A three-dimensional modeling simulation method and system for a T-finned tube out-tube boiling heat exchanger

Abstract

The application relates to the technical field of heat dissipation, and provides a three-dimensional modeling simulation method and system for a T-shaped finned tube out-tube boiling heat exchanger, which comprises the following steps: obtaining effective nucleation point density of each sub-surface in multiple sub-surfaces of a T-shaped finned tube and initial bubble size of each sub-surface; for each sub-surface in the multiple sub-surfaces, determining a boiling type of the sub-surface according to the effective nucleation point density of the sub-surface and the initial bubble size of the sub-surface; the boiling type comprises an easy-boiling surface or a non-easy-boiling surface; for each sub-surface in the multiple sub-surfaces, performing boiling three-dimensional modeling simulation on the sub-surface according to the boiling type of the sub-surface. The accuracy of three-dimensional modeling simulation of the T-shaped finned tube out-tube boiling heat exchanger is improved.

Description

Technical Field

[0001] This application relates to the field of heat dissipation technology, and in particular to a three-dimensional modeling and simulation method and system for a T-shaped finned tube external boiling heat exchanger. Background Technology

[0002] In the design and optimization of industrial heat exchange equipment, engineers have consistently strived to improve energy efficiency and compactness. Especially in developing next-generation high-efficiency industrial heat exchange equipment, such as T-finned tube external boiling heat exchangers for compact refrigeration systems, the market has placed unprecedented demands on energy efficiency ratios and size. This has rendered traditional heat exchanger design methods, such as those relying on simplified two-dimensional models or empirical formulas, inadequate in providing sufficient predictive accuracy. These traditional methods often result in excessively large performance margins during design, making further reduction in equipment size difficult, or causing the equipment's performance to fall short of initial expectations during actual operation.

[0003] Specifically, in the actual manufacturing process, the production of T-shaped finned tubes, including the stretching of the tube, the stamping of the fins, and the connection with the base tube, inevitably leaves microscopic morphological features on the tube wall and fin surface. These microscopic surface inhomogeneities, whether in physical morphology or chemical composition, are not uniformly distributed but exhibit randomness and local differences. In the initial simulation modeling, to simplify calculations and focus on macroscopic geometric effects, these microscopic surface characteristics were idealized and assumed to be uniform and perfect surfaces.

[0004] Due to the microscopic surface inhomogeneities introduced during the manufacturing process, the bubble nucleation behavior is no longer uniform when the refrigerant flows across the surface of the T-finned tube and begins to boil. Tiny cavities of suitable size and shape, as well as areas with low surface energy and poor wettability, are more likely to become effective bubble nucleation sites. Conversely, in areas with overly smooth surfaces, insufficient microscopic defects, or those covered by hydrophilic residues, even if the local superheat reaches the theoretical nucleation conditions, bubbles are difficult to generate effectively, or even higher superheat is required to initiate boiling. This non-uniform distribution of nucleation sites directly leads to significant differences in boiling intensity and bubble generation frequency at different locations within the T-finned tube.

[0005] Ultimately, the aforementioned series of factors—including non-uniform nucleation caused by microscopic surface inhomogeneities, changes in local flow and temperature fields, and the influence of surface properties evolving over time—combined to lead to a significant deviation between the actual heat transfer performance of the prototype and the ideal simulation predictions. While the original three-dimensional simulation model could accurately capture macroscopic geometry and fluid dynamics, it failed to take into account these microscopic surface characteristics and their decisive influence on boiling nucleation, and could not simulate their non-uniform distribution and continuous evolution within the complex T-shaped fin structure. Therefore, it could not accurately predict the heat transfer efficiency and pressure drop of the entire heat exchanger under actual operating conditions. Summary of the Invention

[0006] This application provides a three-dimensional modeling and simulation method and system for T-shaped finned tube external boiling heat exchangers, which can improve the accuracy of three-dimensional modeling and simulation of T-shaped finned tube external boiling heat exchangers.

[0007] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, a three-dimensional modeling and simulation method for an external boiling heat exchanger with T-shaped finned tubes is provided, comprising: obtaining the effective nucleation point density and the initial bubble size of each sub-surface among multiple sub-surfaces of the T-shaped finned tube; determining the boiling type of each sub-surface based on the effective nucleation point density and the initial bubble size; the boiling type includes easily boiling surfaces or not easily boiling surfaces; and performing three-dimensional boiling modeling and simulation on each sub-surface based on its boiling type.

[0008] Through this technical solution, this application can distinguish the boiling type based on the microscopic characteristics (effective nucleation point density and initial bubble size) of different sub-surfaces of T-shaped finned tubes, and perform differentiated three-dimensional modeling and simulation accordingly, thereby more accurately reflecting the non-uniformity in the actual boiling heat transfer process and solving the prediction deviation problem caused by neglecting the microscopic surface characteristics in traditional simulation methods.

[0009] Furthermore, based on the above method, the effective nucleation point density and the initial bubble size of each sub-surface of the T-shaped finned tube are obtained, including: for each sub-surface, obtaining the roughness of the sub-surface and the droplet contact angle of the sub-surface; and determining the effective nucleation point density and the initial bubble size of the sub-surface based on the roughness of the sub-surface and the droplet contact angle of the sub-surface.

[0010] This technical solution enables the indirect and accurate determination of micro-boiling characteristic parameters (effective nucleation point density and initial bubble size) by obtaining easily measurable macroscopic parameters (roughness and droplet contact angle), simplifying the acquisition of microscopic parameters and improving the practicality of the simulation method.

[0011] Furthermore, determining the effective nucleation point density and the initial bubble size of the sub-surface based on the sub-surface roughness and the droplet contact angle of the sub-surface includes: obtaining a first preset correspondence; the first preset correspondence includes a one-to-one correspondence between multiple first pieces of information and multiple second pieces of information, the first pieces of information including a roughness range and a droplet contact angle range, and the second pieces of information including a first effective nucleation point density and a first initial bubble size; using the first information corresponding to the sub-surface roughness and the droplet contact angle of the sub-surface in the first preset correspondence as target first information; using the first effective nucleation point density in the second information corresponding to the target first information in the first preset correspondence as the effective nucleation point density of the sub-surface, and using the first initial bubble size in the second information corresponding to the target first information in the first preset correspondence as the initial bubble size of the sub-surface.

[0012] Through this technical solution, this application can quickly and accurately map macroscopic measurable parameters (roughness and droplet contact angle) to microscopic boiling parameters (effective nucleation point density and initial bubble size) using a preset correspondence, avoiding complex real-time calculations and improving the efficiency and accuracy of parameter acquisition.

[0013] Based on the above, this application further proposes to determine the boiling type of a sub-surface according to the effective nucleation point density and the initial bubble size of the sub-surface, including: obtaining the average curvature of the sub-surface; and determining the boiling type of the sub-surface according to the average curvature, the effective nucleation point density, and the initial bubble size of the sub-surface.

[0014] Through this technical solution, in determining the boiling type of the sub-surface, this application not only considers the microscopic surface characteristics but also introduces the geometric feature of the average curvature of the sub-surface, making the determination of the boiling type more comprehensive and accurate, and better reflecting the influence of the complex geometric structure on the boiling behavior in actual heat exchangers.

[0015] Preferably, determining the boiling type of a sub-surface based on its average curvature, effective nucleation point density, and initial bubble size includes: determining whether the average curvature of the sub-surface is greater than a preset curvature threshold; if the average curvature of the sub-surface is less than or equal to the preset curvature threshold, determining the boiling type of the sub-surface as a non-boiling surface; if the average curvature of the sub-surface is greater than the preset curvature threshold, determining whether the effective nucleation point density of the sub-surface is greater than a preset density threshold, and whether the initial bubble size of the sub-surface is greater than a preset size threshold; if both are true, determining the boiling type of the sub-surface as a boiling surface; otherwise, determining the boiling type of the sub-surface as a non-boiling surface.

[0016] Through this technical solution, this application provides a specific, layered judgment logic to determine the boiling type of the sub-surface. First, it performs preliminary screening by average curvature, and then performs fine judgment by combining the effective nucleation point density and the initial size of the bubbles, making the classification of boiling types more accurate and reasonable.

[0017] In some preferred embodiments, boiling three-dimensional modeling and simulation of the sub-surface is performed based on the boiling type of the sub-surface, including: determining the modeling accuracy of the sub-surface based on the boiling type of the sub-surface; the modeling accuracy of the sub-surface with a boiling type of non-boiling surface is less than the modeling accuracy of the sub-surface with a boiling type of easily boiling surface; and performing boiling three-dimensional modeling and simulation of the sub-surface based on the modeling accuracy of the sub-surface.

[0018] Through this technical solution, this application can dynamically adjust the modeling accuracy according to the boiling type of the sub-surface. High-precision modeling is used for easily boiling surfaces to capture key details, while lower precision is used for non-boiling surfaces to save computing resources. Thus, while ensuring simulation accuracy, simulation efficiency is significantly improved.

[0019] More specifically, the modeling accuracy is the unit mesh size. The modeling accuracy of the sub-surface is determined based on the boiling type of the sub-surface, including: determining whether the boiling type of the sub-surface is an easily boiling surface; if the boiling type of the sub-surface is not an easily boiling surface, determining the modeling accuracy of the sub-surface to be the first unit mesh size; if the boiling type of the sub-surface is an easily boiling surface, obtaining a second preset correspondence; the second preset correspondence includes a one-to-one correspondence between multiple effective nucleation point density ranges and multiple second unit mesh sizes; any second unit mesh size smaller than the first unit mesh size is negatively correlated with the maximum value of the corresponding effective nucleation point density range; the second unit mesh size corresponding to the effective nucleation point density of the sub-surface in the second preset correspondence is taken as the modeling accuracy of the sub-surface.

[0020] Through this technical solution, this application provides a modeling accuracy adjustment strategy based on unit mesh size, and for easily boiling surfaces, it further dynamically adjusts the mesh size according to the effective nucleation point density, thereby achieving more refined resource allocation, ensuring the simulation accuracy of key areas, and optimizing the overall computational cost.

[0021] Based on the above, this application further proposes that, after performing boiling three-dimensional modeling and simulation on the sub-surface according to the boiling type of the sub-surface, the method further includes: obtaining the simulation temperature of the sub-surface whose boiling type is a non-boiling surface during the boiling three-dimensional modeling and simulation process; taking the sub-surface with the simulation temperature greater than a preset temperature threshold as the target sub-surface, and simulating the target sub-surface again.

[0022] Through this technical solution, this application introduces a post-processing optimization mechanism to perform secondary fine simulation on sub-surfaces that are initially judged to be difficult to boil but have a high actual simulation temperature. This effectively makes up for the limitations that may exist in the initial judgment and further improves the accuracy and reliability of the simulation results.

[0023] As a technical improvement, the target sub-surface is simulated again, including: obtaining a third preset correspondence; the third preset correspondence includes a one-to-one correspondence between multiple temperature ranges and multiple third unit mesh sizes; the third unit mesh size corresponding to the temperature range in which the simulation temperature is located in the third preset correspondence is used as the new simulation accuracy of the target sub-surface; the new simulation accuracy of the target sub-surface is greater than the previous simulation accuracy of the target sub-surface; and boiling three-dimensional modeling simulation is performed again on the target sub-surface based on the new simulation accuracy of the target sub-surface.

[0024] Through this technical solution, this application can dynamically adjust its new simulation accuracy (cell mesh size) according to the actual simulation temperature of the target sub-surface, ensuring a more refined simulation of potential "hot spot" areas, thereby more accurately capturing local boiling behavior and further improving the accuracy of simulation results.

[0025] Secondly, this application also discloses a three-dimensional modeling and simulation system for an external boiling heat exchanger of a T-shaped finned tube, comprising: an acquisition device and a processing device; the acquisition device is used to acquire the effective nucleation point density and the initial bubble size of each sub-surface among multiple sub-surfaces of the T-shaped finned tube; the processing device is used to determine the boiling type of each sub-surface according to the effective nucleation point density and the initial bubble size of the sub-surface; the boiling type includes easily boiling surfaces or not easily boiling surfaces; the processing device is used to perform boiling three-dimensional modeling and simulation of each sub-surface according to the boiling type of the sub-surface. Beneficial effects

[0026] This application discloses a three-dimensional modeling and simulation method for an external boiling heat exchanger with T-shaped finned tubes. By obtaining the effective nucleation point density and initial bubble size of each sub-surface of the T-shaped finned tube, the boiling type (easy to boil or difficult to boil) of the sub-surface is determined, and differentiated three-dimensional modeling and simulation are performed on sub-surfaces with different boiling types. This method effectively solves the problem in existing technologies where the influence of micro-surface inhomogeneities of the T-shaped finned tube on boiling nucleation behavior is ignored, leading to significant deviations between simulation results and actual heat exchange performance. By meticulously considering micro-surface characteristics, this application can more accurately capture the differences in boiling intensity and bubble generation frequency in different regions, thereby significantly improving the prediction accuracy of the simulation model. This allows the heat exchanger design to more closely approximate actual operating conditions, avoiding excessive performance margins or insufficient performance. Ultimately, it helps improve the energy efficiency ratio and compactness of the external boiling heat exchanger with T-shaped finned tubes, overcoming the limitations of traditional methods in predicting the performance of complex boiling heat exchangers. Attached Figure Description

[0027] Figure 1 A flowchart illustrating a three-dimensional modeling and simulation method for an external boiling heat exchanger with T-shaped finned tubes provided in this application; Figure 2 A flowchart illustrating another three-dimensional modeling and simulation method for an external boiling heat exchanger with T-shaped finned tubes provided in this application; Figure 3 A flowchart illustrating another three-dimensional modeling and simulation method for an external boiling heat exchanger with T-shaped finned tubes provided in this application; Figure 4 This is a schematic diagram of the architecture of a three-dimensional modeling and simulation system for a T-shaped finned tube external boiling heat exchanger provided in this application. Detailed Implementation

[0028] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0029] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0030] Traditional 3D modeling and simulation methods for external boiling heat exchangers with T-fins often rely on simplified 2D models or estimations based on empirical formulas during equipment design and optimization, resulting in insufficient prediction accuracy. This not only leads to excessively large performance margins in the design, limiting further reduction in equipment size, but may also cause actual operating performance to fall short of expectations. Particularly during manufacturing, the microstructure of the T-finned tube surface can cause non-uniformity in bubble nucleation behavior, leading to significant deviations between actual heat transfer performance and ideal simulation predictions.

[0031] In this regard, such as Figure 1 As shown, a three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger includes: S101. Obtain the effective nucleation point density and the initial bubble size of each sub-surface of the T-shaped finned tube.

[0032] S102. For each of the multiple sub-surfaces, determine the boiling type of the sub-surface based on the effective nucleation point density and the initial bubble size of the sub-surface.

[0033] Boiling types include easily boiling surfaces and non-boiling surfaces.

[0034] S103. For each of the multiple sub-surfaces, perform three-dimensional boiling modeling and simulation of the sub-surface according to the boiling type of the sub-surface.

[0035] This application aims to provide a more accurate and efficient 3D modeling and simulation method for external boiling heat exchangers with T-shaped finned tubes. By introducing the effective nucleation point density and initial bubble size of the sub-surface layer, and determining the boiling type of the sub-surface accordingly, this application can more precisely capture the influence of the microscopic properties of the T-shaped finned tube surface, thereby significantly improving the accuracy of the simulation results and providing strong support for the optimized design of heat exchangers.

[0036] To better understand the technical solutions proposed in this application, some key terms are explained first. T-finned tubes are a common type of heat transfer enhancement element, whose surface is typically divided into multiple sub-surfaces, each representing a local area on the tube wall or fin. Effective nucleation point density refers to the number of microscopic defects per unit area capable of effectively forming bubbles, directly affecting the initiation and intensity of boiling. Initial bubble size refers to the initial diameter of the bubble when it detaches from the nucleation point, closely related to factors such as surface tension, superheat, and nucleation point geometry. Boiling type, in this application, is divided into easily boiling surfaces and difficult-to-boil surfaces, used to characterize the ease of boiling of different sub-surfaces under given heat flux conditions. Easily boiling surfaces typically have a higher effective nucleation point density and a suitable initial bubble size, enabling earlier and more frequent bubble formation; conversely, difficult-to-boil surfaces do not.

[0037] The method proposed in this application first requires obtaining the effective nucleation site density and the initial bubble size of each sub-surface of the T-shaped finned tube. In practice, this step can be achieved in various ways. For example, experimental measurements can be used, such as analyzing the microstructure of each sub-surface of the T-shaped finned tube using atomic force microscopy (AFM) or scanning electron microscopy (SEM), combined with surface wettability testing, to indirectly or directly estimate the effective nucleation site density and the initial bubble size.

[0038] Another approach is to utilize existing databases or empirical formulas for estimation. For example, for T-finned tubes made of different materials, processed using different techniques, and with different surface treatments, a database containing the correspondence between surface roughness, droplet contact angle, effective nucleation point density, and initial bubble size can be pre-established. During simulation, only the surface roughness and droplet contact angle need to be input to retrieve the corresponding effective nucleation point density and initial bubble size from the database.

[0039] After obtaining the effective nucleation point density and initial bubble size for each sub-surface, the next step is to determine the boiling type of each sub-surface based on its effective nucleation point density and initial bubble size. The boiling type is defined as either a readily boiling surface or a not readily boiling surface. The method for determining the boiling type can be based on preset thresholds. For example, an effective nucleation point density threshold and an initial bubble size threshold can be set.

[0040] If the effective nucleation point density and initial bubble size of a sub-surface are both greater than the corresponding threshold, the sub-surface is classified as a readily boiling surface; otherwise, it is classified as a non-boiling surface. This classification method can quickly categorize sub-surfaces, providing a basis for subsequent modeling and simulation.

[0041] Finally, for each of the multiple sub-surfaces, a 3D boiling modeling simulation is performed based on the boiling type of the sub-surface. In this step, the simulation strategy and parameters can be adjusted according to the boiling type of the sub-surface. For example, for easily boiling surfaces, due to their more active bubble nucleation and growth behavior, a finer mesh and a more complex boiling model can be used for simulation to capture their detailed heat transfer and hydrodynamic characteristics.

[0042] For surfaces that are not easily boilable, due to their relatively inactive boiling behavior, a coarser mesh and a simplified boiling model can be used for simulation. This significantly reduces computational costs and simulation time while maintaining a certain level of accuracy. This differentiated simulation strategy effectively balances simulation accuracy and computational efficiency, making the entire 3D modeling and simulation process more efficient and practical.

[0043] The three-dimensional modeling and simulation method for T-shaped finned tube external boiling heat exchangers proposed in this application introduces the effective nucleation point density and initial bubble size of the sub-surface layer, and determines the boiling type of the sub-surface accordingly, thereby realizing a differentiated modeling and simulation strategy. This effectively solves the problem of insufficient accuracy caused by neglecting microscopic surface characteristics in traditional simulation methods.

[0044] Specifically, in traditional methods, the surface of T-finned tubes is typically idealized as a uniform and perfect surface, which differs significantly from the microscopic inhomogeneities present in actual manufacturing processes. This idealization causes simulation models to fail to accurately predict the non-uniformity of bubble nucleation in actual heat exchangers, leading to discrepancies between simulation results and actual performance.

[0045] This application obtains the effective nucleation point density and initial bubble size of each sub-surface, and determines the boiling type of the sub-surface based on these parameters, thereby enabling a more precise characterization of the influence of these parameters on the microscopic properties of the T-finned tube surface. For example, sub-surfaces with high effective nucleation point density and suitable initial bubble size are identified as easily boiling surfaces and can be simulated using a more refined simulation strategy; while sub-surfaces with inactive boiling are identified as difficult to boil and can be simulated using a relatively simplified simulation strategy.

[0046] Compared with existing technologies, the core innovation of this application lies in its introduction of microscopic surface characteristics (such as effective nucleation point density and initial bubble size) into macroscopic three-dimensional modeling and simulation. Based on these microscopic characteristics, different sub-surfaces are classified into boiling types, and differentiated simulation strategies are then employed. This method can more accurately reflect the boiling heat transfer behavior of T-shaped finned tubes under actual operating conditions, significantly improving the accuracy of simulation predictions.

[0047] In this way, engineers can more accurately evaluate the performance of heat exchangers and optimize their structural design, thereby further reducing the size of the equipment while ensuring energy efficiency, and meeting the growing market demand for high-efficiency, compact heat exchangers. The implementation of this application will help overcome the limitations of traditional simulation methods in predictive accuracy, providing more reliable technical support for the design and development of next-generation high-efficiency industrial heat exchange equipment.

[0048] Specifically, such as Figure 2 As shown, in some embodiments of the above-mentioned three-dimensional modeling and simulation method for external boiling heat exchangers of T-shaped finned tubes, the steps of obtaining the effective nucleation point density of each sub-surface and the initial bubble size of each sub-surface in the multiple sub-surfaces of the T-shaped finned tube can be further refined.

[0049] The acquisition process includes: S201. For each of the multiple sub-surfaces, obtain the roughness of the sub-surface and the droplet contact angle of the sub-surface.

[0050] S202. Determine the effective nucleation point density and the initial bubble size of the sub-surface based on the roughness of the sub-surface and the droplet contact angle of the sub-surface.

[0051] Among these, the surface roughness refers to the degree of undulation in the microscopic geometry of the subsurface, which can usually be quantified using a surface roughness measuring instrument, such as a profilometer or atomic force microscope. The droplet contact angle of the subsurface refers to the angle between the liquid droplet formed on the solid surface and the solid surface; it reflects the wettability of the liquid on the solid surface and can be measured using a contact angle measuring instrument. These parameters are key microscopic geometric and physical properties affecting the performance of boiling heat transfer surfaces.

[0052] The proposed method, by acquiring the roughness and droplet contact angle of the sub-surface, can more accurately characterize the microscopic properties of the sub-surface. Roughness directly affects the number and geometry of available nucleation sites on the surface, while the droplet contact angle reflects the interaction between the surface and the fluid, thus influencing bubble formation and detachment behavior. By comprehensively considering these two parameters, a physical correlation can be established between them and the effective nucleation site density and the initial bubble size, thereby providing more accurate input data for subsequent boiling type determination and 3D modeling simulation.

[0053] The above technical solution enables the determination of the effective nucleation point density and initial bubble size on the surface of a T-shaped finned tube based on measurable microscopic surface characteristics (roughness and droplet contact angle). This avoids the difficulty of directly measuring these hard-to-obtain parameters, improving the convenience and accuracy of data acquisition. Consequently, it provides more reliable basic data for subsequent boiling type determination and 3D modeling simulation, thereby enhancing the accuracy and reliability of the entire simulation method.

[0054] Specifically, in some of the above embodiments, the effective nucleation point density of the sub-surface and the initial size of the bubbles on the sub-surface can be determined in the following ways.

[0055] like Figure 3 As shown, this application further proposes a step for determining the effective nucleation point density and the initial bubble size of the sub-surface based on the sub-surface roughness and the droplet contact angle of the sub-surface, including: S301. Obtain the first preset correspondence.

[0056] The first preset correspondence includes a one-to-one correspondence between multiple first pieces of information and multiple second pieces of information. The first pieces of information include the roughness range and the droplet contact angle range. The second pieces of information include the density of the first effective nucleation points and the initial size of the first bubble.

[0057] S302. The first information corresponding to the roughness of the sub-surface and the droplet contact angle of the sub-surface in the first preset correspondence is taken as the target first information.

[0058] S303. The density of the first effective nucleation points in the second information corresponding to the first target information in the first preset correspondence is taken as the density of the effective nucleation points of the sub-surface, and the initial size of the first bubble in the second information corresponding to the first target information in the first preset correspondence is taken as the initial size of the bubble of the sub-surface.

[0059] Specifically, the first pre-defined correspondence can be understood as a pre-established lookup table, database, or mathematical model. Its purpose is to quickly and accurately obtain the corresponding effective nucleation point density and initial bubble size based on the known subsurface roughness and droplet contact angle. Here, multiple pieces of first information refer to combinations of roughness ranges and droplet contact angle ranges; for example, a roughness between 0.1 μm and 0.5 μm and a droplet contact angle between 30° and 60°. Multiple pieces of second information correspond to the first effective nucleation point density and the first initial bubble size under these range combinations. This one-to-one correspondence ensures that for any given combination of roughness and droplet contact angle, a uniquely determined effective nucleation point density and initial bubble size can be found.

[0060] In practical applications, after obtaining the roughness and droplet contact angle of a specific sub-surface, the system matches them with the first information in a first preset correspondence to find the corresponding target first information. Subsequently, the first effective nucleation point density and the first initial bubble size are extracted from the second information associated with this target first information and used as the effective nucleation point density and the initial bubble size of the sub-surface, respectively. This method based on preset correspondence avoids complex real-time calculations and improves the efficiency and accuracy of parameter determination.

[0061] This application's solution establishes a first pre-defined correspondence between surface roughness, droplet contact angle, effective nucleation point density, and initial bubble size. This allows for convenient direct lookup or mapping of key boiling parameters (effective nucleation point density and initial bubble size) based on the physical properties of the subsurface (roughness and droplet contact angle) during 3D modeling and simulation of a T-shaped finned tube external boiling heat exchanger. This method leverages the intrinsic relationship between material surface properties and boiling phenomena, parameterizing the complex physical process and thus simplifying the parameter acquisition process.

[0062] The above technical solution enables rapid and accurate determination of the effective nucleation point density and initial bubble size on the surface of T-shaped finned tubes. Compared to traditional methods that obtain these parameters through complex experimental measurements or theoretical calculations, this application utilizes a pre-defined correspondence, significantly improving the efficiency of parameter acquisition and reducing computational complexity. This provides reliable and efficient data support for subsequent boiling type determination and 3D modeling simulation, enhancing the practicality and engineering application value of the entire simulation method.

[0063] This application further proposes a three-dimensional modeling and simulation method for an external boiling heat exchanger with T-shaped finned tubes, wherein the boiling type of the sub-surface is determined based on the effective nucleation point density and the initial bubble size of the sub-surface, including: Obtain the average curvature of the sub-surface; determine the boiling type of the sub-surface based on the average curvature, the effective nucleation point density of the sub-surface, and the initial bubble size of the sub-surface.

[0064] Specifically, obtaining the average curvature of a sub-surface refers to acquiring the degree of curvature of each sub-surface of a T-finned tube in a local region through geometric analysis or numerical calculation. Average curvature is an important parameter describing surface geometry; its magnitude and sign reflect the surface's unevenness. For example, for a given sub-surface, its average curvature can be obtained by averaging the two principal curvatures at each point on that surface. In practical applications, the average curvature of the sub-surface can be calculated by geometrically processing the CAD model of the T-finned tube or by surface fitting using scanned data.

[0065] The method of determining the boiling type of a subsurface based on its average curvature, effective nucleation point density, and initial bubble size can be understood as comprehensively considering both the macroscopic geometric features and microscopic surface properties of the subsurface. The effective nucleation point density characterizes the number of microscopic defects that can potentially form bubbles per unit area, while the initial bubble size reflects the initial size of the bubble during the nucleation stage. The average curvature, from a geometric perspective, influences the bubble growth space, surface tension distribution, and the adhesion between the bubble and the surface. By combining these three parameters, a more comprehensive and accurate assessment of the boiling behavior of the subsurface can be achieved.

[0066] This application addresses the limitations of relying solely on microscopic surface properties to determine boiling type by introducing the average curvature of the subsurface. Average curvature, as a macroscopic geometric feature, directly influences local fluid dynamics and thermodynamic conditions. For example, in concave regions, bubbles may be more easily trapped and grow, thus promoting boiling; while in convex regions, bubbles may detach more easily from the surface, or nucleation conditions may be suppressed. Due to the significant impact of average curvature on bubble dynamics, combining it with the effective nucleation point density and initial bubble size more accurately reflects the subsurface's performance in the actual boiling process. This comprehensive consideration makes the determination of boiling type more consistent with physical reality, thus providing more reliable input for subsequent simulations.

[0067] By incorporating the average curvature of the sub-surface into the boiling type determination process using the aforementioned technical solutions, the accuracy and reliability of boiling type identification are significantly improved. This allows for more precise 3D modeling and simulation of external boiling heat exchangers with T-finned tubes to capture the boiling characteristics of different sub-surface regions, especially in areas with complex geometries. Consequently, the simulation results more realistically reflect the actual heat exchange process, providing more accurate data support for heat exchanger design optimization and performance prediction, thus enhancing the practical value and engineering guidance significance of the entire simulation method.

[0068] In some preferred embodiments, specifically, when determining the boiling type of a sub-surface, the average curvature of the sub-surface is first obtained. A sub-surface with a high effective nucleation point density and a large initial bubble size typically indicates it to be a readily boiling surface. However, if the average curvature of the sub-surface shows it to be a highly convex region, this convexity may cause bubbles to detach before reaching a large size or inhibit stable bubble growth. In this case, even if the microscopic properties are favorable for boiling, the macroscopic curvature may still classify it as a non-boiling surface. Conversely, if a sub-surface has a moderate effective nucleation point density and initial bubble size, but its average curvature shows it to be a distinctly concave region, this concavity may form bubble traps, promoting stable bubble growth and aggregation, thus classifying it as a readily boiling surface. By establishing a multi-parameter decision model, such as one based on fuzzy logic, neural networks, or pre-defined judgment rules, taking the average curvature, effective nucleation point density, and initial bubble size as inputs, and outputting the boiling type of the sub-surface (readily boiling surface or non-readily boiling surface), a more intelligent and accurate classification can be achieved.

[0069] This application further proposes a method for determining the boiling type of a sub-surface based on the average curvature of the sub-surface, the effective nucleation point density of the sub-surface, and the initial bubble size of the sub-surface. The specific steps include: Determine whether the average curvature of the sub-surface is greater than a preset curvature threshold; if the average curvature of the sub-surface is less than or equal to the preset curvature threshold, determine that the boiling type of the sub-surface is a non-boiling surface; if the average curvature of the sub-surface is greater than the preset curvature threshold, determine whether the effective nucleation point density of the sub-surface is greater than a preset density threshold, and whether the initial bubble size of the sub-surface is greater than a preset size threshold; if both are true, determine that the boiling type of the sub-surface is a boiling surface; otherwise, determine that the boiling type of the sub-surface is a non-boiling surface.

[0070] Specifically, when determining the boiling type of a sub-surface, the average curvature of the sub-surface is first evaluated. Average curvature is an important parameter for measuring the degree of surface curvature; for the boiling process, a larger curvature generally means greater potential for bubble formation and release. Therefore, by comparing the average curvature of the sub-surface with a preset curvature threshold, surfaces with insufficient curvature to support efficient boiling can be preliminarily screened. The preset curvature threshold can be set according to the actual application scenario, fluid properties, and the geometric characteristics of the T-finned tube; for example, it can be obtained through experimental data or empirical formulas.

[0071] Furthermore, if the average curvature of a sub-surface is less than or equal to a preset curvature threshold, the sub-surface is directly identified as a surface that is not prone to boiling. This means that even if the surface may have other features that are conducive to boiling, its overall geometry (curvature) is insufficient to support an effective boiling process.

[0072] However, if the average curvature of the sub-surface exceeds a preset curvature threshold, a more in-depth assessment is required. This involves further determining whether the effective nucleation point density of the sub-surface exceeds a preset density threshold, and whether the initial bubble size on the sub-surface exceeds a preset size threshold. The effective nucleation point density reflects the number of microscopic defects per unit area available for bubble growth, while the initial bubble size is related to the initial diameter of the bubble when it begins to grow at the nucleation point. These two parameters are key indicators for measuring surface boiling activity. The preset density threshold and preset size threshold can also be determined based on experimental data, theoretical models, or engineering experience to ensure the accuracy of the classification.

[0073] Specifically, a sub-surface is identified as a readily boiling surface only when its average curvature, effective nucleation point density, and initial bubble size all meet their respective threshold conditions: the average curvature is greater than a preset curvature threshold, the effective nucleation point density is greater than a preset density threshold, and the initial bubble size is also greater than a preset size threshold. Otherwise, if any one of the above three conditions is not met, the sub-surface is still identified as a non-boiling surface, even if the average curvature is high.

[0074] This application's solution introduces multiple judgment conditions and preset thresholds to classify the boiling types of sub-surfaces more precisely and accurately. First, the average curvature, as a macroscopic geometric feature, can quickly identify surfaces that are not prone to boiling due to geometric limitations, avoiding unnecessary subsequent complex judgments on these surfaces. Second, for surfaces whose curvature meets the conditions, a comprehensive judgment is made by combining two microscopic boiling characteristic parameters: effective nucleation point density and initial bubble size. This hierarchical and progressive judgment logic ensures that a surface is identified as a readily boiling surface only when both macroscopic geometric conditions and microscopic boiling activity conditions are met. Therefore, this solution can more realistically reflect the actual boiling characteristics of T-finned tube surfaces, avoiding misjudgments that may result from single-parameter judgments, thus providing more reliable input for subsequent 3D modeling and simulation.

[0075] The above technical solution significantly improves the accuracy and reliability of surface boiling type determination in 3D modeling and simulation of T-finned tube external boiling heat exchangers. This multi-parameter, multi-threshold-based judgment mechanism makes the boiling type classification more consistent with the actual physical process, avoiding errors caused by simple or single-parameter judgments. Specifically, for surfaces with low curvature, they can be quickly and accurately identified as non-boiling surfaces, reducing unnecessary computational resource consumption; while for surfaces with high curvature, their microscopic boiling characteristics are comprehensively considered to ensure accurate identification of easily boiling surfaces. This precise classification provides high-quality input data for subsequent 3D boiling modeling and simulation, thereby improving the accuracy and predictive ability of the entire simulation method and helping to more accurately evaluate the performance of the heat exchanger.

[0076] In some preferred embodiments, a specific example is given below. Suppose that when determining the boiling type of a sub-surface of a T-shaped finned tube, the average curvature of that sub-surface is first obtained to be 0.05 mm. -1 The preset curvature threshold is set to 0.03mm. -1 Due to 0.05mm -1 Greater than 0.03mm -1 Therefore, the sub-surface enters the second stage of judgment.

[0077] Next, the effective nucleation point density of the sub-surface was determined to be 1000 nucleation points / mm², and the initial bubble size was 0.1 mm. The preset density threshold was set to 800 nucleation points / mm², and the preset size threshold was set to 0.08 mm.

[0078] At this point, it is determined whether the effective nucleation point density of 1000 nucleation points / mm² is greater than the preset density threshold of 800 nucleation points / mm² (yes), and whether the initial bubble size of 0.1 mm is greater than the preset size threshold of 0.08 mm (yes). Since both conditions are met, the sub-surface is identified as an easily boiling surface.

[0079] Conversely, if the average curvature of the other sub-surface is 0.06 mm -1 (greater than the preset curvature threshold of 0.03mm) -1 However, its effective nucleation point density is 700 / mm² (less than the preset density threshold of 800 / mm²), and even if the initial bubble size is 0.12mm (greater than the preset size threshold of 0.08mm), the sub-surface will still be identified as a non-boiling surface.

[0080] For example, if the average curvature of a certain sub-surface is 0.02 mm -1 (less than or equal to the preset curvature threshold of 0.03mm) -1 If the effective nucleation point density and initial bubble size are not significant, then the sub-surface will be directly identified as a non-boiling surface.

[0081] This layered and comprehensive judgment mechanism ensures accurate and reliable classification of the boiling type on the surface of T-shaped finned tubes.

[0082] This application proposes a method to optimize the three-dimensional modeling and simulation process of sub-surface boiling. By determining the modeling accuracy based on the boiling type of the sub-surface, a balance between computational efficiency and simulation accuracy can be achieved.

[0083] In some embodiments described above in this application, boiling three-dimensional modeling and simulation of the sub-surface are performed based on the boiling type of the sub-surface, specifically including: The modeling accuracy of a sub-surface is determined based on its boiling type; the modeling accuracy of a sub-surface with a boiling type that is not easily boilable is less than that of a sub-surface with a boiling type that is easily boilable; and boiling 3D modeling and simulation of the sub-surface is performed based on the modeling accuracy of the sub-surface.

[0084] Specifically, modeling accuracy refers to the level of detail used in 3D modeling and simulation, which affects the accuracy of simulation results and the consumption of computational resources. For example, modeling accuracy can be reflected in the mesh density, the choice of time step, and the complexity of the physical model. Specifically, the modeling accuracy for sub-surfaces with a boiling type of non-boiling is set to be lower than that for sub-surfaces with a boiling type of boiling. This means that for surfaces with inactive boiling behavior, a relatively lower modeling accuracy can be used for simulation to save computational resources; while for surfaces with active boiling behavior, a relatively higher modeling accuracy is required to more accurately capture their complex boiling phenomena. Therefore, performing 3D boiling modeling and simulation of sub-surfaces based on their modeling accuracy ensures that sub-surfaces with different boiling characteristics receive simulation processing commensurate with their importance.

[0085] This application's solution effectively addresses the challenge of balancing efficiency and accuracy in traditional methods by introducing a mechanism that "determines the modeling accuracy of sub-surfaces based on their boiling type." Specifically, since easily boiling surfaces are the primary areas for boiling heat transfer, the generation, growth, and detachment of bubbles significantly impact heat transfer performance, thus requiring higher modeling accuracy to precisely capture these complex microscopic phenomena. Conversely, for non-boiling surfaces, boiling activity is relatively weak, contributing less to overall heat transfer; therefore, their modeling accuracy can be appropriately reduced to minimize unnecessary computation. This differentiated modeling accuracy setting allows for a more rational allocation of computational resources, concentrating more computational power on critical easily boiling regions while avoiding overly detailed calculations in non-critical areas.

[0086] Through the above technical solution, this application can significantly improve the efficiency of 3D modeling and simulation of T-shaped finned tube external boiling heat exchangers, while ensuring the simulation accuracy of key areas (i.e., easily boiling surfaces). This adaptive modeling accuracy adjustment strategy makes the simulation process more efficient and economical, avoiding the problems of wasted computational resources or loss of key information caused by uniform accuracy in traditional methods. Therefore, this application significantly shortens the simulation cycle and reduces computational costs while ensuring the reliability of simulation results, providing a more practical and efficient tool for heat exchanger design optimization.

[0087] In some preferred embodiments, as a specific implementation, it is assumed that when performing three-dimensional boiling modeling simulation on multiple sub-surfaces of a T-shaped finned tube, the boiling type of each sub-surface is first determined based on the effective nucleation point density and initial bubble size. If a sub-surface is determined to be easily boiling, it is assigned higher modeling precision, such as using fine meshing and a smaller time step, to capture its complex phase transitions and bubble dynamics. Conversely, if a sub-surface is determined to be difficult to boil, it is assigned lower modeling precision, such as using relatively coarse meshing and a larger time step, to reduce computational load. For example, an easily boiling surface can be discretized using a mesh size of 0.1 mm, while a difficult-to-boil surface can use a mesh size of 0.5 mm. In this way, the simulation system can intelligently adjust the allocation of simulation resources according to the actual boiling characteristics of the sub-surfaces, thereby significantly improving computational efficiency while ensuring overall simulation accuracy.

[0088] This application further proposes that the above-mentioned modeling accuracy is based on the element mesh size, and that the modeling accuracy of the sub-surface is determined according to the boiling type of the sub-surface, including: Determine whether the boiling type of the sub-surface is an easily boiling surface; if the boiling type of the sub-surface is not an easily boiling surface, determine the modeling accuracy of the sub-surface as the first unit mesh size; if the boiling type of the sub-surface is an easily boiling surface, obtain the second preset correspondence; the second preset correspondence includes a one-to-one correspondence between multiple effective nucleation point density ranges and multiple second unit mesh sizes; for any second unit mesh size smaller than the first unit mesh size, the second unit mesh size is negatively correlated with the maximum value of the corresponding effective nucleation point density range; the second unit mesh size corresponding to the effective nucleation point density of the sub-surface in the second preset correspondence is taken as the modeling accuracy of the sub-surface.

[0089] Specifically, modeling accuracy is defined as the element mesh size, which refers to the size of the basic element used to divide the simulation area during 3D modeling and simulation. The smaller the element mesh size, the higher the modeling accuracy and the richer the details that can be captured, but at the same time, the computational cost is also greater.

[0090] In determining the modeling accuracy of a sub-surface, the boiling type of the sub-surface is first identified. If the sub-surface is not an easily boiling surface, its boiling activity is relatively weak or inactive. In this case, the modeling accuracy of the sub-surface can be determined as the size of the first element mesh. This first element mesh size is usually a relatively large mesh size, designed to balance simulation accuracy and computational efficiency, and to avoid unnecessary fine modeling of inactive boiling regions.

[0091] In practical applications, if the sub-surface is classified as an easily boiling surface, a second preset correspondence needs to be obtained. This second preset correspondence is a pre-established mapping that maps multiple effective nucleation point density ranges to multiple second-element mesh sizes. Effective nucleation point density is a crucial parameter for measuring surface boiling activity; higher density indicates more intense boiling in that region, requiring more refined modeling. Therefore, the second-element mesh size is designed to be smaller than the first-element mesh size to provide higher modeling accuracy. Furthermore, the second-element mesh size is negatively correlated with the maximum value of the corresponding effective nucleation point density range. This means that the higher the effective nucleation point density, the smaller the corresponding second-element mesh size, thereby achieving more refined modeling of the actively boiling region.

[0092] Therefore, by querying the second preset correspondence, the second unit mesh size corresponding to the effective nucleation point density range of the sub-surface is taken as the modeling accuracy of the sub-surface.

[0093] The solution proposed in this application effectively addresses the aforementioned limitations by specifying the modeling accuracy as the unit mesh size and introducing an adaptive mesh generation mechanism based on the effective nucleation point density for easily boiling surfaces. Specifically, for surfaces with inactive boiling, a relatively large first unit mesh size is used for modeling, which can effectively reduce the computational burden. For easily boiling surfaces with active boiling, a single modeling accuracy is no longer used; instead, the unit mesh size is dynamically adjusted based on the differences in the density of local effective nucleation points through a second preset correspondence.

[0094] Regions with higher effective nucleation point density indicate more intense boiling and more complex dynamic processes of bubble formation and delamination. Therefore, they are assigned smaller second-cell mesh sizes to more precisely capture the temperature field, flow field, and phase transition processes in these critical regions. This adaptive meshing strategy allows computational resources to be allocated more rationally to the regions most requiring high-precision simulation, avoiding unnecessary computational waste while ensuring accurate simulation of key boiling phenomena.

[0095] Through the above technical solution, this application achieves significant optimization of the 3D modeling and simulation process for external boiling heat exchangers with T-shaped finned tubes. On the one hand, by using a relatively coarse mesh for surfaces that are not easily boilable, the overall computational cost and simulation time are effectively reduced. On the other hand, for easily boilable surfaces, the modeling accuracy can be adaptively adjusted according to the strength of their local boiling activity (i.e., the effective nucleation point density), allowing for the use of finer meshes in areas of intense boiling. This greatly improves the accuracy and reliability of the simulation results, especially in predicting heat transfer coefficients and bubble dynamics. This modeling and simulation method, which balances refinement and efficiency, provides a more accurate and efficient tool for the design optimization of T-shaped finned tubes.

[0096] This application further proposes an optimization scheme aimed at improving the simulation accuracy of non-boiling surfaces, thereby enhancing the accuracy of the three-dimensional modeling and simulation of the entire T-shaped finned tube external boiling heat exchanger.

[0097] After performing 3D boiling modeling and simulation of the sub-surface based on its boiling type, the above method also includes: During the three-dimensional modeling and simulation of boiling, the simulation temperature of the sub-surface with a boiling type that is not easy to boil is obtained; the sub-surface with a simulation temperature greater than a preset temperature threshold is taken as the target sub-surface, and the target sub-surface is simulated again.

[0098] Specifically, after completing the initial 3D modeling and simulation of boiling, all sub-surfaces identified as non-boiling surfaces need to be monitored to obtain their temperatures during the simulation. The simulation temperature can be understood as the instantaneous or average temperature reached by the non-boiling surface during the simulation. The preset temperature threshold can be understood as an empirical value or a critical temperature set according to design requirements, used to determine whether the non-boiling surface exhibits abnormally active boiling behavior. For example, this threshold can be set based on the boiling point of the fluid, the design conditions of the heat exchanger, and experimental data. When the simulation temperature of the non-boiling surface exceeds the preset temperature threshold, it indicates that the sub-surface may have localized overheating or that the actual boiling intensity is higher than initially expected, requiring more refined analysis. At this point, the sub-surface will be identified as the target sub-surface and simulated again to capture its more accurate boiling behavior.

[0099] The proposed solution effectively addresses the issue of insufficient simulation accuracy for non-boiling surfaces in the basic approach by introducing a monitoring and re-simulation mechanism for the simulated temperature of non-boiling surfaces. Specifically, even if a sub-surface is initially identified as a non-boiling surface, if its simulated temperature significantly increases and exceeds a preset temperature threshold during actual simulation, this usually indicates that the surface may exhibit stronger heat transfer or boiling activity than expected under the current operating conditions.

[0100] By identifying these temperature-anomaly sub-surfaces as target sub-surfaces and resimulating them, more refined modeling strategies or parameter settings can be employed, thereby more accurately capturing their true boiling behavior and heat transfer characteristics. This dynamic feedback and iterative optimization process enables the simulation model to adapt to potentially complex local conditions that may arise during actual operation, avoiding overall simulation errors caused by limitations in the initial classification.

[0101] Through the above technical solution, this application can significantly improve the accuracy of 3D modeling and simulation of T-finned tube external boiling heat exchangers, especially in handling areas that were initially classified as non-boiling surfaces but exhibit high heat loads in actual operation. This dynamic adjustment and re-simulation mechanism based on simulation temperature allows the model to more precisely depict local boiling phenomena, avoiding errors that may arise from a single static classification standard. Therefore, heat exchanger performance predictions that more closely approximate actual operating conditions can be obtained, providing more reliable data support for the optimized design and operation strategies of heat exchangers, thereby improving heat exchange efficiency and system stability.

[0102] In some preferred embodiments, it is assumed that a sub-surface of the T-finned tube, such as the sub-surface located at the bottom of the tube bundle or in the fluid impact region, is initially identified as a non-boiling surface. After the first boiling 3D modeling simulation, the local simulation temperature of this sub-surface is monitored to reach 120°C, while the preset temperature threshold is 110°C. Since the simulation temperature of this sub-surface exceeds the preset temperature threshold, it is identified as a target sub-surface. At this time, the system will initiate a re-simulation process for the target sub-surface. In the re-simulation, a smaller unit mesh size or a more complex boiling model can be used to more accurately capture the heat transfer and phase change processes in this region, thereby obtaining a more accurate local heat transfer coefficient and temperature distribution, and thus correcting the overall heat exchanger performance evaluation.

[0103] This application further proposes steps for resimulating the target sub-surface, including: Obtain the third preset correspondence; the third preset correspondence includes a one-to-one correspondence between multiple temperature ranges and multiple third unit mesh sizes; use the third unit mesh size corresponding to the temperature range where the simulation temperature is located in the third preset correspondence as the new simulation accuracy of the target sub-surface; the new simulation accuracy of the target sub-surface is greater than the previous simulation accuracy of the target sub-surface; perform boiling 3D modeling simulation on the target sub-surface again based on the new simulation accuracy of the target sub-surface.

[0104] Specifically, when simulating the target sub-surface again, it is first necessary to obtain a third pre-defined correspondence. This third pre-defined correspondence is a pre-established mapping relationship that maps different temperature ranges to specific third-element mesh sizes. The temperature range refers to the temperature intervals that may occur during the boiling 3D modeling simulation, which can be divided into several continuous or discrete temperature intervals. The third-element mesh size is a precision parameter used for boiling 3D modeling simulation, usually expressed in units of length; the smaller the value, the higher the modeling accuracy and the more refined the simulation results. This third pre-defined correspondence can be pre-stored in the system based on empirical data, experimental results, or theoretical calculations, for example, in the form of a lookup table, functional relationship, or database.

[0105] Furthermore, after obtaining the simulation temperature of the target sub-surface, the system searches for its corresponding temperature range in a third preset correspondence. Once the temperature range corresponding to the simulation temperature is determined, the third-cell mesh size associated with that temperature range can be obtained from the correspondence. This obtained third-cell mesh size is then determined as the new simulation accuracy of the target sub-surface. It is worth noting that the new simulation accuracy of the target sub-surface is set to be greater than the previous simulation accuracy. This means that the cell mesh size corresponding to the new simulation accuracy will be smaller than the cell mesh size previously used for simulating the target sub-surface, thereby achieving more refined modeling and simulation.

[0106] Therefore, based on the new simulation accuracy of the determined target sub-surface, a boiling 3D modeling simulation is performed on the target sub-surface again. This means that when re-simulating, a smaller unit mesh size will be used to discretize the target sub-surface, thereby more accurately capturing complex phenomena such as temperature gradients, phase transition behavior, and bubble dynamics in the region.

[0107] This application's solution addresses the problem of fixed or imprecise resimulation accuracy in traditional methods by introducing a third pre-defined correspondence and dynamically adjusting the resimulation accuracy based on the actual simulated temperature of the target sub-surface. Specifically, when the target sub-surface exhibits a high temperature in the initial simulation, this typically indicates a more intense or complex boiling heat transfer process in that region, requiring higher simulation accuracy to accurately capture its physical phenomena. By associating the simulation temperature with the pre-defined third-element mesh size, a finer mesh can be used for resimulation in critical areas with higher temperatures, thereby improving the simulation accuracy of local areas. Simultaneously, a relatively coarser mesh can be used for areas with relatively lower temperatures, avoiding unnecessary computational overhead.

[0108] Through the above technical solution, this application can adaptively adjust the re-simulation accuracy according to the specific temperature characteristics of the target sub-surface. This not only significantly improves the accuracy of boiling 3D modeling and simulation, especially in critical high-temperature regions, but also optimizes the allocation of computing resources, avoids unnecessary computational waste, and thus improves the efficiency and reliability of the overall simulation method.

[0109] In some preferred embodiments, assuming that after preliminary boiling 3D modeling simulation of multiple sub-surfaces of a T-shaped finned tube according to the above method, a certain sub-surface is identified as a non-boiling surface, but its local simulation temperature reaches 115°C during the simulation process, and this temperature is higher than a preset temperature threshold (e.g., 100°C), therefore this sub-surface is determined as the target sub-surface. To perform a more accurate re-simulation of this target sub-surface, the system queries a preset third predefined correspondence. This correspondence may be defined as follows: when the simulation temperature is in the range of 100°C to 110°C, the third unit mesh size is 0.5 mm; when the simulation temperature is in the range of 110°C to 120°C, the third unit mesh size is 0.2 mm; when the simulation temperature is higher than 120°C, the third unit mesh size is 0.1 mm. Since the simulation temperature of the target sub-surface is 115°C, which falls within the temperature range of 110°C to 120°C, the new simulation accuracy of this target sub-surface is determined to be 0.2 mm. If the previous simulation accuracy of the target sub-surface (e.g., the cell mesh size used in the initial simulation) was 1.0 mm, then the new simulation accuracy of 0.2 mm is obviously greater than the previous simulation accuracy. Finally, based on this 0.2 mm cell mesh size, the target sub-surface is subjected to another boiling 3D modeling simulation to obtain more accurate and refined local boiling heat transfer characteristics.

[0110] This application also discloses a three-dimensional modeling and simulation system for an external boiling heat exchanger of a T-shaped finned tube, comprising: an acquisition device and a processing device; the acquisition device is used to acquire the effective nucleation point density and the initial bubble size of each sub-surface among multiple sub-surfaces of the T-shaped finned tube; the processing device is used to determine the boiling type of each sub-surface according to the effective nucleation point density and the initial bubble size of the sub-surface; the boiling type includes easily boiling surfaces or not easily boiling surfaces; the processing device is used to perform boiling three-dimensional modeling and simulation of each sub-surface according to the boiling type of the sub-surface.

[0111] The 3D modeling and simulation system for T-shaped finned tube external boiling heat exchangers proposed in this application aims to improve the accuracy of boiling heat transfer simulation results by accurately considering the microscopic characteristics of the T-shaped finned tube surface through a structured device. The system collects key surface parameters through an acquisition device, and a processing device intelligently determines the boiling type of the sub-surface based on these parameters, thereby performing differentiated 3D modeling and simulation. This systematic approach effectively solves the prediction bias problem caused by neglecting microscopic surface inhomogeneities in traditional simulations, providing a more reliable tool for the design and optimization of high-efficiency heat exchangers.

[0112] The specific steps and principles of the three-dimensional modeling and simulation method for T-shaped finned tube external boiling heat exchangers have been described in the above embodiments, and will not be repeated here. It should be emphasized that the system proposed in this application implements the above method through a specific device, thereby providing an operable solution.

[0113] Specifically, the acquisition device of this application is used to acquire the effective nucleation point density and the initial bubble size of each sub-surface of a T-shaped finned tube. As one implementation, the acquisition device may include a data input module configured to receive raw data from an external measuring device (e.g., a surface roughness meter, contact angle meter) or surface parameter information pre-stored in a database. For example, the data input module may be a general-purpose data interface, such as a USB interface, an Ethernet interface, or a wireless communication module, for connecting to an external data source. In some embodiments, the acquisition device may also include a storage module for storing a preset mapping relationship or lookup table corresponding to different surface characteristics (e.g., roughness, droplet contact angle) of effective nucleation point density and initial bubble size. When it is necessary to acquire parameters of a specific sub-surface, the storage module can be queried to obtain the corresponding value.

[0114] Furthermore, the processing apparatus of this application is used to determine the boiling type of each of a plurality of sub-surfaces based on the effective nucleation point density and the initial bubble size of the sub-surface, and to perform three-dimensional boiling modeling and simulation of the sub-surface based on the boiling type. As a preferred embodiment, the processing apparatus may include one or more processors (e.g., a central processing unit (CPU), a graphics processing unit (GPU), or a dedicated digital signal processor (DSP)) and a memory. The memory stores executable program code, which, when executed by the processor, enables the aforementioned functions. Specifically, the processing apparatus may include a boiling type determination module configured to determine whether each sub-surface is a readily boiling surface or a not readily boiling surface based on the effective nucleation point density and the initial bubble size received from the acquisition device, combined with preset determination logic or thresholds. In addition, the processing apparatus may also include a simulation modeling module configured to, based on the boiling type determined by the boiling type determination module, call the corresponding simulation model and parameters (e.g., different mesh generation accuracies, different boiling heat transfer coefficient models) to perform three-dimensional modeling and simulation of each sub-surface of the T-shaped finned tube. For example, for sub-surfaces identified as easily boiling, the simulation modeling module can use a finer mesh and a more complex two-phase flow model for calculation; while for sub-surfaces that are not easily boiling, a relatively coarse mesh and a simplified model can be used to balance simulation accuracy and computational efficiency.

[0115] The core innovation of the 3D modeling and simulation system for T-shaped finned tube external boiling heat exchangers proposed in this application lies in the systematic introduction of microscopic surface characteristics (such as effective nucleation point density and initial bubble size) into the macroscopic 3D modeling and simulation process through the collaborative work of the acquisition and processing devices. Compared with existing simulation systems that typically idealize the heat exchanger surface, this system can more accurately capture the impact of microscopic non-uniformity of the T-shaped finned tube surface on boiling heat transfer during actual manufacturing. By accurately acquiring these microscopic parameters and intelligently classifying different sub-surfaces into boiling types based on these parameters by the processing device, and then adopting differentiated simulation strategies, this system significantly improves the accuracy of simulation predictions. Therefore, engineers can use this system to more accurately evaluate the actual performance of heat exchangers, optimize their structural design, and further reduce the size of equipment while ensuring energy efficiency, meeting the growing market demand for high-efficiency, compact heat exchangers. The implementation of this system provides more reliable and advanced technical support for the design and development of next-generation high-efficiency industrial heat exchange equipment.

[0116] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger, characterized in that, include: Obtain the effective nucleation point density and the initial bubble size of each sub-surface in the multiple sub-surfaces of the T-shaped finned tube; For each of the multiple sub-surfaces, the boiling type of the sub-surface is determined based on the effective nucleation point density and the initial bubble size of the sub-surface; the boiling type includes easily boiling surfaces or difficult-to-boil surfaces. For each of the multiple sub-surfaces, a three-dimensional modeling and simulation of boiling is performed on the sub-surface according to the boiling type of the sub-surface.

2. The three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger according to claim 1, characterized in that, Obtain the effective nucleation point density and the initial bubble size of each sub-surface in the multiple sub-surfaces of the T-shaped finned tube, including: For each of the multiple sub-surfaces, obtain the roughness of the sub-surface and the droplet contact angle of the sub-surface; The effective nucleation point density and initial bubble size of the sub-surface are determined based on the sub-surface roughness and droplet contact angle.

3. The three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger according to claim 2, characterized in that, The effective nucleation point density and initial bubble size of the sub-surface are determined based on the sub-surface roughness and droplet contact angle, including: Obtain a first preset correspondence; the first preset correspondence includes a one-to-one correspondence between multiple first pieces of information and multiple second pieces of information, the first pieces of information includes a roughness range and a droplet contact angle range, the second pieces of information includes a first effective nucleation point density and a first bubble initial size; The roughness of the sub-surface and the droplet contact angle of the sub-surface in the first preset correspondence are taken as the target first information. The density of the first effective nucleation points in the second information corresponding to the first target information in the first preset correspondence is taken as the density of the effective nucleation points of the sub-surface, and the initial size of the first bubble in the second information corresponding to the first target information in the first preset correspondence is taken as the initial size of the bubble of the sub-surface.

4. The three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger according to claim 1, characterized in that, The boiling type of a sub-surface is determined based on the effective nucleation point density and the initial bubble size of the sub-surface, including: Obtain the average curvature of the sub-surface; The boiling type of a sub-surface is determined based on its average curvature, effective nucleation point density, and initial bubble size.

5. The three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger according to claim 4, characterized in that, The boiling type of a sub-surface is determined based on its average curvature, effective nucleation point density, and initial bubble size, including: Determine whether the average curvature of the sub-surface is greater than a preset curvature threshold; If the average curvature of the sub-surface is less than or equal to a preset curvature threshold, the boiling type of the sub-surface is determined to be a non-boiling surface. If the average curvature of the sub-surface is greater than a preset curvature threshold, determine whether the effective nucleation point density of the sub-surface is greater than a preset density threshold, and whether the initial size of the bubbles on the sub-surface is greater than a preset size threshold. If both are true, the boiling type of the sub-surface is determined to be an easily boiling surface; otherwise, the boiling type of the sub-surface is determined to be an indigestible surface.

6. The three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger according to claim 1, characterized in that, Based on the boiling type of the sub-surface, a three-dimensional boiling modeling and simulation of the sub-surface is performed, including: The modeling accuracy of a sub-surface is determined based on its boiling type; the modeling accuracy of a sub-surface with a boiling type that is not easily boilable is less than that of a sub-surface with a boiling type that is easily boilable. Boiling 3D modeling and simulation of the sub-surface is performed based on the modeling accuracy of the sub-surface.

7. The three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger according to claim 6, characterized in that, The modeling accuracy refers to the unit mesh size. The modeling accuracy of the sub-surface is determined based on the boiling type of the sub-surface, including: Determine whether the boiling type of the sub-surface is an easily boiling surface; If the boiling type of the sub-surface is not an easily boiling surface, the modeling accuracy of the sub-surface is determined to be the first unit mesh size; If the boiling type of the sub-surface is an easily boiling surface, a second preset correspondence is obtained; the second preset correspondence includes a one-to-one correspondence between multiple effective nucleation point density ranges and multiple second unit grid sizes; any second unit grid size is smaller than the first unit grid size, and the second unit grid size is negatively correlated with the maximum value of the corresponding effective nucleation point density range; The second cell mesh size corresponding to the effective nucleation point density of the sub-surface in the second preset correspondence is used as the modeling accuracy of the sub-surface.

8. The three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger according to claim 1, characterized in that, After performing three-dimensional boiling modeling and simulation of the sub-surface based on its boiling type, the method further includes: During the three-dimensional modeling and simulation of boiling, the simulation temperature of the sub-surface of the surface with the boiling type being non-boiling is obtained; The sub-surface with a simulated temperature greater than a preset temperature threshold is taken as the target sub-surface, and the target sub-surface is simulated again.

9. The three-dimensional modeling and simulation method for a T-shaped finned tube external boiling heat exchanger according to claim 8, characterized in that, The target sub-surface was simulated again, including: Obtain a third preset correspondence; the third preset correspondence includes a one-to-one correspondence between multiple temperature ranges and multiple third unit grid sizes; The third unit grid size corresponding to the temperature range of the simulated temperature in the third preset correspondence is used as the new simulation accuracy of the target sub-surface; the new simulation accuracy of the target sub-surface is greater than the previous simulation accuracy of the target sub-surface; Based on the new simulation accuracy of the target sub-surface, the target sub-surface is subjected to boiling three-dimensional modeling and simulation again.

10. A three-dimensional modeling and simulation system for a T-shaped finned tube external boiling heat exchanger, characterized in that, include: Acquisition device and processing device; The acquisition device is used to acquire the effective nucleation point density of each sub-surface and the initial bubble size of each sub-surface in the multiple sub-surfaces of the T-shaped finned tube. The processing device is used to determine the boiling type of each of a plurality of sub-surfaces based on the effective nucleation point density and the initial bubble size of the sub-surface; the boiling type includes easily boiling surfaces or difficult-to-boil surfaces. The processing device is used to perform three-dimensional boiling modeling and simulation of each of the multiple sub-surfaces according to the boiling type of the sub-surface.

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