Microstructure size parameter optimization method, system and product based on rheometer simulation

Abstract

The present invention belongs to the field of fluid mechanics technology, and provides a method, system and product for optimizing microstructure size parameters based on rheometer simulation. The technical solution is to establish a model combining a rheometer and a microstructure surface, study the drag reduction rate of the microstructure under different structural parameters and different rotation speeds, analyze its drag reduction mechanism from aspects such as speed and turbulent kinetic energy, and make up for the defect that the rheometer drag reduction experiment has no simulation analysis mechanism. By combining variance analysis with response surface analysis, the optimal microstructure drag reduction parameters that are more in line with reality at different rotation speeds of the rheometer and the law of change of drag reduction rate with structural parameters are obtained, thereby obtaining the optimal microstructure size parameters at different rotation speeds.

Description

Technical Field

[0001] The present invention belongs to the technical field of fluid mechanics, and in particular relates to a method, system and product for optimizing microstructure size parameters based on rheometer simulation. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Rheometer is a commonly used method for testing the drag reduction effect of microstructures. It is widely used due to its high accuracy, excellent detection effect and convenient use. However, there is currently a lack of simulation methods for testing the drag reduction performance of microstructures using rheometers and optimizing microstructure parameters.

[0004] Fluid resistance is widely present in the fields of aviation, shipping, transportation, etc. Reducing this resistance can effectively improve energy efficiency and save energy. Rotating machinery such as water pumps, as a large energy consumer, is widely used in various fields of industrial and agricultural production. Using bionic microstructures to reduce fluid resistance is a widely used method.

[0005] Currently, finite volume method simulation is commonly used to predict and analyze the drag reduction performance of microstructures. However, rheometer, as a common experimental method for measuring microstructure drag reduction, lacks simulation prediction and design optimization methods. Summary of the invention

[0006] In order to solve at least one technical problem existing in the above-mentioned background technology, the present invention provides a microstructure size parameter optimization method, system and product based on rheometer simulation, which establishes a model of a simplified rheometer and combines it with a surface with a microstructure, and uses the finite volume method to simulate the rheometer test drag reduction, which can greatly reduce the experimental cost and the number of experiments, analyze the corresponding relationship between the drag reduction mechanism and the drag reduction rate, and use the simulation combined with orthogonal analysis to guide the parameter design and structural optimization of the microstructure.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] A first aspect of the present invention provides a microstructure parameter optimization simulation method based on a rheometer, comprising the following steps:

[0009] Select microstructural parameters according to the overall size of the rheometer and calculate the value range of the microstructural parameter size;

[0010] Design an orthogonal array based on the value range of microstructure size parameters;

[0011] Based on the orthogonal table and the constructed rheometer test microstructure drag reduction effect simulation model, the fluid dynamics simulation of different microstructure parameters was carried out to obtain the flow field information under different microstructure parameter sizes;

[0012] The flow field information under different microstructure parameter sizes was analyzed by variance analysis without considering the interaction between the microstructure parameters, and the influence trend of different microstructure parameter sizes on the drag reduction rate and wall shear force at different rheometer speeds was obtained;

[0013] The response surface fitting was performed on the flow field information under different microstructure parameter sizes, considering the interaction of each microstructure parameter. The influence trend of different microstructure parameter sizes on the drag reduction rate and wall shear force at different speeds of the rheometer was taken as the dependent variable, and the optimal microstructure size parameters corresponding to different speeds of the rheometer were optimized.

[0014] Furthermore, the calculation formula for the value range of the microstructure parameter is:

[0015] ,

[0016] ,

[0017] ,

[0018] in, is the dimensionless microstructural parameter, is a dimensioned structural size; is the kinematic viscosity of the fluid; is the wall shear velocity; is the wall shear stress; is the density of the fluid; is the hydraulic diameter.

[0019] Furthermore, the orthogonal table designed based on the value range of the microstructure parameters includes: the designed orthogonal table is a three-factor five-level orthogonal table, the three factors correspond to three variables, namely the base, spacing, and height of the microstructure, and the five levels represent that each variable has five different values, and the microstructure parameters of different simulations are determined according to the orthogonal table.

[0020] Furthermore, the determination of the size of the rheometer test microstructure drag reduction effect simulation model includes: the modeling size of the rotor and the relationship between the overall flow domain size diameter and the rotor diameter, and the rotor bottom surface sample and the rotor diameter.

[0021] Furthermore, when fluid dynamics simulation is performed on different microstructure parameters, it includes the determination of simulation parameters, which include boundary conditions, adopted algorithms, model accuracy and convergence conditions, grid division and grid accuracy verification.

[0022] Furthermore, the fluid dynamics simulation of different microstructure parameters is performed to obtain flow field information under different microstructure parameter sizes, including:

[0023] For the cross section of the microstructure where the flow field passes through the axis, the variation law of the velocity at the edge of the microstructure along the Y coordinate is extracted, and its velocity gradient is analyzed. The variation law of the turbulent kinetic energy along the Y coordinate of the part with a rate greater than that of the rotor is extracted, and its turbulent kinetic energy is analyzed.

[0024] Furthermore, an isosceles triangle with a spacing is used as the microstructure, and the selected microstructure parameters include the base, height and spacing of the triangle.

[0025] Furthermore, the drag reduction rate is calculated based on the statistical torque applied to the rotor, and the wall shear force applied is obtained by integrating the wall shear force on the upper surface of the sample to be tested.

[0026] The second aspect of the present invention provides a microstructure parameter optimization simulation system based on a rheometer, comprising:

[0027] A microstructure parameter preliminary determination module is used to select microstructure parameters according to the overall size of the rheometer and calculate the value range of the microstructure parameter size;

[0028] An orthogonal array design module, which is used to design an orthogonal array based on the value range of microstructure size parameters;

[0029] The orthogonal simulation module is used to test the microstructure drag reduction effect simulation model based on the orthogonal table and the constructed rheometer, and to perform fluid dynamics simulation on different microstructure parameters to obtain the flow field information under different microstructure parameter sizes;

[0030] The parameter optimization module is used to perform variance analysis on the flow field information under different microstructure parameter sizes without considering the interaction between the microstructure parameters, so as to obtain the influence trend of different microstructure parameter sizes on the drag reduction rate at different rotation speeds of the rheometer; for the flow field information under different microstructure parameter sizes, response surface fitting is performed taking into account the interaction of each microstructure parameter, and the influence trend of different microstructure parameter sizes on the drag reduction rate at different rotation speeds of the rheometer is taken as the dependent variable, so as to optimize the optimal microstructure size parameters corresponding to different rotation speeds of the rheometer.

[0031] A third aspect of the present invention provides a computer-readable storage medium.

[0032] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps in the microstructure parameter optimization simulation method based on a rheometer as described above.

[0033] A fourth aspect of the present invention provides a computer device.

[0034] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps in the microstructure parameter optimization simulation method based on the rheometer as described above are implemented.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. The present invention establishes a model of a simplified rheometer and combines it with a surface with a microstructure. The finite volume method is used to simulate the drag reduction test of the rheometer, which can greatly reduce the experimental cost and the number of experiments. The corresponding relationship between the drag reduction mechanism and the drag reduction rate is analyzed, and the simulation is combined with orthogonal analysis to guide the parameter design and structural optimization of the microstructure.

[0037] 2. The present invention establishes a model combining a rheometer with a microstructure surface, studies the drag reduction rate of the microstructure under different structural parameters and different rotation speeds, and analyzes its drag reduction mechanism from aspects such as speed and turbulent kinetic energy, thus making up for the defect that the rheometer drag reduction experiment has no simulation analysis mechanism.

[0038] 3. The present invention is more in line with the actual situation of the rheometer experiment process by specifying the wall shear force (specified shear) to simulate the horizontal plane and specifying the moving wall (moving wall) to simulate the rotor. The deviation from the experimental data is less than 10%, which has guiding significance.

[0039] 4. The present invention combines variance analysis with response surface analysis to obtain more practical optimal microstructure drag reduction parameters at different rotation speeds of the rheometer and the law of change of drag reduction rate with structural parameters, thereby obtaining the optimal microstructure size parameters corresponding to different rotation speeds of the rheometer.

[0040] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0042] Figure 1 is a flow chart of a microstructure parameter optimization simulation method based on a rheometer provided in an embodiment of the present invention;

[0043] Figure 2 Schematic diagram of a rheometer simulation model and microstructure parameters provided by an embodiment of the present invention;

[0044] Figure 3Schematic diagram of model boundary conditions and mesh division details provided by an embodiment of the present invention; wherein, (a) boundary conditions of the rheometer simulation model; (b) cross-sectional schematic diagram of the rheometer simulation model; (c) microstructure surface mesh; (d) fluid domain mesh diagram and a local enlarged diagram of its boundary layer;

[0045] Figure 4 It is a grid independence test provided by an embodiment of the present invention;

[0046] Figure 5 is a flow field velocity comparison diagram provided by an embodiment of the present invention;

[0047] Figure 6 is a flow field turbulence kinetic energy comparison diagram provided by an embodiment of the present invention;

[0048] Figure 7 Graphs 1 and 2 show the effects of different parameters of the microstructure provided by the embodiments of the present invention on the drag reduction rate at different rotation speeds, including (a) the effect of the bottom on the drag reduction rate; (b) the effect of the height on the drag reduction rate; and (c) the effect of the spacing on the drag reduction rate. DETAILED DESCRIPTION

[0049] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0050] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0051] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0052] This paper takes an isosceles triangle with a spacing as the cross-sectional shape of the microstructure to conduct numerical simulation research and structural optimization of its drag reduction effect as an example, selects an isosceles triangle as the cross-sectional shape of the microgroove, establishes a rotational flow field simulation model of the rheometer, takes the base, height and spacing of the triangle as variables, uses the orthogonal analysis method combined with the response surface method to explore the optimal structural parameters under four different rotation speeds, and compares and analyzes the turbulent kinetic energy, velocity and other information of the flow field on the smooth surface and the microstructure surface, and explores its drag reduction mechanism. The optimal microstructure size parameters under different rotation speeds are optimized.

[0053] Embodiment 1

[0054] like Figure 1 As shown, in this embodiment, an isosceles triangle with a spacing is used as the cross-sectional shape of the microstructure to perform numerical simulation research and structural optimization on its drag reduction effect. The microstructure parameter optimization simulation method based on the rheometer includes the following steps:

[0055] Step 1: Select microstructure parameters according to the size of the rheometer and calculate the value range of the microstructure parameters; specifically, the steps include:

[0056] Step 101, determining the overall size of the rheometer and selecting microstructure parameters;

[0057] In this embodiment, an isosceles triangle with a spacing is used as the microstructure, and the selected microstructure parameters include the base, height and spacing of the triangle;

[0058] Step 102: Preliminarily calculate the microstructure parameter size according to the dimensionless microstructure parameter calculation formula. The value range is calculated as follows:

[0059] ,

[0060] ,

[0061] ,

[0062] in, is the dimensionless microstructural parameter, is the dimensionless microstructure size; is the kinematic viscosity of the fluid; is the wall shear velocity; is the wall shear stress; is the density of the fluid; is the hydraulic diameter;

[0063] The value ranges of microstructure parameters are shown in Table 1:

[0064] Table 1 Value ranges of microstructural parameters

[0065]

[0066] Step 2: Design an orthogonal table based on the value range of the microstructure size parameters;

[0067] In this embodiment, a gradient is set according to the upper and lower limits of the microstructure parameters, and an orthogonal table is established according to the set gradient. The orthogonal table is used to determine the values ​​of the simulation parameters. In this embodiment, the designed orthogonal table is a three-factor five-level orthogonal table, corresponding to Table 1. The three factors correspond to three variables, namely the bottom, spacing, and height of the microstructure. The five levels represent that each variable has five different values. Table 2 shows a three-factor five-level orthogonal table. The 25 groups in the orthogonal table are 25 groups of size parameters of the microstructure in the simulation, and the microstructure parameters of different simulations are different.

[0068] Table 2 Three factors and five levels orthogonal table

[0069]

[0070] Step 3: Based on the orthogonal table and the constructed rheometer test microstructure drag reduction effect simulation model, fluid dynamics simulation is performed on different microstructure parameters to obtain flow field information under different microstructure parameter sizes, including the following steps:

[0071] Step 301: Establish a simulation model for testing the microstructure drag reduction effect using a rheometer in combination with the actual size of the rheometer;

[0072] In this embodiment, finite volume method simulation is performed using Ansys Fluent.

[0073] According to the actual size of the rheometer, a three-dimensional model is established in Solidworks. The establishment process includes:

[0074] Step 3011, first determine the size of the rheometer simulation model, and model the rotor size at a ratio of 1:1 according to the actual size of the rheometer; since the influence of the peripheral fluid on it can be ignored, in this embodiment, the overall fluid domain size diameter is set to 1.44 times the rotor diameter. At the same time, the rotor bottom surface sample should be slightly larger than the rotor diameter. Figure 2 The figure shows the simulation model of the rheometer and the schematic diagram of the microstructure parameters; wherein a is the distance between the rotor and the microstructure peak, b is the length of the bottom side of the microstructure, s is the spacing of the microstructure, and h is the height of the microstructure.

[0075] Step 3012, setting the distance between the rotor and the sample;

[0076] In this implementation, the upper surface of the bottom sample of the simulation model has no microstructure, and its diameter is set to 30 mm and the height is 2 mm. A rotor with a diameter of 25 mm and a height of 1 mm is established 0.2 mm away from the upper surface of the smooth sample; a spindle with a diameter of 10 mm and a height of 10 mm is established with the center of the rotor as the origin. Finally, a fluid domain with a diameter of 36 mm and a height flush with the upper surface of the rotor spindle is established on the bottom surface of the sample.

[0077] The distance between the rotor and the upper surface of the sample needs to be less than 0.5 mm to allow the microstructure to affect its torque. In this case, the distance is set to 0.2 mm;

[0078] Step 302: Determine the simulation parameters of the simulation model, such as Figure 3 As shown, specifically including:

[0079] Step 3021, boundary condition setting;

[0080] Since the rheometer rotational flow field simulation model has no inlet and outlet, all boundaries are walls.

[0081] For the rotor, its wall boundary condition is set as the moving wall boundary condition, and the origin is specified as the coordinate of its rotation center, the rotation axis is the positive direction of the Y axis, and the speed is set to 1500, 1125, 750, and 375 rpm respectively. The upper surface of the model is specified with a zero shear wall boundary condition to simulate the upper surface of an open liquid pool without restrictions. The remaining walls are set to no-slip boundary conditions, such as Figure 3 As shown in (a) and (b);

[0082] Step 3022: Algorithm, accuracy and convergence conditions are established;

[0083] For the strong rotation flow in this example, the turbulence model uses the Reynolds stress model, which has a good prediction effect for strong rotation flow. Among them, the Reynolds stress model is an existing model and will not be described in detail here;

[0084] In this embodiment, a coupling algorithm is used to solve the algebraic equations. The pressure equation, momentum equation, dissipation rate equation, and Reynolds stress equation all use second-order upwind accuracy. In all models, the residual error condition for convergence judgment of the continuity equation, velocity equation, and specific dissipation rate equation is set to 10 -5 , the residual condition for convergence of each stress equation is set to 10 -6 .

[0085] Step 3023, meshing method. The mesh is generated using Fluent Meshing (2023 R2). The geometric model is spatially discretized using a hexahedral core mesh. Polyhedral meshes are used to fill the area near the wall, and hexahedral meshes are used to fill the rest of the area. Figure 3 As shown in (c) and (d);

[0086] In this embodiment, since it is necessary to pay attention to the wall shear stress and rotor torque, the mesh is locally encrypted on the rotor surface and bottom surface with microstructures. Boundary layer meshes are generated on all wall surfaces to better capture the flow in the near-wall area. The thickness of the first boundary layer is controlled to 4 μm, and the growth rate is set to 1 to ensure that the mesh is uniform, with a total of 10 boundary layers.

[0087] Step 3024: Verify grid accuracy. In finite volume method numerical simulation, the accuracy of the grid will affect the simulation results. Therefore, the model is tested for grid independence, such as Figure 4 As shown, the results show that the number of simulation grids should be controlled above 7.03 million.

[0088] Step 303: Perform fluid dynamics simulation on different microstructure parameters based on the simulation model to obtain flow field information under different microstructure parameters, including:

[0089] For the section of the flow field passing through the axis, the variation law of the velocity at the edge of the microstructure along the Y coordinate is extracted, and its velocity gradient is analyzed. The variation law of the turbulent kinetic energy along the Y coordinate of the part larger than the rotor is extracted, and its turbulent kinetic energy is analyzed. Based on this, the drag reduction mechanism is analyzed and studied.

[0090] Analyze and compare the velocity at coordinate z=0.01236m under different conditions. y The change of coordinates and the turbulent kinetic energy at z=0.01375 y The change of the coordinates is used to explore its drag reduction mechanism. Figure 5 The speed comparison chart shown and Figure 6 The turbulent kinetic energy comparison diagram shown;

[0091] By comparing the velocity information and turbulent kinetic energy information of smooth samples and samples with microstructures, it is analyzed that the drag reduction of the microstructure is achieved by reducing the velocity gradient between the rotor and the microstructure surface, and by keeping the fluid with high turbulent kinetic energy away from the wall in the flow field slightly larger than the rotor diameter, thereby reducing the torque on the rotor (drag reduction) and reducing the wall shear force on the bottom sample surface.

[0092] Step 4: Perform variance analysis on the flow field information under different microstructure parameter sizes without considering the interaction between the microstructure parameters, and obtain the influence trend of different microstructure parameter sizes on the drag reduction rate and wall shear force at different speeds of the rheometer;

[0093] The torque on the rotor is counted and used to calculate the drag reduction rate. The wall shear force in the result is integrated over the upper surface of the sample to obtain the wall shear force it is subjected to. After an orthogonal analysis without considering the interaction between various factors, the influence of different parameters on the drag reduction rate at different speeds is obtained, as shown in Tables 3 to 6:

[0094] Table 3 Effect of different parameters on drag reduction rate at a speed of 1500 rpm

[0095]

[0096] Table 4 Effect of different parameters on drag reduction rate at a speed of 1125 rpm

[0097]

[0098] Table 5 Effect of different parameters on drag reduction rate at a speed of 750 rpm

[0099]

[0100] Table 6 Effect of different parameters on drag reduction rate at a speed of 375 rpm

[0101]

[0102] At the same time, we get Figure 7 The trend diagram of the influence of different microstructure parameters on the drag reduction rate at different speeds is shown; Figure 7 (a) is the effect of the bottom on the drag reduction rate. Figure 7 The middle (b) shows the effect of height on the drag reduction rate. Figure 7 (c) shows the effect of spacing on drag reduction rate.

[0103] Step 5: For the flow field information under different microstructure parameter sizes, a response surface fitting is performed considering the interaction of each microstructure parameter. The influence trend of different microstructure parameter sizes on the drag reduction rate is taken as the dependent variable, and the optimal microstructure size parameters corresponding to different rotation speeds of the rheometer are optimized.

[0104] The present invention combines variance analysis with response surface analysis to obtain more realistic optimal microstructure drag reduction parameters at different speeds of the rheometer and the law of change of drag reduction rate with structural parameters. The drag reduction mechanism is analyzed by analyzing the velocity and turbulent kinetic energy of the flow field. The following conclusions are drawn:

[0105] ① Among the three variables of microstructure, the drag reduction rate is analyzed as the dependent variable, and the most significant factor at different speeds is high; if the shear force on the bottom surface is analyzed as the dependent variable, at high speeds (1500rpm, 1125rpm, 750rpm), the most significant factor is high, and the more significant factor is spacing. At low speeds (375rpm), only high is a more significant factor.

[0106] ② Considering the interaction between factors, the response surface method is used to fit the simulation data, and the optimal structural parameters are calculated when the drag reduction rate and the bottom shear force are 1:1 at different speeds. The optimal structural parameters at 1500rpm are bottom-height-spacing corresponding to 60-100-120; the optimal structural parameters at 1125rpm are bottom-height-spacing corresponding to 120-100-120; the optimal structural parameters at 750rpm are bottom-height-spacing corresponding to 180-100-120; and the optimal structural parameters at 375rpm are bottom-height-spacing corresponding to 60-100-120. Finally, the drag reduction rates of the optimal parameters at each speed are 6.81%, 6.89%, 10.66%, and 9.54%, respectively.

[0107] Embodiment 2

[0108] This embodiment provides a microstructure parameter optimization system based on rheometer simulation, comprising:

[0109] A microstructure parameter preliminary determination module is used to select microstructure parameters according to the overall size of the rheometer and calculate the value range of the microstructure parameter size;

[0110] An orthogonal array design module, which is used to design an orthogonal array based on the value range of microstructure size parameters;

[0111] The orthogonal simulation module is used to test the microstructure drag reduction effect simulation model based on the orthogonal table and the constructed rheometer, and to perform fluid dynamics simulation on different microstructure parameters to obtain the flow field information under different microstructure parameter sizes;

[0112] The parameter optimization module is used to perform variance analysis on the flow field information under different microstructure parameter sizes without considering the interaction between the microstructure parameters, so as to obtain the influence trend of different microstructure parameter sizes on the drag reduction rate at different rotation speeds of the rheometer; for the flow field information under different microstructure parameter sizes, response surface fitting is performed taking into account the interaction of each microstructure parameter, and the influence trend of different microstructure parameter sizes on the drag reduction rate at different rotation speeds of the rheometer is taken as the dependent variable, so as to optimize the optimal microstructure size parameters corresponding to different rotation speeds of the rheometer.

[0113] Embodiment 3

[0114] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps in the microstructure parameter optimization method based on rheometer simulation as described above are implemented.

[0115] Embodiment 4

[0116] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the microstructure parameter optimization method based on rheometer simulation as described above are implemented.

[0117] Embodiment 5

[0118] This embodiment provides a program product, which is a computer program product, including a computer program. When the computer program is executed by a processor, the steps in the microstructure parameter optimization method based on rheometer simulation as described above are implemented.

[0119] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A microstructure parameter optimization method based on rheometer simulation, characterized in that: The steps include: Select microstructural parameters according to the overall size of the rheometer and calculate the value range of the microstructural parameter size; The calculation formula for the value range of microstructure parameters is: ， , ， in, is the dimensionless microstructural parameter, is a dimensioned structural size; is the kinematic viscosity of the fluid; is the wall shear velocity; is the wall shear stress; is the density of the fluid; is the hydraulic diameter; Design an orthogonal array based on the value range of microstructure size parameters; The designed orthogonal table is a three-factor five-level orthogonal table. The three factors correspond to three variables, namely the base, spacing, and height of the microstructure. The five levels represent that each variable has five different values. The microstructure parameters of different simulations are determined according to the orthogonal table. Based on the orthogonal table and the constructed rheometer test microstructure drag reduction effect simulation model, the fluid dynamics simulation of different microstructure parameters was carried out to obtain the flow field information under different microstructure parameter sizes; The fluid dynamics simulation of different microstructure parameters is performed to obtain flow field information under different microstructure parameter sizes, including: For the cross section of the microstructure where the flow field passes through the axis, extract the variation law of the velocity at the edge of the microstructure along the Y coordinate, analyze its velocity gradient, extract the variation law of the turbulent kinetic energy of the part larger than the rotor along the Y coordinate, and analyze its turbulent kinetic energy; The flow field information under different microstructure parameter sizes was analyzed by variance analysis without considering the interaction between the microstructure parameters, and the influence trend of different microstructure parameter sizes on the drag reduction rate and wall shear force at different rheometer speeds was obtained; The response surface fitting was performed on the flow field information under different microstructure parameter sizes, considering the interaction of each microstructure parameter. The influence trend of different microstructure parameter sizes on the drag reduction rate and wall shear force at different speeds of the rheometer was taken as the dependent variable, and the optimal microstructure size parameters corresponding to different speeds of the rheometer were optimized.

2. The microstructure parameter optimization method based on rheometer simulation according to claim 1, characterized in that: The determination of the size of the rheometer test microstructure drag reduction effect simulation model includes: the modeling size of the rotor and the relationship between the overall flow domain size diameter and the rotor diameter, and the rotor bottom surface sample and the rotor diameter.

3. The microstructure parameter optimization method based on rheometer simulation according to claim 1, characterized in that: When fluid dynamics simulation is performed for different microstructure parameters, it includes the determination of simulation parameters, which include boundary conditions, adopted algorithms, model accuracy and convergence conditions, grid division and grid accuracy verification.

4. The microstructure parameter optimization method based on rheometer simulation according to claim 1, characterized in that: An isosceles triangle with a spacing is used as a microstructure, and the selected microstructure parameters include the base, height and spacing of the triangle.

5. The microstructure parameter optimization method based on rheometer simulation according to claim 1, characterized in that: The drag reduction rate is calculated based on the statistical torque applied to the rotor, and the wall shear force applied is obtained by integrating the wall shear force on the upper surface of the sample to be tested.

6. Microstructure parameter optimization system based on rheometer simulation, characterized in that: include: A microstructure parameter preliminary determination module is used to select microstructure parameters according to the overall size of the rheometer and calculate the value range of the microstructure parameter size; The calculation formula for the value range of microstructure parameters is: ， , ， in, is the dimensionless microstructural parameter, is a dimensioned structural size; is the kinematic viscosity of the fluid; is the wall shear velocity; is the wall shear stress; is the density of the fluid; is the hydraulic diameter; An orthogonal array design module, which is used to design an orthogonal array based on the value range of microstructure size parameters; The designed orthogonal table is a three-factor five-level orthogonal table. The three factors correspond to three variables, namely the base, spacing, and height of the microstructure. The five levels represent that each variable has five different values. The microstructure parameters of different simulations are determined according to the orthogonal table. The orthogonal simulation module is used to test the microstructure drag reduction effect simulation model based on the orthogonal table and the constructed rheometer, and to perform fluid dynamics simulation on different microstructure parameters to obtain the flow field information under different microstructure parameter sizes; The fluid dynamics simulation of different microstructure parameters is performed to obtain flow field information under different microstructure parameter sizes, including: For the cross section of the microstructure where the flow field passes through the axis, extract the variation law of the velocity at the edge of the microstructure along the Y coordinate, analyze its velocity gradient, extract the variation law of the turbulent kinetic energy of the part larger than the rotor along the Y coordinate, and analyze its turbulent kinetic energy; The parameter optimization module is used to perform variance analysis on the flow field information under different microstructure parameter sizes without considering the interaction between the microstructure parameters, so as to obtain the influence trend of different microstructure parameter sizes on the drag reduction rate at different rotation speeds of the rheometer; for the flow field information under different microstructure parameter sizes, response surface fitting is performed taking into account the interaction of each microstructure parameter, and the influence trend of different microstructure parameter sizes on the drag reduction rate at different rotation speeds of the rheometer is taken as the dependent variable, so as to optimize the optimal microstructure size parameters corresponding to different rotation speeds of the rheometer.

7. A program product, the program product being a computer program product, comprising a computer program, characterized in that: When the computer program is executed by a processor, the steps in the microstructure parameter optimization method based on rheometer simulation as described in any one of claims 1 to 5 are implemented.

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