CN113673125A - Design method of connecting piece for assembled anti-collision guardrail - Google Patents

Design method of connecting piece for assembled anti-collision guardrail Download PDF

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CN113673125A
CN113673125A CN202110804140.4A CN202110804140A CN113673125A CN 113673125 A CN113673125 A CN 113673125A CN 202110804140 A CN202110804140 A CN 202110804140A CN 113673125 A CN113673125 A CN 113673125A
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connecting piece
value
optimization
design
formula
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CN113673125B (en
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余晓琳
贾布裕
黄逸锋
陈宇轩
颜全胜
杨铮
余春益
吴毓
谭仲德
茅思奕
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South China University of Technology SCUT
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    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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Abstract

The invention discloses a design method of a connecting piece for an assembled anti-collision guardrail, which comprises the following steps: s1, setting a design domain to be optimized and a target mass fraction of the connecting piece, performing numerical calculation analysis by using finite element software, obtaining state information of each unit of the connecting piece as a material updating basis, wherein the state information comprises strain energy value data, and establishing a strain energy value; s2, redistributing the material of the connecting piece according to the hybrid cellular automata algorithm, realizing deletion and retention of the units, and simultaneously verifying whether the convergence of the quality fraction and the constraint condition is met, thereby completing one iteration; s3, outputting the distribution of the materials meeting the convergence as the optimal topological configuration of the connecting piece; s4, selecting the size parameters of the connecting piece as optimization variables, carrying out experimental design by a uniform design method to obtain representative sample point data, and calculating a response value by a finite element method; the energy absorption value of the connecting piece is improved, so that the buffering performance of the anti-collision guardrail is obviously enhanced.

Description

Design method of connecting piece for assembled anti-collision guardrail
Technical Field
The invention relates to the technical field of design of assembly type building component connecting pieces, in particular to a design method of a connecting piece for an assembly type anti-collision guardrail.
Background
Along with the rapid advance of urban bridge construction, bridge assembled design and construction enter into the high quality development stage, show advantages such as high efficiency, few pollution, and to the bridge safety aspect, it is the most effective measure of guaranteeing bridge up traffic safety to set up anti-collision guardrail. Therefore, the fabricated anti-collision guardrail has better superiority and application prospect compared with the traditional cast-in-situ guardrail construction. Compare with traditional cast-in-place guardrail, assembled guardrail has following advantage: 1. the construction time of more than 3 days for the guardrail cast-in-place can be finished in 1 day, the construction period is greatly shortened, the operation risk of workers is effectively reduced, and the requirement of the construction engineering on safe production is met; 2. the method has the advantages that the method is prefabricated in an industrial manner, has a stable and ordered operation process and complete matched equipment, is small in external interference factor, and obviously improves the engineering quality and the processing precision; 3. a large amount of on-site wet operation is transferred to indoor spaces of factories and the like, so that the influence of noise and dust generated by complex working procedures such as on-site concrete vibration on the surrounding environment and residents is eliminated, and the construction waste is reduced; 4. when the guardrail is damaged due to a collision accident, only the damaged guardrail section needs to be dismantled and replaced by a new section, so that the operation, the maintenance and the repair at the later stage are convenient and quick; 5. the prefabricated anti-collision guardrail embeds complicated and various communication and facilities such as street lamp pipelines, accessory facility embedded parts and electric boxes in the factory prefabrication, and improves construction convenience.
However, the assembled guardrail has the core problem of poor integrity, namely, the assembled concrete crash barrier must be connected with the standard guardrail section and the bridge structure into a whole by using proper and reliable connecting pieces and connecting modes during hoisting and installation, namely, the guardrail system has certain overturn resistance through the connection with the bridge deck plate, the excellent vertical connection can meet the requirement of convenience of assembly type development while meeting the actual use function of the structure, namely, the connecting piece has enough strength to bear the damage of the impact load to the guardrail structure when a collision accident happens, and can realize convenient construction, the design optimization of the assembly type crash barrier connecting piece at present only adopts a test comparison method, therefore, a method with theoretical basis is urgently needed to be provided as a guide for the optimal design of the bridge fabricated crash barrier connecting piece.
Disclosure of Invention
In view of the technical problems in the prior art, the invention aims to provide a design method for a connecting piece of an assembled crash barrier. The energy absorption value of the connecting piece is improved, so that the buffering performance of the anti-collision guardrail is obviously enhanced.
In order to achieve the purpose, the invention adopts the following technical scheme:
1. a method of designing a connector for a fabricated crash barrier comprising the steps of:
s1, setting a design domain to be optimized and a target mass fraction of the connecting piece, and performing numerical calculation analysis by using finite element software to obtain state information of each unit of the connecting piece as a material updating basis, wherein the state information comprises strain energy value data and establishes a strain energy value, and an expression formula of the strain energy value is as follows:
Figure BDA0003165735910000021
this is represented by the formula (1),
wherein U is strain energy, i is a cell unit, UiIs a cellular unitStrain energy density, V, stored in the Meta i due to deformationiIs the volume of a cellular unit i;
s2, redistributing the material of the connecting piece according to a hybrid cellular automata algorithm, realizing deletion and retention of the units, and simultaneously verifying whether the mass fraction of the material and the convergence of the constraint condition are met, thereby completing one iteration;
s3, outputting the material distribution meeting the convergence as the optimal topological configuration of the connecting piece, wherein the expression formula of the optimal topology is as follows:
Figure BDA0003165735910000022
this is represented by the formula (2),
in the formula, eiAs an error signal, U*Is a target value of the local rigidity index,
Figure BDA0003165735910000023
the local rigidity index average value of the cellular unit i is obtained;
Figure BDA0003165735910000024
the lower limit of the relative density of the cell is 10-3，xiAs relative density value, UjIs the strain energy value of the adjacent cell,
Figure BDA0003165735910000031
the number of adjacent cells of the current cellular is;
s4, selecting the size parameters of the connecting piece as optimization variables, carrying out experimental design by a uniform design method to obtain representative sample point data, and calculating a response value by a finite element method;
s5, inputting the sample point data into a Matlab program to perform fitting of a Kriging substitution model, so as to obtain a one-to-one corresponding functional relation between the size parameter and the response value, and determining a proper coordination parameter theta through a genetic algorithm;
s6, taking the specific energy absorption value of the connecting piece as an optimization target, taking the maximum main tensile stress of the connecting piece as a constraint condition, carrying out global optimization based on the established substitution model by adopting a genetic algorithm to obtain a group of optimal size parameters meeting the condition, and selecting the optimal size parameters to complete the design of the connecting piece.
Preferably, in step 2, in the iterative process, the material units at the two ends of the upper part of the design domain are gradually removed, and the bottom and the middle material units of the connecting piece are retained, so that a reasonable inverted-T-shaped structure is obtained.
Preferably, in step S2, after 15 iterations, the topology optimization structure tends to converge, and the optimized area quality of the connection piece is 32% to 36% of the area quality before optimization.
Preferably, in step 4, the connecting piece is embedded with the main beam through a bottom plate of the inverted T-shaped structure, the connecting piece is further embedded with the main beam through a web plate, and the thickness T of the web plate is selected1Length of web1Thickness t of the base plate2Length of the bottom plate2Four design parameters were used as size optimization variables.
Preferably, in step S5, a surrogate model is built by using the Kriging toolbox of Matlab, which includes a regression model and a random function, where the regression model is expressed by the following formula:
Figure BDA0003165735910000032
this is equation (3), and the expression formula of the random function is:
Figure BDA0003165735910000033
Figure BDA0003165735910000034
this is represented by the formula (4) wherein,
Figure BDA0003165735910000035
for the regression model function values, F (β, x) ═ β1f1(x)+β2f2(x)+…+βpfp(x) Beta is a regression coefficient, f (x) is a polynomial function of variable x providing a global approximation of the simulation in design space, z (x) is a uniformNormal distribution N (0, σ) from covariance non-zero2) And provides a simulated local approximation, σ being the covariance in the normal distribution N, R (θ, x)i,xj) For any two sample points xi,xjThe correlation function of (2).
Preferably, in step S6, the specific energy absorption value is maximized as an optimization target, and the maximum main tensile stress of the connection piece is taken as a constraint condition, that is, the expression formula of the whole connection piece parameter optimization is as follows:
Figure BDA0003165735910000041
this is represented by the formula (5),
in the formula, y1(x) Is the SEA value of the connector, y2(x) Is the maximum principal tensile stress of the connecting member, y2(0) Is the maximum main tensile stress limit value of the connecting piece, x is t1,l1,t2,l2]To optimize the variable vector, xlIs the lower limit of x, xuIs the upper limit value of x.
Preferably, in step S6, during the genetic algorithm optimization process, after 161 iterations, the maximum likelihood estimation of θ value is performed
Figure BDA0003165735910000042
The minimum value tends to be stable, and the optimal coordination parameter theta is obtained and used for fitting the Kriging model; after 870 iterations, the maximum specific energy absorption value of the connecting piece tends to be stable, and an optimal set of size variable and response value is obtained.
Preferably, the response value of the optimal size variable is compared with the simulation response value of the finite element analysis calculation optimization solution to verify the fitting precision of the Kriging model, and the error between the fitting result of the Kriging model and the finite element calculation result is less than 5%, which indicates that the optimization result is reliable.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the invention relates to a method for designing a connecting piece of an assembled anti-collision guardrail, which adopts a genetic algorithm to carry out global optimization based on an established substitution model to obtain a group of optimal size parameters meeting conditions, selects the optimal size parameters to complete the design of the connecting piece, improves the energy absorption value of the connecting piece and obviously enhances the buffering performance of the anti-collision guardrail.
2. According to the design method for the connecting piece of the assembled anti-collision guardrail, the vertical deformation of the optimized connecting piece is much smaller than that of the connecting piece before optimization, the material is still in an elastic stage, and the connecting strength is still guaranteed after the impact load generated by automobile collision.
3. The design method of the connecting piece for the assembled anti-collision guardrail takes the maximum main tensile stress of the connecting piece as a constraint condition, the tensile stress of the connecting piece mainly appears at the root part and the back part of the guardrail at an impact position, so that part of concrete cracks and impact load is borne by internal reinforcing steel bars, the optimized inverted T-shaped connecting piece enhances the constraint effect on the root part of the guardrail, the stress distribution of a standard section of the anti-collision guardrail is more uniform, and large-area reinforced concrete participates in bearing the impact load generated by vehicle impact together; the optimization of the connecting piece brings more energy absorption to the guardrail system, and the buffering performance of the anti-collision guardrail is obviously enhanced.
4. According to the design method for the connecting piece of the fabricated anti-collision guardrail, the comparison error between the Kriging model fitting result and the finite element calculation result is within 5%, and the optimization result is reliable, compared with the method before optimization, the steel consumption of the connecting piece of each linear meter of the guardrail is reduced by 26.1%, the SEA value is improved by 36.0%, and the maximum main tensile stress is reduced by 9.4%.
Drawings
FIG. 1 is a flow chart of a method of designing a connector for a fabricated crash barrier of the present invention.
Fig. 2 is a connection section topology optimization mass redistribution diagram of the invention.
Fig. 3 is an iterative process diagram of the cell relative density of a connector for a fabricated crash barrier of the present invention.
Fig. 4 is a schematic diagram of the bottom plate and web of the inverted T structure of the present invention.
FIG. 5 is a diagram of the optimization process of the inverted T-shaped structure genetic algorithm of the present invention.
Fig. 6 is a graph of the vertical dynamic displacement time course of the node of the connecting piece.
FIG. 7 is a graph of the lateral dynamic displacement time course of a joint of a connecting piece.
FIG. 8 is a graph of the primary tensile stress profile of the connection.
The method comprises the following steps of a, b, c, D, e, f, CF-an optimal average penalty value, D, T1, T, 2, TyL, TxL, S, and S, wherein the a is iteration 1, the b is iteration 3, the c is iteration 7, the D is iteration 9, the e is iteration 12, the f is iteration 15, the CF is a penalty value, the CF-is an optimal average penalty value, the D is a genetic algebra, the T1 is before connection part optimization, the T2 is after connection part optimization, the TyL is a vertical dynamic displacement value, the TxL is a dynamic lateral displacement value, and the S is a second.
Detailed Description
The following describes the object of the present invention in further detail with reference to the drawings and specific examples, which are not repeated herein, but the embodiments of the present invention are not limited to the following examples.
As shown in fig. 1, a method of designing a connector for a fabricated crash barrier includes the steps of:
s1, setting a design domain to be optimized and a target mass fraction of the connecting piece, and performing numerical calculation analysis by using finite element software to obtain state information of each unit of the connecting piece as a material updating basis, wherein the state information comprises strain energy value data and establishes a strain energy value, and an expression formula of the strain energy value is as follows:
Figure BDA0003165735910000061
this is represented by the formula (1),
wherein U is strain energy, i is a cell unit, UiThe strain energy density, V, stored in the cell unit i due to deformationiIs the volume of a cellular unit i;
s2, redistributing the material of the connecting piece according to a hybrid cellular automata algorithm, realizing deletion and retention of the units, and simultaneously verifying whether the mass fraction of the material and the convergence of the constraint condition are met, thereby completing one iteration; in an iterative process, efficient bottom and middle material units are preserved.
S3, outputting the material distribution meeting the convergence as the optimal topological configuration of the connecting piece, wherein the expression formula of the optimal topology is as follows:
Figure BDA0003165735910000062
this is represented by the formula (2),
in the formula, eiAs an error signal, U*Is a target value of the local rigidity index,
Figure BDA0003165735910000063
the local rigidity index average value of the cellular unit i is obtained;
Figure BDA0003165735910000064
the lower limit of the relative density of the cell is 10-3，xiAs relative density value, UjIs the strain energy value of the adjacent cell,
Figure BDA0003165735910000065
the number of adjacent cells of the current cellular is;
s4, selecting the size parameters of the connecting piece as optimization variables, carrying out experimental design by a uniform design method to obtain representative sample point data, and calculating a response value by a finite element method; the vertical deformation of the optimized connecting piece is much smaller than that before optimization, the material is still in an elastic stage, and the connecting strength is guaranteed after the impact load generated by automobile impact.
S5, inputting the sample point data into a Matlab program to perform fitting of a Kriging substitution model, so as to obtain a one-to-one corresponding functional relation between the size parameter and the response value, and determining a proper coordination parameter theta through a genetic algorithm;
s6, taking the specific energy absorption value of the connecting piece as an optimization target, taking the maximum main tensile stress of the connecting piece as a constraint condition, carrying out global optimization based on the established substitution model by adopting a genetic algorithm to obtain a group of optimal size parameters meeting the condition, selecting the optimal size parameters, completing the design of the connecting piece, improving the energy absorption value of the connecting piece, and obviously enhancing the buffer performance of the anti-collision guardrail.
In step 2, as shown in fig. 2, in the process of Redistribution of the topology optimization Mass of the connecting piece, the iteration of the X axis is the iteration number, the Mass _ Redistribution of the Y axis is the Mass Redistribution, as shown in fig. 3, by taking the 1 st iteration, the 3 rd iteration, the 7 th iteration, the 9 th iteration, the 12 th iteration and the 15 th iteration as examples, in the iteration process, the material units at the two ends of the upper part of the design domain are gradually eliminated, and the stressed bottom and the middle material unit of the connecting piece are retained, so that a reasonable and efficient inverted T-shaped structure is obtained. The iterative process and the final topological result can be obtained, after 15 iterations, the topological optimization result tends to be convergent, and the quality of the optimized area is 0.35 before optimization. In the iteration process, the material units at the two ends of the upper part of the design domain are gradually eliminated, and meanwhile, efficient bottom and middle material units are reserved.
In step S2, after 15 iterations, the topology optimization structure tends to converge, and the optimized area quality of the connection piece accounts for 32% to 36% of the area quality before optimization, and the optimized area quality of the connection piece accounts for 35% of the area quality before optimization in this embodiment.
As shown in figure 4, the connecting piece is embedded with the main beam through the bottom plate of the inverted T-shaped structure, the connecting piece is also embedded with the main beam through the web plate, and the thickness T of the web plate is selected1Length of web1Thickness t of the base plate2Length of the bottom plate2Four design parameters were used as size optimization variables.
Divide each of the 4 optimization variables into 4 levels (t)1——15mm、20mm、25mm、30mm；l1——100mm、110mm、120mm、130mm；t2——5mm、10mm、15mm、20mm；l2120mm, 130mm, 140mm, 150 mm). The sample points and response values are shown in Table 1, according to the uniform design Table U32(44) 32 sets of uniform design experiments were performed. The specific energy absorption value y of the guardrail connecting piece1Maximum principal tensile stress y2As a response value.
TABLE 1 test sample points and response values
Figure BDA0003165735910000071
Figure BDA0003165735910000081
In step S5, a substitution model is built by using the Kriging toolbox of Matlab, which includes a regression model and a random function, where the expression formula of the regression model is:
Figure BDA0003165735910000082
this is equation (3), and the expression formula of the random function is:
Figure BDA0003165735910000083
Figure BDA0003165735910000084
this is represented by the formula (4) wherein,
Figure BDA0003165735910000085
for the regression model function values, F (β, x) ═ β1f1(x)+β2f2(x)+…+βpfp(x) β is a regression coefficient, f (x) is a polynomial function of the variable x providing a global approximation of the simulation in the design space, z (x) is a normal distribution N (0, σ) subject to a covariance non-zero2) And provides a simulated local approximation, σ being the covariance in the normal distribution N, R (θ, x)i,xj) For any two sample points xi,xjThe correlation function of (2).
In step S6, the specific energy absorption value maximization is taken as an optimization target, and the maximum main tensile stress of the connecting member is taken as a constraint condition, that is, the expression formula of the whole connecting member parameter optimization is as follows:
Figure BDA0003165735910000091
this is represented by the formula (5),
in the formula, y1(x) Is the SEA value of the connector, y2(x) Is the most connected with a connecting pieceLarge principal tensile stress, y2(0) The maximum main tensile stress limit of the connecting piece is Q345c material, the yield strength is 345MPa, and x is t1,l1,t2,l2]To optimize the variable vector, xlIs the lower limit of x, xuIs the upper limit value of x.
As shown in fig. 5, in step S6, in the genetic algorithm optimization process, referring to the relationship among the penalty value, the optimal average penalty value, and the genetic algebra, after iteration of 161 generations, the maximum likelihood estimation of the θ value is performed
Figure BDA0003165735910000092
The minimum value tends to be stable, and the optimal coordination parameter theta is obtained and used for fitting the Kriging model; after 870 iterations, the maximum specific energy absorption value of the connecting piece tends to be stable, and an optimal set of size variable and response value is obtained.
And comparing the optimal group of size variables and response values with simulation response values of finite element analysis calculation optimization solutions to verify the fitting precision of the Kriging model, wherein specific values before and after optimization are shown in Table 2, the error between the fitting result of the Kriging model and the finite element calculation result is less than 5%, which indicates that the optimization result is reliable, and compared with the prior optimization, the steel consumption of the connecting piece of each linear meter of the guardrail is reduced by 26.1%, the SEA value is improved by 36.0%, and the maximum main tensile stress is reduced by 9.4%.
TABLE 2 comparative analysis of the optimization results
Figure BDA0003165735910000093
As shown in fig. 6, the Y-axis of the connecting member is a dynamic vertical displacement value, the X-axis time second is used as a unit, the connecting member generates vertical deformation at the moment of two collisions, and there is unrecoverable residual deformation after the collision is completed before the optimization of the connecting member, which indicates that the material of the connecting member is damaged and enters a plastic stage, the vertical dynamic displacement value after the optimization of the connecting member is much smaller than that before the optimization, the material is still in an elastic stage, and the connecting strength is still guaranteed after the impact load generated by the automobile collision.
As shown in fig. 7, the dynamic lateral displacement value of the connecting piece in the Y axis has two peak values, which are respectively generated at the moment of the first collision and the tail collision in the time second of the X axis, and residual displacement exists after the collision is completed; the guardrail structure after the connecting piece is optimized is in whole collision process, and the horizontal dynamic displacement value is showing to be reduced before optimizing, and the optimization of connecting piece makes the guardrail system possess bigger bulk stiffness promptly to effectively avoid the danger that anticollision barrier prefabricated section and decking break away from.
As shown in fig. 8, the tensile stress of the connecting member mainly appears at the guardrail root and the back of the impact position, so that part of concrete cracks and the impact load is borne by the internal steel bars, and the optimized inverted T-shaped connecting member structure is firmly embedded with the bridge deck before the connecting member is optimized compared with the optimized connecting member structure, so that the restraint effect on the guardrail root is enhanced, the stress distribution of the standard section of the anti-collision guardrail is uniform, and large-area reinforced concrete participates in bearing the impact load generated by vehicle impact together; on the other hand, the optimization of the connecting piece brings more energy absorption to the guardrail system, and the buffer performance of the anti-collision guardrail is obviously enhanced.
The above-mentioned embodiments are preferred embodiments of the present invention, and the present invention is not limited thereto, and any other modifications or equivalent substitutions that do not depart from the technical spirit of the present invention are included in the scope of the present invention.

Claims (8)

1. A design method for a connecting piece of an assembled anti-collision guardrail is characterized by comprising the following steps:
s1, setting a design domain to be optimized and a target mass fraction of the connecting piece, and performing numerical calculation analysis by using finite element software to obtain state information of each unit of the connecting piece as a material updating basis, wherein the state information comprises strain energy value data and establishes a strain energy value, and an expression formula of the strain energy value is as follows:
Figure FDA0003165735900000011
this is represented by the formula (1),
wherein U is strain energy, i is a cell unit, UiThe strain energy density, V, stored in the cell unit i due to deformationiIs the volume of a cellular unit i;
s2, redistributing the material of the connecting piece according to a hybrid cellular automata algorithm, realizing deletion and retention of the units, and simultaneously verifying whether the mass fraction of the material and the convergence of the constraint condition are met, thereby completing one iteration;
s3, outputting the material distribution meeting the convergence as the optimal topological configuration of the connecting piece, wherein the expression formula of the optimal topology is as follows:
Figure FDA0003165735900000012
this is represented by the formula (2),
in the formula, eiAs an error signal, U*Is a target value of the local rigidity index,
Figure FDA0003165735900000013
the local rigidity index average value of the cellular unit i is obtained;
Figure FDA0003165735900000014
the lower limit of the relative density of the cell is 10-3，xiAs relative density value, UjIs the strain energy value of the adjacent cell,
Figure FDA0003165735900000015
the number of adjacent cells of the current cellular is;
s4, selecting the size parameters of the connecting piece as optimization variables, carrying out experimental design by a uniform design method to obtain representative sample point data, and calculating a response value by a finite element method;
s5, inputting the sample point data into a Matlab program to perform fitting of a Kriging substitution model, so as to obtain a one-to-one corresponding functional relation between the size parameter and the response value, and determining a proper coordination parameter theta through a genetic algorithm;
s6, taking the specific energy absorption value of the connecting piece as an optimization target, taking the maximum main tensile stress of the connecting piece as a constraint condition, carrying out global optimization based on the established substitution model by adopting a genetic algorithm to obtain a group of optimal size parameters meeting the condition, and selecting the optimal size parameters to complete the design of the connecting piece.
2. A method of designing a connector for a fabricated crash barrier according to claim 1, wherein: in the step 2, in the iteration process, the material units at the two ends of the upper part of the design domain are gradually eliminated, and meanwhile, the bottom and the middle material units of the connecting piece are reserved to obtain a reasonable inverted T-shaped structure.
3. A method of designing a connector for a fabricated crash barrier according to claim 2, wherein: in step S2, after 15 iterations, the topology optimization structure tends to converge, and the optimized area quality of the connection piece is 32% to 36% of the area quality before optimization.
4. A method of designing a connector for a fabricated crash barrier according to claim 1, wherein: in step 4, the connecting piece is embedded with the main beam through the bottom plate of the inverted T-shaped structure, the connecting piece is also embedded with the main beam through the web plate, and the thickness T of the web plate is selected1Length of web1Thickness t of the base plate2Length of the bottom plate2Four design parameters were used as size optimization variables.
5. A method of designing a connector for a fabricated crash barrier according to claim 1, wherein: in step S5, a substitution model is built by using the Kriging toolbox of Matlab, which includes a regression model and a random function, where the expression formula of the regression model is:
Figure FDA0003165735900000021
this is equation (3), and the expression formula of the random function is:
Figure FDA0003165735900000022
Figure FDA0003165735900000023
this is represented by the formula (4) wherein,
Figure FDA0003165735900000024
for the regression model function values, F (β, x) ═ β1f1(x)+β2f2(x)+…+βpfp(x) β is a regression coefficient, f (x) is a polynomial function of the variable x providing a global approximation of the simulation in the design space, z (x) is a normal distribution N (0, σ) subject to a covariance non-zero2) And provides a simulated local approximation, σ being the covariance in the normal distribution N, R (θ, x)i,xj) For any two sample points xi,xjThe correlation function of (2).
6. A method of designing a connector for a fabricated crash barrier according to claim 1, wherein: in step S6, the specific energy absorption value maximization is taken as an optimization target, and the maximum main tensile stress of the connecting member is taken as a constraint condition, that is, the expression formula of the whole connecting member parameter optimization is as follows:
Figure FDA0003165735900000031
this is represented by the formula (5),
in the formula, y1(x) Is the SEA value of the connector, y2(x) Is the maximum principal tensile stress of the connecting member, y2(0) Is the maximum main tensile stress limit value of the connecting piece, x is t1,l1,t2,l2]To optimize the variable vector, xlIs the lower limit of x, xuIs the upper limit value of x.
7. The design method of a connector for a fabricated crash barrier according to claim 1,the method is characterized in that: in step S6, during the genetic algorithm optimization process, after 161 iterations, the maximum likelihood estimation of θ value
Figure FDA0003165735900000032
The minimum value tends to be stable, and the optimal coordination parameter theta is obtained and used for fitting the Kriging model; after 870 iterations, the maximum specific energy absorption value of the connecting piece tends to be stable, and an optimal set of size variable and response value is obtained.
8. A method of designing a connector for a fabricated crash barrier according to claim 7, wherein: and comparing the response value of the optimal size variable with the simulation response value of the finite element analysis calculation optimization solution to verify the fitting precision of the Kriging model, wherein the error between the fitting result of the Kriging model and the finite element calculation result is less than 5%, and the optimization result is reliable.
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