CN110826159A - Multi-way valve simulation analysis and structure optimization method based on Fluent - Google Patents
Multi-way valve simulation analysis and structure optimization method based on Fluent Download PDFInfo
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Abstract
A multi-way valve simulation analysis and structure optimization method based on Fluent belongs to the field of multi-way valve simulation analysis in engineering machinery, and comprises the following steps: firstly, a multi-way valve test experiment table is set up to test the pressure loss and the hydrodynamic force of the multi-way valve under different opening degrees and flow rates. Secondly, establishing a three-dimensional model by utilizing Solidworks according to a two-dimensional drawing, and guiding the model into ANSYS for extracting a flow channel model to divide a grid; and importing the grid model into Fluent to set simulation conditions and perform simulation, fitting the simulation result with the experiment result, and continuously correcting the simulation model. And finally, finding out the key structure size influencing pressure loss and hydrodynamic force according to the corrected simulation model, fitting and solving equations of the structure parameters and the optimization target by utilizing an algorithm tool box of Matlab and Isight, and selecting an optimal solution according to actual requirements. The invention provides a method for optimizing the structural parameters of a multi-way valve by combining experiments and numerical simulation, and provides guidance for the design and production of valve elements.
Description
Technical Field
The invention belongs to the field of multi-way valve simulation analysis in engineering machinery, and relates to a method for multi-way valve simulation analysis and structure optimization design based on Fluent.
Background
The multi-way valve is a multifunctional reversing valve integrating a multi-connection reversing valve, can simultaneously control different actuating mechanisms, thereby realizing the composite action of the actuating mechanisms, and has wide application in various engineering machines. The performance of the multi-way valve directly determines the accuracy of the hydraulic system control. Many scholars at home and abroad develop researches on various characteristics of the multi-way valve by means of theoretical derivation, experiments or simulation. Numerous scholars have made extensive studies on the analysis of the hydrodynamic force of valve-like elements, the jet angle, the pressure loss, etc. For experimental research, due to the limitation of experimental conditions, the state of the flow field in the valve and the stress condition on the wall surface of the valve core cannot be intuitively understood. Meanwhile, for a numerical simulation method, the selection of a simulation boundary model is often inaccurate due to the lack of relevant experimental data as reference, and the condition of a flow field in a valve cannot be simulated really. Meanwhile, the multi-way valve has a complex structure, the design and manufacturing cost of the valve core and the valve body is high, and a large number of elements are difficult to manufacture for structure optimization analysis and experiments. Based on the method, the method for simulation analysis and structure optimization design of the multi-way valve is provided by taking a multi-way valve model applied to engineering as a research object, taking experimental data as a basis and taking numerical simulation as a research means.
Disclosure of Invention
The invention aims to solve the problem that aiming at the defects of the existing experimental and simulation research method, a method for multi-way valve simulation analysis and structure optimization design based on Fluent is provided, the engineering problem of multi-way valve structure optimization is changed into the problem of mathematic and simulation analysis, and a simple and rapid method is provided for multi-way valve structure optimization.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a method for multi-way valve simulation analysis and structure optimization design based on Fluent comprises the following steps:
the first step is as follows: experimental test for hydraulic power and pressure loss of multi-way valve
1.1) building a test bed and connecting a multi-way valve test loop;
1.2) testing the hydraulic power and pressure loss conditions of the multi-way valve under different flow rates and different valve port opening degrees, and recording the obtained data.
The second step is that: simulation analysis of multi-way valve by using Fluent
2.1) obtaining basic size parameters of a multi-way valve model according to a two-dimensional drawing of the multi-way valve, establishing a multi-way valve three-dimensional model with different valve port openings by utilizing Solidworks, and outputting the model as an igs file;
2.2) leading the igs file output in the step 2.1) into a DM model processor in Workbench, and extracting a runner model of oil liquid flowing in the multi-way valve by using a filling and repairing tool in DM. Importing the runner model into a Mesh grid processor in Workbench, dividing the runner model into grids by adopting a multi-zone grid division method, setting the names of each inlet, each outlet and each wall surface of the model, and outputting the names as a Mesh file;
2.3) reading the mesh file obtained in the step 2.2) by using Fluent to perform simulation analysis, setting a simulated mathematical model, physical property parameters and boundary conditions, selecting a calculation method, setting the iteration step number of the model to be 3000 steps, and starting numerical simulation calculation to obtain a simulation result;
the mathematical model comprises a multiphase flow model and a k-e turbulence model; the physical parameters comprise fluid density, dynamic viscosity, saturated vapor pressure and vapor viscosity; the boundary conditions include inlet flow, outlet pressure, and wall conditions.
And 2.4) after the simulation calculation is finished, checking the flow distribution state of each flow field in the multi-way valve by using a Fluent post-processing tool, and observing and recording hydrodynamic force and pressure loss data to obtain a velocity vector cloud picture and a pressure distribution cloud picture at the throttling port of the multi-way valve. And respectively introducing the multi-way valve runner three-dimensional models under different valve port openings, changing the flow at the inlet, keeping other conditions unchanged, performing simulation, and recording hydrodynamic force and pressure loss data.
2.5) comparing the data recorded by the simulation with experimental data, if the error between the data is within the error allowable range, considering that various conditions adopted by the simulation and a meshing method are reliable, and if the error between the data exceeds the error allowable range, repeating the steps from 2.1) to 2.4), and correcting the meshing, the mathematical model and the setting of the boundary condition until the error is within the error allowable range. The tolerance range is within ± 25% based on experimental data.
The third step: analyzing the simulated cloud picture and carrying out optimization analysis on the key size parameters of the valve core
And 3.1) analyzing the speed vector cloud picture and the pressure distribution cloud picture generated by the Fluent in the second step, observing the key position of throttling in the flow field, analyzing the size parameters which may cause key influence on pressure loss and hydrodynamic force, adjusting the size parameters within a certain range, simulating and recording the numerical values of the changed flow, pressure loss and hydrodynamic force again, and finding out the reasonable range of size parameter change.
The size parameters mainly comprise the circumferential number of the throttling grooves at the throttling opening, the depth of the throttling grooves and the shape and size of the throttling grooves.
3.2) firstly, extracting a part of size parameters in the variable range determined in the step 3.1) by utilizing a Latin hypercube sampling method in Matlab as basic data of response surface analysis. Secondly, modeling is carried out again according to a plurality of groups of size parameters generated by the Latin hypercube sampling method, simulation is carried out according to the method of the second step, and the hydrodynamic force and pressure loss data of the multi-way valve under the size parameters are recorded. And finally, performing regression analysis on the size parameters obtained by the Latin hypercube and the corresponding simulation results by using a second-order polynomial response surface model tool in Matlab, and fitting a relational expression between the size parameters and the optimization target (hydrodynamic force and pressure loss).
3.3) solving a relational expression fitted by a second-order polynomial response surface model by using a self-contained genetic algorithm tool kit in Isight, calculating a Pareto optimal solution set, selecting a proper optimal solution according to engineering practice, substituting the proper optimal solution into Fluent to perform simulation verification, and verifying the accuracy of an optimization result. And if the error of the simulation and calculation result is within +/-15% and is obviously improved compared with the result before optimization, the optimization result is considered to be established.
The invention has the advantages that: the method combines the experiment and the simulation, verifies the correctness of a simulation result through experimental data, converts an actual engineering problem into a mathematic and simulation problem by utilizing the flow state of a flow field in the valve in a simulation experiment, finds a shortcut for optimizing and designing the size parameter by utilizing a mature Matlab and Isight algorithm toolbox, and provides a new idea for optimizing the structure of the multi-way valve.
Drawings
FIG. 1 is a schematic diagram of an experimental test of a multi-way valve.
FIG. 2 is a flow chart of experimental, simulation analysis, and optimization design.
Detailed Description
The present invention is further illustrated by the following specific examples.
A multi-way valve simulation analysis and structure optimization method based on Fluent comprises the following steps:
the first step is as follows: experimental test for hydraulic power and pressure loss of multi-way valve
A hydraulic test loop is built on the multi-way valve test bench, and devices required in the experiment comprise a multi-way valve, a pull pressure sensor, a power source, a connecting pipeline, a turbine flowmeter and a pressure sensor. A total of four pressure points were set in the experiment to measure the pressure at four positions of valve P, T, A, B. In the experiment, A, B adopts a mode of no-load connection. The pull pressure sensor is directly connected and fixed with the valve core, the opening degree of the valve port is adjusted and fixed in a thread feeding mode, and the large hydraulic force borne by the valve core when liquid flows through the valve port under different opening degrees is measured. The flow meter is used to monitor and adjust the amount of flow through the test valve system during the experiment. In order to prevent the opening error caused by other factors such as installation and the like, the extending length of the valve core is measured at the other end of the valve core by using an electronically displayed vernier caliper, so that the accuracy of the opening position of the valve core is ensured. At each opening, pressure at P, T, A, B four ports, flow between the AB ports, and hydrodynamic conditions of the valve spool were recorded. And changing the flow at the inlet, repeating the measurement process under different opening degrees and recording data.
The second step is that: flow field simulation analysis of multi-way valve by using Fluent
2.1) obtaining basic size parameters of the multi-way valve according to a two-dimensional drawing of the multi-way valve, and establishing a solid model by utilizing Solidworks. And respectively establishing a valve body and a valve core, and then respectively assembling according to different opening degrees of the valve core. And generating an igs format for the assembled parts and storing the igs format.
2.2) extracting the multi-way valve flow channels under different valve port openings in a Workbench, selecting a DM module in the Workbench, introducing the generated igs file into the DM, and sealing the inlet and the outlet of the valve body. The Surface command is used to create a plane that forms a closed space inside the valve. And filling the internal space of the valve by using a Fill command, and hiding the original model, wherein the rest is the flow channel model part in the valve.
2.3) importing the generated file into a Mesh module in the Workbench to perform Mesh division. And (3) processing the fluid model in the Mesh, selecting a Mesh division mode as CFD, outputting software as Fluent, and setting the maximum structure size and the minimum surface size of the Mesh to be 0.0005 m. And carrying out multi-zone grid division on the flow channel model, and respectively selecting different grid shapes for flow channel model parts with different complexities. The entrance, exit, wall and symmetry planes are named as inlet, outlet, wall and symmetry, respectively, and then the mesh is generated. And checking the distortion degree of the grids and the minimum orthogonal quantity, and if the distortion degree of the grids is concentrated below 0.5 and the minimum orthogonal quantity is concentrated above 0.5, the quality of the grids is considered to be good, or if the quality of the grids is low, the size parameters of the grids need to be modified for regeneration. And saving the generated grids into a mesh file.
2.4) calling Fluent software to read the mesh file in Workbench, and checking whether a negative grid is generated after the grid is loaded. And if the grid is normal, entering the setting of the parameters. Setting a mathematical model (a multiphase flow model and a k-e turbulence model) for multi-way valve model simulation, physical parameters (fluid density, dynamic viscosity, saturated vapor pressure and vapor viscosity), boundary conditions (inlet flow, outlet pressure and wall surface conditions), selecting a calculation method, setting iteration steps of the model as and starting numerical simulation calculation, wherein the Fluent setting process is as follows:
the simulation model is defined as a multi-phase flow model, and the turbulence model selects an RE k-e model. Defining physical parameters of the material, naming the newly-built material as 46oil, and setting fluid density, dynamic viscosity, saturated vapor pressure and vapor viscosity according to the actual oil parameters of the project. And selecting boundary conditions, setting the named inlet as a mass flow inlet, setting the named outlet as a pressure outlet, and setting the wall surface and the symmetrical surface according to defaults. And monitoring the stress surface of the valve core, and newly building resistance in the monitoring, wherein the monitoring surface with the set resistance is the set stress surface of the valve core. The calculation method is selected as a simple algorithm, the initialization method is standard initialization, and the iteration step number is set to be 3000. After the conditions are set, the calculation is started.
After the simulation calculation is finished, obtaining a speed vector cloud picture and a pressure distribution cloud picture at the throttling port of the multi-way valve through a Fluent self-contained post-processing function; the distribution of the flow field at each position in the multi-way valve is displayed. The change conditions of the pressure and the flow speed of the multi-way valve at the outlet of the throttling port can be known from the cloud chart, and meanwhile, the force borne by the force bearing surface of the valve core in the axial direction and the pressure value at the inlet and the outlet of the valve are recorded in the report to calculate the numerical values of pressure loss and hydrodynamic force. And respectively introducing the multi-way valve runner three-dimensional models under different valve port openings, changing the flow at the inlet, keeping other conditions unchanged, performing simulation, and recording hydrodynamic force and pressure loss data.
2.5) comparing the data recorded by the simulation with experimental data, if the error between the data is within the error allowable range, considering that various conditions adopted by the simulation and a meshing method are reliable, and if the error between the data exceeds the error allowable range, repeating the steps from 2.1) to 2.4), and correcting the meshing, the mathematical model and the setting of the boundary condition until the error is within the error allowable range. The tolerance range is within ± 25% based on experimental data.
A third step; analyzing the simulated cloud picture and optimizing and analyzing the valve core size structure
And 3.1) analyzing the speed vector cloud picture and the pressure distribution cloud picture generated by the Fluent in the second step, observing the key position of throttling in the flow field, analyzing the size parameters which may cause key influence on pressure loss and hydrodynamic force, adjusting the size parameters within a certain range, simulating and recording the numerical values of the changed flow, pressure loss and hydrodynamic force again, and finding out the reasonable range of size parameter change. The size parameters of the method mainly comprise the circumferential number of the throttling grooves at the throttling port, the depth of the throttling grooves and the shape and the size of the throttling grooves.
3.2) firstly, extracting a part of size parameters in the variable range determined by 3.1) by utilizing a Latin hypercube sampling method in Matlab as basic data of response surface analysis. Secondly, modeling is carried out again according to a plurality of groups of size parameters generated by the Latin hypercube sampling method, simulation is carried out according to the method of the second step, and the hydrodynamic force and pressure loss data of the multi-way valve under the size parameters are recorded. And finally, performing regression analysis on the size parameters obtained by the Latin hypercube and the corresponding simulation results by using a second-order polynomial response surface model tool in Matlab, and fitting a relational expression between the size parameters and the optimization target (hydrodynamic force and pressure loss). The second-order polynomial response surface model expression is as follows:
in the method, the hydrodynamic force f and the pressure loss delta P are selected as objective functions, the circumferential arrangement number of throttling grooves α is selected, the depth of the throttling grooves β and the structural size a of the throttling grooves are design parameters, and the specific method is as follows:
selecting an experimental design method for an application program module in Matlab, adding three variable parameters of the circumferential arrangement number α of the throttling grooves, the depth β of the throttling grooves and the structural size a of the throttling grooves, and setting the variables according to the range determined in 3.1)Experimental data set. And re-establishing the three-dimensional model according to the generated data set, and re-simulating and analyzing the generated model to obtain the data of the hydraulic power and the pressure loss. Importing the data into Matlab in a table form, selecting a second-order polynomial response surface model for equation fitting, and establishing the second-order polynomial response surface model by a second-order polynomial response surface analysis method as follows:
analysis of variance is an important method for verifying the accuracy of a second-order polynomial response surface model. The negative correlation coefficient R2 is a measure that is well accepted by researchers at present. The negative correlation coefficient R2 is calculated as:
wherein n is the number of test points, y is the hydrodynamic force and pressure loss value corresponding to each test point,is the average value of y and is,
is the fitted value of y. The closer the negative correlation coefficient R2 is to 1 for this response surface model, the more reliable the second order polynomial response surface model obtained through the design points of the latin hypercube sampling. And if the model negative correlation coefficient of the response surface does not meet the condition, readjusting the generation algorithm of the response model, and adjusting the distribution condition of the data points.
3.3) most of the engineering optimization problems belong to multi-objective optimization problems, but because the sub-objectives are often in conflict with each other, the related concepts of the optimal solution are difficult to determine. Currently, the most learner-accepted multi-objective optimal solution concept is the Pareto solution set proposed by french economist v. Solving Pareto solution sets using genetic algorithms is one of the commonly used methods. The multi-target genetic algorithm for neighborhood cultivation is one kind of genetic algorithm and features that adjacent propagation mechanisms are used alternately in order to increase the differentiation degree of excellent individual and inferior individual so as to ensure the genetic probability of excellent individual.
And (3) selecting a neighborhood cultivation multi-target genetic algorithm by using an optimization module under an Isight platform and a genetic algorithm tool box, and setting an initial population quantity of the genetic algorithm of 100, a cross probability of 0.9, a cross distribution index of 10 and a variation distribution index of 20. And driving an optimization process by using the command stream and the batch processing file, and obtaining a Pareto optimal solution through iterative computation. The optimal solution is a solution set of an equation and is an optimal size parameter for an optimization target (pressure loss and hydrodynamic force) obtained by solution. And analyzing the Pareto optimal solution set, selecting the required optimal solution point according to the actual engineering, substituting the optimal solution point into Fluent for simulation verification, and verifying the accuracy of the optimization result. And if the error of the simulation and calculation result is within +/-15% and is obviously improved compared with the result before optimization, the optimization result is considered to be established.
The above-mentioned embodiments only express the embodiments of the present invention, but not should be understood as the limitation of the scope of the invention patent, it should be noted that, for those skilled in the art, many variations and modifications can be made without departing from the concept of the present invention, and these all fall into the protection scope of the present invention.
Claims (5)
1. A multi-way valve simulation analysis and structure optimization method based on Fluent is characterized by comprising the following steps:
the first step is as follows: experimental test for hydraulic power and pressure loss of multi-way valve
1.1) building a test bed and connecting a multi-way valve test loop;
1.2) testing the hydraulic power and pressure loss conditions of the multi-way valve under different flow rates and different valve port openings, and recording the obtained data;
the second step is that: simulation analysis of multi-way valve by using Fluent
2.1) obtaining basic size parameters of a multi-way valve model according to a two-dimensional drawing of the multi-way valve, establishing a multi-way valve three-dimensional model with different valve port openings by utilizing Solidworks, and outputting an igs file;
2.2) leading the igs file output in the step 2.1) into a DM model processor in Workbench, and extracting a runner model of oil liquid flowing in the multi-way valve by using a filling and repairing tool in DM; then leading the runner model into a Mesh grid processor in Workbench, dividing the runner model into grids by adopting a multi-region grid division method, setting the names of each inlet, each outlet and each wall surface of the model, and outputting the names as a Mesh file;
2.3) reading the mesh file obtained in the step 2.2) by using Fluent to perform simulation analysis, setting a simulated mathematical model, physical property parameters and boundary conditions, selecting a calculation method, and starting numerical simulation calculation to obtain a simulation result;
2.4) after simulation calculation is finished, checking flow distribution states of flow fields at all positions in the multi-way valve by using a Fluent post-processing tool, observing and recording hydrodynamic force and pressure loss data, and obtaining a velocity vector cloud picture and a pressure distribution cloud picture at a throttling port of the multi-way valve; respectively introducing a multi-way valve runner three-dimensional model under different valve port openings, changing the flow at an inlet, keeping other conditions unchanged, then performing simulation, and recording hydrodynamic force and pressure loss data;
2.5) comparing the data recorded by simulation with experimental data, if the error between the data is within the error allowable range, considering that various conditions and a meshing method adopted by the simulation are reliable, if the error between the data exceeds the error allowable range, repeating the steps from 2.1) to 2.4), and correcting the settings of meshing, mathematical models and boundary conditions until the error is within the error allowable range;
the third step: analyzing the simulated cloud picture and carrying out optimization analysis on the key size parameters of the valve core
3.1) analyzing a speed vector cloud picture and a pressure distribution cloud picture generated by the Fluent in the second step, observing the key position of throttling in the flow field, analyzing size parameters which may cause key influence on pressure loss and hydrodynamic force, adjusting the size parameters, simulating and recording the numerical values of flow, pressure loss and hydrodynamic force after change again, and finding out the reasonable range of size parameter change;
3.2) firstly, extracting a part of size parameters as basic data of response surface analysis in the variable range determined in the step 3.1) by utilizing a Latin hypercube sampling method in Matlab; secondly, modeling again according to a plurality of groups of size parameters generated by a Latin hypercube sampling method, simulating according to the method of the second step, and recording the hydrodynamic force and pressure loss data of the multi-way valve under the size parameters; finally, carrying out regression analysis on the size parameters obtained by the Latin hypercube and the corresponding simulation results by using a second-order polynomial response surface model tool in Matlab, and fitting a relational expression between the size parameters and the optimization target;
3.3) solving a relational expression fitted by the second-order polynomial response surface model, calculating to obtain a Pareto optimal solution set, selecting a proper optimal solution according to the actual engineering, substituting the proper optimal solution into Fluent for analog simulation verification, and verifying the accuracy of an optimization result; and if the error of the simulation and calculation result is within +/-15% and is improved compared with the result before optimization, the optimization result is considered to be established.
2. The Fluent-based multi-way valve simulation analysis and structure optimization method according to claim 1, wherein the mathematical model in step 2.3) comprises a multi-phase flow model and a k-e turbulence model.
3. The Fluent-based multi-way valve simulation analysis and structure optimization method according to claim 1, wherein the physical parameters in the step 2.3) comprise fluid density, dynamic viscosity, saturated vapor pressure and vapor viscosity; the boundary conditions include inlet flow, outlet pressure, and wall conditions.
4. The Fluent-based multi-way valve simulation analysis and structure optimization method according to claim 1, wherein the error tolerance range in step 2.5) is as follows: within ± 25% of the experimental data.
5. The Fluent-based multi-way valve simulation analysis and structure optimization method is characterized in that the size parameters in the step 3.1) mainly comprise the circumferential number of throttling grooves at the throttling port, the depth of the throttling grooves and the shape and size of the throttling grooves.
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111400934A (en) * | 2020-04-15 | 2020-07-10 | 天华化工机械及自动化研究设计院有限公司 | Method for simulating oxygen content distribution of low-temperature carbonization furnace based on WORKBENCH |
| CN111400958A (en) * | 2020-04-15 | 2020-07-10 | 天华化工机械及自动化研究设计院有限公司 | ANSYS-based simulation method for oxygen content distribution of high-temperature carbonization furnace |
| CN111680370A (en) * | 2020-04-26 | 2020-09-18 | 武汉船用机械有限责任公司 | Design method and design device of hydraulic valve |
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| CN112182791A (en) * | 2020-08-20 | 2021-01-05 | 无锡量子感知技术有限公司 | Analysis method for optimization of turbine generator flow passage structure |
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| CN112651088A (en) * | 2020-09-30 | 2021-04-13 | 中国核动力研究设计院 | Modeling method for dynamic characteristic analysis of pilot operated safety valve and obtained model |
| CN113887153A (en) * | 2021-10-19 | 2022-01-04 | 山东大学 | Physical property table selection method and system in computational fluid mechanics simulation |
| CN114109884A (en) * | 2021-11-16 | 2022-03-01 | 西安热工研究院有限公司 | On-site examination test method for air cooling fan |
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101923590A (en) * | 2010-08-16 | 2010-12-22 | 北京理工大学 | High-efficiency Latin hypercube experimental design method |
| WO2017000011A1 (en) * | 2015-06-30 | 2017-01-05 | Ge Jenbacher Gmbh & Co Og | Method for controlling an internal combustion engine |
-
2019
- 2019-11-13 CN CN201911103679.6A patent/CN110826159B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101923590A (en) * | 2010-08-16 | 2010-12-22 | 北京理工大学 | High-efficiency Latin hypercube experimental design method |
| WO2017000011A1 (en) * | 2015-06-30 | 2017-01-05 | Ge Jenbacher Gmbh & Co Og | Method for controlling an internal combustion engine |
Non-Patent Citations (5)
| Title |
|---|
| RONG L 等: ""Simulation and casting process of aluminum alloy multi-way valve body with various gating systems "", 《ARCHIVES OF FOUNDRY ENGINEERING》 * |
| 周旋 等: ""基于高速开关阀的气动执行器位置伺服控制研究"", 《机电工程技术》 * |
| 张晋 等: ""某双阀芯电液比例多路阀进口节流流场及阀口压降特性研究"", 《中国机械工程》 * |
| 徐莉萍等: "拖拉机液压系统多路阀结构改进及流场仿真", 《液压与气动》 * |
| 王中兴 等: ""基于Kriging模型的某轻型货车悬架系统多目标优化"", 《机械设计与制造》 * |
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| CN112231876B (en) * | 2020-10-23 | 2022-03-01 | 中国核动力研究设计院 | Pipeline system fluid dynamic model generation system and method based on geometric model |
| CN112231876A (en) * | 2020-10-23 | 2021-01-15 | 中国核动力研究设计院 | Pipeline system fluid dynamic model generation system and method based on geometric model |
| CN112287498B (en) * | 2020-10-27 | 2022-05-20 | 哈尔滨工程大学 | Numerical simulation research method for valve core opening degree of three-way spring valve |
| CN112287498A (en) * | 2020-10-27 | 2021-01-29 | 哈尔滨工程大学 | Numerical simulation research method for valve core opening of three-way spring valve |
| CN112632863A (en) * | 2020-12-10 | 2021-04-09 | 上海中联重科桩工机械有限公司 | Multi-way valve simulation modeling method and multi-way valve simulation model |
| CN112632863B (en) * | 2020-12-10 | 2022-11-25 | 上海中联重科桩工机械有限公司 | Multi-way valve simulation modeling method and multi-way valve simulation model establishing method |
| CN113887153A (en) * | 2021-10-19 | 2022-01-04 | 山东大学 | Physical property table selection method and system in computational fluid mechanics simulation |
| CN113887153B (en) * | 2021-10-19 | 2022-12-27 | 山东大学 | Physical property table selection method and system in computational fluid mechanics simulation |
| CN114109884A (en) * | 2021-11-16 | 2022-03-01 | 西安热工研究院有限公司 | On-site examination test method for air cooling fan |
| CN114459750A (en) * | 2022-02-15 | 2022-05-10 | 北京微焓科技有限公司 | Testing method and Tesla valve |
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