A test method and test device for Taylor-Coutt flow under different working conditions

Abstract

The present invention relates to the field of fluid testing technology, and in particular to a test method and test device for Taylor-Cooter flow under different working conditions. By arranging multiple monitoring points on the axial section of the annular flow channel, temperature and velocity distribution data are obtained, and the fluid state is judged in combination with the Taylor number. For laminar flow conditions, the correlation between the viscosity change and flow velocity caused by temperature fluctuations is analyzed, and a temperature-flow velocity correlation factor is constructed. Dynamic correction and fusion are performed based on the temperature difference and flow velocity difference of the monitoring points to quantify the influence of flow resistance; for non-laminar flow conditions, the correction weight is calculated based on the ratio of the actual Taylor number to the critical value and the flow velocity fluctuation characteristics. Finally, a mapping model of the motor speed and the correction weight is established to form a feedback regulation mechanism for adjusting the motor speed during the current test process. This strategy can significantly improve the dynamic adaptability and control accuracy of the working condition simulation.

Description

Technical Field

[0001] The present invention relates to the technical field of fluid testing, and in particular to a Taylor-Cooter flow testing method and a testing device under different working conditions. Background Art

[0002] The fluid flowing between two cylinders significantly increases in complexity as the inner cylinder's rotational speed increases. This complex and variable flow pattern is collectively known as Taylor-Cooter flow. Taylor-Cooter flow is a typical flow pattern found in industrial applications such as rotating machinery, chemical reactors, and nuclear power systems. Research on its flow stability, transition mechanisms, and heat transfer characteristics is of great significance for engineering optimization.

[0003] Taylor-Koot flow can cause dramatic temperature fluctuations. Prolonged temperature fluctuations can lead to thermal fatigue in materials, potentially forming cracks on the shaft and casing surfaces. Furthermore, Taylor-Koot flow can affect the flow stability of the fluid within the nuclear main pump. This unstable flow state can increase pump vibration and noise, impacting normal operation and performance. Therefore, computer-assisted testing of Taylor-Koot flow under different operating conditions is necessary.

[0004] The flow characteristics of Taylor-Couette flow (such as laminar stability, turbulent transition and vortex structure evolution) are significantly affected by the coupling effects of multiple physical fields such as fluid viscosity, speed ratio and temperature field. When simulating different actual working conditions, different device structures and different fluids exhibit different temperature loss phenomena, resulting in uneven fluid viscosity distribution, complex flow resistance, and destruction of the preset speed-flow rate model. Existing experimental devices and methods often ignore the influencing factor of temperature loss. Therefore, there are certain errors in simulating the corresponding parameters under different working conditions, resulting in deviations in the final working condition simulation. Summary of the Invention

[0005] In order to solve the technical problem that when simulating different actual working conditions, different device structures and different fluids exhibit different temperature loss phenomena, resulting in uneven fluid viscosity distribution, complex flow resistance, and destruction of the preset speed-flow rate model, existing test devices and methods often ignore the influencing factor of temperature loss. Therefore, there are certain errors when simulating the corresponding parameters under different working conditions, resulting in deviations in the final working condition simulation. The purpose of the present invention is to provide a test method and test device for Taylor-Cooter flow under different working conditions. The technical solutions adopted are as follows:

[0006] A test method for Taylor-Cooter flow under different operating conditions, including:

[0007] At each motor speed during the historical test process, multiple monitoring positions were set along the radius of the outer cylinder on the same axial cross-section of the annular space between the inner and outer cylinders to obtain the temperature and flow rate of the fluid at the monitoring positions within a preset time period;

[0008] If the Taylor number corresponding to the motor speed is less than or equal to the critical Taylor number; determine the target time, and under each laminar flow, analyze the correlation between the changes in the temperature values ​​and flow rate values ​​between the monitoring positions at the target time to determine the correlation factor; based on the difference in the temperature values ​​and flow rate values ​​between the monitoring positions at the target time, adjust and fuse the correlation factors under each laminar flow to obtain the speed correction weight at the motor speed;

[0009] If the Taylor number corresponding to the motor speed is greater than the critical Taylor number; according to the numerical difference between the Taylor number at the motor speed and the critical Taylor number, and the change fluctuation of the flow rate value at the monitoring position within the preset time period, the speed correction weight at the motor speed is obtained;

[0010] During the current test, the motor speed is adjusted based on the speed correction weight corresponding to the motor speed to obtain the adjusted speed; under the adjusted speed, various parameters during the test are changed to simulate different working conditions.

[0011] Furthermore, the method for obtaining the correlation factor includes:

[0012] Under each laminar flow, the monitoring positions are arranged in order along the central axis of the outer cylinder to obtain a sorted sequence;

[0013] Under the sorting sequence, the Pearson correlation coefficient of the temperature value sequence and the flow rate value scalar sequence of the fluid at all monitoring positions at the target time is calculated, and the Pearson correlation coefficient is normalized to obtain a correlation factor.

[0014] Furthermore, the speed correction weight when the Taylor number corresponding to the motor speed is less than or equal to the critical Taylor number is used as the first speed correction weight, and the speed correction weight when the Taylor number corresponding to the motor speed is greater than the critical Taylor number is used as the second speed correction weight.

[0015] Furthermore, the method for obtaining the first speed correction weight includes:

[0016] Under all laminar flows, all monitoring locations at the same height along the radius of the outer cylinder are considered to be of the same type. Cluster analysis is performed on each type of monitoring location based on the K-means clustering algorithm and the preset K value to obtain the cluster clusters corresponding to each type of monitoring location. The distance metric is the absolute value of the difference in the fluid temperature values ​​between the monitoring locations at the target time.

[0017] Select one laminar flow as the target laminar flow and the other laminar flows as the comparison laminar flows. Under the target laminar flow, in the cluster to which each monitoring position belongs, analyze the difference characteristics of the temperature value and the difference characteristics of the flow velocity value between the monitoring position belonging to the target laminar flow and the monitoring position belonging to the comparison laminar flow, and determine the influencing factor of each monitoring position under the target laminar flow;

[0018] Based on the numerical characteristics and fluctuations of the influencing factors at each monitoring position under each laminar flow, the relevant factors are corrected to obtain the viscosity correction factor under each laminar flow;

[0019] Under each laminar flow, the difference characteristics of the flow velocity values ​​of the fluid between adjacent monitoring positions are integrated to determine the flow velocity similarity factor, wherein the value of the flow velocity similarity factor is a normalized value;

[0020] The viscosity correction factor is weighted and averaged using the velocity similarity factor of the laminar flow, and the obtained weighted result is used as the first speed correction weight under the motor speed.

[0021] Furthermore, the method for obtaining the impact factor includes:

[0022] Under the target laminar flow, in the cluster to which each monitoring location belongs;

[0023] At the target time, calculating the absolute value of the difference between the mean temperature value of the fluid at the monitoring position belonging to the target laminar flow and the mean temperature value of the fluid at the monitoring position belonging to the comparison laminar flow to obtain a temperature difference factor;

[0024] At the target time, calculating the absolute value of the difference between the mean of the flow velocity scalars of the fluid at the monitoring position belonging to the target laminar flow and the mean of the flow velocity scalars of the fluid at the monitoring position belonging to the comparison laminar flow, to obtain a flow velocity difference factor;

[0025] The product of the temperature difference factor and the flow velocity difference factor corresponding to each monitoring position under the target laminar flow is normalized and used as the influencing factor of each monitoring position under the target laminar flow.

[0026] Furthermore, the method for obtaining the viscosity correction factor includes:

[0027] Under each laminar flow, the standard deviation of the influencing factors of all monitoring locations is added to the mean of the influencing factors of all monitoring locations, and the resulting sum is negatively correlated and mapped to the value used as the correction coefficient;

[0028] The product of the correction coefficient corresponding to each laminar flow and the correlation factor is used as the viscosity correction factor under each laminar flow.

[0029] Furthermore, the method for obtaining the flow velocity similarity factor includes:

[0030] Under each laminar flow, the monitoring positions are arranged in order along the central axis of the outer cylinder to obtain a sorted sequence;

[0031] Under the sorting sequence, the absolute value of the difference between the flow velocity values ​​of the fluid at the target time between each two adjacent monitoring positions is calculated as the flow velocity difference parameter;

[0032] The mean values ​​of all flow velocity difference parameters corresponding to the sorting sequence are negatively correlated and normalized to obtain a value which is used as the flow velocity similarity factor of each laminar flow.

[0033] Furthermore, the method for obtaining the second speed correction weight includes:

[0034] In the velocity data at each monitoring location, the modulus of the absolute value of the difference between the velocity vectors at two adjacent moments is used as the velocity difference coefficient;

[0035] The normalized value of the mean value of all flow rate difference coefficients corresponding to all monitoring positions is used as the first speed adjustment factor;

[0036] The difference between the actual Taylor number and the critical Taylor number is used as a second speed adjustment factor;

[0037] A value obtained by performing negative correlation mapping and normalizing the product of the first speed adjustment factor and the second speed adjustment factor is used as the second speed correction weight at the motor speed.

[0038] Furthermore, the method for obtaining the adjusted speed includes:

[0039] The sum of the normalized value of the speed correction weight corresponding to the motor speed in the current test process and the preset parameter is used as the speed adjustment factor;

[0040] The product of the speed adjustment factor and the motor speed of the current test process is used as the adjustment speed of the current test process.

[0041] A test device for Taylor-Koot flow under different working conditions, the test device includes a shell with radial grooves and a rotating shaft, the shell with radial grooves and the rotating shaft forming an inner and outer cylindrical annular space, multiple monitoring positions are set along the radial direction of the outer cylinder on the same axial cross-section of the inner and outer cylindrical annular spaces, an infrared thermometer and a laser Doppler velocimeter are installed on the shell with radial grooves, and are used to obtain temperature data and flow rate data of the fluid at each monitoring position during each Taylor-Koot flow test. The test device is also provided with a control module, and the control module is used to adjust the motor speed of the frequency conversion motor in the current test process according to the speed correction weight of the motor speed in the historical test process, so as to realize the steps of a test method for Taylor-Koot flow under different working conditions.

[0042] The present invention has the following beneficial effects:

[0043] By arranging multiple monitoring locations along the radial direction of the outer cylinder on the same axial cross-section of the inner and outer cylindrical annular spaces, the distribution characteristics of fluid temperature and flow velocity can be accurately captured, providing high-resolution data for subsequent analysis. Different motor speeds correspond to different fluid states, allowing historical test processes to be classified. If the Taylor number corresponding to the motor speed is less than or equal to the critical Taylor number, the fluid is considered to be in a laminar state. Given that temperature differences can cause differences in fluid flow velocity at each monitoring location, the correlation between temperature and flow velocity values ​​was analyzed for each laminar flow. A correlation factor was derived to quantify the impact of temperature fluctuations on the dynamic viscosity changes on flow resistance. Furthermore, temperature differences between different laminar flows can lead to instabilities between adjacent laminar flows, inducing local flow velocity fluctuations. Therefore, the correlation used to calculate the correlation factor may contain certain errors. Therefore, the correlation factor for each laminar flow is adjusted and integrated based on the temperature and flow velocity differences between monitoring locations to obtain a speed correction weight for the motor speed, thereby improving the accuracy of flow prediction. If the Taylor number corresponding to the motor speed is greater than the critical Taylor number, the fluid flow rate will become more complex. Since the Taylor number is the most important parameter in fluid mechanics, used to quantify the relative magnitude of inertial and viscous forces in fluid flow, the speed correction weight under the motor speed is obtained by calculating the dynamic ratio of the actual Taylor number to the critical Taylor number and the fluctuation of the flow rate value at the monitoring location. Finally, a mapping relationship between the motor speed and the speed correction weight is established, and the speed correction weight is used to adjust the motor speed during the current test process, forming a closed-loop feedback control strategy. This allows the speed regulation to better respond to changes in the flow state, effectively improving the dynamic adaptability of the working condition simulation, thereby improving the accuracy of the working condition simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 A structural diagram of a Taylor-Cooter flow test apparatus under different working conditions provided by one embodiment of the present invention;

[0046] Figure 2 A schematic structural diagram of a control module provided by one embodiment of the present invention;

[0047] Figure 3A flow chart of a method for testing Taylor-Cooter flow under different working conditions provided by one embodiment of the present invention;

[0048] Figure 4 A flow chart of a method for obtaining a first speed correction weight provided by one embodiment of the present invention;

[0049] Figure numerals: 1-medium inlet; 2-induction heater, 3-infrared thermometer, 4-variable frequency motor, 5-laser Doppler velocimeter, 6-flow meter, 7-lower heat insulation board, 8-rotating shaft, 9-housing with radial grooves, 10-upper heat insulation board, 11-medium outlet; 200-processor, 201-memory, 202-bus, 203-communication interface. DETAILED DESCRIPTION

[0050] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, details the Taylor-Cooter flow testing method and apparatus proposed by the present invention under various operating conditions, including its specific implementation, structure, features, and effectiveness. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0051] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0052] The following describes in detail a Taylor-Cooter flow test method and a specific test device under different working conditions provided by the present invention with reference to the accompanying drawings.

[0053] See also Figure 1 , which shows a device structure diagram of a Taylor-Cooter flow test device under different working conditions provided by an embodiment of the present invention.

[0054] Fluid enters the test apparatus from the medium inlet 1 via a flowmeter 6, which ensures fluid entry at a predetermined flow rate. The inner and outer cylindrical annular spaces formed between the radially grooved housing 9 and the rotating shaft 8 within the test apparatus serve as the Taylor-Cooter flow test area. An infrared thermometer 3 and a laser Doppler velocimeter 5 are mounted on the radially grooved housing 9 to obtain temperature and velocity data for the fluid at various monitoring locations along the same axial cross-section of the inner and outer cylindrical annular spaces during each Taylor-Cooter flow test. The monitoring locations are evenly distributed along the outer cylinder radius along the axial cross-section. The test apparatus also incorporates two layers of thermal insulation: a lower insulation board 7 and an upper insulation board 10. This ensures that the fluid flow conditions during testing are simulated to the greatest extent possible, evenly distributing the fluid medium within the cavity. An induction heater 2 further processes the fluid, heating it or performing some other type of treatment. A variable-frequency motor 4 controls the fluid flow within the test apparatus, with the fluid exiting through a medium outlet 11.

[0055] In view of the different temperature loss phenomena exhibited by the fluid during the Taylor-Cooter flow test, which will lead to uneven distribution of fluid viscosity and destroy the preset speed-flow rate model, in an embodiment of the present invention, a control module (not shown in the figure) is also provided in the test device. The control module can be used to adjust the motor speed of the variable frequency motor 4, so that the speed adjustment during the test process can better respond to changes in the flow state and improve the accuracy of the working condition simulation.

[0056] The control module includes at least a memory and a processor, see Figure 2 , which shows a structural schematic diagram of a control module provided in one embodiment of the present invention, including a processor 200, a memory 201, a bus 202 and a communication interface 203, wherein the processor 200, the communication interface 203 and the memory 201 are connected via the bus 202; wherein the memory 201 may include a high-speed random access memory, the bus 202 may be an ISA bus, a PCI bus or an EISA bus, etc., and the processor 200 may be an integrated circuit chip with signal processing capabilities; the memory 201 stores at least one instruction, at least one program, a code set or an instruction set, and when the at least one instruction, at least one program, a code set or an instruction set is loaded and executed by the processor, steps in a test method for Taylor-Cooter flow under different working conditions are implemented.

[0057] See also Figure 3 , which shows a flow chart of a method for testing Taylor-Cooter flow under different working conditions provided by one embodiment of the present invention, the method comprising the following steps:

[0058] Step S1: At each motor speed in the historical test process, multiple monitoring positions are set along the radius of the outer cylinder on the same axial section of the inner and outer cylindrical annular spaces to obtain the temperature and flow rate of the fluid at the monitoring positions within a preset time period.

[0059] Taylor-Coutt flow experiments aim to analyze the transition patterns of flow field structures (such as laminar flow, Taylor vortices, spiral flow, and turbulent flow), as well as angular momentum transfer efficiency and torque characteristics, by varying parameters such as the rotational speed of the inner and outer cylinders and the gap width. When the inner cylinder rotates at a low speed, the flow exhibits a stable laminar state (Couette flow), with a linear velocity distribution and no vortex structures. In this state, the flow is dominated by viscosity, and energy dissipation is uniform. In this embodiment of the present invention, the outer cylinder is stationary.

[0060] According to prior knowledge, laminar flow is a basic flow state in fluid mechanics that describes fluid motion. Its characteristic is that the fluid flows in a smooth, orderly layered form, and the exchange of matter or energy between layers occurs only through molecular diffusion. However, due to the limited thermal insulation effect of the actual test device on the flowing liquid, and the liquid itself loses temperature as it flows and contacts the device, when simulating different actual working conditions, the temperature loss phenomenon of the fluid at different locations is different. For example, high shear areas dissipate heat due to viscous dissipation, while the pipe wall temperature is lower due to heat dissipation, resulting in uneven distribution of fluid viscosity, forming complex flow resistance, and destroying the preset speed-flow rate model.

[0061] Therefore, this embodiment of the present invention adjusts the motor speed in the current test process by analyzing the temperature data and flow rate data of the fluid at each motor speed in the historical test process. Specifically, at the motor speed in each historical test process, multiple monitoring positions can be set along the radius direction of the outer cylinder on the same axial section of the inner and outer cylindrical annular spaces under each laminar flow, and the temperature data and flow rate data of the fluid at each monitoring position can be obtained based on the infrared thermometer 3 and the laser Doppler velocimeter 5.

[0062] It should be noted that, in the embodiment of the present invention, the collection time of the temperature data and flow rate data of the fluid at all monitoring positions must be kept consistent. Specifically, the temperature data and flow rate data can be collected within the third minute after the start of the test, that is, the preset time period is within the third minute after the start of the test. The selection of the specific time period can be adjusted according to the implementation scenario and is not limited here; and in the embodiment of the present invention, the collection of flow rate data is a vector with size and direction.

[0063] According to prior knowledge, the Taylor number is the most important dimensionless parameter in fluid mechanics, used to quantify the relative magnitude of inertial and viscous forces in fluid flow. The Taylor number can be used to predict laminar, turbulent, or transitional states. In the test device, the liquid transitions from laminar to turbulent flow based on the actual inner drum speed. During this process, at low Taylor numbers, viscous forces dominate, and the flow becomes laminar; at high Taylor numbers, inertial forces dominate, and the flow transitions to Taylor-Cooter flow. The actual Taylor number at the motor speed can be compared with the critical Taylor number throughout all historical tests to determine the different states of the fluid, allowing for case-by-case analysis to determine the corresponding speed correction weight at the motor speed, representing the degree of motor speed regulation. In this embodiment of the present invention, the speed correction weight when the motor speed corresponds to a Taylor number less than or equal to the critical Taylor number is used as the first motor speed correction weight, and the speed correction weight when the motor speed corresponds to a Taylor number greater than the critical Taylor number is used as the second speed correction weight.

[0064] In this embodiment of the present invention, the critical Taylor number is set to 1780.

[0065] Step S2: If the Taylor number corresponding to the motor speed is less than or equal to the critical Taylor number; determine the target time, and under each laminar flow, analyze the correlation between the changes in the temperature values ​​and the flow rate values ​​between the monitoring positions at the target time, and determine the correlation factor; according to the difference in the temperature values ​​and the difference in the flow rate values ​​between the monitoring positions at the target time, adjust the correlation factors under each laminar flow and fuse them to obtain the speed correction weight under the motor speed.

[0066] When the actual Taylor number at the motor speed is less than or equal to the critical Taylor number, the viscous force dominates and the fluid state mainly exhibits a laminar flow phenomenon. The induction heater 2 in the test device in the embodiment of the present invention will further process the fluid. At this time, the fluid closer to the inner cylinder will lose heat more slowly than the fluid closer to the outer cylinder. According to prior knowledge, if the fluid speeds at different positions are different, it is mainly affected by the centrifugal force and the viscosity of the liquid. At this time, due to the influence of temperature, the temperature difference at different positions will cause the liquid flow rate at each position point to be different; therefore, under each laminar flow, the reason for the flow rate difference will also be affected by the temperature difference; when the temperature rises, the fluid viscosity decreases and the flow resistance decreases, resulting in an increase in flow rate at the same motor speed, and vice versa.

[0067] Because the laminar flow state is relatively stable, a moment is first randomly selected in the preset time period as the target moment (for example, the middle moment is selected as the target moment in this embodiment of the present invention), and then the correlation between the temperature values ​​and flow rate values ​​between the monitoring positions at the target moment is analyzed to determine the correlation factor, which is used to preliminarily reflect the impact of the dynamic change of viscosity caused by temperature fluctuations on the flow rate.

[0068] Preferably, in one embodiment of the present invention, the method for obtaining the correlation factor includes:

[0069] Under each laminar flow, the monitoring positions (one can be randomly selected under each laminar flow) are arranged in order along the central axis of the outer cylinder to obtain a sorting sequence.

[0070] Under the sorting sequence, calculate the Pearson correlation coefficient of the temperature value sequence and the flow rate value scalar sequence (only the size of the flow rate value is discussed) of the fluid at all monitoring positions at the target time. The value range of the Pearson correlation coefficient is -1~1. The closer it is to 1, the more positive correlation there is between the changes in the temperature value sequence and the flow rate value sequence. Based on the above analysis, it can be considered that the greater the impact of temperature on the flow rate, so the Pearson correlation coefficient is normalized to obtain the correlation factor. The larger the correlation factor, the greater the impact of temperature on the flow rate of the fluid. Given that the value of the Pearson correlation coefficient may be positive or negative, the normalization here can be used. function.

[0071] It should be noted that the calculation process of the Pearson correlation coefficient is a well-known technique and will not be described in detail here.

[0072] Under the laminar state, most of the fluid flow is in a stable state, but the temperature and flow velocity distribution between adjacent laminar flows are uneven, which will induce fluctuations in local flow velocity, that is, the boundary layer effect. Therefore, there may be certain errors in the correlation relationship between the changes in the relevant factors calculated based on the temperature values ​​and flow velocity values ​​under each laminar flow. Therefore, according to the difference in temperature values ​​and flow velocity values ​​between all laminar flow monitoring positions at the target time, the relevant factors under each laminar flow are adjusted and fused, and the speed correction weight at the motor speed of each historical test process is obtained, which improves the flow prediction accuracy and significantly reduces the error of fluid state simulation under complex working conditions.

[0073] Preferably, in one embodiment of the present invention, the method for obtaining the first speed correction weight includes:

[0074] See also Figure 4 , which shows a flow chart of a method for obtaining a first speed correction weight in one embodiment of the present invention, the method comprising the following steps:

[0075] Step S201: Under all laminar flows, cluster analysis is performed on the monitoring locations according to the differences in the temperature values ​​of the fluid between the monitoring locations to obtain clusters.

[0076] When laminar flow occurs, the flow velocity of the liquid between two adjacent layers of liquid will be different, and the temperature will also be different, which will cause instability between adjacent laminar flows and induce local fluctuations. The calculation of the aforementioned correlation factor is to analyze the differences in temperature and flow rate values ​​between different monitoring positions in each laminar flow. At the same position (same height) in different laminar flows, when the temperature difference is large and the flow rate also has a large difference, then it is considered that the boundary layer effect between different laminar flows has a greater impact on the correlation factor, and the confidence level of the correlation factor should be reduced.

[0077] First, cluster analysis can be performed based on the differences in temperature values ​​between monitoring locations to obtain clusters.

[0078] Under all laminar flows, all monitoring positions at the same height along the radius of the outer cylinder were regarded as the same type of monitoring positions, and all monitoring positions were preliminarily classified.

[0079] Then, based on the K-means clustering algorithm and the preset K value, a cluster analysis is performed on each type of monitoring location to obtain the cluster cluster corresponding to each type of monitoring location.

[0080] The distance metric is the absolute value of the difference in the temperature values ​​of the fluid between the monitoring positions at the target time, and the optimal K value obtained based on the elbow method is used as the preset K value.

[0081] At this point, all monitoring locations can be clustered, so that under all laminar flows, among all monitoring locations at the same height, the monitoring locations with higher temperature value similarity are grouped into one cluster, thereby obtaining several clusters with the same or similar temperature distribution.

[0082] It should be noted that the K-means clustering algorithm and the elbow method are both well-known technologies, and the specific processes are not described here in detail.

[0083] Step S202: Select any laminar flow as the target laminar flow and the other laminar flows as comparison laminar flows. Under the target laminar flow, in the cluster to which each monitoring position belongs, analyze the difference characteristics of the temperature value and the difference characteristics of the flow velocity value between the monitoring position belonging to the target laminar flow and the monitoring position belonging to the comparison laminar flow, and determine the influencing factor of each monitoring position under the target laminar flow.

[0084] In the aforementioned cluster analysis, all monitoring locations at the same height under laminar flow are clustered based on temperature values. Therefore, the monitoring locations in some clusters may span multiple laminar flows. Therefore, in this step, the boundary layer effect can be further analyzed on this basis to make preliminary corrections to the relevant factors in the subsequent process.

[0085] For ease of explanation and illustration, one laminar flow is selected as the target laminar flow, and the other laminar flows are selected as comparison laminar flows. Under the target laminar flow, in the cluster to which each monitoring position belongs, at the target time, the absolute value of the difference between the mean of the temperature value of the fluid at the monitoring position belonging to the target laminar flow and the mean of the temperature value of the fluid at the monitoring position belonging to the comparison laminar flow is calculated to obtain a temperature difference factor. The larger the temperature difference factor is, the greater the difference in temperature values ​​at the monitoring positions at the same height is. In the same way, at the target time, the absolute value of the difference between the mean of the flow velocity value scalar of the fluid at the monitoring position belonging to the target laminar flow and the mean of the flow velocity value scalar of the fluid at the monitoring position belonging to the comparison laminar flow is calculated to obtain a flow velocity difference factor. The larger the flow velocity difference factor is, the greater the difference in flow velocity values ​​at the monitoring positions at the same height is.

[0086] When the temperature difference factor is larger and the flow velocity difference factor is also larger, it means that the influence of temperature on fluid velocity is also greater and the boundary layer effect is more obvious. Therefore, the product of the temperature difference factor and the flow velocity difference factor corresponding to each monitoring position under the target laminar flow is normalized and used as the influencing factor of each monitoring position under the target laminar flow. The larger the influencing factor, the greater the local fluctuation of the target laminar flow, and the lower the confidence of the corresponding correlation factor.

[0087] Step S203: Preliminary correction is performed on the relevant factors based on the numerical characteristics and fluctuations of the influencing factors at the monitoring position under each laminar flow, to obtain the viscosity correction factor under each laminar flow.

[0088] Based on the above steps, the impact factor corresponding to each monitoring position under each laminar flow can be obtained. The larger the impact factor, the lower the confidence of the correlation factor corresponding to the laminar flow. Here, the standard deviation of the impact factors of all monitoring positions can be calculated under each laminar flow. The smaller the standard deviation, the smaller the fluctuation of the impact factors of all monitoring positions under the laminar flow, and the more concentrated the distribution. Then, the standard deviation is added to the mean of the impact factors of all monitoring positions. The smaller the sum value, the smaller the local fluctuation of the monitoring position under the laminar flow, and the more concentrated the distribution. Therefore, the confidence of the correlation factor corresponding to the laminar flow is higher. Therefore, the above sum value is negatively correlated and mapped to achieve logical relationship correction to obtain a correction coefficient. The larger the correction coefficient, the higher the confidence of the correlation factor. The negative correlation mapping here can be performed using the formula ,in, It represents the exponential function with the natural constant e as the base, and x represents the independent variable.

[0089] Finally, the product of the correction coefficient corresponding to each laminar flow and the correlation factor is taken as the viscosity correction factor under each laminar flow. At this time, the larger the viscosity correction factor, the greater the influence of temperature on the flow velocity of the fluid.

[0090] Step S204: Under each laminar flow, the difference characteristics of the flow velocity values ​​of the fluid between adjacent monitoring positions are integrated to determine the flow velocity similarity factor.

[0091] As the rotation speed of the inner drum increases, the viscosity between the liquids decreases, and the difference in fluid flow rates between different monitoring positions corresponding to the same laminar flow gradually increases; the greater the difference in fluid flow rates, the lower the dominant weight of the viscosity, and the lower the reference weight of the viscosity correction factor.

[0092] Therefore, under each laminar flow, the monitoring positions are arranged in order along the central axis of the outer cylinder to obtain a sorting sequence.

[0093] Under the sorting sequence, the absolute value of the difference in the flow velocity values ​​of the fluid between each two adjacent monitoring positions at the target time is calculated as the flow velocity difference parameter. The larger the flow velocity difference parameter is, the greater the deviation in the flow velocity value of the fluid between the two adjacent monitoring positions is, and the dominant weight of viscosity needs to be reduced.

[0094] The negative correlation mapping and normalization of the mean values ​​of all velocity difference parameters corresponding to the sorting sequence are used as the velocity similarity factor of each laminar flow. It can be understood that the larger the velocity similarity factor is, the higher the similarity of the velocity values ​​of the fluid between the monitoring positions under each laminar flow, and the higher the reference weight of the viscosity correction factor. The negative correlation mapping and normalization processing here can be used as the formula ,in, It represents the exponential function with the natural constant e as the base, and x represents the independent variable.

[0095] Step S205: The velocity similarity factor of the laminar flow and the viscosity correction factor are integrated to obtain a first speed correction weight at the motor speed in each historical test process.

[0096] Based on the above steps, the velocity similarity factor and viscosity correction factor of each laminar flow can be obtained. When the actual Taylor number at the motor speed is less than or equal to the critical Taylor number, the viscous force dominates and the laminar flow is stable. Therefore, the velocity similarity factor of the laminar flow is used to weight the viscosity correction factor and average it, and the obtained weighted result is directly used as the first speed correction weight at the motor speed in each historical test process. At this time, the motor speed correction weight incorporates the effect of temperature on the flow rate, so it can more accurately reflect the changing characteristics of the fluid viscosity caused by temperature changes. The larger the first speed correction weight, the greater the fluid viscosity, and the variable frequency motor needs to output a larger torque to maintain the speed. Conversely, the smaller the first speed correction weight, the smaller the fluid viscosity, and the closer the state is to the critical state. The speed can be appropriately lowered to maintain laminar flow stability.

[0097] Step S3: If the Taylor number corresponding to the motor speed is greater than the critical Taylor number; based on the numerical difference between the Taylor number at the motor speed and the critical Taylor number, and the change fluctuation of the flow rate value at the monitoring position within the preset time period, the speed correction weight at the motor speed is obtained.

[0098] When the critical Taylor number is reached, and the flow is between the critical Taylor number and the critical threshold of turbulence, the liquid's state transitions from laminar flow to Taylor-Cooter flow. The fluid is no longer a simple circumferential laminar flow, but instead forms pairs of counter-rotating vortex rings. These vortex rings are periodically alternating along the axial direction of the cylinder. Under laminar flow, the flow velocity values ​​at each monitoring position are theoretically parallel to each other, but the direction of the flow velocity also changes, and the flow is axisymmetric about the axis of rotation (i.e., the flow pattern is exactly the same in any circumferential direction at the same axial position). Analysis shows that near critical conditions and with well-controlled parameters, the position, size, and intensity of the vortex cells do not change over time. This is one of the most fundamental differences from subsequent wave-like vortices and turbulence. Therefore, the speed correction weight (second speed correction weight) at the motor speed can be derived based on the numerical difference between the Taylor number and the critical Taylor number at the motor speed, as well as the fluctuations in the flow velocity values ​​at the monitoring position over a preset time period.

[0099] Preferably, in one embodiment of the present invention, the method for obtaining the second speed correction weight includes:

[0100] In the flow rate data at each monitoring position, the modulus of the absolute value of the difference between the flow rate value vectors at each two adjacent moments is used as the flow rate difference coefficient. The smaller the flow rate difference coefficient, the lower the complexity of the change in the flow rate value at the monitoring position at different moments under the current speed, the more stable the fluid state is, and the lower the feedback demand for reducing the motor speed is. Therefore, the mean of all the flow rate difference coefficients corresponding to all monitoring positions is normalized as the first speed adjustment factor. The larger the first speed adjustment factor, the greater the demand for reducing the motor speed.

[0101] The difference between the actual Taylor number and the critical Taylor number is used as the second speed adjustment factor. The larger the second speed adjustment factor, the greater the degree of exceeding the critical state. At this time, the possibility of changes in the position, size and intensity of the vortex cells is greater. In order to maintain stability, the motor speed needs to be lowered.

[0102] Finally, the product of the first speed adjustment factor and the second speed adjustment factor is negatively correlated and normalized to obtain the value as the second speed correction weight under the motor speed. The larger the second speed correction weight, the higher the motor speed needs to be adjusted. Conversely, the smaller the second speed correction weight, the more chaotic the fluid state is, and the speed can be appropriately lowered to maintain fluid stability. The negative correlation mapping and normalization can be performed using the formula ,in, It represents the exponential function with the natural constant e as the base, and x represents the independent variable.

[0103] Step S4: During the current test, the motor speed is adjusted based on the speed correction weight corresponding to the motor speed to obtain an adjusted speed; under the adjusted speed, various parameters during the test are changed to simulate different working conditions.

[0104] Based on the above steps, the speed correction weight corresponding to each motor speed can be obtained. Then, during the current test process, the motor speed can be adjusted based on the speed correction weight corresponding to the motor speed to obtain the adjusted speed.

[0105] Preferably, in one embodiment of the present invention, the method for obtaining the adjusted rotational speed includes:

[0106] The sum of the normalized value of the speed correction weight corresponding to the motor speed of the current test process and the preset parameter is used as the speed adjustment factor. Based on the analysis in steps S2 and S3, it can be seen that the larger the speed correction weight is, the faster the speed of the variable frequency motor can be appropriately increased. Conversely, the smaller the speed correction weight is, the faster the speed of the variable frequency motor can be appropriately decreased. Therefore, the speed correction weight corresponding to the motor speed of the current test process is normalized so that its value range is between 0 and 1. Then, the sum of the normalized value and the preset parameter is used as the speed adjustment factor. In this embodiment of the present invention, the preset parameter is set to 0.5. At this time, the speed adjustment factor is greater than 1, which can achieve an increase in speed. Conversely, the speed adjustment factor is still less than 1, which can achieve a decrease in speed. Normalization is a technical means well known to those skilled in the art. The normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0107] Finally, the product of the speed adjustment factor and the motor speed of the current test process can be used as the adjustment speed of the current test process.

[0108] At this point, by analyzing the impact of temperature changes on the fluid flow rate, the motor speed of the variable frequency motor 4 during the test is adjusted to make it better respond to the flow changes of the fluid. Then, by using the control variable method, by changing various parameters in the test process, such as the gap width, the ratio of the inner and outer cylinder radii, etc., simulations under various working conditions can be performed, thereby improving the dynamic adaptability and accuracy of the working condition simulation.

[0109] In summary, by arranging multiple monitoring locations along the radial direction of the outer cylinder on the same axial cross-section of the inner and outer cylindrical annular spaces, the distribution characteristics of fluid temperature and flow velocity can be accurately captured, providing high-resolution data for subsequent analysis. Different motor speeds correspond to different fluid states, allowing historical test processes to be classified. If the Taylor number corresponding to the motor speed is less than or equal to the critical Taylor number, the fluid is considered to be in a laminar state. Given that temperature differences can cause differences in fluid flow velocity at each monitoring location, the correlation between temperature and flow velocity values ​​was analyzed for each laminar flow. A correlation factor was derived to quantify the impact of temperature fluctuations on the dynamic viscosity changes on flow resistance. Furthermore, temperature differences between different laminar flows can lead to instabilities between adjacent laminar flows, inducing local flow velocity fluctuations. Therefore, the correlation used to calculate the correlation factor may contain certain errors. Therefore, the correlation factor for each laminar flow is adjusted based on the temperature and flow velocity differences between monitoring locations and then integrated to obtain a speed correction weight for each motor speed, thereby improving flow prediction accuracy. If the Taylor number corresponding to the motor speed is greater than the critical Taylor number, the fluid flow rate will become more complex. Since the Taylor number is the most important parameter in fluid mechanics, used to quantify the relative magnitude of inertial and viscous forces in fluid flow, the speed correction weight under the motor speed is obtained by calculating the dynamic ratio of the actual Taylor number to the critical Taylor number and the fluctuation of the flow rate value at the monitoring location. Finally, a mapping relationship between the motor speed and the speed correction weight is established, and the speed correction weight is used to adjust the motor speed during the current test process, forming a closed-loop feedback control strategy. This allows the speed regulation to better respond to changes in the flow state, effectively improving the dynamic adaptability of the working condition simulation, thereby improving the accuracy of the working condition simulation.

[0110] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0111] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A test method for Taylor-Cooter flow under different working conditions, characterized in that: The method comprises: At each motor speed during the historical test process, multiple monitoring positions were set along the radius of the outer cylinder on the same axial cross-section of the annular space between the inner and outer cylinders to obtain the temperature and flow rate of the fluid at the monitoring positions within a preset time period; If the Taylor number corresponding to the motor speed is less than or equal to the critical Taylor number; determine the target time, and under each laminar flow, analyze the correlation between the changes in the temperature values ​​and flow rate values ​​between the monitoring positions at the target time to determine the correlation factor; based on the difference in the temperature values ​​and flow rate values ​​between the monitoring positions at the target time, adjust and fuse the correlation factors under each laminar flow to obtain the speed correction weight at the motor speed; If the Taylor number corresponding to the motor speed is greater than the critical Taylor number; according to the numerical difference between the Taylor number at the motor speed and the critical Taylor number, and the change fluctuation of the flow rate value at the monitoring position within the preset time period, the speed correction weight at the motor speed is obtained; During the current test, the motor speed is adjusted based on the speed correction weight corresponding to the motor speed to obtain the adjusted speed; under the adjusted speed, various parameters during the test are changed to simulate different working conditions.

2. The test method for Taylor-Cooter flow under different working conditions according to claim 1, characterized in that: The method for obtaining the correlation factor includes: Under each laminar flow, the monitoring positions are arranged in order along the central axis of the outer cylinder to obtain a sorted sequence; Under the sorting sequence, the Pearson correlation coefficient of the temperature value sequence and the flow rate value scalar sequence of the fluid at all monitoring positions at the target time is calculated, and the Pearson correlation coefficient is normalized to obtain a correlation factor.

3. The test method for Taylor-Cooter flow under different working conditions according to claim 1, characterized in that: The speed correction weight when the Taylor number corresponding to the motor speed is less than or equal to the critical Taylor number is used as the first speed correction weight, and the speed correction weight when the Taylor number corresponding to the motor speed is greater than the critical Taylor number is used as the second speed correction weight.

4. The test method for Taylor-Cooter flow under different working conditions according to claim 3, characterized in that: The method for obtaining the first speed correction weight includes: Under all laminar flows, all monitoring locations at the same height along the radius of the outer cylinder are considered to be of the same type. Cluster analysis is performed on each type of monitoring location based on the K-means clustering algorithm and the preset K value to obtain the cluster clusters corresponding to each type of monitoring location. The distance metric is the absolute value of the difference in the fluid temperature values ​​between the monitoring locations at the target time. Select one laminar flow as the target laminar flow and the other laminar flows as the comparison laminar flows. Under the target laminar flow, in the cluster to which each monitoring position belongs, analyze the difference characteristics of the temperature value and the difference characteristics of the flow velocity value between the monitoring position belonging to the target laminar flow and the monitoring position belonging to the comparison laminar flow, and determine the influencing factor of each monitoring position under the target laminar flow; Based on the numerical characteristics and fluctuations of the influencing factors at each monitoring position under each laminar flow, the relevant factors are corrected to obtain the viscosity correction factor under each laminar flow; Under each laminar flow, the difference characteristics of the flow velocity values ​​of the fluid between adjacent monitoring positions are integrated to determine the flow velocity similarity factor, wherein the value of the flow velocity similarity factor is a normalized value; The viscosity correction factor is weighted and averaged using the velocity similarity factor of the laminar flow, and the obtained weighted result is used as the first speed correction weight under the motor speed.

5. The test method for Taylor-Cooter flow under different working conditions according to claim 4, characterized in that: The method for obtaining the impact factor includes: Under the target laminar flow, in the cluster to which each monitoring location belongs; At the target time, calculating the absolute value of the difference between the mean temperature value of the fluid at the monitoring position belonging to the target laminar flow and the mean temperature value of the fluid at the monitoring position belonging to the comparison laminar flow to obtain a temperature difference factor; At the target time, calculating the absolute value of the difference between the mean of the flow velocity scalars of the fluid at the monitoring position belonging to the target laminar flow and the mean of the flow velocity scalars of the fluid at the monitoring position belonging to the comparison laminar flow, to obtain a flow velocity difference factor; The product of the temperature difference factor and the flow velocity difference factor corresponding to each monitoring position under the target laminar flow is normalized and used as the influencing factor of each monitoring position under the target laminar flow.

6. The test method for Taylor-Cooter flow under different working conditions according to claim 4, characterized in that: The method for obtaining the viscosity correction factor includes: Under each laminar flow, the standard deviation of the influencing factors of all monitoring locations is added to the mean of the influencing factors of all monitoring locations, and the resulting sum is negatively correlated and mapped to the value used as the correction coefficient; The product of the correction coefficient corresponding to each laminar flow and the correlation factor is used as the viscosity correction factor under each laminar flow.

7. The test method for Taylor-Cooter flow under different working conditions according to claim 4, characterized in that: The method for obtaining the flow velocity similarity factor includes: Under each laminar flow, the monitoring positions are arranged in order along the central axis of the outer cylinder to obtain a sorted sequence; Under the sorting sequence, the absolute value of the difference between the flow velocity values ​​of the fluid at the target time between each two adjacent monitoring positions is calculated as the flow velocity difference parameter; The mean values ​​of all flow velocity difference parameters corresponding to the sorting sequence are negatively correlated and normalized to obtain a value which is used as the flow velocity similarity factor of each laminar flow.

8. The test method for Taylor-Cooter flow under different working conditions according to claim 3, characterized in that: The method for obtaining the second speed correction weight includes: In the velocity data at each monitoring location, the modulus of the absolute value of the difference between the velocity vectors at two adjacent moments is used as the velocity difference coefficient; The normalized value of the mean value of all flow rate difference coefficients corresponding to all monitoring positions is used as the first speed adjustment factor; The difference between the actual Taylor number and the critical Taylor number is used as a second speed adjustment factor; A value obtained by performing negative correlation mapping and normalizing the product of the first speed adjustment factor and the second speed adjustment factor is used as the second speed correction weight at the motor speed.

9. The test method for Taylor-Cooter flow under different working conditions according to claim 1, characterized in that: The method for obtaining the adjusted speed includes: The sum of the normalized value of the speed correction weight corresponding to the motor speed in the current test process and the preset parameter is used as the speed adjustment factor; The product of the speed adjustment factor and the motor speed of the current test process is used as the adjustment speed of the current test process.

10. A test device for Taylor-Cooter flow under different working conditions, characterized in that: The test device includes a shell with radial grooves and a rotating shaft, which form an inner and outer cylindrical annular space. On the same axial section of the inner and outer cylindrical annular space, multiple monitoring positions are set along the radial direction of the outer cylinder. An infrared thermometer and a laser Doppler velocimeter are installed on the shell with radial grooves to obtain temperature data and flow rate data of the fluid at each monitoring position during each Taylor-Cooter flow test. The test device is also provided with a control module, which is used to adjust the motor speed of the variable frequency motor during the current test process according to the speed correction weight of the motor speed during the historical test process, so as to realize the steps of the Taylor-Cooter flow test method under different working conditions as described in any one of claims 1 to 9.

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