A Simulation and Optimization Method for Bandgap Design of Metamaterial Steel-Concrete Tube Columns Based on Finite Element Method
By optimizing the gap design of metamaterial steel-concrete composite columns using the finite element method, the problem of mismatch between the gap and the seismic frequency range in traditional design was solved, improving the dynamic load resistance and safety of the structure, while achieving lightweighting and cost optimization.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHANGSHU INSTITUTE OF TECHNOLOGY
- Filing Date
- 2025-11-25
- Publication Date
- 2026-06-30
AI Technical Summary
Traditional methods have failed to effectively match the gap between metamaterial steel-concrete composite columns and the seismic frequency range, resulting in their weak resistance to dynamic loads such as earthquakes and wind vibrations.
By using the finite element method, the band gap design of metamaterial steel-concrete composite columns is optimized. By using the modification amount of target material parameters and band gap data, the material parameters are iteratively adjusted to match the seismic frequency range, ensuring that the band gap coincides with the frequency range of significant energy distribution of seismic events.
It improves the resistance of metamaterial steel-concrete composite columns to dynamic loads such as earthquakes and wind vibrations, enhances structural safety and lightweight design, and reduces material usage and construction costs.
Smart Images
Figure CN121189110B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of electronic digital data processing technology, specifically to a simulation optimization method for the design of band gap in metamaterial steel-concrete composite columns based on the finite element method. Background Technology
[0002] Precisely designing the band gap of metamaterial steel-concrete composite columns can precisely suppress the propagation of vibration energy in specific frequency bands, thereby significantly improving the structure's resistance to dynamic loads such as earthquakes and wind-induced vibrations, effectively protecting the safety of the main structure. Simultaneously, this targeted design helps achieve structural lightweighting, avoids excessive redundancy, and optimizes material usage and construction costs. Precise band gap control is the core guarantee for this type of structure to achieve its exceptional performance.
[0003] Traditional methods uniformly set the same material parameters for multiple metamaterial steel-concrete composite columns in a metamaterial steel-concrete composite column array. However, this does not take into account the incomplete matching of existing band gaps with the seismic frequency ranges borne by the target area when there are many seismic frequency ranges. As a result, the metamaterial steel-concrete composite columns have relatively weak resistance to dynamic loads such as earthquakes and wind vibrations. Summary of the Invention
[0004] To address the technical problem of incomplete matching between the band gap of existing metamaterial steel-concrete composite columns and the seismic frequency range experienced by the target area, the present invention aims to provide a finite element method-based simulation optimization method for the design of band gaps in metamaterial steel-concrete composite columns. The specific technical solution adopted is as follows:
[0005] This invention provides a simulation and optimization method for the design of cross-sections in metamaterial steel-concrete composite columns based on the finite element method. The method includes:
[0006] By utilizing the amount of bandgap data modification that affects the target bandgap performance data when the target material parameters of the target steel-concrete composite column are modified, the initial material modification amount of the target material parameters and the target bandgap are determined.
[0007] By using the previous bandgap data modification amount, initial material modification amount, and actual data change amount of the target bandgap performance data in the target bandgap, the target material parameter modification amount for this time is determined;
[0008] By iteratively modifying the target material, the material parameter formula and the modified current target bandgap are obtained, and the overlapping frequency range between the current target bandgap and the significant energy distribution frequency range in the seismic azimuth is determined.
[0009] The degree of conformity of the material parameter formulation to the target steel-concrete composite column is determined by using the overlapping frequency range, and the target material parameter formulation is obtained based on the degree of conformity.
[0010] Furthermore, the determination of the initial material modification amount of the target material parameters and the target bandgap by utilizing the bandgap data modification amount affecting the target bandgap performance data when modifying the target material parameters of the target steel-concrete composite column includes:
[0011] Determine the maximum value of band gap data modification and the number of band gap performance types in the target band gap performance data when the target material parameters of the target steel tube concrete column are modified.
[0012] By using the maximum value of bandgap data modification and the number of bandgap behavior types, the degree of reduction in the modification of the target material parameters is calculated;
[0013] By utilizing the degree of reduction in modification and the maximum value of bandgap data modification, the initial material modification amount and target bandgap of the target material parameters are determined.
[0014] Furthermore, determining the initial material modification amount and target bandgap of the target material parameters by utilizing the degree of reduction and the maximum value of the bandgap data modification includes:
[0015] The maximum value among the maximum values of each bandgap data modification is taken as the maximum modification, and the bandgap corresponding to the maximum modification is taken as the target bandgap.
[0016] The expected change in the target material parameters is obtained by using the maximum modification amount and the maximum value of the bandgap data modification amount;
[0017] The initial material modification amount of the target material parameters is calculated by using the degree of reduction of the modification and the expected amount of change.
[0018] Furthermore, determining the target material modification amount for this target material parameter by utilizing the previous bandgap data modification amount, the initial material modification amount, and the actual data change amount of the target bandgap performance data in the target bandgap includes:
[0019] Using the maximum modification amount and the degree of modification reduction corresponding to the previous bandgap data modification amount, the expected modification change amount of the previous target bandgap performance data is calculated;
[0020] Determine the difference in data change between the actual data change in the target bandgap performance data of the previous test and the expected modification amount;
[0021] By using the difference between the actual data change and the expected change, the degree of reduction in the modification of the target material parameters relative to the previous target material parameters is determined.
[0022] Using the degree of reduction in modification and the initial material modification amount, the target material modification amount for this target material parameter is calculated.
[0023] Furthermore, by utilizing the difference in data change between the actual data change and the expected modification change, the degree of reduction in the modification of the target material parameters relative to the previous target material parameters is determined, including:
[0024] Determine the frequency difference between the target bandgap performance data after the previous modification of the target material parameters and the corresponding frequencies of the significant energy distribution frequency range in the seismic events in the target area;
[0025] By utilizing the frequency difference, the difference in data change between the actual data change and the expected modification change, the degree of reduction in the modification of the target material parameters relative to the previous target material parameters is calculated.
[0026] Furthermore, the step of iteratively modifying the material parameter formulation and the modified current target bandgap using the target material modification amount includes:
[0027] The target material parameters are modified using the target material modification amount to obtain the modified current target material parameters and the corresponding modified current target bandgap;
[0028] Determine the frequency differences between the modified current target bandgap performance data and the corresponding frequencies of significant energy distribution frequency intervals in seismic events in the target region;
[0029] If the frequency differences are all less than the preset frequency, stop iteratively modifying the target material parameters and the target bandgap performance data affected by the modification of the target material parameters.
[0030] Furthermore, the determination of the degree of conformity of the material parameter formulation to the target steel-concrete composite column using the coincident frequency range includes:
[0031] The degree of skewness in satisfying the current target band gap of the target steel-concrete composite column is determined by the number of overlapping frequency intervals and the seismic azimuth angle.
[0032] The degree of conformity of each material parameter formulation to the target steel-concrete composite column is determined by the degree of eccentricity.
[0033] Furthermore, the determination of the degree of skewness in satisfying the current target bandgap by utilizing the number of overlapping frequency intervals and the seismic azimuth angle includes:
[0034] Determine the acute angle between the line connecting the target concrete-filled steel tube column to the central column in the concrete-filled steel tube column array and the horizontal rightward direction.
[0035] By using the absolute value of the difference between the acute angle and the seismic azimuth angle and the number of overlapping frequency intervals, the degree of skewness of the target steel-concrete composite column in meeting the current target gap is calculated.
[0036] Furthermore, the determination of the conformity of each material parameter formulation to the target steel-concrete composite column by satisfying the degree of eccentricity includes:
[0037] Determine the current target band gap in the target steel-concrete composite column that satisfies the eccentricity greater than the preset eccentricity threshold and record it as the eccentricity-satisfied band gap;
[0038] Determine the frequency range that satisfies the eccentric bandgap and the material parameter formulation, and determine the width ratio between the overlapping frequency range and the complete frequency range that satisfies the eccentric bandgap.
[0039] By utilizing the degree of weight distribution, the width ratio, and the number of weight distribution gaps, the degree of conformity of each material parameter formulation to the target steel-concrete composite column is calculated.
[0040] Furthermore, the process of obtaining the target material parameter formulation based on the degree of conformity includes:
[0041] Determine the degree of conformity of each material parameter formulation to the target steel-concrete composite column, and take the material parameter formulation corresponding to the maximum degree of conformity as the target material parameter formulation.
[0042] The present invention has the following beneficial effects:
[0043] This invention pre-modifies data in a reference supermaterial steel-concrete composite column based on the influence of different material parameters on the corresponding band gap condition. It then rationally adjusts the data modification compensation based on feedback from changes in the band gap condition under different material parameter data modifications. The band gap condition of different supermaterial steel-concrete composite columns is acquired with a focus on the directionality of seismic vibration. Material parameters for different locations are acquired based on the suitability of the obtained band gap condition under different material parameter combinations with the required location. This results in a more complete match between the band gap of the supermaterial steel-concrete composite column and the seismic frequency range experienced by the target area, thereby significantly enhancing the supermaterial steel-concrete composite column's resistance to dynamic loads such as earthquakes and wind vibrations, including a stronger ability to attenuate seismic signals, and ensuring greater safety for personnel located within the supermaterial steel-concrete composite column structure. Attached Figure Description
[0044] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0045] Figure 1A flowchart illustrating the steps of a finite element-based metamaterial steel-concrete composite column bandgap design simulation optimization method provided in one embodiment of the present invention;
[0046] Figure 2 This is a detailed flowchart of step S1 in a finite element-based metamaterial steel-concrete composite column bandgap design simulation optimization method provided in an embodiment of the present invention.
[0047] Figure 3 This is a detailed flowchart of step S2 in a finite element-based metamaterial steel-concrete composite column bandgap design simulation optimization method provided in an embodiment of the present invention.
[0048] Figure 4 This is a detailed flowchart of step S3 in a finite element-based metamaterial steel-concrete composite column bandgap design simulation optimization method provided in an embodiment of the present invention.
[0049] Figure 5 This is a detailed flowchart of step S4 in a finite element-based metamaterial steel-concrete composite column bandgap design simulation optimization method provided in an embodiment of the present invention.
[0050] Figure 6 This is a detailed flowchart of step S42 in a finite element-based metamaterial steel-concrete composite column bandgap design simulation optimization method provided in an embodiment of the present invention.
[0051] Figure 7 This is a schematic diagram of the hardware operating environment of the finite element-based metamaterial steel-concrete composite column bandgap design simulation and optimization equipment involved in the embodiments of the present invention.
[0052] Figure 8 This is a schematic diagram illustrating the relationship between the steel tube concrete column array and the seismic orientation in the finite element-based metamaterial steel tube concrete column bandgap design simulation optimization method involved in the embodiments of the present invention.
[0053] Figure 9 This is a schematic diagram illustrating the overlap frequency range between the biased bandgap and the material parameter formulation in the finite element-based metamaterial steel-concrete composite column bandgap design simulation optimization method involved in the embodiments of the present invention. Detailed Implementation
[0054] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a finite element-based simulation optimization method for band gap design of metamaterial steel-concrete composite columns proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.
[0055] It should be noted that, in order to ensure that the calculation results are meaningful, when performing fractional operations, if the denominator is 0, a parameter adjustment factor greater than 0 needs to be added to the denominator to prevent the denominator from being 0. The value of the parameter adjustment factor shall be set by the implementer according to the actual situation, and this application does not impose any special restrictions.
[0056] It should be noted that, for ease of calculation, all indicator data involved in the calculation in this embodiment of the invention have undergone data preprocessing to eliminate the influence of dimensions. The specific methods for eliminating the influence of dimensions are well known to those skilled in the art and are not limited here.
[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0058] The following description, in conjunction with the accompanying drawings, details the specific scheme of the finite element-based simulation optimization method for bandgap design of metamaterial steel-concrete composite columns provided by this invention.
[0059] Example 1:
[0060] For the finite element method-based simulation optimization method for band gap design of metamaterial steel-concrete composite columns provided in this invention, please refer to [link to relevant documentation]. Figure 1 The diagram illustrates a flowchart of the steps for a finite element-based simulation optimization method for the design of gapless steel-concrete composite columns using metamaterials.
[0061] The finite element method-based simulation optimization method for the design of cross-sections in metamaterial steel-concrete composite columns includes:
[0062] Step S1: Using the amount of bandgap data modification that affects the target bandgap performance data when the target material parameters of the target steel tube concrete column are modified, determine the initial material modification amount of the target material parameters and the target bandgap.
[0063] In this embodiment, the seismic external excitation frequency at the installation location of the metamaterial steel tube concrete column can first be obtained:
[0064] Multiple (typically ≥3, the more the better, and the higher the accuracy) seismic stations are densely deployed within the target area (or near its boundaries). Broadband or high-sensitivity short-period seismometers are used, equipped with high-precision data acquisition devices (24-bit or higher). All stations are strictly synchronized (GPS timing accuracy better than 1ms). Data is transmitted to the central processing station in real time for storage of raw waveform data.
[0065] The location of seismic waves reaching the seismic station is determined using the time difference method. The significant energy distribution frequency ranges (i.e., the main frequency bands where seismic wave energy is concentrated) in seismic events within the target area are identified using the source spectrum estimation method.
[0066] The band structure of a metamaterial steel-concrete composite column was calculated using the finite element method, and its flexural bandgap characteristics were analyzed. The specific steps are as follows:
[0067] Construct periodic units (such as squares or hexagons) with a unit cell side length L=20cm, and embed resonant units (such as rubber-lead block structures) inside.
[0068] Apply Floquet periodic boundary conditions using COMSOL Multiphysics (a multiphysics simulation software based on finite element analysis) or ABAQUS (another multiphysics simulation software based on finite element analysis) to ensure continuity between elements.
[0069] The concrete and cover plate are constructed using 3D solid elements (C3D8R) with an eight-node reduced integral format, while the steel pipes are constructed using shell elements (S4R). The mesh size is set to 20mm for concrete and 25mm for steel pipes.
[0070] Apply a harmonic excitation force with a frequency range covering the expected bandgap interval (e.g., 10-50 Hz). Use a characteristic frequency solver to perform a wave vector scan of the Brillouin zone boundary to calculate the band structure.
[0071] The band structure of cell vibrations is calculated using a characteristic frequency solver, and the effects of different geometric parameters (such as aggregate type and coating thickness) are compared.
[0072] Extract the dispersion curve and identify the bandgap range (such as the start frequency, cutoff frequency, and bandgap width).
[0073] The initial reference material parameters for the metamaterial steel-concrete composite column are divided into concrete material and steel tube material. The concrete material parameters include: density, elastic modulus, shear modulus, Poisson's ratio, compressive strength, tensile strength, shear strength, strain rate coefficient, damage coefficient, and pressure hardening coefficient.
[0074] Steel pipe materials include: density, elastic modulus, shear modulus, yield strength (divided into inner and outer steel pipes), Poisson's ratio, tangent modulus, and strain rate parameters.
[0075] For step S1 in this embodiment, the material parameters of the reference supermaterial steel tube concrete column need to be modified appropriately in stages according to the influence of different material parameters on the corresponding band gap of the supermaterial steel tube concrete column.
[0076] Specifically, modifications to different material parameters may have varying impacts on the bandgap characteristics (data) of metamaterial steel-concrete composite columns, including bandgap width, bandgap cutoff frequency, and bandgap initiation frequency. For example, increasing the core column density lowers both the bandgap initiation and cutoff frequencies, resulting in a low-frequency bandgap. Modifying a single material parameter can alter multiple bandgap characteristics. Therefore, to prevent the cumulative effects of multiple material parameter modifications on a single bandgap, which could lead to excessive discrepancies between the bandgap data and the significant energy distribution frequency range observed in actual seismic events, modifications to material parameters should be made in small, incremental steps.
[0077] Specifically, please refer to Figure 2 Step S1 includes:
[0078] Step S11: Determine the maximum value of the band gap data modification amount and the number of band gap performance types of the target band gap performance data affected by the modification of the target material parameters of the target steel tube concrete column.
[0079] Step S12: Calculate the degree of reduction in the modification of the target material parameters using the maximum value of the bandgap data modification and the number of bandgap performance types.
[0080] Step S13: Using the degree of reduction and the maximum value of bandgap data modification, determine the initial material modification amount and target bandgap of the target material parameters.
[0081] Further, step S13 includes:
[0082] The maximum value among the maximum values of each bandgap data modification is taken as the maximum modification, and the bandgap corresponding to the maximum modification is taken as the target bandgap.
[0083] The expected change in the target material parameters is obtained by using the maximum modification amount and the maximum value of the bandgap data modification amount;
[0084] The initial material modification amount of the target material parameters is calculated by using the degree of reduction of the modification and the expected amount of change.
[0085] In this embodiment, when different material parameters are changed during historical operations, the types and amounts of data changes in the performance of the metamaterial steel tube concrete column corresponding to each gap are obtained.
[0086] Based on the differences between the current metamaterial steel-concrete composite column (denoted as the target steel-concrete composite column, referring to any metamaterial steel-concrete composite column) material parameter configuration and the significant energy distribution frequency range in the actual target area seismic events, the material parameters that can be modified to approximate the bandgap performance data with the significant energy distribution frequency range in the seismic events are selected for modification and analysis.
[0087] The number of types of bandgap behavior that may be affected by modifying the relevant material parameter j (as the target material parameter, referring to any material parameter). The maximum modification amount of the relevant material parameter j in the historical modified data on the unit parameter data of different bandgap performance data k (as the target bandgap performance data, referring to any bandgap performance data) (i.e., the maximum value of the bandgap data modification) is obtained.
[0088] The maximum amount of change in bandgap performance data k corresponding to the unit parameter data when the material parameter j is modified. The expected modification value of the bandgap performance data k after modifying the unit data volume of material parameter j is used. The maximum modification amount of the bandgap performance data k among multiple current bandgap types is determined by comparing the current bandgap obtained from metamaterial steel-concrete composite columns with the significant energy distribution frequency range in seismic events in the target area. The maximum value among the maximum modifications of data in each bandgap is obtained, and the corresponding bandgap m is marked as the target bandgap. The maximum modification amount... Divide by the maximum amount of modification The expected change in material parameter j is obtained. .
[0089] The number of bandgap manifestations after modifying material parameter j The larger the value, the greater the maximum amount of modification. When the value of j is larger, modifications to the material parameter j will cause significant changes in the corresponding bandgap of the metamaterial steel-concrete composite column. To prevent excessive changes in the bandgap from leading to repeated modifications to the material parameters of the metamaterial steel-concrete composite column, and to ensure that the final obtained bandgap is closer to the frequency range of significant energy distribution in seismic events, the amount of modification to the material parameter j in a single modification should be reduced.
[0090] This allows us to determine the extent to which the material parameter j of the current metamaterial steel-concrete composite column under band gap has been modified and reduced. for:
[0091] ;
[0092] In the formula, Indicates the number of bandgap manifestation types. This indicates the maximum amount of modification (to the bandgap data).
[0093] Using the maximum-minimum normalization method After normalization, we get Its range is [0, 0.5].
[0094] when The larger the value, the smaller the modification to material parameter j should be. Therefore, the initial material modification amount for material parameter j can be obtained. for:
[0095] ;
[0096] In the formula, This reduces the degree of the above-mentioned normalized modifications; This represents the expected change in material parameter j.
[0097] The amount of modification of different material parameters is obtained, and then the corresponding band gap of the supermaterial steel tube concrete column after the material parameters are modified is obtained through the above implementation process.
[0098] Step S2: Using the previous bandgap data modification amount, initial material modification amount, and actual data change amount of the target bandgap performance data in the target bandgap, determine the target material parameter modification amount for this time.
[0099] In this embodiment, it is also necessary to determine the degree of similarity between the modified material parameter data and the data of the significant energy distribution frequency range in the seismic event, as well as the degree of similarity to the expected modified value (maximum modification amount). The degree of modification is adjusted appropriately based on the differences in the data. The band gap satisfaction of different metamaterial steel-concrete composite columns in the metamaterial steel-concrete composite column array is obtained with an emphasis on the azimuth and intensity of the earthquake.
[0100] After modifying the material parameters, the actual amount of change in bandgap performance data may not be the same as the expected amount. Therefore, the degree of modification of the material parameter data should be judged based on the actual change in bandgap performance data.
[0101] Specifically, please refer to Figure 3 Step S2 includes:
[0102] Step S21: Calculate the expected change in the target bandgap performance data from the previous step by using the maximum modification amount and the degree of modification reduction corresponding to the previous bandgap data modification amount.
[0103] Step S22: Determine the data change difference between the actual data change in the target bandgap performance data of the previous test and the expected modification change.
[0104] Step S23: Using the difference in data change between the actual data change and the expected modification change, determine the degree of reduction in the modification of the target material parameters relative to the previous target material parameters;
[0105] Further, step S23 specifically includes:
[0106] Determine the frequency difference between the target bandgap performance data after the previous modification of the target material parameters and the corresponding frequencies of the significant energy distribution frequency range in the seismic events in the target area;
[0107] By utilizing the frequency difference, the difference in data change between the actual data change and the expected modification change, the degree of reduction in the modification of the target material parameters relative to the previous target material parameters is calculated.
[0108] Step S24: Using the degree of reduction of the modification and the initial material modification amount, calculate the target material modification amount of the target material parameters for this time.
[0109] In this embodiment, after the (i-1)th modification of the material parameter j (as the previous modification), the actual change in the bandgap performance data k in the bandgap m is determined. Obtain it.
[0110] When analyzing the modification amount of material parameter j data for the (i-1)th time, the maximum modification amount is also obtained simultaneously. and The magnitude of the two values is multiplied to obtain the expected change in bandgap behavior data k in bandgap m when the material parameter j is modified for the (i-1)th time. .
[0111] Calculate the frequency difference between the value of the band gap performance data k in band gap m and the corresponding frequency in the significant energy distribution frequency interval of the seismic event in the target area after the (i-1)th modification of the material parameter j data. .
[0112] When the material parameter j is modified for the (i-1)th time, the frequency difference between the modified value of the bandgap performance data k and the required value in the significant energy distribution frequency range of the seismic event. The smaller the value, the greater the change in the actual data of the bandgap performance data k. Changes from the expected amount Difference ( - That is, the greater the difference in the data changes, the more the amount of material parameter j should be modified at one time.
[0113] This allows us to determine the degree of reduction in the modification of material parameter j compared to the (i-1)th modification (the degree of reduction in modification). :
[0114] ;
[0115] In the formula, For the frequency difference, This represents the actual change in the bandgap performance data k. The expected amount of modification change is given, where norm represents the normalization process.
[0116] Using the maximum-minimum normalization method After normalization, we get This linearly maps the range to [0, 0.8].
[0117] When adjusting the scaling The larger the value, the greater the reduction in the size of the i-th modification of material parameter j compared to the (i-1)-th modification. Therefore, the amount of data modification to material parameter j in the i-th modification (denoted as the target material modification amount) can be obtained. ):
[0118] .
[0119] In the formula, This represents the initial material modification amount for material parameter j in the (i-1)th iteration. This indicates the degree of reduction in the modification after normalization.
[0120] Step S3: Iteratively modify the material parameter formula and the modified current target bandgap using the target material modification amount, and determine the overlapping frequency range between the current target bandgap and the significant energy distribution frequency range in the seismic azimuth.
[0121] Specifically, please refer to Figure 4 Step S3, which iteratively modifies the material parameter formula and the modified current target bandgap using the target material modification amount, includes:
[0122] Step S31: Modify the target material parameters using the target material modification amount to obtain the modified current target material parameters and the corresponding modified current target bandgap;
[0123] Step S32: Determine the frequency differences between the modified current target bandgap performance data of each bandgap and the corresponding frequencies of the significant energy distribution frequency intervals in the seismic events in the target region;
[0124] Step S33: If the frequency differences are all less than the preset frequency, stop iteratively modifying the target material parameters and the target bandgap performance data affected by the modification of the target material parameters.
[0125] The initial material modification amount obtained in the above embodiment can be considered as the calculation process for the first modification of material parameter j. This embodiment describes the calculation process for each subsequent addition or subtraction of material parameter j, that is, iteratively modifying material parameter j using the target material modification amount obtained each time to obtain the modified current target material parameter and the corresponding modified current target bandgap. Simultaneously, multiple material parameters are modified, and the frequency difference between the bandgap performance data after the material parameters are modified and the corresponding frequency (required value) in the significant energy distribution frequency interval of the seismic event in the target area is considered. The iterative modification and adjustment stops when all values are less than 5Hz (preset frequency), including stopping iterative modifications to the target material parameters and the target bandgap performance data affected by the modification of the target material parameters. After stopping iterative modifications, multiple combinations of material parameters for each modification are obtained, which constitute the material parameter formulation.
[0126] The significant energy distribution frequency range in the earthquake azimuth is obtained. It is then determined whether the current target band gap containing frequency range d overlaps with the significant energy distribution frequency range in the earthquake azimuth.
[0127] Step S4: Determine the degree of conformity of the material parameter formula to the target steel tube concrete column using the overlapping frequency range, and obtain the target material parameter formula based on the degree of conformity.
[0128] Specifically, please refer to Figure 5 Step S4, which uses the overlapping frequency range to determine the degree of conformity of the material parameter formula to the target steel-concrete composite column, includes:
[0129] Step S41: Determine the degree of skewness of the target steel-concrete composite column in meeting the current target band gap by using the number of overlapping frequency intervals and the seismic azimuth angle.
[0130] Further, step S41 specifically includes:
[0131] Determine the acute angle between the line connecting the target concrete-filled steel tube column to the central column in the concrete-filled steel tube column array and the horizontal rightward direction.
[0132] By using the absolute value of the difference between the acute angle and the seismic azimuth angle and the number of overlapping frequency intervals, the degree of skewness of the target steel-concrete composite column in meeting the current target gap is calculated.
[0133] In this embodiment, in order to maximize the attenuation of seismic signals by the metamaterial steel-concrete composite column array, the relationship between the metamaterial steel-concrete composite columns at different positions in the array and the seismic azimuth should be considered. Different material parameters should be set for the metamaterial steel-concrete composite columns at different positions so that the metamaterial steel-concrete composite columns at different positions can adjust the corresponding bandgap range in response to the vibration signals transmitted from the corresponding seismic azimuth.
[0134] Please refer to Figure 8 , Figure 8 This is a schematic diagram illustrating the relationship between the steel tube concrete column array and the seismic orientation in the finite element-based metamaterial steel tube concrete column bandgap design simulation optimization method involved in the embodiments of the present invention.
[0135] Obtain the acute angle between the direction of the line connecting any metamaterial steel-concrete composite column g (here, the target steel-concrete composite column, referring to any metamaterial steel-concrete composite column) to the position of the central column in the array and the horizontal rightward direction. And the angle of the earthquake azimuth h (the horizontal angle between the direction of seismic wave propagation and the reference direction (set to the right)). (less than 90 degrees).
[0136] The significant energy distribution frequency intervals at the earthquake azimuth h are acquired. The number of overlapping frequency intervals between the current target band gap m containing frequency interval d and the significant energy distribution frequency intervals existing at the earthquake azimuth is determined. .
[0137] When the number of overlapping frequency intervals The larger the acute angle, the greater the included angle. relative to earthquake azimuth angle absolute value of the difference The smaller the value, the earlier the metamaterial steel-concrete composite column g comes into contact with the vibration signal of the seismic azimuth h compared to other metamaterial steel-concrete composite columns. Furthermore, the frequency range corresponding to the current target band gap m exists in multiple seismic azimuths. Therefore, the frequency range corresponding to the current target band gap m has a greater impact on the metamaterial steel-concrete composite column g, and the metamaterial steel-concrete composite column g should place greater emphasis on satisfying the current target band gap m.
[0138] This allows us to determine the degree of skewness in satisfying the current target bandgap m for the metamaterial steel-concrete composite column g. :
[0139] ;
[0140] In the formula, Indicates the number of overlapping frequency intervals. Indicates the acute angle included. relative to earthquake azimuth angle The absolute value of the difference.
[0141] Using the maximum-minimum normalization method After normalization, we get Its range is [0,1].
[0142] Step S42: Determine the degree of conformity of each material parameter formula to the target steel-concrete composite column by using the degree of eccentricity.
[0143] In this embodiment, appropriate material parameters are arranged for the metamaterial steel-concrete composite columns at different locations based on the degree of weight skewness required.
[0144] Simply changing material parameters often cannot fully guarantee that the frequency range of all band gaps is consistent with the frequency range of significant energy distribution in seismic events. Therefore, for metamaterial steel-concrete composite columns at different locations, corresponding material parameters are set with emphasis on their satisfaction of different band gaps, so that the entire metamaterial steel-concrete composite column array can meet the requirements of all band gaps.
[0145] Further, please refer to Figure 6 Step S42 specifically includes:
[0146] Step S421: Determine the current target gap in the target steel-concrete composite column that satisfies the eccentricity greater than the preset eccentricity threshold and record it as the eccentricity-satisfied gap;
[0147] Step S422: Determine the frequency range that satisfies the overlap between the biased bandgap and the material parameter formulation, and determine the width ratio between the overlapped frequency range and the complete frequency range that satisfies the biased bandgap.
[0148] Step S423: Using the degree of eccentricity, the width ratio, and the number of eccentricity gaps, calculate the degree of conformity of each material parameter formula to the target steel tube concrete column.
[0149] In this embodiment, the g-band gap of the metamaterial steel-concrete composite column satisfies the degree of eccentricity. The current target bandgap (with a preset bias threshold, which can be adjusted) is recorded as the biased bandgap.
[0150] All material parameter adjustments can be combined with the operations described in the above embodiments to obtain all suitable material parameter combinations, i.e., all material parameter formulations. The corresponding band gaps under different suitable material parameter combinations are then obtained.
[0151] Calculate the frequency range of multiple band gaps obtained under any material parameter formula v, and determine the degree of eccentricity of the band gap in the metamaterial steel-concrete composite column g. The bandgap frequency range is satisfied.
[0152] Please refer to Figure 9 , Figure 9 This is a schematic diagram illustrating the overlap frequency range between the biased bandgap and the material parameter formulation in the finite element-based metamaterial steel-concrete composite column bandgap design simulation optimization method involved in the embodiments of the present invention.
[0153] calculate The percentage of the frequency range (coinciding frequency range) included in the bandgap obtained under the material parameter formulation v, which satisfies the eccentric bandgap requirement, relative to the full frequency range of the eccentric bandgap. That is, the width ratio .
[0154] against The degree of eccentricity of the eccentricity band gap is determined when the supermaterial steel-concrete composite column g satisfies multiple eccentricity band gaps. The larger the band gap, the better the band gap obtained from the material parameter formulation v. The frequency bandwidth ratio of the biased bandgap The larger the value, the better the material parameter formulation v meets the requirements for the band gap performance at the location of the metamaterial steel tube concrete column g, and the more the material parameter formulation v should be used as the material parameter arrangement for the metamaterial steel tube concrete column g.
[0155] This allows us to determine the degree to which the material parameter formulation v conforms to the requirements of the metamaterial steel-concrete composite column g. :
[0156] ;
[0157] In the formula, Indicates the degree of emphasis. Indicates the width percentage. for The requirement is to prioritize the number of band gaps.
[0158] Furthermore, step S4, which obtains the target material parameter formulation based on the degree of conformity, specifically includes:
[0159] Determine the degree of conformity of each material parameter formulation to the target steel-concrete composite column, and take the material parameter formulation corresponding to the maximum degree of conformity as the target material parameter formulation.
[0160] In this embodiment, the degree of conformity between multiple material parameter formulations and metamaterial steel-concrete composite columns at different locations is calculated. The degree of conformity obtained for a single metamaterial steel-concrete composite column at a single location is also calculated. Among them, the largest The corresponding material parameter formula is the final material parameter arrangement for the supermaterial steel tube concrete column at this location.
[0161] In addition, the material parameters at different locations in the metamaterial steel tube concrete column array can be visualized.
[0162] The above embodiments accurately obtain the material parameters of metamaterial steel-concrete composite columns at different locations. The obtained material parameter arrangements are then stored in correspondence with the locations of the metamaterial steel-concrete composite columns.
[0163] The material parameters of the metamaterial steel-concrete composite columns at different locations in the array were obtained using SQL queries and then visualized in a table, as shown in Table 1 below:
[0164] Table 1
[0165]
[0166] This invention pre-modifies data in a reference supermaterial steel-concrete composite column based on the influence of different material parameters on the corresponding band gap condition. It then rationally adjusts the data modification compensation based on feedback from changes in the band gap condition under different material parameter data modifications. The band gap condition of different supermaterial steel-concrete composite columns is acquired with a focus on the directionality of seismic vibration. Material parameters for different locations are acquired based on the suitability of the obtained band gap condition under different material parameter combinations with the required location. This results in a more complete match between the band gap of the supermaterial steel-concrete composite column and the seismic frequency range experienced by the target area, thereby significantly enhancing the supermaterial steel-concrete composite column's resistance to dynamic loads such as earthquakes and wind vibrations, including a stronger ability to attenuate seismic signals, and ensuring greater safety for personnel located within the supermaterial steel-concrete composite column structure.
[0167] Example 2:
[0168] This invention also proposes a simulation and optimization device for the design of gap-bounded metamaterial steel-concrete composite columns based on the finite element method. The device can be a computer, a server, or a combination of multiple devices.
[0169] like Figure 7 As shown, Figure 7 This is a schematic diagram of the hardware operating environment of the finite element-based metamaterial steel-concrete composite column bandgap design simulation and optimization equipment involved in the embodiments of the present invention.
[0170] like Figure 7As shown, the finite element method-based metamaterial steel-concrete composite column bandgap design simulation and optimization device may include: a processor 1001, such as a CPU; a network interface 1004; a user interface 1003; a memory 1005; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display or an input unit such as a control panel; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or non-volatile memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001. The memory 1005, as a computer storage medium, may include a bandgap design simulation and optimization program.
[0171] Those skilled in the art will understand that Figure 7 The hardware structure shown does not constitute a limitation on the device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.
[0172] Continue to refer to Figure 7 , Figure 7 The memory 1005, which is a computer-readable storage medium, may include an operating device, a user interface module, a network communication module, and a bandgap design simulation optimization program.
[0173] exist Figure 7 In this embodiment, the network communication module is mainly used to connect to the server and can communicate with the server for data; while the processor 1001 can call the bandgap design simulation optimization program stored in the memory 1005 and execute the steps in the above embodiments.
[0174] Based on the hardware structure of the above-mentioned finite element-based metamaterial steel-concrete composite column bandgap design simulation and optimization device, various embodiments of the finite element-based metamaterial steel-concrete composite column bandgap design simulation and optimization method of the present invention are implemented.
[0175] Furthermore, the present invention also provides a computer-readable storage medium. The computer-readable storage medium stores a bandgap design simulation optimization program, wherein, when executed by a processor, the bandgap design simulation optimization program implements the steps of the above-described finite element-based metamaterial steel-concrete composite column bandgap design simulation optimization method.
[0176] The method implemented when the bandgap design simulation optimization program is executed can be referred to in various embodiments of the present invention’s metamaterial steel tube concrete column bandgap design simulation optimization method based on finite element method, and will not be repeated here.
[0177] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0178] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
[0179] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0180] The above description is only a preferred embodiment of the present invention and does not limit the scope of protection of the present invention. All equivalent structural / method transformations made under the inventive concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the scope of protection of the present invention.
Claims
1. A simulation and optimization method for the design of cross-gap reinforced concrete steel tubular columns based on finite element method, characterized in that, The method includes: By utilizing the amount of bandgap data modification that affects the target bandgap performance data when the target material parameters of the target steel-concrete composite column are modified, the initial material modification amount of the target material parameters and the target bandgap are determined. By using the previous bandgap data modification amount, initial material modification amount, and actual data change amount of the target bandgap performance data in the target bandgap, the target material parameter modification amount for this time is determined; By iteratively modifying the target material, the material parameter formula and the modified current target bandgap are obtained, and the overlapping frequency range between the current target bandgap and the significant energy distribution frequency range in the seismic azimuth is determined. The degree of conformity of the material parameter formulation to the target steel-concrete composite column is determined by using the overlapping frequency range, and the target material parameter formulation is obtained based on the degree of conformity.
2. The simulation and optimization method for band gap design of metamaterial steel-concrete composite columns based on finite element method according to claim 1, characterized in that, The determination of the initial material modification amount of the target material parameters and the target bandgap, based on the bandgap data modification amount affecting the target bandgap performance data when modifying the target material parameters of the target steel-concrete composite column, includes: Determine the maximum value of band gap data modification and the number of band gap performance types in the target band gap performance data when the target material parameters of the target steel tube concrete column are modified. By using the maximum value of bandgap data modification and the number of bandgap behavior types, the degree of reduction in the modification of the target material parameters is calculated; By utilizing the degree of reduction in modification and the maximum value of bandgap data modification, the initial material modification amount and target bandgap of the target material parameters are determined.
3. The simulation and optimization method for band gap design of metamaterial steel-concrete composite columns based on finite element method according to claim 2, characterized in that, The process of determining the initial material modification amount and target bandgap of the target material parameters by utilizing the degree of reduction in modification and the maximum value of bandgap data modification includes: The maximum value among the maximum values of each bandgap data modification is taken as the maximum modification, and the bandgap corresponding to the maximum modification is taken as the target bandgap. The expected change in the target material parameters is obtained by using the maximum modification amount and the maximum value of the bandgap data modification amount; The initial material modification amount of the target material parameters is calculated by using the degree of reduction of the modification and the expected amount of change.
4. The simulation and optimization method for band gap design of metamaterial steel-concrete composite columns based on finite element method according to claim 3, characterized in that, The determination of the target material modification amount for this target material parameter using the previous bandgap data modification amount, the initial material modification amount, and the actual data change amount of the target bandgap performance data in the target bandgap includes: Using the maximum modification amount and the degree of modification reduction corresponding to the previous bandgap data modification amount, the expected modification change amount of the previous target bandgap performance data is calculated; Determine the difference in data change between the actual data change in the target bandgap performance data of the previous test and the expected modification amount; By using the difference between the actual data change and the expected change, the degree of reduction in the modification of the target material parameters relative to the previous target material parameters is determined. Using the degree of reduction in modification and the initial material modification amount, the target material modification amount for this target material parameter is calculated.
5. The simulation and optimization method for band gap design of metamaterial steel-concrete composite columns based on finite element method according to claim 4, characterized in that, The method of determining the degree of reduction in the modification of the target material parameters relative to the previous modification by utilizing the data change difference between the actual data change and the expected modification change includes: Determine the frequency difference between the target bandgap performance data after the previous modification of the target material parameters and the corresponding frequencies of the significant energy distribution frequency range in the seismic events in the target area; By utilizing the frequency difference, the difference in data change between the actual data change and the expected modification change, the degree of reduction in the modification of the target material parameters relative to the previous target material parameters is calculated.
6. The method for simulation and optimization of band gap design of metamaterial steel-concrete composite columns based on finite element method according to claim 1, characterized in that, The process of iteratively modifying the material parameter formulation and the modified current target bandgap using the target material modification amount includes: The target material parameters are modified using the target material modification amount to obtain the modified current target material parameters and the corresponding modified current target bandgap; Determine the frequency differences between the modified current target bandgap performance data and the corresponding frequencies of significant energy distribution frequency intervals in seismic events in the target region; If the frequency differences are all less than the preset frequency, stop iteratively modifying the target material parameters and the target bandgap performance data affected by the modification of the target material parameters.
7. The simulation and optimization method for band gap design of metamaterial steel-concrete composite columns based on finite element method according to claim 1, characterized in that, The determination of the degree of conformity of the material parameter formulation to the target steel-concrete composite column using the coincident frequency range includes: The degree of skewness in satisfying the current target band gap of the target steel-concrete composite column is determined by the number of overlapping frequency intervals and the seismic azimuth angle. The degree of conformity of each material parameter formulation to the target steel-concrete composite column is determined by the degree of eccentricity.
8. The simulation and optimization method for band gap design of metamaterial steel-concrete composite columns based on finite element method according to claim 7, characterized in that, The method of determining the degree of skewness in satisfying the current target band gap by utilizing the number of overlapping frequency intervals and seismic azimuth angles includes: Determine the acute angle between the line connecting the target concrete-filled steel tube column to the central column in the concrete-filled steel tube column array and the horizontal rightward direction. By using the absolute value of the difference between the acute angle and the seismic azimuth angle and the number of overlapping frequency intervals, the degree of skewness of the target steel-concrete composite column in meeting the current target gap is calculated.
9. The simulation and optimization method for band gap design of metamaterial steel-concrete composite columns based on finite element method according to claim 7, characterized in that, The determination of the conformity of each material parameter formulation to the target steel-concrete composite column by satisfying the degree of eccentricity includes: Determine the current target band gap in the target steel-concrete composite column that satisfies the eccentricity greater than the preset eccentricity threshold and record it as the eccentricity-satisfied band gap; Determine the frequency range that satisfies the eccentric bandgap and the material parameter formulation, and determine the width ratio between the overlapping frequency range and the complete frequency range that satisfies the eccentric bandgap. By utilizing the degree of weight distribution, the width ratio, and the number of weight distribution gaps, the degree of conformity of each material parameter formulation to the target steel-concrete composite column is calculated.
10. The simulation and optimization method for band gap design of metamaterial steel-concrete composite columns based on finite element method according to claim 1, characterized in that, The method of obtaining the target material parameter formulation based on the degree of conformity includes: Determine the degree of conformity of each material parameter formulation to the target steel-concrete composite column, and take the material parameter formulation corresponding to the maximum degree of conformity as the target material parameter formulation.