Heat sink evaluation method, apparatus, non-transitory storage medium, and electronic device

Abstract

This application discloses a heat sink evaluation method, apparatus, non-volatile storage medium, and electronic device. The method includes: establishing an initial heat sink model corresponding to a target heat sink, the initial heat sink model including a substrate main body region, an initial liquid metal filling region, a heat source region, and a support pillar structure model; randomly generating a bubble model and adding the randomly generated bubble model to the initial heat sink model to obtain a first target heat sink model; adding a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, the boundary of the surface tension gradient effect field being the interface between the liquid metal and gas in the second target heat sink model; and determining the heat dissipation capacity evaluation result of the target heat sink based on the second target heat sink model. This application solves the technical problem that the inability to accurately evaluate the heat dissipation capacity of heat sinks in related technologies leads to the inability to effectively optimize heat sink performance.

Description

Technical Field

[0001] This application relates to the field of simulation modeling, and more specifically, to a heat sink evaluation method, apparatus, non-volatile storage medium, and electronic device. Background Technology

[0002] In related technologies, the heat sink models established for evaluating heat sinks often fail to effectively couple the Marangoni effect, also known as the surface tension gradient effect. This leads to a significant discrepancy between the heat sink's heat dissipation capacity assessment results and its actual heat dissipation capacity.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This application provides a heat sink evaluation method, apparatus, non-volatile storage medium, and electronic device to at least solve the technical problem that the heat sink performance cannot be effectively optimized due to the inability to accurately evaluate the heat dissipation capacity of the heat sink in related technologies.

[0005] According to one aspect of the embodiments of this application, a heat sink evaluation method is provided, comprising: establishing an initial heat sink model corresponding to a target heat sink, wherein the initial heat sink model includes a substrate main body region, an initial liquid metal filling region, a heat source region, and a support column structure model; randomly generating a bubble model and adding the randomly generated bubble model to the initial heat sink model to obtain a first target heat sink model, wherein the bubble model includes randomly generated bubbles containing gas; adding a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between liquid metal and gas in the second target heat sink model; and determining the heat dissipation capacity evaluation result of the target heat sink based on the second target heat sink model, wherein the heat dissipation capacity evaluation result includes test results obtained by testing the second target heat sink model under different preset test conditions.

[0006] Optionally, randomly generating the bubble model includes: determining a preset ratio; randomly generating cylindrical bubbles with circular or elliptical cross-sections until the ratio of the total volume of the bubbles in the bubble model to the cavity volume of the initial radiator model is the preset ratio.

[0007] Optionally, adding a randomly generated bubble model to the initial radiator model to obtain the first target radiator model includes: determining the bubble region corresponding to the bubble model in the initial radiator model, wherein the bubble region is located in the initial liquid metal filling region; determining the difference between the initial liquid metal filling region and the bubble region, and using the difference as the liquid metal filling region in the first target radiator model; adding the bubble model to the bubble region to obtain the first target radiator model.

[0008] Optionally, the method further includes: determining the material properties of multiple components in the second target heat sink model based on the material information of the target heat sink; setting the physical field information of the second target heat sink model, wherein the physical field information includes at least laminar flow information, phase field information, ambient temperature information and initial temperature information.

[0009] Optionally, adding a surface tension gradient effect field to the first target heat sink model to obtain the second target heat sink model includes: determining the surface tension of the interface based on material information and physical field information; and adding a surface tension gradient effect field to the first target heat sink model based on the surface tension to obtain the second target heat sink model.

[0010] Optionally, there are multiple heat source regions. The preset test conditions include the number of heat source regions activated during the test and the total power of the activated heat source regions. The test results include the temperature cloud map, velocity cloud map and pressure cloud map of the liquid metal in the second target radiator model, and the temperature cloud map, velocity cloud map and pressure cloud map of the gas in the second target radiator model.

[0011] Optionally, the method further includes: meshing the second target heat sink model, wherein the mesh cell size corresponding to the interface is smaller than the mesh cell size corresponding to the region other than the interface in the second target heat sink model, and the mesh cell density corresponding to the interface is greater than the mesh cell density corresponding to the region other than the interface in the second target heat sink model.

[0012] According to another aspect of the embodiments of this application, a heat sink evaluation device is also provided, comprising: a first processing module, configured to establish an initial heat sink model corresponding to a target heat sink, wherein the initial heat sink model includes a substrate main body region, an initial liquid metal filling region, a heat source region, and a support column structure model; a second processing module, configured to randomly generate a bubble model and add the randomly generated bubble model to the initial heat sink model to obtain a first target heat sink model, wherein the bubble model includes randomly generated bubbles containing gas; a third processing module, configured to add a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between liquid metal and gas in the second target heat sink model; and a fourth processing module, configured to determine the heat dissipation capacity evaluation result of the target heat sink based on the second target heat sink model, wherein the heat dissipation capacity evaluation result includes the test results of the second target heat sink model under different preset test conditions.

[0013] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, wherein a program is stored in the non-volatile storage medium, wherein the program controls the device where the non-volatile storage medium is located to execute a heat sink evaluation method when it runs.

[0014] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory and a processor, the processor being configured to run a program stored in the memory, wherein the program executes a heat sink evaluation method during runtime.

[0015] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of a heat sink evaluation method.

[0016] In this embodiment, an initial heat sink model corresponding to the target heat sink is established. This initial heat sink model includes a substrate body region, an initial liquid metal filling region, a heat source region, and a support column structure model. A bubble model is randomly generated and added to the initial heat sink model to obtain a first target heat sink model, which includes randomly generated bubbles containing gas. A surface tension gradient effect field is added to the first target heat sink model to obtain a second target heat sink model, where the boundary of the surface tension gradient effect field is the interface between the liquid metal and gas in the second target heat sink model. Based on the second target heat sink model, the heat dissipation capacity evaluation result of the target heat sink is determined. This evaluation result includes test results obtained by testing the second target heat sink model under different preset test conditions. By adding a surface tension gradient effect field to the heat sink model, the actual heat dissipation situation of the heat sink is simulated more accurately, thus achieving the technical effect of accurately evaluating the heat dissipation capacity of the heat sink. This solves the technical problem that the heat sink performance cannot be effectively optimized due to the inability to accurately evaluate the heat dissipation capacity of the heat sink in related technologies. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 This is a schematic diagram of the structure of a computer terminal (or mobile device) according to an embodiment of this application;

[0019] Figure 2 This is a schematic flowchart of a radiator evaluation method provided according to an embodiment of this application;

[0020] Figure 3 This is a schematic diagram of a heat sink model provided according to an embodiment of this application;

[0021] Figure 4 This is a schematic diagram of a heat sink evaluation process provided according to an embodiment of this application;

[0022] Figure 5 This is a schematic diagram of a radiator evaluation device provided according to an embodiment of this application. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] As high-power lasers, advanced electronic chips, and other high-end equipment become increasingly miniaturized and denser, their heat flux density is rising dramatically, pushing traditional heat dissipation technologies to their limits. Liquid metals (such as gallium-based alloys), due to their extremely high thermal conductivity and fluidity, have become a highly promising next-generation cooling medium. In practical applications, to prevent the oxidation of liquid metals, protective gases such as nitrogen are often introduced into the encapsulation cavity, thus forming a dynamic "gas-liquid metal" two-phase flow system.

[0026] This system involves a complex multiphysics coupling process: the thermal field (heat generation by the heating element), the flow field (flow of liquid metal and gas), and the phase field (interfacial evolution of gas and liquid due to flow) interact with each other. Particularly for high surface tension fluids like liquid metal, the Marangoni effect induced by the temperature gradient becomes a key factor driving flow, influencing interfacial stability, and bubble dynamics. Therefore, accurate simulation of this multiphysics coupling process is crucial for optimizing heat sink performance.

[0027] Currently, for numerical simulations of such problems, most techniques employ commercial software based on Computational Fluid Dynamics (CFD) (such as ANSYS Fluent and COMSOL Multiphysics) for modeling. A common approach is to use the VOF (Volume of Fluid) method or a homogeneous flow model to simplify the handling of gas-liquid two-phase flows.

[0028] The following defects exist in related technologies, which prevent the realistic and accurate simulation of the physical processes of two-phase flow in liquid metal:

[0029] 1. Insufficient capture of dynamic interfaces: Traditional VOF methods or homogeneous flow models have limited accuracy when dealing with drastic changes in interface topology (such as bubble merging and breaking). They often treat the interface as a simple geometric boundary and cannot accurately describe the transient mass and momentum exchange between the protective gas and the liquid metal.

[0030] 2. Neglecting key physical effects: Existing models generally fail to effectively couple the Marangoni effect. For liquid metals, the surface tension is highly sensitive to temperature changes, and neglecting this effect will lead to serious deviations in the prediction of interfacial flow, bubble movement paths, and final heat dissipation capacity.

[0031] 3. Low accuracy of physical property parameters: Key physical property parameters of liquid metals in the model (such as viscosity, surface tension coefficient and their rate of change with temperature) are mostly empirical values ​​or simplified to constants. This inaccurate parameter input directly reduces the computational reliability of the entire model and fails to reflect the real situation in terms of physical essence.

[0032] These shortcomings make it difficult for existing models to guide the design and process optimization of high-precision, high-reliability liquid metal radiators.

[0033] To address the aforementioned issues, this application provides relevant solutions, which are detailed below.

[0034] According to an embodiment of this application, a method embodiment for evaluating a heat sink is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0035] The methods and embodiments provided in this application can be executed on mobile terminals, computer terminals, or similar computing devices. Figure 1 A hardware block diagram of a computer terminal (or mobile device) for implementing a heat sink evaluation method is shown. Figure 1As shown, the computer terminal 10 (or mobile device 10) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0036] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0037] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the heat sink evaluation method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned heat sink evaluation method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0038] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0039] The display may be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0040] Under the above operating environment, embodiments of this application provide a radiator evaluation method, such as... Figure 2 As shown, the method includes the following steps:

[0041] Step S202: Establish an initial heat sink model corresponding to the target heat sink. The initial heat sink model includes a substrate body area, an initial liquid metal filling area, a heat source area, and a support column structure model.

[0042] In some embodiments of this application, the initial heat sink model can be a theoretical model of two-phase flow of liquid metal in a closed cavity.

[0043] As an optional implementation, when setting the physics field for the initial heat sink model, the flow state of the liquid metal alloy can be determined to be laminar. When describing the gas-liquid two-phase flow process within the closed cavity, the physics field selection in the simulation modeling software sequentially selects fluid flow, multiphase flow, two-phase flow, phase field, and laminar flow. When describing the heat transfer process in the substrate body region containing the embedded liquid metal, heat transfer, solid-fluid heat transfer, and other methods are selected. The solution mode is set to transient, and the preset study and transient phase initialization of the selected physics field interface are chosen from the study selection menu of the simulation modeling software.

[0044] Step S204: Randomly generate a bubble model and add the randomly generated bubble model to the initial heat sink model to obtain the first target heat sink model, wherein the bubble model includes randomly generated bubbles containing gas.

[0045] In the technical solution provided in step S204, the step of randomly generating a bubble model includes: determining a preset ratio; randomly generating cylindrical bubbles with a circular or elliptical cross-section until the ratio of the total volume of the bubbles in the bubble model to the cavity volume of the initial radiator model is the preset ratio.

[0046] In some embodiments of this application, the step of adding a randomly generated bubble model to an initial heat sink model to obtain a first target heat sink model includes: determining the bubble region corresponding to the bubble model in the initial heat sink model, wherein the bubble region is located in the initial liquid metal filling region; determining the difference between the initial liquid metal filling region and the bubble region, and using the difference as the liquid metal filling region in the first target heat sink model; adding the bubble model to the bubble region to obtain the first target heat sink model.

[0047] In some embodiments of this application, an initial heat sink model can be constructed within the 3D modeling space of simulation modeling software, based on the structure of an actual liquid metal heat sink. This model includes a substrate main body region, an initial liquid metal filling region, a heat source region, and a support column structure model. The initial liquid metal filling region is a rectangular region, which will subsequently be differenced with the imported bubble region. Through joint modeling using simulation modeling software and data processing software, bubble models with randomly distributed positions, sizes, and shapes are generated in the data processing software. Considering that the volume of randomly shaped ellipsoids is difficult to calculate, cylindrical bubbles with circular or elliptical cross-sections are generated during bubble modeling. The volume of a cylindrical bubble is the product of its cross-sectional area and cavity height. During the modeling process, the volumes of all cylindrical bubbles can be continuously accumulated until the ratio of the total volume of the bubble model to the cavity volume of the initial heat sink model reaches a target ratio. At this point, generation stops, and the bubble domain model file is output. Import the bubble domain model file into the simulation modeling software. Perform a difference operation between the constructed initial liquid metal filling region and the bubble region to obtain the actual initial liquid metal filling region, which is the liquid metal filling region in the first target heat sink model. The first target heat sink model after filling is as follows. Figure 3 As shown. Figure 3 As can be seen, the gas inside the bubble can be nitrogen. The liquid metal can be an alloy. The liquid enters and the bubble is located within the cavity formed by the substrate.

[0048] Step S206: Add a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between the liquid metal and the gas in the second target heat sink model.

[0049] In some embodiments of this application, the method further includes: determining the material properties of multiple components in a second target heat sink model based on the material information of the target heat sink; setting the physical field information of the second target heat sink model, wherein the physical field information includes at least laminar flow information, phase field information, ambient temperature information and initial temperature information.

[0050] Optionally, based on the material information of the target heat sink, the material properties of multiple components in the second target heat sink model can be determined. For example, the substrate body region, heat source region, and support pillar structure model are solid domains, with silicon selected as the material for the solid domain; nitrogen is selected as the material for the gas domain; and the liquid metal filling region is set using custom material properties, with input physical property parameters calculated based on first principles and molecular dynamics. These physical property parameters include density ρ, viscosity μ, surface tension σ(T) as a function of temperature, and surface tension temperature coefficient. σ / T, thermal conductivity k, and specific heat capacity at constant pressure Cp. Where density ρ is the mass of liquid metal per unit volume, viscosity μ is the internal friction coefficient within the liquid metal that hinders its relative flow, and surface tension σ(T) is the surface tension at the interface between the liquid metal and the gas as a function of temperature; the surface tension temperature coefficient... σ / T is the rate of change of surface tension with temperature, the thermal conductivity k is the coefficient of the ability of liquid metal to conduct heat, and the specific heat capacity at constant pressure Cp is the heat absorbed or released by a unit mass of liquid metal when the temperature changes by a unit under constant pressure.

[0051] In some embodiments of this application, the physical field information can be set in the following manner:

[0052] Laminar flow information settings

[0053] In the physical model of laminar flow, gravity is enabled, the inner wall of the main substrate area and the surface of the support column structure model are set to a non-slip state, a location is selected at the outer boundary of the main substrate area as a pressure constraint point, the pressure at this location is set to one standard atmosphere, and the hydrostatic pressure compensation function is enabled.

[0054] Phase field information settings

[0055] The initial value of fluid 1 in the phase field can be set as the liquid metal filling region, and the initial value of fluid 2 can be set as the bubble region. The wetting wall contact angle of the phase field is determined by Young's equation. The surface energy densities corresponding to solid and fluid 1 and solid and fluid 2 are obtained based on first-principles calculations and molecular dynamics calculations.

[0056] Solid and fluid heat transfer information settings

[0057] The initial temperature for solid and fluid heat transfer can be set to 25℃, and the ambient temperature can also be set to 25℃. The outer wall of the second target heat sink model is set to a natural convection state, while the remaining walls are set to a non-slip and adiabatic state. The heat source region is set as multiple independently switchable heat chip regions, for example, four. The four heat chip regions are numbered sequentially in a clockwise order, and each of the four heat chip regions is defined as an independent heat source domain. Each heat source domain is allocated the same total heat generation power P. The activation state of each heat source domain is controlled by a parameterized switching function to achieve four heating modes: activating only the first heat chip region, activating the first two heat chip regions simultaneously, activating the first three heat chip regions simultaneously, and activating all four heat chip regions simultaneously. The total heat generation power P is set as a global parameter and its value is obtained using a parameterized scanning method. Each combination of heating mode and total heat generation power forms an independent operating condition. For each operating condition, the maximum substrate temperature T_max, the temperature difference between chips ΔT_chip, and the thermal resistance R_th are automatically solved sequentially and output. The formula for calculating the thermal resistance is R_th = (T_max – T_ref) / P.

[0058] As an optional implementation, the step of adding a surface tension gradient effect field to the first target heat sink model to obtain the second target heat sink model includes: determining the surface tension of the interface based on material information and physical field information; and adding a surface tension gradient effect field to the first target heat sink model based on the surface tension to obtain the second target heat sink model. The surface tension gradient effect field is also known as the Marangoni field.

[0059] In some embodiments of this application, surface tension can be calculated using the following formula:

[0060] σ(T) = σ0– γ·(T – T_ref)

[0061] The γ value can be calculated based on material and physical field information. Specifically, γ is the surface tension temperature coefficient of liquid metal, which is obtained through first-principles calculations and molecular dynamics based on the liquid metal material information of the target heat sink. First, the basic surface energy, interatomic interaction potential, and other microscopic physical properties of the liquid metal are calculated using first-principles calculations to build an accurate physical model and parameter boundaries for molecular dynamics simulation. Then, a molecular dynamics model is constructed based on the above microscopic physical properties to simulate the microscopic evolution process of the interface between liquid metal and protective gas under different temperature conditions. The characteristic curve of surface tension changing with temperature is obtained by fitting the model, and the absolute value of the slope of the characteristic curve is extracted as the γ value. At the same time, the physical field information of the second target heat sink model is combined to verify the adaptability of the calculated γ value, so that the γ value matches the physical field parameters such as laminar flow information, phase field information, and temperature information set in the model. This ensures that the surface tension calculated based on the γ value can accurately reflect the actual physical properties of the liquid metal and gas interface in the model, and finally, the γ value that can be directly substituted into the surface tension calculation formula is determined.

[0062] Step S208: Based on the second target radiator model, determine the heat dissipation capacity evaluation result of the target radiator, wherein the heat dissipation capacity evaluation result includes the test results obtained by testing the second target radiator model under different preset test conditions.

[0063] In some embodiments of this application, the method further includes: meshing the second target heat sink model, wherein the mesh cell size corresponding to the interface is smaller than the mesh cell size corresponding to the region other than the interface in the second target heat sink model, and the mesh cell density corresponding to the interface is greater than the mesh cell density corresponding to the region other than the interface in the second target heat sink model.

[0064] Optionally, a physics-controlled mesh generation method can be used during mesh generation, setting the overall mesh cell size of the second target heat sink model to a finer level. Furthermore, local mesh refinement is applied to the interface between the liquid metal and gas, i.e., the liquid metal-bubble interface, by setting the mesh cell size at this interface to extremely fine. This results in a mesh cell size at the interface being smaller than the mesh cell size of the regions outside the interface in the second target heat sink model, and a higher mesh cell density at the interface than the overall mesh cell density of the regions outside the interface in the second target heat sink model.

[0065] The purpose of performing the above-mentioned meshing on the second target radiator model is twofold. First, by relying on the physical field to control the meshing method, the mesh structure is adapted to the physical field distribution characteristics of the model, ensuring the basic accuracy and rationality of the overall simulation calculation. Second, by locally refining the liquid metal-bubble interface, the interfacial dynamics at this interface can be accurately captured, clearly restoring the transient changes of the interface under the action of the surface tension gradient effect field. This avoids simulation deviations in key physical processes such as interface flow and bubble evolution caused by insufficient mesh precision. At the same time, the refined mesh can also improve the accuracy of the coupled solution of phase field, flow field, and thermal field at the interface, making the subsequent evaluation results of the radiator's heat dissipation capacity more consistent with the actual situation.

[0066] In some embodiments of this application, there are multiple heat source regions. The preset test conditions include the number of heat source regions activated during the test and the total power of the activated heat source regions. The test results include temperature cloud maps, velocity cloud maps, and pressure cloud maps of the liquid metal in the second target radiator model, as well as temperature cloud maps, velocity cloud maps, and pressure cloud maps of the gas in the second target radiator model.

[0067] In some embodiments of this application, a method such as... is also provided. Figure 4 The radiator evaluation process, as shown, comprises three stages: input parameters, physics field setup, and result output. The input parameter stage primarily provides high-precision physical property parameters, which serve as the core inputs, providing an accurate physical property basis for subsequent calculations in the physics field module. The physics field setup stage includes three core steps: solid and fluid heat transfer setup, phase field setup, and laminar flow setup. These steps are clearly coupled: the solid and fluid heat transfer setup is coupled with the phase field setup through the Marangoni effect (surface tension gradient effect); the phase field setup is coupled with the laminar flow setup through two-phase flow, phase field, and non-isothermal flow, jointly constructing a multi-physics field coupled simulation model. The result output stage, based on the coupled calculations of the above physics fields, outputs results such as dynamic gas-liquid interface, temperature distribution, and flow and pressure distribution. These results are then fed back to the phase field module, forming a complete simulation closed loop, ultimately achieving an accurate evaluation of the radiator's heat dissipation capacity.

[0068] In some embodiments of this application, in order to further demonstrate the impact of adding the surface tension gradient effect field on the accuracy of the heat sink capacity assessment, the heat dissipation capacity assessment results of the heat sink were solved and compared based on the heat sink model with the added surface tension gradient effect field and the heat sink model without the added surface tension gradient effect field.

[0069] Optionally, for the heat sink model without the added surface tension gradient effect field, the solver is first set up and the solution operation is performed. The auxiliary scanning function is enabled, and the parameter of the total heating power P of the heating unit is added. Solutions under different heating powers are output according to a specific step size. Then, in the second step of the study, the time step is set to 1 second, and the solution time is 0.01 seconds. After the solution is completed, the results are post-processed to obtain the temperature, velocity, and pressure contour maps of the liquid metal and gas without the coupled surface tension gradient effect field. The evolution process of the gas-liquid interface is extracted by setting an isosurface with a volume fraction of 0.5. Simultaneously, key parameters for evaluating heat dissipation capacity, such as the substrate maximum temperature T_max, the inter-chip temperature difference ΔT_chip, and the thermal resistance R_th, are obtained. The substrate maximum temperature T_max is the highest temperature value in the main area of ​​the substrate in the model; the inter-chip temperature difference ΔT_chip is the temperature difference between the various heat source areas in the model; and the thermal resistance R_th is the resistance encountered during the transfer of heat from the heat source to the environment, calculated using the formula R_th = (T_max –T_ref) / P, where T_ref is the ambient temperature and P is the total heating power of the heating unit.

[0070] For the heat sink model with added surface tension gradient effect field, first, based on the heat sink model without added surface tension gradient effect field, add a surface tension gradient effect field to the interface between liquid metal and gas in the multiphysics nodes of the model. The surface tension of the interface is expressed by the formula σ(T) = σ0 – γ The surface tension gradient field (T – T_ref) is calculated, where σ(T) is the surface tension at the transient temperature T, σ0 is the basic surface tension at the reference temperature T_ref, γ is the surface tension temperature coefficient, given by first-principles calculations and molecular dynamics, T is the transient temperature at the interface, and T_ref is the reference temperature. After loading the surface tension gradient field, the model is meshed using the same meshing method as the radiator model without the surface tension gradient field. The solver is then set and solved, maintaining the same setup as the radiator model without the surface tension gradient field. Specifically, in the first step of the study, the auxiliary scanning function is enabled, the total heating power P of the heating unit is added, and solutions at different heating powers are output according to a specific step size. In the second step, the time step is set to 1 second, and the solution time is 0.01 seconds. After completing the solution in seconds, the solution results are post-processed to output the temperature cloud map, velocity cloud map, and pressure cloud map of liquid metal and gas under the model. At the same time, the key parameters for heat dissipation capacity evaluation, such as the maximum substrate temperature T_max, the temperature difference between chips ΔT_chip, and the thermal resistance R_th, are obtained under the model.

[0071] After solving the two models, the heat dissipation capacity assessment results were compared and analyzed. Without adding the surface tension gradient effect field, the gas-liquid interface in the model was almost static, the bubbles maintained their initial spherical shape, the temperature gradient accumulated along the fluid flow direction, and the inter-chip temperature difference ΔT_chip was relatively large. The heat dissipation capacity assessment results deviated significantly from the actual heat dissipation of the radiator. With the addition of the surface tension gradient effect field, the surface tension gradient drove the gas-liquid interface to slide rapidly. The bubbles were stretched and split under the action of the fluid and formed a circulating flow with the liquid metal. The high-temperature area in the model was quickly flattened, the inter-chip temperature difference ΔT_chip was significantly reduced, and the maximum substrate temperature T_max and thermal resistance R_th also showed reasonable changing trends. The heat dissipation capacity assessment results were more consistent with the actual heat dissipation conditions of the radiator. This clearly demonstrates that the accuracy of the heat dissipation capacity assessment results was significantly improved after adding the surface tension gradient effect field.

[0072] By establishing an initial heat sink model corresponding to the target heat sink, which includes a substrate main body area, an initial liquid metal filling area, a heat source area, and a support column structure model; randomly generating a bubble model and adding it to the initial heat sink model to obtain a first target heat sink model, wherein the bubble model includes randomly generated bubbles containing gas; adding a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between the liquid metal and the gas in the second target heat sink model; and determining the heat dissipation capacity evaluation result of the target heat sink based on the second target heat sink model, wherein the heat dissipation capacity evaluation result includes test results obtained by testing the second target heat sink model under different preset test conditions, by adding a surface tension gradient effect field to the heat sink model, the purpose of more accurately simulating the actual heat dissipation of the heat sink is achieved, thereby realizing the technical effect of accurately evaluating the heat dissipation capacity of the heat sink, and thus solving the technical problem that the heat sink performance cannot be effectively optimized due to the inability to accurately evaluate the heat dissipation capacity of the heat sink in related technologies.

[0073] The solution provided in this application has the following advantages over related technologies:

[0074] Improving the simulation accuracy of radiator models: This application couples the phase field method and the surface tension gradient effect in the radiator model, which can reproduce the dynamic evolution process of bubbles and the flow state of the interface between liquid metal and gas with high fidelity. Compared with the modeling methods in related technologies, the simulation accuracy of liquid metal fluids is significantly improved, and it can more accurately reflect the actual flow field changes inside the radiator.

[0075] Enhancing the reliability of radiator heat dissipation capacity prediction results: This application obtains high-precision liquid metal physical property parameters based on first-principles calculations and molecular dynamics, and uses them as input parameters for the radiator model. This reduces the uncertainty of model parameter input from a physical perspective, making the prediction results of radiator heat dissipation capacity more scientifically based and improving the reliability and accuracy of the prediction results.

[0076] Making model simulation more closely match actual engineering application scenarios: This application constructs a random initial bubble field that conforms to the actual process by randomly generating bubble models and adding them to the initial heat sink model. This simulates the non-uniform distribution of bubbles caused by factors such as surface inhomogeneity in the actual process, making the initial settings of the model highly consistent with the initial conditions of the actual operation of the heat sink, and effectively improving the engineering practical value of the model simulation results.

[0077] This application provides effective theoretical guidance for the optimized design of liquid metal radiators: The radiator model can accurately predict the heat dissipation performance parameters of the radiator under different preset test conditions. It can accurately analyze the core heat dissipation performance indicators such as the thermal resistance of the radiator under different heat flux densities and different bubble contents. This not only provides a powerful theoretical tool for the structural and process optimization design of liquid metal radiators, but also enables in-depth analysis of the internal heat dissipation mechanism of the radiator, providing a clear direction for the optimization and improvement of the radiator.

[0078] This application provides a radiator evaluation device. Figure 5 This is a schematic diagram of the device. From Figure 5 As can be seen from the diagram, the device includes: a first processing module 50, used to establish an initial heat sink model corresponding to the target heat sink, wherein the initial heat sink model includes a substrate main body area, an initial liquid metal filling area, a heat source area, and a support column structure model; a second processing module 52, used to randomly generate a bubble model and add the randomly generated bubble model to the initial heat sink model to obtain a first target heat sink model, wherein the bubble model includes randomly generated bubbles containing gas; a third processing module 54, used to add a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between the liquid metal and the gas in the second target heat sink model; and a fourth processing module 56, used to determine the heat dissipation capacity evaluation result of the target heat sink based on the second target heat sink model, wherein the heat dissipation capacity evaluation result includes the test results of the second target heat sink model under different preset test conditions.

[0079] In some embodiments of this application, the step of the second processing module 52 randomly generating bubble models includes: determining a preset ratio; randomly generating cylindrical bubbles with circular or elliptical cross-sections until the ratio of the total volume of the bubbles in the bubble model to the cavity volume of the initial radiator model is the preset ratio.

[0080] In some embodiments of this application, the step of the second processing module 52 adding a randomly generated bubble model to the initial heat sink model to obtain the first target heat sink model includes: determining the bubble region corresponding to the bubble model in the initial heat sink model, wherein the bubble region is located in the initial liquid metal filling region; determining the difference between the initial liquid metal filling region and the bubble region, and using the difference as the liquid metal filling region in the first target heat sink model; adding the bubble model to the bubble region to obtain the first target heat sink model.

[0081] In some embodiments of this application, the third processing module 54 is further configured to: determine the material properties of multiple components in the second target heat sink model based on the material information of the target heat sink; and set the physical field information of the second target heat sink model, wherein the physical field information includes at least laminar flow information, phase field information, ambient temperature information and initial temperature information.

[0082] In some embodiments of this application, the third processing module 54 adds a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, including: determining the surface tension of the interface based on material information and physical field information; and adding a surface tension gradient effect field to the first target heat sink model based on the surface tension to obtain a second target heat sink model.

[0083] In some embodiments of this application, there are multiple heat source regions. The preset test conditions include the number of heat source regions activated during the test and the total power of the activated heat source regions. The test results include temperature cloud maps, velocity cloud maps, and pressure cloud maps of the liquid metal in the second target radiator model, as well as temperature cloud maps, velocity cloud maps, and pressure cloud maps of the gas in the second target radiator model.

[0084] In some embodiments of this application, the fourth processing module 56 is further configured to perform mesh generation on the second target heat sink model, wherein the mesh cell size corresponding to the interface is smaller than the mesh cell size corresponding to the region other than the interface in the second target heat sink model, and the mesh cell density corresponding to the interface is greater than the mesh cell density corresponding to the region other than the interface in the second target heat sink model.

[0085] It should be noted that each module in the above-mentioned heat sink evaluation device can be a program module (e.g., a set of program instructions to implement a certain function) or a hardware module. For the latter, it can be manifested in the following forms, but is not limited to them: each of the above modules is manifested as a processor, or the functions of each of the above modules are implemented by a processor.

[0086] According to an embodiment of this application, a non-volatile storage medium is also provided, which stores a program. During program execution, the program controls the device containing the non-volatile storage medium to perform the following heat sink evaluation method: establishing an initial heat sink model corresponding to a target heat sink, wherein the initial heat sink model includes a substrate main body region, an initial liquid metal filling region, a heat source region, and a support pillar structure model; randomly generating a bubble model and adding the randomly generated bubble model to the initial heat sink model to obtain a first target heat sink model, wherein the bubble model includes randomly generated bubbles containing gas; adding a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between the liquid metal and gas in the second target heat sink model; and determining the heat dissipation capacity evaluation result of the target heat sink based on the second target heat sink model, wherein the heat dissipation capacity evaluation result includes test results obtained by testing the second target heat sink model under different preset test conditions.

[0087] According to an embodiment of this application, an electronic device is also provided, including: a memory and a processor, wherein the processor is used to run a program stored in the memory, wherein the program executes the following heat sink evaluation method: establishing an initial heat sink model corresponding to a target heat sink, wherein the initial heat sink model includes a substrate main body region, an initial liquid metal filling region, a heat source region, and a support column structure model; randomly generating a bubble model and adding the randomly generated bubble model to the initial heat sink model to obtain a first target heat sink model, wherein the bubble model includes randomly generated bubbles containing gas; adding a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between liquid metal and gas in the second target heat sink model; and determining the heat dissipation capacity evaluation result of the target heat sink based on the second target heat sink model, wherein the heat dissipation capacity evaluation result includes test results obtained by testing the second target heat sink model under different preset test conditions.

[0088] According to an embodiment of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the following steps of a heat sink evaluation method: establishing an initial heat sink model corresponding to a target heat sink, wherein the initial heat sink model includes a substrate main body region, an initial liquid metal filling region, a heat source region, and a support column structure model; randomly generating a bubble model and adding the randomly generated bubble model to the initial heat sink model to obtain a first target heat sink model, wherein the bubble model includes randomly generated bubbles containing gas; adding a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between liquid metal and gas in the second target heat sink model; and determining the heat dissipation capacity evaluation result of the target heat sink based on the second target heat sink model, wherein the heat dissipation capacity evaluation result includes test results obtained by testing the second target heat sink model under different preset test conditions.

[0089] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0090] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0091] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0093] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0094] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for evaluating radiators, characterized in that, include: An initial heat sink model corresponding to the target heat sink is established, wherein the initial heat sink model includes a substrate body area, an initial liquid metal filling area, a heat source area, and a support column structure model; A bubble model is randomly generated and added to the initial radiator model to obtain a first target radiator model, wherein the bubble model includes randomly generated bubbles containing gas. A surface tension gradient effect field is added to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between liquid metal and gas in the second target heat sink model. Based on the second target radiator model, the heat dissipation capacity evaluation result of the target radiator is determined, wherein the heat dissipation capacity evaluation result includes test results obtained by testing the second target radiator model under different preset test conditions.

2. The radiator evaluation method according to claim 1, characterized in that, Randomly generated bubble models include: Determine the preset ratio; Randomly generate cylindrical bubbles with circular or elliptical cross-sections until the ratio of the total volume of the bubbles in the bubble model to the cavity volume of the initial radiator model is the preset ratio.

3. The radiator evaluation method according to claim 1, characterized in that, Adding the randomly generated bubble model to the initial radiator model to obtain the first target radiator model includes: Determine the bubble region corresponding to the bubble model in the initial radiator model, wherein the bubble region is located in the initial liquid metal filling region; Determine the difference between the initial liquid metal filling region and the bubble region, and use the difference as the liquid metal filling region in the first target heat sink model; The bubble model is added to the bubble region to obtain the first target heat sink model.

4. The radiator evaluation method according to claim 1, characterized in that, The method further includes: Based on the material information of the target radiator, the material properties of multiple components in the second target radiator model are determined; The physical field information of the second target heat sink model is set, wherein the physical field information includes at least laminar flow information, phase field information, ambient temperature information and initial temperature information.

5. The radiator evaluation method according to claim 4, characterized in that, Adding a surface tension gradient effect field to the first target heat sink model yields the second target heat sink model, which includes: Based on the material information and the physical field information, the surface tension of the interface is determined; Based on the surface tension, a surface tension gradient effect field is added to the first target heat sink model to obtain the second target heat sink model.

6. The radiator evaluation method according to claim 1, characterized in that, The number of heat source regions is multiple, and the preset test conditions include the number of heat source regions activated during the test, and the total power of the activated heat source regions. The test results include temperature cloud maps, velocity cloud maps, and pressure cloud maps of the liquid metal within the second target radiator model, as well as temperature cloud maps, velocity cloud maps, and pressure cloud maps of the gas within the second target radiator model.

7. The radiator evaluation method according to claim 1, characterized in that, The method further includes: The second target heat sink model is meshed, wherein the mesh cell size corresponding to the interface is smaller than the mesh cell size corresponding to the region other than the interface in the second target heat sink model, and the mesh cell density corresponding to the interface is greater than the mesh cell density corresponding to the region other than the interface in the second target heat sink model.

8. A radiator evaluation device, characterized in that, include: The first processing module is used to establish an initial heat sink model corresponding to the target heat sink, wherein the initial heat sink model includes a substrate body area, an initial liquid metal filling area, a heat source area, and a support column structure model. The second processing module is used to randomly generate a bubble model and add the randomly generated bubble model to the initial heat sink model to obtain a first target heat sink model, wherein the bubble model includes randomly generated bubbles containing gas. The third processing module is used to add a surface tension gradient effect field to the first target heat sink model to obtain a second target heat sink model, wherein the boundary of the surface tension gradient effect field is the interface between liquid metal and gas in the second target heat sink model. The fourth processing module is used to determine the heat dissipation capacity evaluation result of the target heat sink based on the second target heat sink model, wherein the heat dissipation capacity evaluation result includes the test results of the second target heat sink model under different preset test conditions.

9. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores a program, wherein when the program is executed, it controls the device containing the non-volatile storage medium to perform the heat sink evaluation method according to any one of claims 1 to 7.

10. An electronic device, characterized in that, include: A memory and a processor, the processor being configured to run a program stored in the memory, wherein the program, when running, executes the heat sink evaluation method according to any one of claims 1 to 7.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the radiator evaluation method according to any one of claims 1 to 7.

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