A tube bundle convection heat exchange characteristic test experiment system and method based on digital twinning technology

Abstract

The application provides a kind of pipe bundle convection heat transfer characteristic test experimental system and experimental method based on digital twinborn technology, belongs to pipe bundle convection heat transfer characteristic test field.For solving the problem that students are difficult to intuitively analyze the movement of fluid and heat transfer process in the existing heat transfer experiment teaching, it is difficult to deeply understand the complex relationship between heat transfer and fluid mechanics, and the experimental operation and data acquisition function are not intelligent and efficient enough.A virtual and real digital twinborn experiment system is constructed, the virtual twinborn model is continuously optimized through real-time data interaction, the model accuracy and reliability are improved;Compared with the traditional virtual experiment system, the authenticity and reliability of the application are higher;Temperature, pressure field monitoring function can be realized in the area where sensors are difficult to arrange in the structure of pipe bundle heat exchanger, whether there is overtemperature and overpressure can be found in time;And to a certain extent, the temperature and pressure distribution of the system at future time is calculated, the advanced prediction and early warning function is realized to prevent equipment damage or cause safety accidents.

Description

Technical Field

[0001] This invention relates to the field of testing technology for the convective heat transfer characteristics of tube bundle structures, and more specifically, to an experimental system and method for testing the convective heat transfer characteristics of tube bundles based on digital twin technology. Background Technology

[0002] Currently, digital technology has become one of the key driving forces for the development and upgrading of various industries. In the field of industrial production, digital technology, through the introduction of intelligent manufacturing systems, the Internet of Things (IoT), and robotic automation, has achieved precise control and optimized resource allocation in the production process, greatly improving production efficiency and product quality. In energy and power engineering majors, flow heat transfer experiments are an important component of professional courses such as heat transfer / thermal engineering, and are crucial for understanding and mastering the mechanism of heat transfer by fluids in pipes and equipment. In these experiments, by simulating the motion of fluids in actual engineering, the influence of factors such as flow velocity, fluid properties, pipe structure, and temperature difference on heat transfer efficiency can be studied.

[0003] Existing patents, such as a supercritical carbon dioxide device for reactor thermal engineering experimental teaching (patent number: CN202110168687.X) and a desktop air-plate-fin heat exchanger performance testing device (patent number: CN112432798A), provide systems suitable for heat exchanger experimental teaching and reactor thermal hydraulic experimental teaching, respectively. However, they have significant disadvantages in data acquisition, automation, experimental flexibility, and teaching auxiliary functions. This makes it difficult to arrange sensor areas within the tube bundle heat exchanger structure for real-time monitoring of temperature and pressure fields, and it is impossible to effectively achieve advanced prediction and early warning. The system has low calculation speed and a single simulation scenario, making it impossible to achieve multi-scenario simulation. Furthermore, students cannot intuitively observe and participate in the experimental process, resulting in poor experience and failing to meet the needs of modern teaching and scientific research. Summary of the Invention

[0004] The technical problem to be solved by this invention is:

[0005] To address the problems in existing heat transfer experimental teaching systems where students struggle to intuitively analyze fluid motion and heat transfer processes, gain a deeper understanding of the complex interplay between heat transfer and fluid mechanics, and where experimental operation and data acquisition functions are not sufficiently intelligent and efficient.

[0006] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0007] This invention provides an experimental system for testing the convective heat transfer characteristics of tube bundles based on digital twin technology, including a physical experiment module, a virtual twin system module, and a human-computer interaction module.

[0008] The physical experiment module includes an experimental section, a gas path unit, and a measurement and acquisition unit. It is used to introduce heated air into the experimental section through the gas path unit and the heating tube in the experimental section, and to collect data on air flow, air temperature at the inlet and outlet of the experimental section, and pipe wall temperature in the experimental section in real time through the measurement and acquisition unit.

[0009] The virtual twin system module includes a CFD simulation model, a data-driven model, and a Modelica-based virtual system model. It is used to calculate the three-dimensional temperature and velocity fields of the data collected by the physical experiment module and display them in real time through a three-dimensional cloud map. It is also used to display the temperature and pressure results of each node in real time and provide experimental correlation error analysis and correlation correction functions.

[0010] The human-computer interaction module provides an interface for users to interact with the virtual twin system module. Users can set experimental parameters, select steady-state or transient operating conditions, and choose the correlation formula for calculating the friction resistance coefficient and heat transfer coefficient through the human-computer interaction module. After calculation and analysis by the virtual twin system module, the results are displayed in the human-computer interaction module.

[0011] Furthermore, the experimental section includes a square channel and a tube bundle arranged within the square channel. The tube bundle includes several evenly distributed circular electric heating tubes, each of which is connected to a multi-loop power box. This is used to conduct experimental research on the convective heat transfer characteristics under conditions of uniform heating power distribution and non-uniform heat power distribution within the square channel. The tube bundle is divided into an inlet section, a fully developed section, and a turbulence section along the airflow direction.

[0012] The air circuit unit is connected to the inlet of the test section. The air circuit unit includes a voltage frequency converter, a centrifugal induced draft fan and a flow regulating valve connected in sequence, which are used to introduce air with speed and temperature into the test section.

[0013] The measurement and acquisition unit includes a gas mass flow meter, a multi-channel temperature monitoring instrument, and a camera. The gas mass flow meter is used to acquire the air flow rate in the tube bundle in real time. The multi-channel temperature monitoring instrument is used to acquire the air temperature at the inlet and outlet of the experimental section and the tube wall temperature in the experimental section in real time. The camera is used to monitor the entire experimental system.

[0014] Furthermore, it also includes a control unit, which includes a controller. The controller is connected to a multi-loop power box, a voltage inverter, a centrifugal induced draft fan, a flow regulating valve, a gas mass flow meter, a multi-channel temperature monitoring instrument, and a camera, respectively, and is used to control the setting of various parameters in the physical experiment module and collect real-time data of the experimental process.

[0015] Furthermore, the CFD simulation model is used to calculate the three-dimensional temperature and velocity fields, enabling real-time three-dimensional display of the temperature and pressure fields during the experiment; the Modelica-based virtual system model runs synchronously with the physical experiment module, displays the temperature and pressure results of each node in real time, and provides experimental correlation error analysis and correlation correction functions.

[0016] Furthermore, when calculating the friction resistance coefficient, the appropriate correlation formula should be selected according to the type of pipeline;

[0017] When the channel type is a circular tube channel, the correlation is:

[0018] Laminar flow region: λ l =64 / Re

[0019] Turbulent region: λ t =0.3164 / Re 0.25

[0020] Where Re is the Reynolds number; λ1 is the friction drag coefficient in the laminar flow region; λ t The friction drag coefficient in the turbulent region;

[0021] When the channel type is a tube bundle channel, the correlation is:

[0022] Laminar flow region: λ l =C l / Re

[0023] Transition zone: λ tr =λ l (1-ψ) 1 / 3 +λ t ψ 1 / 3

[0024] Turbulent region: λ t =C t / Re 0.18

[0025] Among them, C1 and C t These are empirical values ​​for the laminar and turbulent flow regions, respectively, used to describe the influence of the roughness of the pipe's internal wall on the fluid flow; ψ is the intermittent coefficient.

[0026] When the channel type is a non-circular cross-section channel, the correlation is:

[0027] Turbulent region:

[0028] Among them, A and G * All are geometric constants;

[0029] When the channel type is a non-circular cross-section channel, the correlation is:

[0030] Turbulent region:

[0031] Where C1 is the laminar flow geometric factor;

[0032] When the channel type is a tube bundle channel, the correlation is:

[0033] Turbulent region:

[0034] in:

[0035] Where P / D is the pitch ratio, λ R The friction coefficient is the coefficient of friction when the tube bundle channel is smooth.

[0036] Furthermore, based on the type of calculation relationship, the corresponding correlation for calculating the heat transfer coefficient of the tube bundle channel is selected as follows:

[0037] When the calculation relation is Weisman, Nu cir The calculation formula is as follows:

[0038] Cloburn formula: Nu cir =0.023Re 0.8 Pr 1 / 3

[0039] Where Pr is the Prandtl number;

[0040] The correlation for ψ is calculated as follows:

[0041] Triangular arrangement: 1.1 ≤ P / D ≤ 1.5, ψ = 1.130P / D - 0.2609

[0042] Square arrangement: 1.1≤P / D≤1.3, ψ=1.826P / D-1.0430

[0043] When the calculation relation is Presser, Nu cir The calculation formula is as follows:

[0044] Dittus-Boelter formula: Nu cir =0.023Re 0.8 Pr 0.4

[0045] The correlation for ψ is calculated as follows:

[0046] Triangular arrangement: 1.05≤P / D≤2.2ψ=0.9696+0.0783P / D-0.1283e -2.4(P / D-1)

[0047] Square arrangement: 1.05≤P / D≤1.9ψ=0.9217+0.1478P / D-0.113e -7(P / D-1)

[0048] When the calculation relation is Markoczy, Nu cir The calculation formula is as follows:

[0049] Dittus-Boelter formula: Nu cir =0.023Re 0.8 Pr 0.4

[0050] The correlation for ψ is calculated as follows:

[0051] ψ = 1 + 0.9120Re -0.1 Pr 0.4 (1-2.0043e -B )

[0052] For B,

[0053] Triangular arrangement: 1.0 ≤ P / D ≤ 2.0

[0054] Square arrangement: 1.0 ≤ P / D ≤ 1.8

[0055] When the calculation relation is Markoczy, Nu cir The calculation formula is as follows:

[0056] Dittus-Boelter formula: Nu cir =0.023Re 0.8 Pr 0.4

[0057] The correlation for ψ is calculated as follows:

[0058] ψ=P1P2 / D

[0059] For square and equilateral triangle arrangements: ψ = P / D.

[0060] Furthermore, the human-computer interaction module includes a parameter setting area, a function selection area, a real-time monitoring area for the experimental system, a 3D cloud map display area, a real-time experimental data display area, and an error analysis area.

[0061] The parameter setting area is used by users to set the input values ​​of heating power and Reynolds number, select steady-state or transient operating conditions, and select the correlation formula for calculating the friction resistance coefficient and heat transfer coefficient. The temperature and pressure parameters of the node are displayed by inputting the node position.

[0062] The function selection area is used to select the acquisition channel;

[0063] The real-time monitoring area of ​​the experimental system is used to monitor the actual operation of the experimental system.

[0064] The three-dimensional cloud map display area is used to calculate the velocity field and temperature field data in the tube bundle channel under the current working condition using the virtual twin system module, and output the three-dimensional cloud map of the velocity field and temperature field to the interface in the form of a cloud map.

[0065] The real-time experimental data display area is used to display real-time data changes after parameter settings and function selections;

[0066] The error analysis area is used to analyze different results corresponding to different correlations, including verification points, experimental values, simulated values, and error values.

[0067] This invention provides an experimental method for testing the convective heat transfer characteristics of tube bundles based on digital twin technology, comprising the following steps:

[0068] S100: Activate the physical experiment module and start the centrifugal induced draft fan. Introduce air with speed and temperature into the experimental section by adjusting the voltage inverter and airflow regulating valve. Apply corresponding heating power to the tube bundle of the experimental section through the multi-loop output power box. Real-time acquisition of airflow is also included. The inlet and outlet air temperature and the tube wall temperature of the experimental section are also acquired in real time by a multi-channel temperature monitoring instrument. At the same time, the acquired data is transmitted to the virtual twin system module in real time.

[0069] S200. Click on this experimental system to enter the start interface. Enter your name and student ID to enter the system. Click on the experimental system monitoring and adjust the camera position as needed. In the system interface, by inputting the node position, the system displays the node's temperature and pressure parameters. You can also set the input values ​​for heating power and Reynolds number, select steady-state or transient operating conditions, and choose the correlation formula for calculating the friction resistance coefficient and heat transfer coefficient to view the result deviation. Combine this with the heat transfer teaching content to perform error analysis and correlation correction. In the system interface, select the channel you want to collect data from using the checkboxes, and click the "Start Collection" and "Stop Collection" buttons to collect experimental data in real time and stop collection. The data is displayed in numerical and curve formats.

[0070] S300. By clicking the "Result Error Analysis" button, the system outputs a table, which includes verification points, experimental values, simulation values, and error values. This interface displays different results corresponding to different correlations, and allows users to consider the direction of correlation correction based on the data.

[0071] S400. Students select the specified cloud area and location according to the requirements of the experiment guide, and then click the "Temperature Cloud Map Display" and "Velocity Cloud Map Display" buttons to visualize the velocity cloud map and temperature cloud map.

[0072] Compared with the prior art, the beneficial effects of the present invention are:

[0073] This invention discloses an experimental system and method for testing the convective heat transfer characteristics of tube bundles based on digital twin technology. It constructs a virtual-real integrated digital twin experimental system, fully utilizing physical models, sensor updates, and historical operational data. It integrates multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes, completing mapping in virtual space to reflect the entire lifecycle of the corresponding physical equipment. Compared to traditional virtual experimental systems, this invention offers higher realism and reliability. Furthermore, with the aid of the digital virtual model, it enables temperature and pressure field monitoring in areas of the tube bundle heat exchanger structure where sensors are difficult to place. By monitoring the temperature and pressure of the equipment, it can promptly detect over-temperature and over-pressure situations. It can also calculate the future temperature and pressure distribution of the system to a certain extent, achieving advanced prediction and early warning functions to prevent equipment damage or safety accidents.

[0074] This invention adopts a multi-user virtual system, which can meet the experimental needs of multiple students at the same time without the need to purchase a large number of expensive and complex experimental equipment, thus reducing the economic cost of experiments. At the same time, through the virtual experimental system, students can practice experimental operations without time and space restrictions, improving the accessibility and flexibility of experimental teaching.

[0075] A highly realistic CFD simulation model was established to simulate the heat transfer characteristics of tube bundle flow under different operating conditions. The internal three-dimensional flow and temperature field were vividly and graphically displayed to deepen students' understanding of the knowledge points. The introduction of the data-driven model enabled rapid calculation, thereby realizing real-time interaction between the physical system and the virtual twin system. The virtual experimental system model based on Modelica provided global modeling and offered flow heat transfer correlation modification functions to help students deeply understand the relationship between flow heat transfer and heat transfer parameters.

[0076] This invention realizes real-time monitoring, high-fidelity CFD simulation model, data-driven approach, global modeling, and correlational modification functions, and can be used for experiments on the thermal performance and resistance characteristics of tube bundle heat transfer flow. In addition, this invention can not only be used for university professional courses, but also serve as a similar modeling experimental system for large tube bundle heat exchangers in practical engineering applications. The research results of this system can provide a reference for the operation, maintenance, monitoring, and early warning of large tube bundle heat exchangers. The digital system construction method of this invention is also applicable to large tube bundle heat exchangers and can be extended to the construction of digital twin systems for tube bundle heat exchange structures in practical engineering applications. Attached Figure Description

[0077] Figure 1 This is a structural diagram of a tube bundle convection heat transfer characteristic testing experimental system based on digital twin technology in an embodiment of the present invention;

[0078] Figure 2 This is a physical diagram of the physical experimental module in an embodiment of the present invention;

[0079] Figure 3 The images shown are physical diagrams of a multi-loop power box and schematic diagrams of uniformly and non-uniformly distributed thermal power input in an embodiment of the present invention.

[0080] Figure 4 The figures show the vertical section, cross-sectional view, and physical diagram of the positioning grid of the tube bundle experimental section structure in the embodiment of the present invention.

[0081] Figure 5 This is a curve fitting diagram of the frictional resistance characteristics of the tube bundle channel in an embodiment of the present invention;

[0082] Figure 6 Nu / Pr in the embodiments of the present invention 0.4 Curve fitting plot as Re changes;

[0083] Figure 7 This is a cloud map showing the flow field and temperature field inside the tube bundle structure in an embodiment of the present invention;

[0084] Figure 8 This is a schematic diagram of the bilinear interpolation algorithm in an embodiment of the present invention;

[0085] Figure 9 This is a structural diagram of the virtual experiment system based on Modelica in an embodiment of the present invention;

[0086] Figure 10 This is a functional layout diagram of the main interface of the experimental system in this embodiment of the invention;

[0087] Figure 11 This is a structural diagram of the experimental system in an embodiment of the present invention;

[0088] Figure 12 This is an optimization relationship diagram between the physical experiment module and the virtual experiment system in an embodiment of the present invention;

[0089] Figure 13 This is a diagram showing the experimental system's entry interface and monitoring functions in an embodiment of the present invention.

[0090] Figure 14 This is an interface diagram of the parameter setting area in an embodiment of the present invention;

[0091] Figure 15 This is a diagram showing the real-time curve of experimental data and the function for judging data stability in an embodiment of the present invention;

[0092] Figure 16 These are error analysis diagrams for different correlation types in embodiments of the present invention;

[0093] Figure 17 This is a three-dimensional display diagram of the velocity field and temperature field in the simulation experiment of this invention.

[0094] exist Figure 3 In the non-uniformly distributed heat power input, from left to right are the central pipe heating, the upper left part heating, and the left side heating, respectively. Detailed Implementation

[0095] In the description of this invention, it should be noted that the terms used in the various embodiments, such as "upper," "lower," "front," "rear," "left," and "right," which indicate orientation, are only used to simplify the description of the positional relationships based on the accompanying drawings and do not mean that the components and devices referred to must be operated in accordance with the specific orientations and defined operations, methods, and structures in the specification. Such directional terms do not constitute a limitation of this invention.

[0096] In the description of this invention, it should be noted that the terms "first," "second," and "third" mentioned in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," and "third" may explicitly or implicitly include one or more of that feature.

[0097] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0098] Specific Implementation Plan 1: Combining Figures 1 to 16 As shown, this invention provides an experimental system for testing the convective heat transfer characteristics of tube bundles based on digital twin technology, including a physical experimental module, a virtual twin system module, and a human-computer interaction module.

[0099] The physical experimental module includes an experimental section, a gas path unit, a control unit, and a measurement and acquisition unit.

[0100] The experimental section includes a square channel and a tube bundle installed within the square channel. The tube bundle includes several evenly distributed circular electric heating tubes, each of which is connected to a multi-loop power box. This is used to conduct experimental research on the convective heat transfer characteristics under conditions of uniform and non-uniform heat power distribution within the square channel. The tube bundle is divided into an inlet section, a fully developed section, and a turbulence section along the airflow trajectory.

[0101] The inlet section is three times the diameter or side length of the tube bundle. The cross-section of the tube bundle can be circular or square. Its function is to gradually guide the fluid to a stable flow state within the pipe, reduce non-uniformity, and create conditions for the formation of the fully developed section. The fully developed section is the area where the fluid gradually reaches a stable flow state within the pipe, occupying most of the pipe length, approximately 20 to 40 times the tube bundle diameter. In the fully developed section, the fluid velocity profile is no longer affected by the pipe wall and inlet conditions, and the fluid flow becomes more uniform and predictable, making the measurement of fluid characteristics more accurate. Therefore, the fully developed section can serve as an ideal area for experiments and measurements. The turbulence section is the end region of the pipe, typically within 3 to 5 times the tube bundle diameter at the end of the pipe. Its function is to guide the fluid to flow smoothly out of the pipe and reduce flow instability caused by changes in the geometry of the pipe end.

[0102] The air circuit unit is connected to the variable diameter joint at the inlet of the test section. The air circuit unit includes a voltage frequency converter, a centrifugal induced draft fan and a flow regulating valve connected in sequence, which are used to introduce air at a certain speed and temperature into the test section.

[0103] The measurement and acquisition unit includes a gas mass flow meter, a multi-channel temperature monitoring instrument, and a camera. The gas mass flow meter is used to acquire the air flow rate in the tube bundle in real time. The multi-channel temperature monitoring instrument is used to acquire the air temperature at the inlet and outlet of the experimental section and the tube wall temperature in the experimental section in real time. The camera is used to monitor the entire experimental system.

[0104] The control unit includes a controller, which is connected to a multi-loop power box (physical structure as shown in the image). Figure 3 The following components are connected: a voltage frequency converter (Zhouzheng Technology CBT-1009, DAQM-4206), a centrifugal induced draft fan (Yinben YN5-47), a flow regulating valve (Maisi Intelligent EV4300-1.5G1), a gas mass flow meter (Kuizhuo Instrument KZ-HWL-100), a multi-channel temperature monitoring instrument (Lianyi Instrument TempPatrol SH-X), and a camera (Ezviz C6CN). This is used to control the parameter settings in the physical experiment module and collect real-time data of the experiment process.

[0105] The physical experimental module serves as the physical component of the virtual twin system module. Through experimental studies on the flow resistance and convective heat transfer characteristics of the tube bundle channel, it explores the influence and internal mechanism of different thermal parameters on the flow and heat transfer characteristics within the tube bundle channel. This is used to demonstrate the frictional resistance characteristics and the relationship between heat transfer characteristics and Reynolds number in unconventional tube bundle channels. The frictional resistance characteristic curve of the tube bundle channel is fitted to the heat transfer characteristic of the tube bundle channel, i.e., Nu / Pr. 0.4 Curve fitting as a function of Re is shown below Figure 5 , Figure 6 As shown;

[0106] The virtual twin system module includes a CFD simulation model, a data-driven model, and a Modelica-based virtual system model. The CFD simulation model vividly displays the three-dimensional velocity and temperature fields inside the experimental section to students through visualization, enabling numerous simulation experiments under different working conditions and establishing a database. Due to the slow simulation speed and long processing time of the CFD simulation model, it is difficult to meet the real-time interactive requirements of the digital twin model. Therefore, a data-driven model is introduced. By filtering and classifying the database and using a bilinear interpolation algorithm, the three-dimensional velocity and temperature fields are rapidly calculated, allowing for real-time three-dimensional display of the temperature and pressure fields during the experiment. The bilinear interpolation algorithm is an existing technology, and its principle is as follows... Figure 8 As shown, by performing linear interpolation between known points to estimate the temperature and pressure values ​​at the target location, a smooth transition of the image is achieved, ensuring good visual quality when the image is zoomed in or out; the Modelica-based virtual system model is as follows. Figure 9 As shown, it runs synchronously with the physical experiment module to display the temperature and pressure results of each node in real time, and provides experimental correlation error analysis and correlation correction functions. This function has been embedded in the Modelica-based virtual system module to deepen students' understanding of the flow heat transfer correlations learned in the textbook. When calculating the friction resistance coefficient, the corresponding correlation is selected according to the type of pipe and different working conditions.

[0107] When the channel type is a circular tube channel, the correlation is:

[0108] Laminar flow region: λ l =64 / Re

[0109] Turbulent region: λ t =0.3164 / Re 0.25

[0110] Where Re is the Reynolds number; λ1 is the friction drag coefficient in the laminar flow region; λ t The friction drag coefficient in the turbulent region;

[0111] When the channel type is a tube bundle channel, the correlation is:

[0112] Laminar flow region: λ l =C l / Re

[0113] Transition zone: λ tr =λ l (1-ψ) 1 / 3 +λ t ψ 1 / 3

[0114] Turbulent region: λ t =C t / Re 0.18

[0115] Among them, C1 and C t These are empirical values ​​for the laminar and turbulent flow regions, respectively, used to describe the influence of the roughness of the pipe's internal wall on the fluid flow; ψ is the intermittent coefficient, related to the laminar transition Reynolds number Re. bL and turbulent transition Reynolds number Re bT Related; λ tr The frictional resistance coefficient in the transition zone;

[0116] When the channel type is a non-circular cross-section channel, the correlation is:

[0117] Turbulent region:

[0118] Among them, A and G * All are geometric constants and are functions of Re in laminar flow only;

[0119] When the channel type is a non-circular cross-section channel, the correlation is:

[0120] Turbulent region:

[0121] C1 is called the laminar flow geometry factor, which is determined by the boundary conditions and the geometry of the channel cross section.

[0122] When the channel type is a tube bundle channel, the correlation is:

[0123] Turbulent region:

[0124] in:

[0125] Where P / D is the nodal diameter ratio; λ R The coefficient of friction when the tube bundle channel is smooth;

[0126] Based on the type of calculation relationship, the corresponding tube bundle channel heat transfer coefficient is selected and the correlation is calculated as follows:

[0127] When the calculation relation is Weisman, Nu cir The calculation formula is as follows:

[0128] Cloburn formula: Nu cir =0.023Re 0.8 Pr 1 / 3

[0129] Where Pr is the Prandtl number;

[0130] The correlation for ψ is calculated as follows:

[0131] Triangular arrangement: 1.1 ≤ P / D ≤ 1.5, ψ = 1.130P / D - 0.2609

[0132] Square arrangement: 1.1≤P / D≤1.3, ψ=1.826P / D-1.0430

[0133] When the calculation relation is Presser, Nu cir The calculation formula is as follows:

[0134] Dittus-Boelter formula: Nu cir =0.023Re 0.8 Pr 0.4

[0135] The correlation for ψ is calculated as follows:

[0136] Triangular arrangement: 1.05≤P / D≤2.2ψ=0.9696+0.0783P / D-0.1283e -2.4(P / D-1)

[0137] Square arrangement: 1.05≤P / D≤1.9ψ=0.9217+0.1478P / D-0.113e -7(P / D-1)

[0138] When the calculation relation is Markoczy, Nu cir The calculation formula is as follows:

[0139] Dittus-Boelter formula: Nu cir =0.023Re 0.8 Pr 0.4

[0140] The correlation for ψ is calculated as follows:

[0141] ψ = 1 + 0.9120Re -0.1 Pr 0.4 (1-2.0043e -B )

[0142] For B,

[0143] Triangular arrangement: 1.0 ≤ P / D ≤ 2.0

[0144] Square arrangement: 1.0 ≤ P / D ≤ 1.8

[0145] When the calculation relation is Markoczy, Nu cir The calculation formula is as follows:

[0146] Dittus-Boelter formula: Nu cir =0.023Re 0.8 Pr 0.4

[0147] The correlation for ψ is calculated as follows:

[0148] ψ = P1P2 / D,

[0149] For square and equilateral triangle arrangements: ψ = P / D

[0150] Since convective heat transfer is a key and challenging aspect of heat transfer, as it involves the coupling of flow and heat transfer problems and complex flows such as turbulence and flow around the tube, the internal flow heat transfer mechanism is obscure and difficult for students to understand. Therefore, a high-fidelity CFD simulation model was established for the physical experiment module. This model was used to simulate the heat transfer characteristics of tube bundle flow under different operating conditions, aiming to vividly and graphically demonstrate the internal three-dimensional velocity and temperature fields to students in a visual form.

[0151] Visual interface such as Figure 7 As shown, plane represents the cross-sectional position. Planes 1 through 6 are longitudinal sections, corresponding to the upstream of the positioning grid, the entrance of the positioning grid, the root of the swirl wing, the top of the swirl wing, the downstream of the positioning grid, and the downstream of the positioning grid, respectively. Planes 7 through 10 are transverse sections. Z represents the Z-axis coordinate, which is perpendicular to the entrance section and is used to display the specific geometric position of planes 1 through 6. The entrance of the positioning grid is set to Z = 0. Figure 7 The displayed visualization interface helps students understand and master the laws of internal flow and heat transfer. Among them, the CFD simulation model and the data-driven model focus more on the three-dimensional display of the velocity and temperature fields of the experimental section, while the virtual experimental system model based on Modelica focuses more on global modeling and helps students understand the relationship between flow heat transfer and heat transfer parameters through correlation.

[0152] The human-computer interaction module provides an interface for users to interact with the virtual twin system module. The human-computer interaction module includes a parameter setting area, a function selection area, a real-time monitoring area for the experimental system, a 3D cloud map display area, a real-time experimental data display area, and an error analysis area.

[0153] Combination Figure 14 As shown, the parameter setting area is used by users to set the input values ​​of heating power and Reynolds number, select steady-state or transient operating conditions, and select the correlation formula for calculating the friction resistance coefficient and heat transfer coefficient. The temperature and pressure parameters of the node can be displayed through the input node position.

[0154] The function selection area is used to select the acquisition channel;

[0155] Combination Figure 13 As shown, the real-time monitoring area of ​​the experimental system is used to help students grasp the actual operation of the experimental system. The real-time monitoring area of ​​the experimental system is displayed as the background of the start interface. The status of the experimental system can be clearly seen in the interface. The position of the camera can be flexibly adjusted to view the area of ​​interest as needed.

[0156] Combination Figure 17 As shown, the three-dimensional cloud map display area is used to display three-dimensional cloud maps of the velocity field and temperature field. This function utilizes the virtual twin system module to quickly calculate the velocity field and temperature field data within the tube bundle channel under the current operating conditions, and outputs them to the interface in the form of cloud maps, making it easy for users to understand the overall velocity and temperature distribution. In actual use, students, according to the requirements of the experimental guide, first select the steady-state or transient operating conditions through the parameter setting area, then select the cross-section or overall part and the specific location, and finally click "Temperature Cloud Map Display" and "Velocity Cloud Map Display" to visualize the temperature cloud map and velocity cloud map.

[0157] Combination Figure 15 As shown, the real-time experimental data display area is used to display the changes in experimental data after parameter settings and function selections, helping users to have a clear understanding of the monitored data and to easily grasp the experimental progress. This function collects the friction section pressure difference and temperature data of the measuring point, plots the real-time change curves and displays the real-time values, and automatically prompts and displays the average values ​​of the stable pressure difference and temperature data when the data is stable. In actual use, the user selects the channel to be collected by checking the leftmost checkbox, and then clicks the "Start Collection" button and "Stop Collection" button to collect experimental data in real time and end the collection. The data is displayed in numerical and curve form, showing the interface of partial data collection process, the collection of experimental data for all channels, and the interface of data reaching stability.

[0158] Combination Figure 16 As shown, the error analysis area is used to analyze the different results corresponding to the correlation calculated using different friction resistance coefficients and heat transfer coefficients, including the experimental values, simulation values, and error values ​​of the verification points; after clicking "Result Error Analysis", the corresponding interface will pop up. Through this interface, students can clearly and intuitively see the different results corresponding to different correlations and refer to the data to think about the direction of correlation correction.

[0159] Users can select different regions (inlet section, fully developed section, turbulence section) for experimental research according to experimental requirements. Real-time monitoring of experimental data can be achieved. Sufficient flow field parameters are obtained by CFD simulation based on known input parameter combinations. The target input flow field data is obtained through data-driven model interpolation calculation. After visualization processing, temperature / velocity distribution cloud maps and node parameters are obtained for students to understand the underlying principles of the experiment. Students can select different regions to view the three-dimensional visualized temperature field according to experimental requirements, select different flow heat transfer experimental correlations to view the result deviations, and conduct error analysis and correlation correction in conjunction with heat transfer teaching content.

[0160] Combination Figure 4 As shown, the cross-sectional dimensions of the square channel are 100mm × 100mm. The square channel is composed of 25 stainless steel electric heating tubes with an outer diameter of 10mm arranged in a square. The distance between two adjacent stainless steel electric heating tubes is 19mm. The distance between the stainless steel electric heating tubes located at the edge and the side wall of the square channel is 2.5mm. The rated voltage of the multi-circuit power box is 36V and the rated power is 50W.

[0161] Combination Figure 3 As shown, by heating with electric heating tubes at different positions and in different numbers in the tube bundle, experimental research can be carried out on the convective heat transfer characteristics under conditions of uniform and non-uniform heat power distribution in the tube bundle.

[0162] Combination Figure 1 and Figure 4 As shown, the square pipe is equipped with two support mechanisms, and a flow-dispersing grid (also a positioning grid with a flow-dispersing function) is installed between the two support mechanisms. The space from the inlet to the positioning mechanism is the inlet section, the space from the positioning mechanism to the flow-dispersing grid is the fully developed section, and the space from the flow-dispersing grid to the outlet is the flow-dispersing section. A physical diagram of the flow-dispersing grid is provided. Figure 4 As shown, in addition to its positioning and support function, it is used to stir up the flow field and generate turbulence to enhance heat transfer. It can realize the experimental and analysis of convective heat transfer characteristics under inlet, full development, and turbulence conditions respectively.

[0163] Specific Implementation Plan Two: Combining Figures 1 to 16 As shown, this invention provides an experimental method for testing the convective heat transfer characteristics of tube bundles based on digital twin technology, comprising the following steps:

[0164] S100. Before the experiment, ensure that all experimental equipment is started correctly, and that all real-time acquisition devices and the computer are in working order. During the experiment, first turn on the physical experiment module and the centrifugal fan. Introduce air at a certain speed and temperature into the experimental section by adjusting the voltage inverter and the air volume regulating valve. Apply the corresponding heating power to the tube bundle in the experimental section through the multi-loop output power box. The air flow rate is collected in real time by the data acquisition module. The inlet and outlet air temperatures of the experimental section and the tube wall temperature of the experimental section are collected in real time by the multi-channel temperature monitoring instrument. At the same time, the real-time data is transmitted to the virtual twin system module.

[0165] S200, combined Figure 10 and Figure 13 As shown, click on this experimental system to enter the start interface. After entering your name and student ID, you will enter the system interface. Click the "Real-time Monitoring of Experimental System" button to adjust the camera position as needed. Figure 10 and 14 As shown, the system interface displays the temperature and pressure parameters of a node by inputting its location. Users can also set the input values ​​for heating power and Reynolds number, select steady-state or transient operating conditions, and choose the correlation formula for calculating the frictional resistance coefficient and heat transfer coefficient. This allows users to examine the results using different flow heat transfer experimental correlation formulas, and to perform error analysis and correlation correction in conjunction with heat transfer teaching content. Figure 10 and 15 As shown, in the system interface, you can select the channel you want to collect by checking the leftmost checkbox, and click the "Start Collection" button and "Stop Collection" to collect experimental data in real time and stop the collection. The data is displayed in numerical and curve form. The interface can also display the interface of partial data collection process, the collection of experimental data of all channels, and the interface of data stability.

[0166] S300, combined Figure 10 and 16 As shown, in the system interface, by clicking the "Result Error Analysis" button, the system outputs a table, which includes verification points, experimental values, simulation values ​​and error values. Through this interface, students can clearly and intuitively see the different results corresponding to different correlations, and refer to the data to think about the direction of correlation correction.

[0167] S400, combined Figure 17 As shown, in the system interface, students select a specified cloud area and location according to the requirements of the experiment guide, and then click the "Temperature Cloud Map Display" and "Velocity Cloud Map Display" buttons to visualize the velocity cloud map and temperature cloud map.

[0168] The other combinations and connections in this implementation scheme are the same as in Specific Implementation Scheme 1.

[0169] After implementing each functional module, the implementation effect was tested. The implementation of each function in the interface was displayed in turn. Then, the system performance was analyzed. The performance analysis mainly consisted of the running time of each functional module and the error analysis of the fast calculation module. The display of the main system interface had a long running time due to the arrangement of a large number of components, while the fast calculation of the velocity field and temperature field had a long running time due to the large amount of data. Overall, the system running time was short, meeting the requirement of speed. The error analysis mainly focused on the fast calculation module. In the simulation experiment, ten working conditions were selected for system and simulation calculations and then compared. The average error was 4.77%. This shows that the single-phase convective heat transfer experimental system based on digital twin technology proposed in this invention has high real-time performance and accuracy.

[0170] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A tube bundle counter-current heat exchange characteristic test experimental system based on digital twin technology, characterized in that: It includes a physical experiment module, a virtual twin system module, and a human-computer interaction module. The physical experiment module includes an experimental section, a gas path unit, and a measurement and acquisition unit. It is used to introduce heated air into the experimental section through the gas path unit and the heating tube in the experimental section, and to collect data on air flow, air temperature at the inlet and outlet of the experimental section, and pipe wall temperature in the experimental section in real time through the measurement and acquisition unit. The virtual twin system module includes a CFD simulation model, a data-driven model, and a Modelica-based virtual system model. It is used to calculate the three-dimensional temperature field and three-dimensional velocity field of the data collected by the physical experiment module and display them in real time through a three-dimensional cloud map. It is also used to display the temperature and pressure results of each node in real time and provide experimental correlation error analysis and correlation correction functions. The human-computer interaction module is used to provide an interface for users to interact with the virtual twin system module. Users can set the experimental parameters of the virtual twin system module, select steady-state or transient operating conditions, and select the correlation formula for calculating the friction resistance coefficient and heat transfer coefficient through the human-computer interaction module. After calculation and analysis by the virtual twin system module, the results are displayed in the human-computer interaction module. The experimental section includes a square channel and a tube bundle installed within the square channel. The tube bundle includes several evenly distributed circular electric heating tubes, each of which is connected to a multi-loop power box. This is used to conduct experimental research on the convective heat transfer characteristics under conditions of uniform and non-uniform heating power distribution within the square channel. The tube bundle is divided into an inlet section, a fully developed section, and a turbulence section along the airflow direction. The air circuit unit is connected to the inlet of the test section. The air circuit unit includes a voltage frequency converter, a centrifugal induced draft fan and a flow regulating valve connected in sequence, which are used to introduce air with speed and temperature into the test section. The measurement and acquisition unit includes a gas mass flow meter, a multi-channel temperature monitoring instrument, and a camera. The gas mass flow meter is used to acquire the air flow rate in the tube bundle in real time. The multi-channel temperature monitoring instrument is used to acquire the air temperature at the inlet and outlet of the experimental section and the tube wall temperature in the experimental section in real time. The camera is used to monitor the entire experimental system. It also includes a control unit, which includes a controller. The controller is connected to a multi-loop power box, a voltage inverter, a centrifugal induced draft fan, a flow regulating valve, a gas mass flow meter, a multi-channel temperature monitoring instrument, and a camera, respectively, and is used to control the setting of various parameters in the physical experiment module and collect real-time data of the experiment process. The CFD simulation model is used to calculate the three-dimensional temperature field and the three-dimensional velocity field, enabling real-time three-dimensional display of the temperature field and pressure field during the experiment. The Modelica-based virtual system model runs synchronously with the physical experiment module, displays the temperature and pressure results of each node in real time, and provides experimental correlation error analysis and correlation correction functions.

2. The tube bundle convection heat transfer characteristic test system based on digital twin technology according to claim 1, characterized in that: The human-computer interaction module includes a parameter setting area, a function selection area, a real-time monitoring area for the experimental system, a 3D cloud map display area, a real-time experimental data display area, and an error analysis area. The parameter setting area is used by users to set the input values ​​of heating power and Reynolds number, select steady-state or transient operating conditions, and select the correlation formula for calculating the friction resistance coefficient and heat transfer coefficient. The temperature and pressure parameters of the node are displayed by inputting the node position. The function selection area is used to select the acquisition channel; The real-time monitoring area of ​​the experimental system is used to monitor the actual operation of the experimental system. The three-dimensional cloud map display area is used to calculate the velocity field and temperature field data in the tube bundle channel under the current working condition using the virtual twin system module, and output the velocity field and temperature field three-dimensional cloud map in the form of a cloud map; The real-time experimental data display area is used to display real-time data changes after parameter settings and function selections; The error analysis area is used to analyze different results corresponding to different correlations, including verification points, experimental values, simulated values, and error values.

3. An experimental method for testing the tube bundle convection heat transfer characteristics based on digital twin technology as described in claim 1 or 2, characterized in that, Includes the following steps: S100: Activate the physical experiment module and start the centrifugal induced draft fan. Introduce air with velocity and temperature into the experimental section by adjusting the voltage frequency converter and flow regulating valve. Apply corresponding heating power to the tube bundle in the experimental section through the multi-loop power box. Real-time acquisition of air flow rate, as well as real-time acquisition of air temperature at the inlet and outlet of the experimental section and tube wall temperature by a multi-channel temperature monitoring instrument, and simultaneous transmission of the acquired data to the virtual twin system module. S200. Click on the experimental system to enter the start interface. Enter your name and student ID to enter the system. Click on the experimental system monitoring and adjust the camera position as needed. In the system interface, input the node position to display node temperature and pressure parameters. You can also set the input values ​​for heating power and Reynolds number, select steady-state or transient operating conditions, and select the correlation formula for calculating the friction resistance coefficient and heat transfer coefficient to view the result deviation. Combine the heat transfer teaching content to perform error analysis and correlation correction. In the system interface, select the channel you want to collect data through the check box, and click the "Start Collection" and "Stop Collection" buttons to collect experimental data in real time and stop collection. The data is displayed in numerical and curve form. S300. By clicking the "Result Error Analysis" button, the system outputs a table, which includes verification points, experimental values, simulation values, and error values. It displays different results corresponding to different correlations and allows users to consider the direction of correlation correction based on the data. S400. Students output three-dimensional cloud maps of the velocity and temperature fields in the form of cloud maps, according to the requirements of the experimental manual.

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