CN113673125B - Design method of connecting piece for assembled anti-collision guardrail - Google Patents
Design method of connecting piece for assembled anti-collision guardrail Download PDFInfo
- Publication number
- CN113673125B CN113673125B CN202110804140.4A CN202110804140A CN113673125B CN 113673125 B CN113673125 B CN 113673125B CN 202110804140 A CN202110804140 A CN 202110804140A CN 113673125 B CN113673125 B CN 113673125B
- Authority
- CN
- China
- Prior art keywords
- connecting piece
- value
- optimization
- design
- optimal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- 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
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Refuge Islands, Traffic Blockers, Or Guard Fence (AREA)
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 of a connecting piece and a target mass fraction, and performing numerical calculation and 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 a strain energy value is established; s2, redistributing materials of the connecting piece according to a mixed cellular automaton algorithm, deleting and reserving units, and verifying whether convergence of quality scores and constraint conditions is met or not at the same time, so that one iteration is completed; s3, material distribution output meeting convergence is used as an optimal topological configuration of the connecting piece; s4, selecting the dimension parameters of the connecting piece as optimization variables, performing test design through a uniform design method to obtain representative sample point data, and calculating a response value through a finite element method; the energy absorption value of the connecting piece is improved, so that the buffer performance of the anti-collision guardrail is obviously enhanced.
Description
Technical Field
The invention relates to the technical field of design of connecting pieces of assembled building components, in particular to a method for designing connecting pieces of assembled anti-collision guardrails.
Background
Along with the rapid promotion of urban bridge construction, the bridge assembly type design and construction enter a high-quality development stage, and the advantages of high efficiency, little pollution and the like are shown, and in the aspect of bridge safety, the arrangement of the anti-collision guardrail is the most effective measure for ensuring the driving safety on the bridge. Therefore, the assembled anti-collision guardrail has better superiority and application prospect compared with the traditional cast-in-situ guardrail construction. Compared with the traditional cast-in-situ guardrail, the assembled guardrail has the following advantages: 1. the construction time of the guardrail in-situ casting exceeds 3 days, the prefabrication construction can be completed within 1 day, the construction period is greatly shortened, the risk of workers is effectively reduced, and the requirement of safety production of constructional engineering is met; 2. the method has the advantages of factory prefabrication, relatively stable and orderly operation flow and perfect matched equipment, small external interference factors, and remarkable improvement of engineering quality and machining precision; 3. a large amount of site wet operation is transferred to indoor spaces such as factories and the like, so that the influence of noise and dust generated by complex working procedure construction such as site concrete vibration and the like on the surrounding environment and residents is eliminated, and the construction waste is reduced; 4. when the guardrail is damaged due to collision accidents, only the damaged guardrail section is removed and replaced with a new section, and the later operation, maintenance and repair are convenient and quick; 5. the prefabricated anti-collision guardrail is used for embedding complex and numerous communication and street lamp pipelines, auxiliary facility embedded parts, electric boxes and other facilities in the prefabricated anti-collision guardrail during factory prefabrication, so that the construction convenience is improved.
However, the fabricated guardrail has the core problem that the fabricated concrete anti-collision guardrail has poor integrity, namely, the fabricated concrete anti-collision guardrail is required to be connected with the standard section of the guardrail 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 anti-overturning property through the connection with the bridge deck, and the superior vertical connection can meet the convenience requirement of fabricated development while meeting the actual use function of the structure, namely, the connecting pieces have enough strength to bear the damage of impact load to the guardrail structure and can realize convenience construction when collision accidents happen, and the design optimization of the fabricated anti-collision guardrail connecting pieces at present is generally only a test comparison method, so that a theoretical basis method is urgently required to be provided as the guidance of the optimized design of the fabricated anti-collision guardrail connecting pieces of the bridge.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention aims to provide a design method of a connecting piece for an assembled anti-collision guardrail. The energy absorption value of the connecting piece is improved, so that the buffer performance of the anti-collision guardrail is obviously enhanced.
In order to achieve the above purpose, the invention adopts the following technical scheme:
1. a method of designing a connector for an assembled crash barrier, comprising the steps of:
s1, setting a design domain to be optimized and a target mass fraction of a connecting piece, and performing numerical calculation and 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 a strain energy value is established, and the expression formula of the strain energy value is as follows:this is represented by formula (1),
wherein U is strain energy, i is a cellular unit, U i For strain energy density, V, stored in the cell unit i due to deformation i The volume of the cell unit i;
s2, redistributing materials of the connecting piece according to a mixed cellular automaton algorithm, deleting and reserving units, and verifying whether the quality fraction of the materials and the convergence of constraint conditions are met or not at the same time, so that one iteration is completed;
s3, outputting material distribution meeting convergence, and taking the material distribution as an optimal topological configuration of the connecting piece, wherein an expression formula of the optimal topology is as follows:
this is represented by formula (2),
in the formula e i As error signal, U * Is a target value of the local rigidity index,the local rigidity index average value of the cell unit i; />Taking 10 as the lower limit value of the relative density of the unit -3 ，x i As relative density value, U j Is the strain energy value of the neighbor cells, +.>The number of neighbor cells is the number of the current cell;
s4, selecting the size parameter of the connecting piece as an optimization variable, performing test design through a uniform design method to obtain representative sample point data, and calculating a response value through a finite element method;
s5, inputting sample point data into a Matlab program to perform fitting of a Kriging substitution model, so that a one-to-one corresponding function relation between the size parameters and the response values is obtained, 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, adopting a genetic algorithm to carry out global optimization based on the established substitution model, obtaining a group of optimal size parameters meeting the condition, selecting the optimal size parameters, and completing the design of the connecting piece.
Preferably, in step 2, in the iterative process, the material units at both ends of the upper part of the design domain are gradually removed, while the material units at the bottom and the middle part of the connecting piece are reserved, 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 mass of the optimized region of the connecting piece accounts for 32% -36% of the mass of the region before optimization.
Preferably, in step 4, the connecting piece is engaged with the main beam through the bottom plate of the inverted T-shaped structure, the connecting piece is engaged with the main beam through the web plate, and the web plate thickness T is selected 1 Web length l 1 Thickness t of bottom plate 2 Length of bottom plate l 2 Four design parameters were used as dimensional optimization variables.
Preferably, in step S5, a surrogate model is built by using the Kriging toolbox of Matlab, and the surrogate model includes two parts, namely a regression model and a random function, and the expression formula of the regression model is as follows:this is equation (3), and the expression of the random function is:
this is represented by the formula (4), wherein,for regression model function values, F (β, x) =β 1 f 1 (x)+β 2 f 2 (x)+…+β p f p (x) Beta is a regression coefficient, f (x) is a polynomial function of the variable x, providing a global approximation of the simulation in design space, z (x) is a normal distribution N (0, sigma) subject to covariance non-zero 2 ) And provides a local approximation of the simulation, σ being the covariance in the normal distribution N, R (θ, x i ,x j ) For any two sample points x i ,x j Is a function of the correlation function of (a).
Preferably, in step S6, the maximum principal tensile stress of the connecting piece is used as a constraint condition with the maximization of the specific energy absorption value as an optimization target, that is, the expression formula of the parameter optimization of the whole connecting piece is as follows:this is represented by formula (5),
wherein y is 1 (x) For the connector SEA value, y 2 (x) For maximum principal tensile stress of the connecting piece, y 2 (0) For the maximum main tensile stress limit of the connecting piece, x= [ t ] 1 ,l 1 ,t 2 ,l 2 ]To optimize the variable vector, x l Is x lower limitValue, x u The upper limit of x.
Preferably, in step S6, in the genetic algorithm optimizing process, after 161 iterations, the maximum likelihood estimation of the θ valueThe minimum value tends to be stable, and the optimal coordination parameter theta is obtained and used for Kriging model fitting; after 870 generations of iteration, the maximum value of the specific energy absorption of the connecting piece tends to be stable, and an optimal set of size variables and response values are 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:
1. according to the design method of the connecting piece for the fabricated anti-collision guardrail, the genetic algorithm is adopted to conduct global optimization based on the established substitution model, a group of optimal size parameters meeting the conditions are obtained, the optimal size parameters are selected, the design of the connecting piece is completed, the energy absorption value of the connecting piece is improved, and the buffering performance of the anti-collision guardrail is remarkably enhanced.
2. According to the design method of the connecting piece for the assembled anti-collision guardrail, the vertical deformation of the connecting piece after optimization is much smaller than that before optimization, the material is still in an elastic stage, and the connecting strength is ensured after the impact load generated by the automobile collision acts.
3. According to the design method of the connecting piece for the assembled anti-collision guardrail, the maximum main tensile stress of the connecting piece is used as a constraint condition, and the tensile stress of the connecting piece mainly occurs at the root and the back of the guardrail at the collision position, so that part of concrete cracks and is borne by impact load through internal reinforcing steel bars, the constraint effect on the root of the guardrail is enhanced by the optimized inverted T-shaped connecting piece, 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 collision; 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 of the connecting piece for the fabricated anti-collision guardrail, the comparison error of the Kriging model fitting result and the finite element calculation result is within 5%, so that the optimization result is reliable, compared with the prior optimization, the steel consumption of the connecting piece per linear meter of the guardrail is reduced by 26.1%, the SEA value is improved by 36.0%, and the maximum principal 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 topologically optimized mass-weight distribution diagram of a connector section of the present invention.
Fig. 3 is a unit relative density iteration process diagram of a connector for a fabricated crash barrier of the invention.
Fig. 4 is an optimized schematic of the bottom plate and web of the inverted T-shaped structure of the present invention.
FIG. 5 is a diagram of the process of optimizing the inverted T-shaped structure genetic algorithm of the present invention.
Fig. 6 is a graph of node vertical dynamic displacement time course of a connector.
FIG. 7 is a graph of node lateral dynamic displacement time course for a connector.
Fig. 8 is a principal tensile stress distribution diagram of a connection.
Wherein a is the 1 st iteration, b is the 3 rd iteration, c is the 7 th iteration, D is the 9 th iteration, e is the 12 th iteration, f is the 15 th iteration, CF is the penalty value, CF-is the best average penalty value, D is the genetic algebra, T1 is the connecting piece before optimization, T2 is the connecting piece after optimization, tyL is the vertical dynamic displacement value, txL is the dynamic lateral displacement value, and S is seconds.
Detailed Description
The present invention will be described in further detail with reference to the drawings and specific examples, which are not to be construed as limiting the embodiments of the present invention.
As shown in fig. 1, a design method of a connection piece for a fabricated crash barrier includes the following steps:
s1, setting a design domain to be optimized and a target mass fraction of a connecting piece, and performing numerical calculation and 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 a strain energy value is established, and the expression formula of the strain energy value is as follows:this is represented by formula (1),
wherein U is strain energy, i is a cellular unit, U i For strain energy density, V, stored in the cell unit i due to deformation i The volume of the cell unit i;
s2, redistributing materials of the connecting piece according to a mixed cellular automaton algorithm, deleting and reserving units, and verifying whether the quality fraction of the materials and the convergence of constraint conditions are met or not at the same time, so that one iteration is completed; in the iterative process, efficient bottom and middle material units are preserved.
S3, outputting material distribution meeting convergence, and taking the material distribution as an optimal topological configuration of the connecting piece, wherein an expression formula of the optimal topology is as follows:
this is represented by formula (2),
in the formula e i As error signal, U * Is a target value of the local rigidity index,the local rigidity index average value of the cell unit i; />Taking 10 as the lower limit value of the relative density of the unit -3 ，x i As relative density value, U j Is the strain energy value of the neighbor cells, +.>The number of neighbor cells is the number of the current cell;
s4, selecting the size parameter of the connecting piece as an optimization variable, performing test design through a uniform design method to obtain representative sample point data, and calculating a response value through 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 piece still has the guarantee of the connecting strength after the impact load generated by the automobile impact acts.
S5, inputting sample point data into a Matlab program to perform fitting of a Kriging substitution model, so that a one-to-one corresponding function relation between the size parameters and the response values is obtained, 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, adopting a genetic algorithm to carry out global optimization based on the established substitution model, obtaining 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 buffering performance of the anti-collision guardrail.
In step 2, as shown in fig. 2, in the process of topological optimization of quality Redistribution of the connecting piece, the iteration time is the operation of the X axis, the mass_redistribution of the Y axis is the quality Redistribution, and as shown in fig. 3, 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 two ends of the upper part of the design domain are gradually removed, and meanwhile, the stressed bottom and middle material units of the connecting piece are reserved, so that a reasonable and efficient inverted T-shaped structure is obtained. The iteration process and the final topology result can be obtained, the topology optimization result tends to be converged after 15 iterations, and the quality of the optimized area is 0.35 before optimization. In the iterative process, the material units at the two ends of the upper part of the design domain are gradually removed, and meanwhile, the 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 mass of the connecting piece accounts for 32% -36% of the area mass before optimization, and in this embodiment, the optimized area mass of the connecting piece accounts for 35% of the area mass before optimization.
As shown in fig. 4, the connecting piece is mutually 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 web plate thickness T is selected 1 Web length l 1 Thickness t of bottom plate 2 Length of bottom plate l 2 Four design parameters were used as dimensional optimization variables.
Each 4 optimization variables was divided into 4 levels (t 1 ——15mm、20mm、25mm、30mm；l 1 ——100mm、110mm、120mm、130mm；t 2 ——5mm、10mm、15mm、20mm；l 2 120mm, 130mm, 140mm, 150 mm). Sample points and response values are shown in Table 1, according to the uniform design table U 32 (4 4 ) 32 sets of uniform design tests were performed. The guardrail connecting piece is compared with the energy absorption value y 1 Maximum principal tensile stress y 2 As a response value.
TABLE 1 test sample points and response values
In step S5, a Kriging toolbox of Matlab is utilized to build a substitution model, wherein the substitution model comprises a regression model and a random function, and the expression formula of the regression model is as follows:this is equation (3), and the expression of the random function is:
this is represented by the formula (4), wherein,for regression model function values, F (β, x) =β 1 f 1 (x)+β 2 f 2 (x)+…+β p f p (x) Beta is a regression coefficient, f (x) is a polynomial function of the variable x, providing a global approximation of the simulation in design space, z (x) is a normal distribution N (0, sigma) subject to covariance non-zero 2 ) And provides a local approximation of the simulation, σ being the covariance in the normal distribution N, R (θ, x i ,x j ) For any two sample points x i ,x j Is a function of the correlation function of (a).
In step S6, the maximum principal tensile stress of the connecting piece is used as a constraint condition by taking the maximization of the specific energy absorption value as an optimization target, that is, the expression formula of the parameter optimization of the whole connecting piece is as follows:
this is represented by formula (5),
wherein y is 1 (x) For the connector SEA value, y 2 (x) For maximum principal tensile stress of the connecting piece, y 2 (0) For the maximum main tensile stress limit of the connecting piece, the maximum main tensile stress limit is Q345c material, the yield strength is 345MPa, and x= [ t ] 1 ,l 1 ,t 2 ,l 2 ]To optimize the variable vector, x l For x lower limit value, x u The upper limit of x.
As shown in fig. 5, in step S6, in the genetic algorithm optimizing process, the relation among the penalty value, the optimal average penalty value and the genetic algebra is referred to, and after 161 iterations, the maximum likelihood estimation of the θ value is performedThe minimum value tends to be stable, and the optimal coordination parameter theta is obtained and used for Kriging model fitting; after 870 generations of iteration, the maximum value of the specific energy absorption of the connecting piece tends to be stable, and an optimal set of size variables and response values are obtained.
The optimal set of size variables and response values are compared with simulation response values of an optimization solution calculated by finite element analysis to verify the fitting precision of the Kriging model, specific numerical values before and after optimization are shown in table 2, the error between the fitting result of the Kriging model and the calculation result of the finite element is smaller than 5%, the reliability of the optimization result is shown, compared with the prior optimization, the consumption of steel of the connecting piece of the guardrail per linear meter is reduced by 26.1%, the SEA value is improved by 36.0%, and the maximum principal tensile stress is reduced by 9.4%.
Table 2 comparison analysis of optimized results
As shown in fig. 6, the dynamic vertical displacement value of the connecting piece on the Y axis is a dynamic vertical displacement value, the time second of the X axis is used as a unit, the connecting piece generates vertical deformation at the moment of two collisions, unrecoverable residual deformation exists after the collision is completed before the optimization of the connecting piece, which indicates that the material of the connecting piece is damaged and enters a plastic stage, the vertical dynamic displacement value of the connecting piece after the optimization is much smaller than that before the optimization, the material is still in an elastic stage, and the connecting strength guarantee is still provided after the impact load generated by the automobile collision.
From FIG. 7, two peaks appear in the dynamic lateral displacement value of the connecting piece in the Y axis, which respectively occur at the moment of the initial collision and the moment of 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 has the obvious reduction before the transverse dynamic displacement value is optimized in the whole collision process, namely, the guardrail system has larger overall rigidity due to the optimization of the connecting piece, so that the danger that the anti-collision guardrail precast block is separated from the bridge deck is effectively avoided.
As shown in fig. 8, the tensile stress of the connecting piece mainly occurs at the root and the back of the guardrail at the impact position, so that part of concrete cracks and is borne by impact load by the internal reinforcing steel bars, the optimized inverted-T-shaped connecting piece structure is firmly embedded with the bridge deck plate before the connecting piece is optimized compared with the optimized connecting piece, the constraint effect on the root of the guardrail is enhanced, the stress distribution of the 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; on the other hand, 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.
The above embodiments are preferred examples of the present invention, and the present invention is not limited thereto, and any other modifications or equivalent substitutions made without departing from the technical aspects of the present invention are included in the scope of the present invention.
Claims (6)
1. A method of designing a connector for an assembled crash barrier, comprising the steps of:
s1, setting a design domain to be optimized and a target mass fraction of a connecting piece, and performing numerical calculation and 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 a strain energy value is established, and the expression formula of the strain energy value is as follows:this is represented by formula (1),
wherein U is strain energy, i is a cellular unit, U i For strain energy density, V, stored in the cell unit i due to deformation i The volume of the cell unit i;
s2, redistributing materials of the connecting piece according to a mixed cellular automaton algorithm, deleting and reserving units, and verifying whether the quality fraction of the materials and the convergence of constraint conditions are met or not at the same time, so that one iteration is completed; in the iterative process, the material units at the two ends of the upper part of the design domain are gradually removed, and meanwhile, the material units at the bottom and the middle part of the connecting piece are reserved, so that a reasonable inverted T-shaped structure is obtained;
s3, outputting material distribution meeting convergence, and taking the material distribution as an optimal topological configuration of the connecting piece, wherein an expression formula of the optimal topology is as follows:
this is represented by formula (2),
in the formula e i As error signal, U * Is a target value of the local rigidity index,the local rigidity index average value of the cell unit i; />Taking 10 as the lower limit value of the relative density of the unit -3 ，x i As relative density value, U j Is the strain energy value of the neighbor cells, +.>The number of neighbor cells is the number of the current cell;
s4, selecting the size parameter of the connecting piece as an optimization variable, performing test design through a uniform design method to obtain representative sample point data, and calculating a response value through a finite element method; the connecting piece is mutually embedded with the main beam through a bottom plate of the inverted T-shaped structure, the connecting piece is also embedded with the main beam through a web plate, and the thickness T of the web plate is selected 1 Web length l 1 Thickness t of bottom plate 2 Length of bottom plate l 2 Four design parameters are used as size optimization variables;
s5, inputting sample point data into a Matlab program to perform fitting of a Kriging substitution model, so that a one-to-one corresponding function relation between the size parameters and the response values is obtained, 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, adopting a genetic algorithm to carry out global optimization based on the established substitution model, obtaining a group of optimal size parameters meeting the condition, selecting the optimal size parameters, and completing 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 S2, after 15 iterations, the topological optimization structure tends to converge, and the optimized area mass of the connecting piece accounts for 32% -36% of the area mass before optimization.
3. A method of designing a connector for a fabricated crash barrier according to claim 1, wherein: in step S5, a Kriging toolbox of Matlab is utilized to build a substitution model, wherein the substitution model comprises a regression model and a random function, and the expression formula of the regression model is as follows:this is equation (3), and the expression of the random function is:
this is the formula (4), in the formulas (3), (4),for regression model function values, F (β, x) =β 1 f 1 (x)+β 2 f 2 (x)+…+β p f p (x) Beta is a regression coefficient, f (x) is a polynomial function of the variable x, providing a global approximation of the simulation in design space, z (x) is a normal distribution N (0, sigma) subject to covariance non-zero 2 ) And provides a local approximation of the simulation, σ being the covariance in the normal distribution N, R (θ, x i ,x j ) For any two sample points x i ,x j Is a function of the correlation function of (a).
4. A method of designing a connector for a fabricated crash barrier according to claim 1, wherein: in step S6, the specific energy absorption value is maximized as the bestAnd (3) taking the maximum main tensile stress of the connecting piece as a constraint condition, namely, an expression formula for optimizing the parameters of the whole connecting piece is as follows:
wherein y is 1 (x) For the connector SEA value, y 2 (x) For maximum principal tensile stress of the connecting piece, y 2 (0) For the maximum main tensile stress limit of the connecting piece, x= [ t ] 1 ,l 1 ,t 2 ,l 2 ]To optimize the variable vector, x l For x lower limit value, x u The upper limit of x.
5. A method of designing a connector for a fabricated crash barrier according to claim 1, wherein: in step S6, in the genetic algorithm optimizing process, after 161 generations of iteration, the maximum likelihood estimation of the θ valueThe minimum value tends to be stable, and the optimal coordination parameter theta is obtained and used for Kriging model fitting; after 870 generations of iteration, the maximum value of the specific energy absorption of the connecting piece tends to be stable, and an optimal set of size variables and response values are obtained.
6. The method of designing a connector for a fabricated crash barrier of claim 5, 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%, which indicates that the optimization result is reliable.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110804140.4A CN113673125B (en) | 2021-07-16 | 2021-07-16 | Design method of connecting piece for assembled anti-collision guardrail |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110804140.4A CN113673125B (en) | 2021-07-16 | 2021-07-16 | Design method of connecting piece for assembled anti-collision guardrail |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113673125A CN113673125A (en) | 2021-11-19 |
| CN113673125B true CN113673125B (en) | 2023-08-22 |
Family
ID=78539373
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110804140.4A Active CN113673125B (en) | 2021-07-16 | 2021-07-16 | Design method of connecting piece for assembled anti-collision guardrail |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113673125B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117162263B (en) * | 2023-11-02 | 2023-12-29 | 江苏菲尔浦工程科技有限公司 | Method and system for optimizing concrete production process |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020215533A1 (en) * | 2019-04-26 | 2020-10-29 | 大连理工大学 | Structural topology optimization method based on material-field reduction series expansion |
| WO2020224634A1 (en) * | 2019-05-09 | 2020-11-12 | 江苏大学 | Subregion hybrid cellular automata method for solving vehicle body thickness optimization |
| CN112100774A (en) * | 2020-09-16 | 2020-12-18 | 哈尔滨理工大学 | Variable density method-based stress and strain energy double-constraint topology optimization method |
-
2021
- 2021-07-16 CN CN202110804140.4A patent/CN113673125B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020215533A1 (en) * | 2019-04-26 | 2020-10-29 | 大连理工大学 | Structural topology optimization method based on material-field reduction series expansion |
| WO2020224634A1 (en) * | 2019-05-09 | 2020-11-12 | 江苏大学 | Subregion hybrid cellular automata method for solving vehicle body thickness optimization |
| CN112100774A (en) * | 2020-09-16 | 2020-12-18 | 哈尔滨理工大学 | Variable density method-based stress and strain energy double-constraint topology optimization method |
Non-Patent Citations (1)
| Title |
|---|
| 汽车车身耐撞框架结构设计研究;谭纯;陈涛;杨枫;;现代制造工程(第02期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113673125A (en) | 2021-11-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106126849B (en) | Nonlinear topological optimization method for vehicle body welding spot arrangement | |
| CN103034766B (en) | A kind of laying angular direction of definite Test of Laminate Composites and the method for thickness | |
| CN113673125B (en) | Design method of connecting piece for assembled anti-collision guardrail | |
| KR101507082B1 (en) | Optimal seismic retrofit method and system for the existing buildings using the braces | |
| CN106257541A (en) | A kind of modification method of bridge finite element model | |
| CN106844965A (en) | A kind of method that continuous bridge practical stiffness is recognized based on static test | |
| CN106202841A (en) | A kind of Optimization Design of bed piece supported at three point position | |
| CN111046494B (en) | Simplified vehicle body floor design method based on multi-component structural form | |
| CN111950075A (en) | Multidisciplinary multi-constraint sequential optimization method for hypersonic aircraft structure | |
| CN116720258A (en) | Battery pack bottom scraping safety-oriented aluminum alloy protection structure section-arrangement design method | |
| Kaveh et al. | Optimum design of castellated beams: Effects of composite action and semi-rigid connections | |
| CN106021802A (en) | Finite element calculation method for strength of embedded-beam-containing honeycomb sandwich structure | |
| CN115906572A (en) | Topological optimization design method of concrete filled steel tube sleeper structure based on APDL | |
| Zindani et al. | A decision-making approach for material selection of polymeric composite bumper beam | |
| Zhao et al. | Finite element model updating of bridge structures based on improved response surface methods | |
| Chalouhi et al. | Topological and size optimization of RC beam bridges: an automated design approach for cost effective and environmental friendly solutions | |
| Gao et al. | Kriging surrogate model based optimisation of welded bogie frame for fatigue improvement | |
| Dackman et al. | Steel sandwich decks in medium span bridges | |
| CN107463734B (en) | Method and device for calculating train body mode of motor train unit | |
| Mai et al. | Density-Based Optimization for Strut-Tie Modeling | |
| Khouri Chalouhi | Optimal design solutions of concrete bridges considering environmental impact and investment cost | |
| Siwowski | FEM modelling and analysis of a certain aluminium bridge deck panel | |
| CN113392450B (en) | Method, device and system for evaluating health state of railway pier | |
| CN117077486A (en) | Multi-objective comprehensive optimization design method and system for group nailing steel-concrete composite beam | |
| CN109033572B (en) | Linear elasticity method for analyzing ultimate bearing capacity of box-type section frame structure |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |