CN111783219A - Pipeline optimization design method and exhaust pipeline - Google Patents
Pipeline optimization design method and exhaust pipeline Download PDFInfo
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- CN111783219A CN111783219A CN202010430501.9A CN202010430501A CN111783219A CN 111783219 A CN111783219 A CN 111783219A CN 202010430501 A CN202010430501 A CN 202010430501A CN 111783219 A CN111783219 A CN 111783219A
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Abstract
The invention belongs to the technical field of pipeline design, and particularly discloses a pipeline optimization design method and an exhaust pipeline. The pipeline optimization design method adopts script commands to realize data butt joint and call among three-dimensional modeling software, fluid simulation software and multi-objective optimization software, can realize automatic and continuous operation of serialization operations such as modeling, simulation and result analysis, and improves the pipeline optimization design efficiency; before multi-objective optimization design, initial three-dimensional modeling and fluid simulation are carried out, design variables are parameterized, and therefore in the modeling process of optimization calculation and fluid simulation analysis, three-dimensional modeling software and fluid simulation software automatically modify and regenerate a pipeline three-dimensional model and a fluid calculation model according to parameter changes of design variable combinations, three-dimensional modeling and fluid simulation time is saved, and pipeline optimization design efficiency is improved. The exhaust pipeline adopts the pipeline optimization design method, so that the optimization design efficiency of the exhaust pipeline is improved.
Description
Technical Field
The invention relates to the technical field of pipeline design, in particular to a pipeline optimization design method and an exhaust pipeline.
Background
The exhaust pipeline of the gasoline engine is arranged on the limited space of the automobile chassis, mainly plays a role of exhausting combustion waste gas in a cylinder of the gasoline engine, and is very complex in structure. A three-way catalyst, a particle trap, a muffler and the like are generally arranged on an exhaust pipeline and used for purifying harmful emissions such as CO, HC, NOx and soot in the exhaust gas of an engine, reducing pollution and reducing exhaust noise of the engine. The smoothness of the exhaust gas in the exhaust pipeline directly influences the dynamic property and the fuel economy of the engine, and the smaller the pressure drop of the exhaust pipeline is, the more beneficial to improving the dynamic property of the engine and reducing the oil consumption of the engine is. Therefore, the performance of the engine exhaust line directly affects the dynamic performance, fuel economy, emissions and comfort of the entire vehicle.
When designing an exhaust pipe, an automobile and an engine engineer typically perform the following steps: the method comprises the steps of drawing a three-dimensional model of the exhaust pipeline by using three-dimensional drawing software, extracting a fluid domain of the model, introducing the fluid domain into CFD fluid analysis software, dividing grids by using the fluid analysis software, setting boundary conditions, carrying out CFD simulation operation, adjusting the three-dimensional model of the exhaust pipeline according to a simulation result, and completing a first round of simulation optimization work. And repeating the process of the first round of simulation by using the adjusted three-dimensional model of the exhaust pipeline, and finishing the second round of optimization. According to the difference of the design experience of engineers, the design and the design of an exhaust pipeline are finalized, and several to dozens of rounds of simulation optimization are usually needed. Each round of simulation optimization involves three-dimensional mapping, meshing, and simulation data analysis tasks that can be time and effort intensive for the engineer. Moreover, the traditional design method has long development period, depends on the experience of engineers, has certain blindness, wastes most time on repeated work, and has development efficiency which cannot keep pace with the rhythm of the current automobile market.
The prior art provides a method for optimizing the three-dimensional shape of an exhaust pipeline, which comprises the following steps: the method comprises the steps of drawing a three-dimensional model of the exhaust pipeline by using three-dimensional drawing software, extracting a fluid domain of the model, introducing the fluid domain into CFD fluid analysis software, simplifying and dividing the model by using the fluid analysis software, setting boundary conditions, and carrying out CFD simulation operation, if a simulation result does not meet requirements, deforming the grid by using grid deformation software Sculptor, and introducing the deformed grid into STAR-CCM + for optimization until the grid meeting design requirements is found.
In the three-dimensional shape optimization method for the exhaust pipeline provided by the prior art, because grid deformation is a non-parametric design mode, the defects that a model is inconvenient to modify, a relation cannot be established between sizes, the model cannot be described in a parametric mode and the like exist.
Disclosure of Invention
The invention aims to provide a pipeline optimization design method, which improves the efficiency of pipeline optimization design and saves the time cost of pipeline optimization design.
Another object of the present invention is to provide an exhaust pipe, which reduces the design time of the exhaust pipe and improves the efficiency of the optimal design of the exhaust pipe.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for optimizing and designing a pipeline comprises the following steps:
in three-dimensional modeling software, a pipeline three-dimensional model is established, the pipeline three-dimensional model is parameterized, and a plurality of parameters are selected as design variables;
the fluid simulation software reads the pipeline three-dimensional model data through a first script command, performs initial fluid simulation, and stores an operation command text of the initial fluid simulation;
in multi-objective optimization software, generating a design variable combination based on an optimization objective;
three-dimensional modeling and fluid simulation are carried out based on design variable combination: for each design variable combination, the three-dimensional modeling software imports the design variable combination through a second script command and modifies the pipeline three-dimensional model, the fluid simulation software imports the modified pipeline three-dimensional model through the first script command and performs fluid simulation on the modified pipeline three-dimensional model based on the operation command text, and the multi-objective optimization software reads fluid simulation result data related to the optimization target through a third script command;
judging whether the fluid simulation result data of the design variable combination meets the optimization target, if not, regenerating the design variable combination by the multi-objective optimization software and returning to the step of performing three-dimensional modeling and fluid simulation based on the design variable combination; and if so, ending the optimization calculation.
As a preferred technical solution of a pipeline optimization design method, the design variable combination includes an initial design variable combination and an optimization design variable combination;
before the three-dimensional modeling and fluid simulation based on the design variable combination is executed for the first time, generating a plurality of initial design variable combinations based on the multi-objective optimization software, and when the fluid simulation result data of all the initial design variable combinations do not meet the optimization target, regenerating the optimized design variable combination by the multi-objective optimization software and executing the three-dimensional modeling and fluid simulation based on the design variable combination;
and judging whether the fluid simulation result data of the optimized design variable combination meets the optimization target, if so, selecting the current optimized design variable combination as the optimal design variable combination, and if not, regenerating the optimized design variable combination by the multi-objective optimization software and executing the steps of three-dimensional modeling and fluid simulation based on the design variable combination.
As a preferred technical solution of the pipeline optimization design method, in the multi-objective optimization software, the initial design variable combinations are generated based on a DOE test method.
As an optimal technical solution of a pipeline optimization design method, the DOE-based test method specifically refers to: determining the value range of each design variable based on the installation and processing requirements of the pipeline, determining a feasible domain of the initial design variable combination according to the value range of each design variable, and selecting a plurality of discrete points in the feasible domain to form a plurality of initial design variable combinations.
As a preferred technical solution of a method for optimally designing a pipeline, before the combination of the optimized design variables is generated again for the first time, the multi-objective optimization software analyzes the correlation between each design variable and the optimization target based on the relationship between the fluid simulation result data of all the initial combination of the design variables and the optimization target, and determines the optimization direction of each design variable;
the regeneration of the optimal design variable combination by the multi-objective optimization software specifically refers to: and regenerating a new optimized design variable combination based on the optimization direction of each design variable and the relationship between the fluid simulation result of the current optimized design variable combination and the optimization target.
When the optimal design variable combination is generated again in the initial execution, the initial design variable combination with the fluid simulation result data closest to the optimization target in all the initial design variable combinations is selected as the initial optimal design variable combination.
As a preferred technical solution of the pipeline optimization design method, before the multi-objective optimization software is executed to regenerate the optimization design variable combination, it is determined whether the generated number of the optimization design variable combination is greater than a preset value or whether the optimization time is greater than a preset time, if so, a group of the optimization design variables of which the fluid simulation result data is closest to the optimization target is selected as the optimal design variable combination to be output, the optimization process is ended, and if not, the step of regenerating the optimization design variable combination by the multi-objective optimization software is continuously executed.
As a preferred technical scheme of the pipeline optimization design method, the optimization target comprises the reduction of pipeline pressure drop and the improvement of outlet section flow uniformity of the pipe part to be optimized.
As an optimal technical scheme of the pipeline optimization design method, the pipeline comprises an exhaust manifold, a pipe part to be optimized, a three-way catalyst, a particle catcher and a silencer which are sequentially connected, and the design variables are design parameters of the pipe part to be optimized.
An exhaust pipeline is designed and formed by adopting the pipeline optimization design method.
The invention has the beneficial effects that:
according to the pipeline optimization design method provided by the invention, due to the fact that the data butt joint and call among the three-dimensional modeling software, the fluid simulation software and the multi-objective optimization software are realized by adopting the script commands, the automatic continuous operation of the serialized operations such as modeling, simulation and result analysis can be realized, and the pipeline optimization design efficiency is improved;
because the initial three-dimensional modeling and the design variable parameterization are carried out before the optimization calculation, the three-dimensional modeling software can automatically change and modify the generated pipeline three-dimensional model according to the parameters of the design variable combination in the modeling process of the optimization calculation, and the three-dimensional modeling time in the optimization calculation process is saved;
meanwhile, because the initial fluid simulation is carried out based on the initial three-dimensional modeling and the operation command text of the initial fluid simulation is stored, in the simulation process of the optimization calculation, the modified model can be automatically adaptively modified and set based on the design in the initial fluid simulation, and the time for modeling and parameter setting in the optimization calculation fluid simulation is saved.
The exhaust pipeline provided by the invention is formed by adopting the pipeline optimization design method to carry out optimization design, so that the optimization design efficiency of the exhaust pipeline is improved, and the optimization design cost of the exhaust pipeline is reduced.
Drawings
FIG. 1 is a flow chart of a method for optimally designing a pipeline according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an exhaust pipeline according to a second embodiment of the present invention;
FIG. 3 is a schematic structural view of a pipe portion to be optimized according to a second embodiment of the present invention before optimization;
fig. 4 is a schematic structural diagram of the optimized pipe portion to be optimized according to the second embodiment of the present invention.
The figures are labeled as follows:
1-a pipe section to be optimized; 2-an exhaust manifold; 3-a three-way catalyst; 4-a particle trap; 5-silencer.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
In the description of the present invention, unless expressly stated or limited otherwise, the terms "connected," "connected," and "fixed" are to be construed broadly, e.g., as meaning permanently connected, removably connected, or integral to one another; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In the present invention, unless otherwise expressly stated or limited, "above" or "below" a first feature means that the first and second features are in direct contact, or that the first and second features are not in direct contact but are in contact with each other via another feature therebetween. Also, the first feature being "on," "above" and "over" the second feature includes the first feature being directly on and obliquely above the second feature, or merely indicating that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature includes the first feature being directly under and obliquely below the second feature, or simply meaning that the first feature is at a lesser elevation than the second feature.
In the description of the present embodiment, the terms "upper", "lower", "right", etc. are used in an orientation or positional relationship based on that shown in the drawings only for convenience of description and simplicity of operation, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used only for descriptive purposes and are not intended to have a special meaning.
Example one
Fig. 1 is a flowchart of a pipeline optimization design method provided in an embodiment of the present invention, and as shown in fig. 1, the embodiment provides a pipeline optimization design method, which can be applied to the optimization design of pipelines in various industries, so as to meet the requirements of the pipelines on flow characteristics such as uniformity and pressure drop of fluid flowing therein.
Specifically, the method for optimally designing a pipeline provided by the embodiment includes the following steps:
s101, determining an optimization target and initial design parameters;
in the process of flowing fluid in the pipe part to be optimized, the fluid flow field is greatly influenced by the upstream and downstream connecting structure of the pipe part to be optimized, so that the flow in the pipe part to be optimized in the subsequent fluid simulation is closer to the real flow field, and the pipeline not only comprises the pipe part to be optimized, but also comprises a structure which is connected to the upstream and downstream of the pipe part to be optimized and closely related to the fluid flow field.
That is, in the present embodiment, the pipeline includes the pipe portion to be optimized and the connection structure that is connected upstream and downstream of the pipe portion to be optimized and has a significant influence on the flow field flow in the pipe portion to be optimized. In other embodiments, the pipeline may also comprise only the pipe section to be optimized, if high simulation accuracy is not pursued.
The initial design parameters include not only the design parameters of the pipe portion to be optimized, but also the design parameters of other structures connected upstream and downstream of the pipe portion to be optimized.
The initial design parameters may be determined based on design experience or general optimization algorithms.
The initial design parameters are related to the basic shape of the pipe part to be optimized, and the basic shape of the pipe part to be optimized is generally preliminarily set based on the upstream and downstream connecting structure and the pipeline installation environment, for example, the pipe part to be optimized is a straight pipe pipeline, a bent pipe pipeline or a flared pipe pipeline.
Initial design parameters of the pipe section to be optimized include, but are not limited to: the caliber of two ends of the pipe part, the whole length of the pipe part, the length of the straight pipe part, the length of the arc-shaped part of the pipe part, the radian of the arc-shaped part of the pipe part, the included angle between the two adjacent straight pipe parts and the like.
In the present embodiment, only the vessel portion to be optimized is taken as the optimization target.
The optimization objective is usually related to the actual application scenario of the pipeline, and in the pipeline design, the optimization objective usually includes: reducing the pressure drop of the pipeline, improving the flow uniformity of the cross section of the outlet and the like.
Step S102, establishing a first script command for realizing data butt joint and calling of three-dimensional modeling software and fluid simulation software, a second script command for realizing data butt joint of the three-dimensional modeling software and multi-objective optimization software and a third script command for realizing data butt joint of the multi-objective optimization software and the fluid simulation software in an operating system;
the first script command comprises an intermediate file saving command for saving the pipeline three-dimensional model established in the three-dimensional modeling software into an intermediate file for fluid simulation, and further comprises an intermediate file calling command for calling the intermediate file by the fluid simulation software.
The format of the intermediate file may be, but is not limited to, the iges format, so long as the fluid simulation software can be invoked and identified.
The operating system may be, but is not limited to, a DOS system.
S103, establishing a three-dimensional pipeline model in three-dimensional modeling software, parameterizing the three-dimensional pipeline model, and selecting a plurality of parameters as design variables;
specifically, the method comprises the following steps:
step S1031, based on the initial design parameters, establishing a three-dimensional model of the pipeline in three-dimensional modeling software;
the three-dimensional modeling software may be, but is not limited to, Creo, UG, SolidWorks, and the like.
Modeling by three-dimensional modeling software based on initial design parameters is a conventional setting in the art and is not described herein again.
Step S1032, parameterizing the three-dimensional model;
the built three-dimensional model is parameterized by a parameterization module built in the three-dimensional modeling software to generate model parameters.
And step S1033, extracting a plurality of design parameters in the pipe part to be optimized, which are closely related to the optimization target, as design variables based on the optimization target.
The design variables are selected based on the optimization objective, and the design variables may include all initial design parameters of the tubular portion to be optimized, or may include only a part of the initial design parameters of the tubular portion to be optimized, which have a relatively large influence on the flow field.
By selecting the parameterized design variables, the three-dimensional modeling software can automatically modify and regenerate the pipeline three-dimensional model according to the parameter change of the design variables in the subsequent pipeline three-dimensional modeling process without manually performing modeling operation. With the increase of the times of modifying the three-dimensional model of the pipeline, the time required by three-dimensional modeling in the whole pipeline optimization design process can be greatly shortened, and the pipeline optimization efficiency is improved.
Step S104, reading pipeline three-dimensional model data through a first script command by fluid simulation software, performing initial fluid simulation, and storing an operation command text of the initial fluid simulation;
the method specifically comprises the following steps:
step S1041, generating a fluid simulation model by the fluid simulation software based on the called intermediate text data;
the fluid simulation software can be but is not limited to STAR-CCM +, Fluent and the like, and generates a fluid simulation model through model data of the intermediate file based on an own algorithm.
Due to the limitation of simulation precision, when the pipeline three-dimensional model is complex, the fluid simulation model may be simplified to a certain extent relative to the pipeline three-dimensional model, and the model can be simplified automatically through fluid simulation software or manually.
And step S1042, extracting a fluid domain based on the fluid simulation model, and meshing the fluid domain.
This process is a conventional process of fluid simulation, and is not described in detail in this embodiment.
And S1043, selecting a logistics model for simulation calculation, setting boundary conditions, setting iteration ending conditions (including iteration convergence conditions, maximum iteration steps and the like), and the like.
This process is a conventional process of fluid simulation, and is not described in detail in this embodiment.
And step S1044, carrying out fluid simulation calculation until the calculation result meets the iteration end condition.
And S1045, extracting and outputting fluid simulation result data related to the optimization target based on the simulation calculation result.
S105, establishing a multi-objective optimization model in multi-objective optimization software, and generating a plurality of initial design variable combinations based on an optimization objective;
the multi-objective optimization software may be, but is not limited to, modeFrontier, Isight, MATLAB, and the like.
The method specifically comprises the following steps:
s1051, selecting a DOE test design method;
the DOE test design method comprises the steps of selecting a pipeline optimization algorithm, a design variable combination forming method, a data screening method, a correlation analysis method and the like.
The DOE test design method can be selected through a DOE module in multi-objective optimization software based on the working condition of the pipeline.
Step S1052, setting the value range of each design variable;
setting a proper value range for each design variable according to the conditions of installation of a pipe part to be optimized, connection with an upstream and downstream structure, sample piece manufacturing and the like;
step S1053, generating an initial design variable combination table;
and determining feasible domains formed by all the design variables based on the value range of each design variable. If there are N design variables, the feasible domain is an N-dimensional coordinate system, each design variable combination is one discrete coordinate point in the N-dimensional coordinate system, and a plurality of discrete coordinate points in the feasible domain are selected to form a plurality of initial design variable combinations.
A number of initial design variable combinations are stored in the multi-objective optimization software in tabular text and are invoked sequentially in a specific order.
The initial design variables can be selected in a manual input mode in the multi-objective optimization software, or the multi-objective optimization software can select the initial design variables according to a built-in selection algorithm, or a mode of combining manual input and automatic generation of the multi-objective optimization software can be adopted.
S106, performing three-dimensional modeling and fluid simulation on each initial design variable combination based on the initial design variable combination;
the method specifically comprises the following steps:
step S1061, importing the initial design variable combination and modifying the pipeline three-dimensional model by the three-dimensional modeling software through a second script command;
because the initial three-dimensional modeling and the design variable parameterization are carried out, the three-dimensional modeling software can automatically change and modify the generated pipeline three-dimensional model according to the parameters of the design variable combination in the modeling process of the optimization calculation, and the three-dimensional modeling time in the optimization calculation process is saved.
Step S1062, introducing the modified pipeline three-dimensional model into the fluid simulation software through a first script command, and performing fluid simulation on the modified pipeline three-dimensional model based on the operation command text;
because the initial design parameters are adopted to perform the initial fluid simulation, the model simplification method, the fluid domain extraction mode, the grid setting parameters and the physical model in the initial fluid simulation process, and the setting of the boundary conditions and the convergence conditions are saved, the current fluid simulation parameters can be automatically set based on the saved initial fluid simulation settings in each subsequent fluid simulation process, manual operation is avoided, the fluid simulation time is saved, and the fluid simulation efficiency is improved.
And step S1063, reading fluid simulation result data related to the optimization target by the multi-target optimization software through a third script command.
And if the optimization target comprises pipeline pressure drop, introducing the average pressure drop value of the fluid inlet and the fluid outlet in the pipe part to be optimized into the multi-target software through a third script command.
And if the optimization target comprises outlet section flow uniformity, introducing outlet section flow velocity distribution data of the pipe part to be optimized into multi-target optimization software through a third script file.
The fluid simulation result data to be derived can be specifically set according to the target to be optimized.
Step S107, judging whether the fluid simulation result data of all the initial design variable combinations do not meet the optimization target, if so, executing step S108, and if not, executing step S117;
step 108, calculating the correlation between each initial design variable and an optimization target based on fluid simulation result data of all initial design variable combinations in multi-objective optimization software;
and calculating the relevance and sensitivity of each initial design variable and an optimization target based on an algorithm built in the multi-target optimization software.
S109, selecting a plurality of initial design variables with strong sensitivity to the optimization target as optimization design variables from all the initial design variables, and determining the optimization direction of each optimization design variable based on the correlation between the optimization design variables and the optimization target;
step S110, selecting a group of initial design variable combinations with fluid simulation result data closest to an optimization target from all the initial design variable combinations as initial optimization design variable combinations;
the initial optimized design variable combination comprises a plurality of optimized design variable parameters and parameters of unselected optimized design variables in the initial design variables, so that when the optimized design variable combination is subsequently adopted for modeling and simulation calculation, the optimized variable parameters and the non-optimized variable parameters in the optimized design variable combination cover corresponding parameters in original three-dimensional modeling, and the subsequent optimization process, modeling and fluid simulation are optimized based on the parameters in the reorganized initial optimized variable combination as an optimization starting point.
S111, performing three-dimensional modeling and fluid simulation based on the optimized design variable combination;
for the specific steps, reference may be made to steps S1061 to S1063, which are not described herein again.
Step S112, judging whether the fluid simulation result data of the optimized design variable combination meets an optimization target, if not, executing step S113, and if so, executing step S115;
step S113, judging whether the generated number of the optimized design variable combinations is larger than a preset value, if not, executing step S114, and if so, executing step S116;
step S114, generating a new group of optimized design variable combinations based on the correlation between the fluid simulation result data of the current optimized design variable combinations and the optimization target and the optimization direction of each optimized design variable, and returning to the step S111;
step S115, determining the current optimized design variable combination as the optimal design variable combination, and executing step S118;
step S116, selecting a group of optimized design variables with the fluid simulation result data closest to the optimization target from all the optimized design variable combinations as the optimal design variable combination, and executing step S118;
step S117, selecting a group of initial design variable combinations with the fluid simulation result data optimal relative to the design target from all the initial design variable combinations as the optimal design variable combination, and executing step S118;
and S118, reading the optimal design variable combination through the second script file by the three-dimensional modeling software, modifying and producing the optimal three-dimensional model based on the optimal design variable combination, and obtaining the optimal design parameters of the pipe part to be optimized in the optimal three-dimensional model.
And step S119, finishing optimization.
According to the pipeline optimization design method provided by the embodiment, due to the fact that data butt joint and call among three-dimensional modeling software, fluid simulation software and multi-objective optimization software are achieved through the script commands, automatic and continuous operation of serialization operations such as modeling, simulation and result analysis can be achieved, and pipeline optimization design efficiency is improved;
because the initial three-dimensional modeling and the design variable parameterization are carried out before the optimization calculation, the three-dimensional modeling software can automatically change and modify the generated pipeline three-dimensional model according to the parameters of the design variable combination in the modeling process of the optimization calculation, and the three-dimensional modeling time in the optimization calculation process is saved;
meanwhile, because the initial fluid simulation is carried out based on the initial three-dimensional modeling, in the simulation process of the optimization calculation, the modified model can be automatically adaptively modified and set based on the design in the initial fluid simulation, so that the modeling and parameter setting time in the optimization calculation of the fluid simulation is saved;
in addition, in the process of optimization calculation, a plurality of groups of initial design variable groups are set, each group of initial design variable combination is modeled and simulated, the relevance and the sensitivity of each design variable and an optimization target can be judged according to fluid simulation result data of the initial design variable combination, the optimization direction of each design variable can be judged better while a better optimization starting point design variable combination is selected, the subsequent optimization calculation time and the number of steps required by optimization are saved, and the optimization design effect is improved.
Example two
Referring to fig. 2 to 4, the present embodiment provides a pipeline design method, which optimizes and designs a pipe portion 1 to be optimized of an exhaust pipeline in an engine based on specific refinements of the pipeline optimization design method in the first embodiment, so as to reduce exhaust pipeline resistance reduction and improve flow uniformity of the exhaust pipeline.
In this embodiment, the three-dimensional modeling software is Creo, the fluid simulation software is STAR-CCM +, and the multi-objective optimization software is Modfr. It is understood, however, that the three-dimensional modeling software, the fluid analysis software, and the multi-objective optimization software may not be limited to Creo, STAR-CCM +, and Modfr.
Specifically, the method for designing a pipeline provided by this embodiment includes:
step S201, determining an optimization target and an initial design parameter;
in this embodiment, the optimization objectives include: reduce the pressure drop of the exhaust pipeline and improve the flow uniformity of the exhaust pipeline.
Step S202, establishing a first script command for realizing data docking and calling of the three-dimensional modeling software and the fluid simulation software, a second script command for realizing data docking of the three-dimensional modeling software and the multi-objective optimization software and a third script command for realizing data docking of the multi-objective optimization software and the fluid simulation software in the DOS.
Step S203, three-dimensional modeling of the exhaust pipeline is carried out in Creo based on the initial design parameters, the three-dimensional model of the exhaust pipeline is parameterized, and a plurality of design variables are extracted.
Preferably, the exhaust pipeline comprises an exhaust manifold 2, a pipe portion to be optimized 1, a three-way catalyst 3, a particle trap 4, a silencer 5 and related connecting pipelines which are communicated in sequence. According to the modeling of the exhaust pipeline, the influence of the flow fields of the upstream pipeline and the downstream pipeline can be considered in the flow field of the pipe part 1 to be optimized, so that the flow field in the pipe part 1 to be optimized is more fit with the flow field distribution in the practical application process of the pipe part 1 to be optimized in fluid simulation analysis, and the simulation precision and the optimization effect are improved.
It is to be understood that the exhaust line may include only the pipe portion 1 to be optimized without including the exhaust manifold 2, the three-way catalyst 3, the particulate trap 4, and the muffler 5, when high optimization accuracy is not pursued.
Design variables of the pipe section 1 to be optimized include sd13, sd14, sd18, sd19, sd2, sd3, sd34, sd41, sd48, which are respectively specified: the pipe comprises a fluid inlet caliber, a fluid outlet caliber, a total length of a pipe part, a length of a straight line section of the fluid inlet, a length of a straight line section of the fluid outlet, a bending radian of a first pipeline, a bending radian of a second pipeline and an included angle between the straight line section of the fluid inlet and the straight line section of the fluid outlet.
Step S204, operating a first script command in the DOS, and enabling STAR-CCM + to call a pipeline three-dimensional model in Creo to perform fluid simulation analysis;
the method specifically comprises the following steps:
step S2041, operating an intermediate file storage command in the DOS, and converting the three-dimensional data model in the Creo into the file Creo _ igs in the iges format.
Step S2042, calling a command in the DOS by the intermediate file to enable STAR-CCM + to call a Creo _ igs file;
step S2043, generating an initial fluid simulation model by the read creo _ igs file through STAR-CCM +;
step S2044, setting fluid domain division and grid division on the initial simulation model;
wherein, for the three-way catalytic converter 3 and the particle catcher 4, the treatment is carried out according to the porous medium model, the shearing hexahedral mesh is selected, and other areas are set as polyhedral meshes.
S20045, selecting a physical model and setting boundary conditions and iteration ending conditions for the initial simulation model;
step S2046, performing fluid simulation until the calculation result meets the convergence condition or the iteration step number reaches the set step number;
step S2047, pressure drop data and cross-section flow uniformity data are obtained;
the Pressure Drop is a statistic of the flow Pressure loss between the inlet and the outlet of the tube 1 to be optimized, denoted by Pressure _ Drop _ para, and the cross-sectional flow uniformity, in particular the flow uniformity at the outlet cross-section of the tube 1 to be optimized, comprises two parameters UI _ para (uniformity index) and VI _ para (velocity index), denoted respectively by UI _ para and VI _ para.
The Uniformity index calculation formula:
velocity index is the ratio of the radius value at the position where the Velocity is maximum on a circular cross section to the radius value of the circular cross section.
Step S2048, saving the operation command text from step S2043 to step S2047;
step S205, generating a data text Input _ creo of a plurality of initial design variable combinations by a DOE module of the modeFrontier based on an optimization target and the range of each design variable, and generating Input _ creo _ text;
step S206, performing three-dimensional modeling and fluid simulation on each initial design variable combination based on the initial design variable combination;
the method specifically comprises the following steps:
step S2061, the DOS runs a second script command, drives Creo software to read the initial design variable combination in Input _ Creo _ text according to the characteristic sequence and modifies the three-dimensional model according to the read initial design variable combination;
s2062, running an intermediate file storage command in the first script command by the DOS to guide the modified three-dimensional model into a file creo _ igs in an iges format;
step S2063, running and running an intermediate file reading command in the first script command by the DOS to drive STAR-CCM + and call a Creo _ igs file;
step S2064, modeling, simulating and calculating results of the STAR-CCM + through the saved operation command text to obtain the results;
in the fluid simulation modeling, the automatic connection between the pipe part 1 to be optimized and the upstream and downstream components is realized by Boolean operation.
Step S2065: the DOS runs a third script command to import the pressure drop data and cross-sectional flow uniformity data in STAR-CCM + into modeFrontier;
the steps S2061 to S2065 are repeatedly executed until the fluid simulation result data of all the initial design variable combinations are introduced into the modeFrontier.
Step S207, judging whether the fluid simulation result data of all the initial design variable combinations do not meet the optimization target, if so, executing step S208, and if not, executing step S217;
step 208, in the multi-objective optimization software, calculating the correlation between each initial design variable and the optimization objective based on the fluid simulation result data of all the initial design variable combinations;
s209, selecting a plurality of initial design variables with strong sensitivity to the optimization target as optimization design variables from all the initial design variables, and determining the optimization direction of each optimization design variable based on the correlation between the optimization design variables and the optimization target;
step S210, selecting a group of initial design variable combinations with fluid simulation result data closest to an optimization target from all the initial design variable combinations as initial optimization design variable combinations;
step S211, performing three-dimensional modeling and fluid simulation based on the optimized design variable combination;
for the specific steps, reference may be made to steps S2061 to S2065, which are not described herein again.
Step S212, judging whether the pressure drop data and the cross-section flow uniformity data meet the optimization target, if not, executing step S213, and if so, executing step S215;
the smaller the values of Pressure _ Drop _ para and VI _ para set in the DOE, the better, the larger the value of UI _ para, the better. Usually VI _ para is less than 0.7 and UI _ para is greater than 0.9;
step S213, judging whether the generated number of the optimized design variable combinations is larger than a preset value, if not, executing step S214, and if so, executing step S216;
step S214, generating a new group of optimized design variables based on the correlation between the fluid simulation result data of the current optimized design variables and the optimization target and the optimization direction of each optimized design variable, and returning to the step S211;
step S215, determining the current optimized design variable combination as the optimal design variable combination, and executing step S218;
step S216, selecting a group of optimized design variables with the fluid simulation result data closest to the optimized target in all the optimized design variable combinations as the optimal design variable combination, and executing step S218;
step S217, selecting a group of initial design variable combinations with the fluid simulation result data optimal relative to the design target from all the initial design variable combinations as optimal design variable combinations, and executing step S218;
step S218, the Creo reads the optimal design variable combination through the second script file, and modifies and produces the optimal three-dimensional model based on the optimal design variable combination to obtain the optimal design parameters of the pipe part 1 to be optimized in the optimal three-dimensional model.
And step S219, finishing optimization.
The embodiment also provides an exhaust pipeline which is designed by the pipeline optimization design method.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for optimizing and designing a pipeline is characterized by comprising the following steps:
in three-dimensional modeling software, a pipeline three-dimensional model is established, the pipeline three-dimensional model is parameterized, and a plurality of parameters are selected as design variables;
the fluid simulation software reads the pipeline three-dimensional model data through a first script command, performs initial fluid simulation, and stores an operation command text of the initial fluid simulation;
in multi-objective optimization software, generating a design variable combination based on an optimization objective;
three-dimensional modeling and fluid simulation are carried out based on design variable combination: for each design variable combination, the three-dimensional modeling software imports the design variable combination through a second script command and modifies the pipeline three-dimensional model, the fluid simulation software imports the modified pipeline three-dimensional model through the first script command and performs fluid simulation on the modified pipeline three-dimensional model based on the operation command text, and the multi-objective optimization software reads fluid simulation result data related to the optimization target through a third script command;
judging whether the fluid simulation result data of the design variable combination meets the optimization target, if not, regenerating the design variable combination by the multi-objective optimization software and returning to the step of performing three-dimensional modeling and fluid simulation based on the design variable combination; and if so, ending the optimization calculation.
2. The method of claim 1, wherein the design variable combinations include an initial design variable combination and an optimized design variable combination;
before the three-dimensional modeling and fluid simulation based on the design variable combination is executed for the first time, generating a plurality of initial design variable combinations based on the multi-objective optimization software, and when the fluid simulation result data of all the initial design variable combinations do not meet the optimization target, regenerating the optimized design variable combination by the multi-objective optimization software and executing the three-dimensional modeling and fluid simulation based on the design variable combination;
and judging whether the fluid simulation result data of the optimized design variable combination meets the optimization target, if so, selecting the current optimized design variable combination as the optimal design variable combination, and if not, regenerating the optimized design variable combination by the multi-objective optimization software and executing the steps of three-dimensional modeling and fluid simulation based on the design variable combination.
3. The optimized design method for pipelines according to claim 2, wherein in the multi-objective optimization software the initial design variable combinations are generated based on DOE test methods.
4. The pipeline optimization design method according to claim 3, wherein the DOE-based test method specifically refers to: determining the value range of each design variable based on the installation and processing requirements of the pipeline, determining a feasible domain of the initial design variable combination according to the value range of each design variable, and selecting a plurality of discrete points in the feasible domain to form a plurality of initial design variable combinations.
5. The pipeline optimization design method of claim 2, wherein, prior to the initial execution of the regeneration of the optimal design variable combinations, the multi-objective optimization software analyzes the correlation of each of the design variables with the optimization objective based on the relationship of the fluid simulation result data of all of the initial design variable combinations with the optimization objective and determines the optimization direction of each of the design variables;
the regeneration of the optimal design variable combination by the multi-objective optimization software specifically refers to: and regenerating a new optimized design variable combination based on the optimization direction of each design variable and the relationship between the fluid simulation result of the current optimized design variable combination and the optimization target.
6. The pipeline optimization design method according to claim 5, wherein, when the optimal design variable combination is generated again in the first execution, the initial design variable combination with the fluid simulation result data closest to the optimization target in all the initial design variable combinations is selected as the initial optimal design variable combination.
7. The pipeline optimization design method according to claim 6, wherein before the multi-objective optimization software is executed to regenerate the combination of the optimized design variables, it is determined whether the generated number of the combination of the optimized design variables is greater than a preset value or whether the optimization time is greater than a preset time, if so, a group of the optimized design variables of which the fluid simulation result data is closest to the optimization objective is selected as an optimal design variable combination to be output, the optimization process is ended, and if not, the step of regenerating the combination of the optimized design variables by the multi-objective optimization software is continuously executed.
8. The pipeline optimization design method according to claim 7, wherein the optimization objectives include reducing pipeline pressure drop and improving outlet cross-sectional flow uniformity of the pipe portion to be optimized.
9. The pipeline optimization design method according to any one of claims 1 to 8, characterized in that the pipeline comprises an exhaust manifold (2), a pipe portion to be optimized (1), a three-way catalyst (3), a particle trap (4) and a silencer (5) which are connected in sequence, and the design variables are design parameters of the pipe portion to be optimized (1).
10. An exhaust pipeline, characterized in that it is designed by using the pipeline optimization design method according to any one of claims 1-9.
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