugated steel plate shear walls mainly relies on engineers' experience or isolated analysis of single performance characteristics, lacking a systematic parametric design process. The influence mechanisms of each parameter are complex and interdependent, making it difficult to achieve synergistic optimization of multiple objectives such as load-bearing capacity, deformation, and energy dissipation through conventional methods. At the same time, traditional design methods cannot accurately quantify the comprehensive impact of parameter adjustments on the overall hysteretic performance and buckling stability of the structure. As a result, the final design scheme often fails to achieve the optimal balance between safety, economy, and seismic performance, which restricts the refined design and engineering application of such high-performance shear walls. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a method for improving the load-bearing performance of flat and corrugated steel plate shear walls based on parameter optimization. This method addresses the problem that existing designs for flat and corrugated steel plate shear walls often rely on experience and single-objective analysis, lacking a systematic parameter flow. The complex coupling between parameters makes it difficult for traditional methods to achieve multi-objective synergistic optimization of load-bearing capacity, deformation, and energy dissipation. Furthermore, it fails to accurately quantify the comprehensive impact of parameter adjustments on the structural hysteretic performance and buckling stability, resulting in an inability to optimally balance safety, economy, and seismic performance, thus hindering the refined design and application of this structure.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] The method for improving the bearing capacity of flat and corrugated steel plate shear walls based on parameter optimization according to the present invention comprises the following steps:

[0007] Step S1: Parameter definition and input: Define and input the geometric and material parameters of the shear wall. The wall parameters are encoded and stored according to a preset data structure and format to construct a wall parameter configuration set.

[0008] Step S2: Finite element simulation and analysis: Automatically read the wall parameter configuration set, establish a finite element analysis model of the flat steel plate and corrugated steel plate shear wall, perform eigenvalue buckling analysis and nonlinear hysteresis analysis, organize the buckling analysis results and hysteresis analysis results in a structured manner, and output a comprehensive performance index report;

[0009] Step S3: Multi-objective collaborative optimization: Define an objective function based on the comprehensive performance index report, establish a multi-objective optimization model with the objective function as the optimization objective, and perform collaborative optimization on the wall parameter configuration set in the multi-objective optimization model to determine the optimal parameter matching range for the shear wall bearing capacity;

[0010] Step S4: Design document generation and output: Based on the optimal parameter matching interval and the wall parameter configuration set, generate the corresponding shear wall construction details, and output the shear wall construction details as engineering documents to guide production and manufacturing.

[0011] Furthermore, the wall parameters include corrugation geometric parameters, component size parameters, connection structure parameters, and overall mechanical parameters;

[0012] The corrugated geometric parameters include the amplitude, wavelength, amplitude-to-wavelength ratio, and corrugation angle of the corrugated steel plate.

[0013] The component dimensional parameters include the thickness of the flat steel plate, the thickness of the corrugated steel plate, and the combination relationship between the thicknesses of the two.

[0014] The connection construction parameters include the bolt spacing used to connect the flat steel plate and the corrugated steel plate, and the bolt spacing is related to the wavelength.

[0015] The overall mechanical parameters include the height-to-thickness ratio of the wall segment, the shear span ratio, and the design axial compression ratio.

[0016] Furthermore, the establishment of the finite element analysis model includes calculating the wall thickness and width, and generating corrugated steel plate geometry and flat steel plate geometry.

[0017] The wall parameter configuration set is read, and using the overall mechanical parameters therein, combined with the wall member height given in the engineering specifications, the wall member thickness and width are calculated.

[0018] The calculation process for the wall thickness is as follows:

[0019]

[0020] in, For a given wall height, The height-to-thickness ratio of the wall segment. For wall thickness;

[0021] The calculation process for the width of the wall segment is as follows:

[0022]

[0023] in, The shear span ratio of the wall segment. The width of the wall segment.

[0024] Furthermore, based on the corrugated geometric parameters and component size parameters, and combined with the actual dimensions of the wall segment, a corrugated steel plate geometry is generated. The process is as follows:

[0025] Let the width of the wall segment be the X-axis, the height of the wall segment be the Y-axis, and the plane normal of the wall segment be the Z-axis. Establish a global rectangular coordinate system.

[0026] Within a single wavelength, the mid-surface profile function of the corrugated steel plate is defined as follows:

[0027]

[0028] in, The preset crest length coefficient, For wavelength, The horizontal length of the wave crest segment;

[0029]

[0030] in, For amplitude, For the undulation angle, This represents the horizontal projection length of the slope segment;

[0031]

[0032] in, The horizontal length of the trough segment;

[0033] In summary, the mid-surface profile function within a single wavelength is defined as:

[0034]

[0035] in, Let X be the coordinate variable along the X-axis. This is a function for the mid-surface contour line;

[0036] In the global rectangular coordinate system, the mid-surface profile function is periodically repeated along the X-axis to form a corrugated steel plate profile function covering the width of the wall segment, denoted as:

[0037]

[0038] in, For the profile function of corrugated steel plate;

[0039] The corrugated steel plate profile function is stretched along the Y-axis to the height of the wall limb, thus obtaining the mid-surface of the corrugated steel plate.

[0040] Extract the thickness of the corrugated steel plate from the component's dimensional parameters, and perform a double-sided offset on the mid-surface of the corrugated steel plate along the Z-axis to generate the corrugated steel plate geometry, which is parametrically represented as follows:

[0041]

[0042] in, The middle surface of the corrugated steel plate This refers to the preset coordinate reference value of the corrugated steel plate's mid-surface in the Z-axis direction. For the thickness of the corrugated steel plate, For the generated corrugated steel plate geometry;

[0043] Extract the thickness of the flat steel plate from the component size parameters, and combine it with the width of the wall segment to generate the flat steel plate geometry, which is parameterized as follows:

[0044] in, The Z-axis coordinates of the preset flat steel plate mid-surface are: For the thickness of the flat steel plate, For the generated flat steel plate geometry;

[0045] The corrugated steel plate geometry and the flat steel plate geometry are assembled according to the design positions given in the engineering specifications to obtain the assembled geometry.

[0046] Constrain all degrees of freedom at the bottom of the assembly geometry and perform a fixed-end simulation.

[0047] Extract the design axial compression ratio from the overall mechanical parameters, and calculate the axial load by combining the wall thickness, wall width, and preset steel yield strength. Apply the axial load to the top of the assembled geometry using the following formula:

[0048]

[0049] in, To design the axial compression ratio, For the yield strength of steel, For axial loads;

[0050] The assembly geometry with complete freedom constraints and axial load application constitutes the finite element analysis model.

[0051] Establish a loading control point at the position of the central axis at the top of the finite element analysis model.

[0052] Furthermore, a preset horizontal reference shear force is applied at the loading control point for eigenvalue buckling analysis, the process of which is as follows:

[0053] Solve the eigenvalue equation and calculate the eigenvalues. The equation is as follows:

[0054]

[0055] in, The initial linear stiffness matrix of the finite element analysis model is automatically generated from the model geometry and material properties. This is the geometric stiffness matrix automatically generated on the finite element analysis model of axial load; The eigenvectors corresponding to the eigenvalues; For eigenvalues;

[0056] The minimum positive eigenvalue obtained is denoted as the critical buckling load.

[0057] Based on the critical buckling load, the critical buckling shear force and elastic buckling shear stress of the wall pier during elastic instability are calculated and integrated into the buckling analysis results, the formula of which is as follows:

[0058]

[0059]

[0060]

[0061] in, This is the critical buckling load. For horizontal reference shear force, The critical buckling shear force. Let be the cross-sectional area of ​​the wall segment. It is the elastic buckling shear stress.

[0062] Furthermore, a predicted yield displacement is applied at the loading control point for nonlinear hysteresis analysis, the process of which is as follows:

[0063] The formula for calculating the yield displacement load at the loading control point is as follows:

[0064]

[0065] in, For the k-th time step, for The displacement multiple corresponding to the time step. For the estimated yield displacement, Time step ;

[0066] All the obtained yield displacement loads are arranged according to time steps and denoted as the yield displacement sequence, as follows:

[0067]

[0068] Based on the yield displacement sequence, the horizontal reaction force at the corresponding loading control point is calculated at each time step. The horizontal reaction force is obtained by solving the following equation:

[0069]

[0070] in, The response function for the loaded control points is determined by the material nonlinearity and geometric nonlinearity of the finite element analysis model. This represents the horizontal reaction force at the k-th time step.

[0071] All the obtained horizontal reaction forces are arranged according to time steps and denoted as the horizontal reaction force sequence, as follows:

[0072]

[0073] The real-time relationship between the yield displacement sequence and the horizontal reaction force sequence is denoted as a hysteresis curve, which is a set of points, as follows:

[0074]

[0075] in, The total number of time steps. The hysteresis curve;

[0076] Based on the hysteresis curve, the ductility coefficient, cumulative energy dissipation, and equivalent viscous damping ratio are calculated. The resulting calculations are unified as hysteresis analysis results, and the calculation process is as follows:

[0077]

[0078] in, It is the ductility coefficient;

[0079]

[0080] in, The horizontal reaction force at the (k-1)th time step. The yield displacement load at the (k-1)th time step. For cumulative energy consumption;

[0081]

[0082]

[0083] in, For the maximum yield displacement load, For the maximum horizontal reaction force, The area of ​​the enclosing triangle, The area of ​​the closed region enclosed by the hysteresis curve is given. It is the equivalent viscous damping ratio.

[0084] Furthermore, the buckling analysis results and hysteresis analysis results are extracted from the comprehensive performance index report.

[0085] The critical buckling shear force is used as a stability index, the product of the maximum horizontal reaction force and the ductility coefficient is used as a bearing capacity ductility index, and the equivalent viscous damping ratio is used as an energy dissipation capacity index.

[0086] Objective functions are constructed based on various performance indicators. These objective functions include a stability objective function, a load-bearing capacity-ductility objective function, and an energy dissipation objective function. The construction process is as follows:

[0087] The stability objective function is expressed as follows:

[0088]

[0089] in, This is a reference value for the critical buckling shear force. Let the stability objective function be...

[0090] The objective function for bearing capacity ductility is expressed as follows:

[0091]

[0092] in, This is a reference value for the maximum horizontal reaction force. This is a reference value for the ductility coefficient. The objective function is the load-bearing capacity ductility.

[0093] The energy consumption objective function is expressed as follows:

[0094]

[0095] in, This is a reference value for the equivalent viscous damping ratio. The objective function is energy consumption.

[0096] Furthermore, the process for constructing a multi-objective optimization model is as follows:

[0097] Extract the corrugated geometry parameters and connection construction parameters from the wall parameter configuration set.

[0098] The design variable vector is constructed by selecting the amplitude-to-wavelength ratio and the corrugation angle from the corrugation geometry parameters, and the bolt spacing from the connection construction parameters, as shown below:

[0099]

[0100] in, The amplitude-to-wavelength ratio, Bolt spacing, To design a variable vector;

[0101] Based on given engineering specifications, boundary constraints are applied to the amplitude-to-wavelength ratio, corrugation angle, and bolt spacing, denoted as:

[0102]

[0103] in, The minimum amplitude-to-wavelength ratio, The maximum amplitude wavelength ratio, For the minimum bend angle, For the maximum undulation angle, Minimum bolt spacing This represents the maximum bolt spacing;

[0104] To ensure the matching of bolt arrangement, structural constraints are applied to the bolt spacing, denoted as:

[0105]

[0106] in, This is the preset bolt spacing coefficient;

[0107] Combining the objective function, design variable vector, boundary constraints, and construction constraints, a multi-objective optimization model is established, as follows:

[0108]

[0109]

[0110]

[0111] in, Let the objective function vector be... This indicates that the constraint is satisfied.

[0112] Furthermore, the collaborative optimization process is as follows:

[0113] Within the boundary constraints and construction constraints, multiple sets of design variable vectors are randomly selected to form an initial solution set, denoted as:

[0114]

[0115] in, No. A vector of design variables, This represents the preset total number of design variable vectors. This is the initial solution set;

[0116] Let the objective function vector corresponding to each design variable vector in the initial solution set be denoted as:

[0117]

[0118] The initial solution set is non-dominated and sorted according to the target value vector, and the design variable vectors are divided into multiple frontier levels:

[0119] For any two design variable vectors, the objective function vector should simultaneously satisfy the following conditions:

[0120]

[0121] Then it means Dominate , recorded as ;in, For the first One objective function, This is one of the design variable vectors in the initial solution set;

[0122] From the initial solution set, identify all design variable vectors that are not dominated by any other design variable vectors, and form the first frontier level, denoted as:

[0123]

[0124] in, It is the first frontier level;

[0125] From the residual design variable vectors of the initial solution set, identify all design variable vectors that are not dominated by the residual design variable vectors, forming the second frontier level, denoted as:

[0126]

[0127] in, This is one of the remaining design variable vectors in the initial solution set. It is the second frontier level;

[0128] Repeat the above process until all design variable vectors in the initial solution set are divided into multiple frontier levels;

[0129] Design variable vectors are selected in descending order of their frontier level to obtain high-quality design variable vectors.

[0130] Two high-quality design variable vectors are randomly selected to generate a new design variable vector, using the following formula:

[0131]

[0132] in, To design high-quality variable vectors, For random weights, Design a new variable vector;

[0133] Repeat this process to integrate all the new design variable vectors obtained into a new generation of solution set;

[0134] The new generation of solution set is used as the initial solution set for the next iteration, and the process of forming the new generation of solution set is repeated in this way.

[0135] When the loop iteration reaches the preset maximum number of iterations, the iteration terminates, and the new generation of solution set obtained at this time is output as the optimal frontier solution set.

[0136] By statistically analyzing all design variable vectors in the optimal front solution set, the value ranges of the amplitude-to-wavelength ratio, the bend angle, and the bolt spacing are finally obtained:

[0137]

[0138]

[0139]

[0140] in, For the optimal frontier solution set, This represents the lower limit of the optimal range for the amplitude-to-wavelength ratio. This represents the upper limit of the optimal range for the amplitude-to-wavelength ratio. This represents the lower limit of the optimal range for the bend angle. This represents the upper limit of the optimal range for the bend angle. This represents the lower limit of the optimal range for bolt spacing. This represents the upper limit of the optimal range for bolt spacing;

[0141] Based on the given engineering specifications, the ranges of the amplitude-to-wavelength ratio, the bend angle, and the bolt spacing are rationally adjusted, and the optimal parameter matching interval is output as follows:

[0142]

[0143] Furthermore, the process for generating the detailed structural drawings of the shear wall is as follows:

[0144] Select a set of amplitude-to-wavelength ratio, corrugation angle, and bolt spacing that conform to engineering specifications from the optimal parameter matching range.

[0145] Extract the corrugated geometric parameters from the wall parameter configuration set, and calculate the specific wave amplitude value by combining the wavelength in the corrugated geometric parameters. The formula is as follows:

[0146]

[0147] in, For the selected amplitude-to-wavelength ratio, For specific amplitude values;

[0148] By calling the corrugated steel plate profile function and using the specific amplitude value, wavelength and selected corrugation angle, the three-dimensional geometry of the corrugated steel plate is obtained.

[0149] Using the selected bolt spacing as a reference, the coordinates of each bolt hole position are calculated and determined along the domain of the corrugated steel plate profile function. The calculation process is as follows:

[0150] Along the X-axis of the global rectangular coordinate system, starting from the edge of one side of the wall, and using the selected bolt spacing as a fixed interval, the X-axis coordinate values ​​of each column of bolt holes are determined sequentially, using the following formula:

[0151]

[0152] in, For the selected bolt spacing, For the first The X-axis coordinates of the bolt hole positions in the column; The total number of bolt rows satisfies ;

[0153] Substituting the X-coordinate of each column of bolt holes into the corrugated steel plate profile function, we obtain the Z-axis coordinate value of the bolt holes:

[0154]

[0155] in, For the first The Z-axis coordinates of the bolt hole positions in the column;

[0156] Arrange multiple rows of bolts along the Y-axis at the connection spacing specified in the engineering specifications, and obtain the Y-axis coordinate values ​​of the bolt hole positions, represented as:

[0157]

[0158] in, For the first The Y-axis coordinate value of the bolt hole position in the row; The total number of bolt rows satisfies ;

[0159] Based on the above calculations, all bolt hole coordinates are integrated to form a bolt hole coordinate set, denoted as:

[0160]

[0161] Extract the component size parameters from the wall parameter configuration set, and based on the thickness of the flat steel plate, combine the wall limb thickness and wall limb width to obtain the three-dimensional geometry of the flat steel plate;

[0162] By combining the three-dimensional geometry and bolt hole coordinates, a detailed structural drawing of the shear wall is obtained.

[0163] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0164] The method of this invention constructs a fully automated framework that integrates various parameters such as corrugated geometry, component dimensions, connection structure, and overall mechanics. Based on parametric scripts, it automatically generates finite element models, performs buckling and hysteresis analysis, and extracts comprehensive performance indicators, realizing closed-loop calculation from design parameters to performance evaluation. This significantly improves the systematicness, repeatability, and efficiency of flat and corrugated steel plate shear wall design.

[0165] The method of this invention establishes a three-objective optimization model that integrates stability, bearing capacity ductility, and energy dissipation capacity, and adopts a collaborative optimization strategy of non-dominated sorting and multi-generation iteration. Under the condition of satisfying engineering constraints, it automatically searches for the optimal matching range of key parameters such as amplitude-to-wavelength ratio, zigzag angle, and bolt spacing. This achieves a synergistic improvement in bearing capacity, deformation, and energy dissipation performance at the parameter level, overcomes the limitations of traditional reliance on experience and single-objective design, and provides a scientific basis and practical tool for the refined design of high-performance shear walls. Attached Figure Description

[0166] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0167] Figure 1 This is a schematic diagram of the overall working process of the method of the present invention;

[0168] Figure 2 This is a schematic diagram of the parameter definition and input process of the method of the present invention;

[0169] Figure 3 This is a schematic diagram of the finite element simulation and analysis process of the method of the present invention;

[0170] Figure 4 This is a schematic diagram of the multi-objective collaborative optimization process of the method of the present invention;

[0171] Figure 5 This is a schematic diagram of the process for generating and outputting design documents for the method of this invention. Detailed Implementation

[0172] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to embodiments and accompanying drawings. The content mentioned in the embodiments is not intended to limit the present invention.

[0173] Reference Figure 1 As shown, this invention is a method for improving the bearing capacity of flat and corrugated steel plate shear walls based on parameter optimization. The steps are as follows:

[0174] Step S1: Parameter definition and input: Define and input the geometric and material wall parameters of the shear wall. The wall parameters are encoded and stored according to the preset data structure and format to construct a wall parameter configuration set, which is then transmitted to step S2.

[0175] The wall parameters are directly related to the overall stability and bearing mechanism of the shear wall, and specifically include corrugated geometric parameters, component size parameters, connection construction parameters and overall mechanical parameters;

[0176] The corrugated geometry parameters define the cross-sectional shape characteristics of the embedded corrugated steel plate, specifically including the amplitude, wavelength, amplitude-to-wavelength ratio, and corrugation angle of the corrugated steel plate.

[0177] The component size parameters define the physical dimensions of each component plate, specifically including the thickness of the flat steel plate, the thickness of the corrugated steel plate, and the combination relationship between their thicknesses.

[0178] The connection construction parameters define key structural details that ensure the coordinated operation of the various plates, specifically including the bolt spacing used to connect the flat steel plate and the corrugated steel plate, wherein the bolt spacing is related to the wavelength.

[0179] The overall mechanical parameters define the macroscopic mechanical characteristics of the shear wall as an integral load-bearing component, specifically including the height-to-thickness ratio of the wall limbs, the shear span ratio, and the design axial compression ratio.

[0180] Step S2: Finite Element Simulation and Analysis: Automatically read the wall parameter configuration set, establish finite element analysis models of flat steel plate and corrugated steel plate shear walls, perform eigenvalue buckling analysis and nonlinear hysteresis analysis, structure and organize the buckling analysis results and hysteresis analysis results, and output a comprehensive performance index report.

[0181] The establishment of the finite element analysis model includes calculating the wall thickness and width, and generating corrugated steel plate geometry and flat steel plate geometry.

[0182] The wall parameter configuration set is read, and using the overall mechanical parameters therein, combined with the wall member height given in the engineering specifications, the wall member thickness and width are calculated.

[0183] The calculation process for the wall thickness is as follows:

[0184]

[0185] in, For a given wall height, The height-to-thickness ratio of the wall segment. For wall thickness;

[0186] The calculation process for the width of the wall segment is as follows:

[0187]

[0188] in, The shear span ratio of the wall segment. The width of the wall segment;

[0189] Based on the corrugated geometric parameters and component size parameters, and combined with the actual dimensions of the wall segment, a corrugated steel plate geometry is generated. The process is as follows:

[0190] Establish a global rectangular coordinate system with the width of the wall segment as the X-axis, the height as the Y-axis, and the plane normal of the wall segment as the Z-axis.

[0191] Within a single wavelength range, the mid-surface profile function of the corrugated steel plate is defined as follows:

[0192]

[0193] in, The preset crest length coefficient, For wavelength, The horizontal length of the wave crest segment;

[0194]

[0195] in, For amplitude, For the undulation angle, This represents the horizontal projection length of the slope segment;

[0196]

[0197] in, The horizontal length of the trough segment;

[0198] In summary, the mid-surface profile function within a single wavelength is defined as:

[0199]

[0200] in, Let X be the coordinate variable along the X-axis. This represents the Z-axis axial coordinate value corresponding to the X-axis position of the mid-surface contour line;

[0201] The mid-surface profile function is periodically repeated along the X-axis to form a corrugated steel plate profile function covering the width of the wall segment, denoted as:

[0202]

[0203] in, For the profile function of corrugated steel plate;

[0204] The corrugated steel plate profile function is stretched along the Y-axis to the height of the wall limb to obtain the mid-surface of the corrugated steel plate, which is parametrically represented as follows:

[0205]

[0206] in, For the middle surface, The coordinates of the two-dimensional parametric surface are given. These are the coordinates of a point in three-dimensional space.

[0207] Finally, the mid-surface is offset on both sides along the Z-axis to generate the corrugated steel plate geometry, represented as:

[0208]

[0209] in, The thickness of the corrugated steel plate. For the generated corrugated steel plate geometry;

[0210] Based on the component size parameters and the actual dimensions of the wall limb, a flat steel plate geometry is generated, represented as follows:

[0211] in, The Z-axis coordinates of the preset flat steel plate mid-surface are: For the thickness of the flat steel plate, For the generated flat steel plate geometry;

[0212] The corrugated steel plate geometry and the flat steel plate geometry are assembled according to the design positions given in the engineering specifications to obtain the assembled geometry.

[0213] Constrain all degrees of freedom at the bottom of the assembly geometry and perform a fixed-end simulation.

[0214] The design axial compression ratio in the overall mechanical parameters, combined with the wall thickness, wall width, and preset steel yield strength, is used to calculate the axial load, which is then applied to the top of the assembled geometry. The formula is as follows:

[0215]

[0216] in, To design the axial compression ratio, For the yield strength of steel, For axial loads;

[0217] The assembly geometry subject to constraints and axial loads is transformed into a finite element analysis model, and a loading control point is established at the position of the central axis at the top of the finite element analysis model.

[0218] A horizontal reference shear force is applied at the loading control point to perform eigenvalue buckling analysis, the procedure of which is as follows:

[0219] Solve the eigenvalue equation and calculate the eigenvalues. The equation is as follows:

[0220]

[0221] in, This is the initial linear stiffness matrix of the finite element analysis model. The geometric stiffness matrix generated by axial load. For the corresponding feature vector, For eigenvalues;

[0222] The minimum positive eigenvalue obtained is denoted as the critical buckling load factor. Based on the critical buckling load factor, the critical buckling shear force and elastic buckling shear stress at the elastic instability of the wall limb are calculated and integrated into the buckling analysis results, the formula of which is as follows:

[0223]

[0224]

[0225]

[0226] in, The critical buckling load factor. For horizontal reference shear force, The critical buckling shear force. Let be the cross-sectional area of ​​the wall segment. It is the elastic buckling shear stress;

[0227] A predicted yield displacement is applied at the loading control point to simulate seismic action for nonlinear hysteresis analysis. The procedure is as follows:

[0228] The formula for calculating the yield displacement load is as follows:

[0229]

[0230] in, The estimated yield displacement; This is an increasing displacement factor used to simulate a gradually increasing displacement amplitude; The i-th yield displacement load;

[0231] All the obtained yield displacement loads are denoted as the yield displacement sequence, as follows:

[0232]

[0233] Based on the yield displacement sequence, the horizontal reaction force at the corresponding loading control point is calculated at each time step. The horizontal reaction force is obtained by solving the following equation:

[0234]

[0235] in, For the k-th time step, Here are the nodal displacement vectors of the finite element analysis model. This is the transformation vector that maps the nodal force vector to the horizontal reaction force at the loading control point.

[0236] The real-time relationship between the horizontal reaction force sequence and the yield displacement sequence is denoted as a hysteresis curve, which can be defined as a set of points, as follows:

[0237]

[0238] in, Let be the yield displacement load at the k-th time step. Let the horizontal reaction force be at the k-th time step. This represents the total number of time steps.

[0239] Based on the hysteresis curve, the ductility coefficient, cumulative energy dissipation, and equivalent viscous damping ratio are calculated. The resulting calculations are unified as hysteresis analysis results, and the calculation process is as follows:

[0240]

[0241] in, It is the ductility coefficient;

[0242]

[0243] in, The horizontal reaction force at the (k+1)th time step. The yield displacement load at the (k+1)th time step. For cumulative energy consumption;

[0244]

[0245]

[0246] in, For the maximum yield displacement load, For the maximum horizontal reaction force, The area of ​​the enclosing triangle, Let be the area of ​​a single hysteresis loop. It is the equivalent viscous damping ratio.

[0247] Step S3: Multi-objective collaborative optimization: Define the objective function according to the comprehensive performance index report, establish a multi-objective optimization model with the objective function as the optimization objective, and perform collaborative optimization on the wall parameter configuration set in the multi-objective optimization model to determine the optimal parameter matching interval of the shear wall bearing capacity.

[0248] Extract the buckling analysis results and hysteresis analysis results from the comprehensive performance index report.

[0249] The critical buckling shear force is used as a stability index, the product of the maximum horizontal reaction force and the ductility coefficient is used as a bearing capacity ductility index, and the equivalent viscous damping ratio is used as an energy dissipation capacity index.

[0250] Objective functions are constructed based on various performance indicators. These objective functions include a stability objective function, a load-bearing capacity-ductility objective function, and an energy dissipation objective function. The construction process is as follows:

[0251] The stability objective function is expressed as follows:

[0252]

[0253] in, This is a reference value for the critical buckling shear force. Let the stability objective function be...

[0254] When the stability objective function is greater than 1, the current stability is better than the reference value;

[0255]

[0256]

[0257]

[0258]

[0259] and

[0260]

[0261]

[0262]

[0263]

[0264] and

[0265] The process for constructing a multi-objective optimization model is as follows:

[0266] Extract the corrugated geometry parameters and connection construction parameters from the wall parameter configuration set.

[0267] The design variable vector is constructed by selecting the amplitude-to-wavelength ratio and the corrugation angle from the corrugation geometry parameters, and the bolt spacing from the connection construction parameters, as shown below:

[0268]

[0269] in, The amplitude-to-wavelength ratio, Bolt spacing;

[0270] Based on given engineering specifications, boundary constraints are applied to the amplitude-to-wavelength ratio, corrugation angle, and bolt spacing, denoted as:

[0271]

[0272] To ensure the matching of bolt arrangement, structural constraints are applied to the bolt spacing, denoted as:

[0273]

[0274] in, This is the preset bolt spacing coefficient;

[0275] Combining the objective function, design variable vector, boundary constraints, and construction constraints, a multi-objective optimization model is established, as follows:

[0276]

[0277]

[0278]

[0279] in, Let the objective function vector be... Let the stability objective function be... Let the load-bearing capacity ductility objective function be... Let the energy consumption objective function be... To design variable vectors, This indicates that the constraint is satisfied;

[0280] The collaborative optimization process is as follows:

[0281] Within the boundary constraints and construction constraints, multiple sets of design variable vectors are randomly selected to form an initial solution set, denoted as:

[0282]

[0283] in, No. A vector of design variables, This represents the preset total number of design variable vectors. This is the initial solution set;

[0284] Let the objective function vector corresponding to each design variable vector in the initial solution set be denoted as:

[0285]

[0286] The initial solution set is non-dominated and sorted according to the target value vector, and the design variable vectors are divided into multiple frontier levels:

[0287] For any two design variable vectors, the objective function vector should simultaneously satisfy the following conditions:

[0288]

[0289]

[0290] From the initial solution set, identify all design variable vectors that are not dominated by any other design variable vectors, and form the first frontier level, denoted as:

[0291]

[0292] in, It is the first frontier level;

[0293] From the residual design variable vectors of the initial solution set, identify all design variable vectors that are not dominated by the residual design variable vectors, forming the second frontier level, denoted as:

[0294]

[0295] in, It is the second frontier level;

[0296] Repeat the above process until all design variable vectors in the initial solution set are divided into multiple frontier levels.

[0297] The first frontier is the best frontier, the second frontier is the next best, and so on.

[0298] Design variable vectors are selected in descending order of frontier level to obtain high-quality design variable vectors.

[0299] Two high-quality design variable vectors are randomly selected to generate a new design variable vector, using the following formula:

[0300]

[0301]

[0302] Repeat this process to integrate all the new design variable vectors obtained into a new generation of solution set;

[0303] The new generation of solution set is used as the initial solution set for the next iteration, and the process of forming the new generation of solution set is repeated in this way.

[0304] When the loop iteration reaches the preset maximum number of iterations, the iteration terminates, and the new generation of solution set obtained at this time is output as the optimal frontier solution set.

[0305] By statistically analyzing all design variable vectors in the optimal front solution set, the ranges of values ​​for the amplitude-to-wavelength ratio, the bend angle, and the bolt spacing are obtained:

[0306]

[0307]

[0308]

[0309] in, For the optimal frontier solution set, This represents the lower limit of the optimal range for the amplitude-to-wavelength ratio. This represents the upper limit of the optimal range for the amplitude-to-wavelength ratio. This represents the lower limit of the optimal range for the bend angle. This represents the upper limit of the optimal range for the bend angle. This represents the lower limit of the optimal range for bolt spacing. This represents the upper limit of the optimal range for bolt spacing;

[0310] Based on the given engineering specifications, the value range of the design variables is rationally adjusted, and the optimal parameter matching interval is output, as shown below:

[0311]

[0312] Step S4: Design document generation and output: Based on the optimal parameter matching interval and the wall parameter configuration set, generate the corresponding shear wall construction details, and output the shear wall construction details as engineering documents to guide production and manufacturing.

[0313] The process for generating detailed structural drawings of the shear wall is as follows:

[0314] From the optimal parameter matching interval, select a set of amplitude-to-wavelength ratio, corrugation angle, and bolt spacing that conform to engineering specifications, denoted as:

[0315]

[0316] in, For the selected amplitude-to-wavelength ratio, For the selected bend angle, The selected bolt spacing;

[0317] Extract the corrugated geometric parameters from the wall parameter configuration set, and calculate the specific amplitude value based on the ratio of the wavelength in the corrugated geometric parameters to the selected amplitude wavelength, using the following formula:

[0318]

[0319] in, For specific amplitude values;

[0320] By calling the corrugated steel plate profile function and using the specific amplitude value, wavelength and selected corrugation angle, the three-dimensional geometry of the corrugated steel plate is obtained.

[0321] Using the selected bolt spacing as a reference, the coordinates of each bolt hole position are calculated and determined along the domain of the corrugated steel plate profile function. The calculation process is as follows:

[0322] Along the X-axis direction of the corrugated steel plate, starting from one edge of the wall segment, and using the selected bolt spacing as a fixed interval, determine the X-axis coordinate values ​​of each column of bolt holes sequentially. The formula is as follows:

[0323]

[0324] in, For the first The X-axis coordinates of the bolt hole positions in the column; The total number of bolt rows satisfies ;

[0325] Substituting the X-coordinate of each column of bolt holes into the mid-surface contour function, we obtain the Z-axis coordinate value of the bolt hole:

[0326]

[0327]

[0328]

[0329]

[0330] in, For the first The Y-axis coordinate value of the bolt hole position in the row; The total number of bolt rows satisfies ;

[0331] Based on the above calculations, all bolt hole coordinates are integrated to form a bolt hole coordinate set, denoted as:

[0332]

[0333] Extract the component size parameters from the wall parameter configuration set, and based on the thickness of the flat steel plate, combine the wall limb thickness and wall limb width to obtain the three-dimensional geometry of the flat steel plate;

[0334] By combining the three-dimensional geometry and bolt hole coordinates, a detailed structural drawing of the shear wall is obtained.

[0335] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for improving the bearing capacity of flat and corrugated steel plate shear walls based on parameter optimization, characterized in that, The steps are as follows: Step S1: Parameter definition and input: Define and input the geometric and material parameters of the shear wall. The wall parameters are encoded and stored according to a preset data structure and format to construct a wall parameter configuration set. Step S2: Finite element simulation and analysis: Automatically read the wall parameter configuration set, establish a finite element analysis model of the flat steel plate and corrugated steel plate shear wall, perform eigenvalue buckling analysis and nonlinear hysteresis analysis, organize the buckling analysis results and hysteresis analysis results in a structured manner, and output a comprehensive performance index report; Step S3: Multi-objective collaborative optimization: Define an objective function based on the comprehensive performance index report, establish a multi-objective optimization model with the objective function as the optimization objective, and perform collaborative optimization on the wall parameter configuration set in the multi-objective optimization model to determine the optimal parameter matching range for the shear wall bearing capacity; Step S4: Design document generation and output: Based on the optimal parameter matching interval and the wall parameter configuration set, generate the corresponding shear wall construction details, and output the shear wall construction details as engineering documents to guide production and manufacturing.

2. The method according to claim 1, characterized in that, The wall parameters include corrugation geometry parameters, component size parameters, connection structure parameters, and overall mechanical parameters; The corrugated geometric parameters include the amplitude, wavelength, amplitude-to-wavelength ratio, and corrugation angle of the corrugated steel plate. The component dimensional parameters include the thickness of the flat steel plate, the thickness of the corrugated steel plate, and the combination relationship between the thicknesses of the two. The connection construction parameters include the bolt spacing used to connect the flat steel plate and the corrugated steel plate, and the bolt spacing is related to the wavelength. The overall mechanical parameters include the height-to-thickness ratio of the wall segment, the shear span ratio, and the design axial compression ratio.

3. The method according to claim 2, characterized in that, The establishment of the finite element analysis model includes calculating the wall thickness and width, and generating corrugated steel plate geometry and flat steel plate geometry. The wall parameter configuration set is read, and using the overall mechanical parameters therein, combined with the wall member height given in the engineering specifications, the wall member thickness and width are calculated. The calculation process for the wall thickness is as follows: in, For a given wall height, The height-to-thickness ratio of the wall segment. For wall thickness; The calculation process for the width of the wall segment is as follows: in, The shear span ratio of the wall segment. The width of the wall segment.

4. The method according to claim 3, characterized in that, Based on the corrugated geometric parameters and component size parameters, and combined with the actual dimensions of the wall segment, a corrugated steel plate geometry is generated. The process is as follows: Let the width of the wall segment be the X-axis, the height of the wall segment be the Y-axis, and the plane normal of the wall segment be the Z-axis. Establish a global rectangular coordinate system. Within a single wavelength, the mid-surface profile function of the corrugated steel plate is defined as follows: in, The preset crest length coefficient, For wavelength, The horizontal length of the wave crest segment; in, For amplitude, For the undulation angle, This represents the horizontal projection length of the slope segment; in, The horizontal length of the trough segment; In summary, the mid-surface profile function within a single wavelength is defined as: in, Let X be the coordinate variable along the X-axis. This is a function for the mid-surface contour line; In the global rectangular coordinate system, the mid-surface profile function is periodically repeated along the X-axis to form a corrugated steel plate profile function covering the width of the wall segment, denoted as: in, For the profile function of corrugated steel plate; The corrugated steel plate profile function is stretched along the Y-axis to the height of the wall limb, thus obtaining the mid-surface of the corrugated steel plate. Extract the thickness of the corrugated steel plate from the component's dimensional parameters, and perform a double-sided offset on the mid-surface of the corrugated steel plate along the Z-axis to generate the corrugated steel plate geometry, which is parametrically represented as follows: in, The middle surface of the corrugated steel plate This refers to the preset coordinate reference value of the corrugated steel plate's mid-surface in the Z-axis direction. For the thickness of the corrugated steel plate, For the generated corrugated steel plate geometry; Extract the thickness of the flat steel plate from the component size parameters, and combine it with the width of the wall segment to generate the flat steel plate geometry, which is parameterized as follows: in, The Z-axis coordinates of the preset flat steel plate mid-surface are: For the thickness of the flat steel plate, For the generated flat steel plate geometry; The corrugated steel plate geometry and the flat steel plate geometry are assembled according to the design positions given in the engineering specifications to obtain the assembled geometry. Constrain all degrees of freedom at the bottom of the assembly geometry and perform a fixed-end simulation. Extract the design axial compression ratio from the overall mechanical parameters, and calculate the axial load by combining the wall thickness, wall width, and preset steel yield strength. Then, apply the axial load to the top of the assembled geometry using the following formula: in, To design the axial compression ratio, For the yield strength of steel, For axial loads; The assembly geometry with complete freedom constraints and axial load application constitutes the finite element analysis model. Establish a loading control point at the position of the central axis at the top of the finite element analysis model.

5. The method according to claim 4, characterized in that, A preset horizontal reference shear force is applied at the loading control point for eigenvalue buckling analysis, and the procedure is as follows: Solve the eigenvalue equation and calculate the eigenvalues. The equation is as follows: in, The initial linear stiffness matrix of the finite element analysis model is automatically generated from the model geometry and material properties. This is the geometric stiffness matrix automatically generated on the finite element analysis model of axial load; The eigenvectors corresponding to the eigenvalues; For eigenvalues; The minimum positive eigenvalue obtained is denoted as the critical buckling load. Based on the critical buckling load, the critical buckling shear force and elastic buckling shear stress of the wall pier during elastic instability are calculated and integrated into the buckling analysis results, the formula of which is as follows: in, This is the critical buckling load. For horizontal reference shear force, The critical buckling shear force. Let be the cross-sectional area of ​​the wall segment. It is the elastic buckling shear stress.

6. The method according to claim 4, characterized in that, The estimated yield displacement is applied at the loading control point for nonlinear hysteresis analysis, and the procedure is as follows: The formula for calculating the yield displacement load at the loading control point is as follows: in, For the k-th time step, for The displacement multiple corresponding to the time step. For the estimated yield displacement, Time step ; All the obtained yield displacement loads are arranged according to time steps and denoted as the yield displacement sequence, as follows: Based on the yield displacement sequence, the horizontal reaction force at the corresponding loading control point is calculated at each time step. The horizontal reaction force is obtained by solving the following equation: in, The response function for the loaded control points is determined by the material nonlinearity and geometric nonlinearity of the finite element analysis model. This represents the horizontal reaction force at the k-th time step. All the obtained horizontal reaction forces are arranged according to time steps and denoted as the horizontal reaction force sequence, as follows: The real-time relationship between the yield displacement sequence and the horizontal reaction force sequence is denoted as a hysteresis curve, which is a set of points, as follows: in, The total number of time steps. The hysteresis curve; Based on the hysteresis curve, the ductility coefficient, cumulative energy dissipation, and equivalent viscous damping ratio are calculated. The resulting calculations are unified as hysteresis analysis results, and the calculation process is as follows: in, It is the ductility coefficient; in, The horizontal reaction force at the (k-1)th time step. The yield displacement load at the (k-1)th time step. For cumulative energy consumption; in, For the maximum yield displacement load, For the maximum horizontal reaction force, The area of ​​the enclosing triangle, The area of ​​the closed region enclosed by the hysteresis curve is given. It is the equivalent viscous damping ratio.

7. The method according to claim 6, characterized in that, Extract the buckling analysis results and hysteresis analysis results from the comprehensive performance index report. The critical buckling shear force is used as a stability index, the product of the maximum horizontal reaction force and the ductility coefficient is used as a bearing capacity ductility index, and the equivalent viscous damping ratio is used as an energy dissipation capacity index. Objective functions are constructed based on various performance indicators. These objective functions include a stability objective function, a load-bearing capacity-ductility objective function, and an energy dissipation objective function. The construction process is as follows: The stability objective function is expressed as follows: in, This is a reference value for the critical buckling shear force. Let the stability objective function be... The objective function for bearing capacity ductility is expressed as follows: in, This is a reference value for the maximum horizontal reaction force. This is a reference value for the ductility coefficient. The objective function is the load-bearing capacity ductility. The energy consumption objective function is expressed as follows: in, This is a reference value for the equivalent viscous damping ratio. The objective function is energy consumption.

8. The method according to claim 7, characterized in that, The process of constructing a multi-objective optimization model is as follows: Extract the corrugated geometry parameters and connection construction parameters from the wall parameter configuration set. The design variable vector is constructed by selecting the amplitude-to-wavelength ratio and the corrugation angle from the corrugation geometry parameters, and the bolt spacing from the connection construction parameters, as shown below: in, The amplitude-to-wavelength ratio, Bolt spacing, To design a variable vector; Based on given engineering specifications, boundary constraints are applied to the amplitude-to-wavelength ratio, corrugation angle, and bolt spacing, denoted as: in, The minimum amplitude-to-wavelength ratio, The maximum amplitude-to-wavelength ratio, For the minimum bend angle, For the maximum undulation angle, Minimum bolt spacing This represents the maximum bolt spacing; To ensure the matching of bolt arrangement, structural constraints are applied to the bolt spacing, denoted as: in, This is the preset bolt spacing coefficient; Combining the objective function, design variable vector, boundary constraints, and construction constraints, a multi-objective optimization model is established, as follows: in, Let the objective function vector be... This indicates that the constraint is satisfied.

9. The method according to claim 8, characterized in that, The collaborative optimization process is as follows: Within the boundary constraints and construction constraints, multiple sets of design variable vectors are randomly selected to form an initial solution set, denoted as: in, No. A vector of design variables, This represents the preset total number of design variable vectors. This is the initial solution set; Let the objective function vector corresponding to each design variable vector in the initial solution set be denoted as: The initial solution set is non-dominated and sorted according to the target value vector, and the design variable vectors are divided into multiple frontier levels: For any two design variable vectors, the objective function vector should simultaneously satisfy the following conditions: Then it means Dominate , recorded as ;in, For the first One objective function, This is one of the design variable vectors in the initial solution set; From the initial solution set, identify all design variable vectors that are not dominated by any other design variable vectors, and form the first frontier level, denoted as: in, It is the first frontier level; From the residual design variable vectors of the initial solution set, identify all design variable vectors that are not dominated by the residual design variable vectors, forming the second frontier level, denoted as: in, This is one of the remaining design variable vectors in the initial solution set. It is the second frontier level; Repeat the above process until all design variable vectors in the initial solution set are divided into multiple frontier levels; Design variable vectors are selected in descending order of their frontier level to obtain high-quality design variable vectors. Two high-quality design variable vectors are randomly selected to generate a new design variable vector, using the following formula: in, To design high-quality variable vectors, For random weights, Design a new variable vector; Repeat this process to integrate all the new design variable vectors obtained into a new generation of solution set; The new generation of solution set is used as the initial solution set for the next iteration, and the process of forming the new generation of solution set is repeated in this way. When the loop iteration reaches the preset maximum number of iterations, the iteration terminates, and the new generation of solution set obtained at this time is output as the optimal frontier solution set. By statistically analyzing all design variable vectors in the optimal front solution set, the value ranges of the amplitude-to-wavelength ratio, the bend angle, and the bolt spacing are finally obtained: in, For the optimal frontier solution set, This represents the lower limit of the optimal range for the amplitude-to-wavelength ratio. This represents the upper limit of the optimal range for the amplitude-to-wavelength ratio. This represents the lower limit of the optimal range for the bend angle. This represents the upper limit of the optimal range for the bend angle. This represents the lower limit of the optimal range for bolt spacing. This represents the upper limit of the optimal range for bolt spacing; Based on the given engineering specifications, the ranges of the amplitude-to-wavelength ratio, the bend angle, and the bolt spacing are rationally adjusted, and the optimal parameter matching interval is output as follows:

10. The method according to claim 9, characterized in that, The process for generating detailed structural drawings of the shear wall is as follows: Select a set of amplitude-to-wavelength ratio, corrugation angle, and bolt spacing that conform to engineering specifications from the optimal parameter matching range. Extract the corrugated geometric parameters from the wall parameter configuration set, and calculate the specific wave amplitude value by combining the wavelength in the corrugated geometric parameters. The formula is as follows: in, For the selected amplitude-to-wavelength ratio, For specific amplitude values; By calling the corrugated steel plate profile function and using the specific amplitude value, wavelength and selected corrugation angle, the three-dimensional geometry of the corrugated steel plate is obtained. Using the selected bolt spacing as a reference, the coordinates of each bolt hole position are calculated and determined along the domain of the corrugated steel plate profile function. The calculation process is as follows: Along the X-axis of the global rectangular coordinate system, starting from the edge of one side of the wall, and using the selected bolt spacing as a fixed interval, the X-axis coordinate values ​​of each column of bolt holes are determined sequentially, using the following formula: in, For the selected bolt spacing, For the first The X-axis coordinates of the bolt hole positions in the column; The total number of bolt rows satisfies ; Substituting the X-coordinate of each column of bolt holes into the corrugated steel plate profile function, we obtain the Z-axis coordinate value of the bolt holes: in, For the first The Z-axis coordinates of the bolt hole positions in the column; Arrange multiple rows of bolts along the Y-axis at the connection spacing specified in the engineering specifications, and obtain the Y-axis coordinate values ​​of the bolt hole positions, represented as: in, For the first The Y-axis coordinate value of the bolt hole position in the row; The total number of bolt rows satisfies ; Based on the above calculations, all bolt hole coordinates are integrated to form a bolt hole coordinate set, denoted as: Extract the component size parameters from the wall parameter configuration set, and based on the thickness of the flat steel plate, combine the wall limb thickness and wall limb width to obtain the three-dimensional geometry of the flat steel plate; By combining the three-dimensional geometry and bolt hole coordinates, a detailed structural drawing of the shear wall is obtained.

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