A method and system for performance analysis and optimization of a multi-working fluid multi-liquid wick structure heat pipe

Abstract

This invention discloses a method and system for performance analysis and optimization of heat pipes with multi-working-fluid and multi-wick structures, belonging to the field of heat pipe thermal management technology. The method uses the CGS unit system to complete parameter standardization and initialization, calculates the thermophysical parameters of the multi-working-fluid and the hydraulic characteristics of the multi-wick, couples five types of pressure drops and incorporates the compressible flow effect of the adiabatic section, constructs a sound velocity and carry-over limit model, and completes directional optimization through multi-strategy iteration to output performance curves. The system includes parameter, property, hydraulic, coupling, calculation, optimization, and output modules. This invention covers the entire temperature range of -50 to 1200℃, is compatible with five types of wicks, has high calculation accuracy, can predict failure, is highly efficient in iteration, and is practical for engineering applications. It is suitable for the design, verification, and optimization of heat pipes in spacecraft thermal control, high-end electronic heat dissipation, and nuclear energy device thermal management.

Description

Technical Field

[0001] This invention belongs to the field of heat pipe thermal management technology, specifically relating to a method and system for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures. Background Technology

[0002] As a passive element that achieves efficient heat transfer through the vapor-liquid phase change of the working fluid, heat pipes have been widely used in aerospace thermal control, high-end electronic equipment heat dissipation, industrial waste heat recovery, and nuclear power plant thermal management due to their advantages of high heat transfer efficiency, no moving parts, and high reliability. The heat transfer performance of a heat pipe is determined by the synergistic matching of the thermophysical properties of the working fluid, the wick structure, geometric parameters, and operating conditions. The accuracy and versatility of its performance analysis methods directly determine the rationality and reliability of the heat pipe design.

[0003] Current mainstream methods for analyzing heat pipe performance still have significant technical limitations: First, the working fluid adaptability is limited. Most methods are designed only for water working fluid or a single liquid metal working fluid, which cannot cover the full temperature range of application scenarios from -50 to 1200℃. The liquid metal working fluid required for heat dissipation of high-temperature thrusters in spacecraft and the water working fluid required for heat dissipation of electronic equipment at room temperature cannot be analyzed by the same model. Cross-scenario applications require the redevelopment of calculation logic, which is extremely inefficient. Secondly, the compatibility of the liquid suction core structure is insufficient. It can only complete calculations for single structures such as circular channels and uniform cores, and cannot be adapted to complex structures such as spiral grooves, annular channels, and coreless structures. In particular, the spiral groove liquid suction core has an extended flow path and a tilted steam flow area due to the spiral angle, and traditional methods cannot accurately calculate its hydraulic characteristics. Third, the multiphysics coupling accuracy is low. It generally assumes that the steam flow is incompressible and ignores the compressibility effect under high flow velocity in the adiabatic section. At the same time, it simplifies the coupling calculation of liquid friction pressure drop, steam friction pressure drop and capillary pressure drop, which makes it impossible to accurately predict the pressure field in the high temperature heat pipe scenario. Furthermore, it does not consider the gravity-assisted effect brought about by the heat pipe tilt angle, resulting in serious distortion of performance prediction under tilted installation conditions. Fourth, the failure limit analysis is lacking. The maximum heat transfer of the heat pipe is estimated only by empirical formulas. The physical calculation models of the speed of sound limit and the carry limit are not systematically integrated. It is impossible to accurately predict the failure risks of heat pipe heat transfer interruption and wick drying under high load conditions, which can easily lead to the failure of the thermal management system. Fifth, the optimization capability is insufficient, and it is unable to complete targeted iterative optimization of core design parameters such as capillary radius, channel size, and heat pipe length. The design and development cycle of new heat pipes is long and their engineering practicality is poor.

[0004] To address the aforementioned issues, there is an urgent need for a heat pipe performance analysis method that can adapt to multiple types of working fluids and multiple liquid-absorbing cores, accurately couple multiple physical fields, and possess directional optimization capabilities, thereby solving the pain points of existing methods such as poor versatility, low computational accuracy, and weak engineering adaptability. Summary of the Invention

[0005] The technical problem to be solved by this invention is to provide a method and system for performance analysis and optimization of heat pipes with multi-working fluid and multi-wick structure, which addresses the shortcomings of the prior art. This method solves the technical problems of existing heat pipe performance analysis methods, such as single working fluid compatibility, poor wick structure compatibility, low accuracy of multi-physics coupling, lack of extreme condition analysis, and insufficient iterative optimization capability. It has strong versatility, high calculation accuracy, high iteration efficiency, and good engineering applicability.

[0006] The present invention adopts the following technical solution: A method for performance analysis and optimization of heat pipes with multi-working-fluid and multi-absorbent core structures includes the following steps: S1. The geometric parameters, operating parameters, and calculation control parameters of the heat pipe are standardized and initialized using the centimeter-gram-second unit system, and the basic physical constants, calculation thresholds and basic geometric quantities of the heat pipe are set. S2. Based on the type of working fluid determined in the initialization, calculate the thermophysical parameters of the working fluid at the current working temperature using the corresponding experimental fitting formula; S3. Based on the type of liquid-absorbing core determined in the initialization, the corresponding hydraulic calculation model is used to calculate the liquid flow area, steam flow area, hydraulic radius and friction coefficient. S4. Based on the thermophysical parameters of the working fluid obtained in S2 and the liquid flow area, steam flow area, hydraulic radius, and friction coefficient obtained in S3, couple the calculation of liquid friction pressure drop, steam friction pressure drop, inertial pressure drop, hydrostatic pressure drop, and capillary pressure drop. For heat pipes containing adiabatic sections, incorporate the compressible flow effect of the adiabatic section into the pressure drop calculation to complete the coupled calculation of the pressure field and temperature field. S5. Based on the pressure field and temperature field parameters obtained from the coupling calculation in S4, construct the calculation model of the sound speed limit and the carrying limit to obtain the maximum safe heat transfer threshold of the heat pipe. S6. Using capillary radius, operating temperature, heat pipe length, and channel size as optimization targets, based on the coupling calculation results of S4 and the maximum safe heat transfer threshold obtained in S5, it uses iterative convergence logic with linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation to complete the directional iterative optimization of capillary radius, operating temperature, heat pipe length, or channel size, and outputs the optimized heat pipe performance parameters.

[0007] Preferably, in S1, the calculation control parameters include the loop start value, loop end value, loop step size, and calculation type; the basic physical constants include pi and gravitational acceleration g = 980 cm / s². 2 The universal gas constant R; the calculation threshold includes an iterative convergence threshold of 1×10⁻⁶. -5 Minimum heat transfer threshold 1×10 -5 erg / s.

[0008] Preferably, in S2, the working fluid type includes lithium, sodium, potassium, mercury or water; the thermophysical parameters of the working fluid include saturation pressure, molar mass, liquid density, liquid viscosity, latent heat of vaporization, surface tension and specific heat ratio.

[0009] Preferably, in S3, the liquid-absorbing core type includes coreless, circular channel, annular channel, spiral groove, or uniform core; the dedicated hydraulic calculation model includes a coreless structure model based on liquid film Reynolds number, a circular channel model based on multi-channel parallel flow channel, an annular channel model based on rectangular annular flow channel approximation, a spiral groove model based on the effective length of spiral expansion, and a uniform liquid-absorbing core model based on porous media.

[0010] Preferably, in S4, the incorporation of the compressible flow effect of the adiabatic section specifically includes: When the length of the adiabatic section is greater than 0, calculate the Mach number at the evaporator outlet and the Reynolds number on the steam side; determine the friction coefficient, and calculate the flow function and the maximum flow function; if the flow function is less than the maximum flow function, it is determined to be sonic flow; otherwise, solve for the Mach number at the outlet of the adiabatic section using the Newton-Raphson iteration method; calculate the pressure ratio based on the pressure ratio function, and then solve for the outlet pressure and pressure drop of the adiabatic section; solve for the outlet saturation temperature of the adiabatic section based on the outlet pressure of the adiabatic section, thus completing the coupling of the pressure field and the temperature field.

[0011] Preferably, in S5, constructing the calculation model for the speed of sound and the carry-over limit specifically includes: For the sound speed limit, the heat transfer limit of the sound speed limit is calculated based on the relationship between the stagnation pressure and the saturation temperature when the steam flow rate reaches the sound speed; for the carry-over limit, the heat transfer limit of the carry-over limit is calculated based on the Podenstein number and correction factor of the steam flowing at high speed carrying the liquid.

[0012] Preferably, in S6, the iterative convergence logic employing linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation specifically includes: In the first iteration, the optimization variables are amplified by 1.1 times, and the convergence benchmark and convergence deviation are initialized. The relative deviation is calculated. If the relative deviation is less than the convergence threshold, the iteration is considered to have converged; otherwise, the correction step is initiated. The iteration slope is calculated, and the optimization variables are corrected. If the relative deviation is greater than the minimum convergence deviation, the iteration is considered to be diverging, and the optimization variables are forcibly corrected. If the optimization variables have no physical meaning, the optimization variables are reset. If gravity assistance exists and the liquid friction pressure drop meets specific conditions, the gravity assistance flag is turned off and the iteration counter is reset.

[0013] Preferably, in S6, the optimized heat pipe performance parameters output specifically include: Output capillary pressure drop-channel number curve, heat transfer-sound velocity limit-temperature curve, saturation temperature-length distribution curve, or heat transfer-channel size curve.

[0014] Preferably, the geometric parameters include at least one of the following: evaporation section length, adiabatic section length, condensation section length, pipe cross-sectional area, heat pipe inclination angle, pipe radius, wick thickness, porosity, channel wall thickness, maximum channel spacing, wall thickness, tortuosity, channel size, number of channels, number of auxiliary channels, number of spiral groove turns, mesh count of the wire mesh wick, and wire diameter.

[0015] Secondly, embodiments of the present invention provide a performance analysis and optimization system for heat pipes with multi-working-fluid and multi-wick structures, comprising: The parameter module uses a centimeter-gram-second unit system to standardize and initialize the geometric parameters, operating parameters, and calculation control parameters of the heat pipe, and completes the setting of basic physical constants, calculation thresholds, and calculation of basic geometric quantities of the heat pipe. The physical properties module calculates the thermophysical parameters of the working fluid at the current operating temperature using the corresponding experimental fitting formula, based on the working fluid type determined during initialization. The hydraulic module, based on the type of liquid suction core determined during initialization, uses a dedicated hydraulic calculation model corresponding to the structure to calculate the liquid flow area, steam flow area, hydraulic radius, and friction coefficient. The coupling module, based on the thermophysical parameters of the working fluid obtained from the physical properties module and the liquid flow area, steam flow area, hydraulic radius, and friction coefficient obtained from the hydraulic module, performs coupled calculations of liquid friction pressure drop, steam friction pressure drop, inertial pressure drop, hydrostatic pressure drop, and capillary pressure drop. For heat pipes containing adiabatic sections, the compressible flow effect of the adiabatic section is incorporated into the pressure drop calculation, thus completing the coupled calculation of the pressure field and temperature field. The calculation module, based on the pressure field and temperature field parameters obtained by the coupling module, constructs a calculation model for the sound speed limit and the carrying limit, and obtains the maximum safe heat transfer threshold of the heat pipe. The optimization module uses capillary radius, operating temperature, heat pipe length, and channel size as optimization targets. Based on the coupling calculation results of the coupling module and the maximum safe heat transfer threshold obtained by the calculation module, it adopts iterative convergence logic with linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation to complete the targeted iterative optimization of capillary radius, operating temperature, heat pipe length, or channel size. The output module is used to output the optimized heat pipe performance parameters obtained by the optimization module.

[0016] Thirdly, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures.

[0017] Fourthly, embodiments of the present invention provide a computer-readable storage medium including a computer program, which, when executed by a processor, implements the steps of the above-described method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures.

[0018] Fifthly, a chip includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures.

[0019] In a sixth aspect, embodiments of the present invention provide an electronic device, including a computer program, which, when executed by the electronic device, implements the steps of the above-described method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures.

[0020] Compared with the prior art, the present invention has at least the following beneficial effects: A performance analysis and optimization method for heat pipes with multi-working-fluid and multi-wick structures is proposed. This method decouples the heat transfer process of the heat pipe into four core physical processes and establishes a standardized calculation logic for the entire process, including parameter initialization, property calculation, hydraulic calculation, pressure drop coupling, limit calculation, and iterative optimization. The CGS unit system unifies the calculation benchmark from macroscopic geometric quantities to microscopic thermophysical properties, eliminating dimensional errors in multi-physics coupling and ensuring calculation stability across the entire temperature range, from low-temperature electronic heat dissipation to high-temperature aerospace thermal control. Secondly, by establishing a modular and universal calculation framework, the complex phase change heat transfer process is decoupled, allowing the algorithm to flexibly adapt to different working fluids and wick structures without rewriting core code for each structure, significantly improving cross-scenario reusability. Finally, through a closed-loop iterative optimization logic, a leap from single-condition calculation to full-parameter directional optimization is achieved. This not only verifies heat pipe performance but also directly outputs the optimal design scheme, significantly shortening the heat pipe development cycle.

[0021] Furthermore, setting specific iterative convergence thresholds provides a clear termination condition for the algorithm, avoiding error accumulation due to insufficient computational precision or infinite loops due to excessively high precision requirements, thus ensuring a balance between computational efficiency and accuracy. Fixing constants such as gravitational acceleration within the CGS system ensures consistency of calculation results across different geographical locations. In addition, setting a minimum heat transfer threshold effectively filters out physically invalid micro-heat transfer data, preventing numerical oscillations in the computational model under low-load conditions and improving the algorithm's robustness under extreme conditions.

[0022] Furthermore, by establishing a dedicated experimental fitting formula library for these five typical working fluids (including room temperature water, low temperature mercury, and high temperature liquid metal), this invention can accurately capture the nonlinear property changes of different working fluids during phase transition. Through an independent property calculation module, it ensures that the calculation error of the thermophysical properties of the working fluid is minimized in high temperature aerospace thermal control or room temperature electronic heat dissipation scenarios.

[0023] Furthermore, by calculating the effective length of the spiral expansion, the resistance path of the liquid flow was precisely corrected; simultaneously, by correcting the steam flow area, the obstruction effect of the spiral groove on steam flow was accurately reflected. This calculation method based on geometric reconstruction significantly improves the accuracy of hydraulic calculations for complex structures such as spiral grooves, enabling more accurate performance predictions of the designed heat pipes under high-speed rotation or high heat flux density conditions.

[0024] Furthermore, by introducing Newton's iterative method to solve for the Mach number, the pressure and temperature fields were precisely coupled, accurately simulating the expansion work and temperature change process of steam within the adiabatic section. This significantly reduced the performance prediction error of the heat pipe under near-sonic speed limits, providing crucial data support for the safe design of high-power heat pipes.

[0025] Furthermore, the sonic limit model, through saturated temperature-pressure coupling calculations, can accurately pinpoint the critical heat transfer at which the steam flow rate reaches the local speed of sound, preventing heat pipe blockage. The carry-over limit model, incorporating the Potentstein number and correction coefficients, precisely describes the shear-carrying effect of high-speed steam flow on the liquid film, accurately predicting the critical point of wick drying, and ensuring that the designed heat pipe will not fail due to insufficient heat transfer limit throughout its entire lifespan.

[0026] Furthermore, the algorithm first amplifies the variables by a factor of 1.1 as intelligent initial values, significantly shortening the search path; then, it introduces linear interpolation correction to replace the traditional step-size reduction, improving approximation efficiency; most importantly, it incorporates a double safety net of divergence suppression and physical constraints, immediately forcing corrections once an iteration direction error or parameter out-of-bounds error is detected to prevent computational crashes. A gravity-assisted adaptation mechanism ensures that, under inclined conditions, the algorithm can automatically identify and disable inapplicable gravity-assisted models, guaranteeing the universality of the computation.

[0027] Furthermore, by outputting the capillary pressure drop-channel number curve, the influence of the wick structure parameters on the reflux capacity can be visually observed, allowing for the selection of the optimal channel number to balance flow resistance and capillary force. The output heat transfer-sound velocity limit-temperature curve clearly demonstrates the maximum load-bearing capacity of the heat pipe at different operating temperatures, helping designers avoid the dangerous zone of the sound velocity limit.

[0028] Furthermore, the performance of heat pipes is highly dependent on geometric details. By incorporating these microscopic geometric parameters into the calculation system, this invention can distinguish the subtle effects of different manufacturing processes on performance.

[0029] It is understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0030] In summary, this invention addresses the shortcomings of existing technologies, such as poor versatility, low accuracy, and weak optimization capabilities, through full-temperature-range working fluid adaptation, accurate modeling of complex wicking structures, compressible flow coupling in the adiabatic section, and multi-strategy iterative optimization algorithms. It enables cross-scenario reuse, significantly improves the efficiency and reliability of heat pipe design, and has significant engineering application value.

[0031] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0032] Figure 1 This is a flowchart illustrating the overall process of the method of the present invention. Figure 2 The graph shows the calculated performance results of the heat pipe under the capillary radius optimization mode. Figure 3 The graph shows the calculation results of heat pipe heat transfer and sound velocity limit under the optimized operating temperature mode. Figure 4 This is a graph showing the calculated saturation temperature distribution under the heat pipe length optimization mode; Figure 5 The graph shows the calculated performance results of the heat pipe under the channel size optimization mode; Figure 6 This is a schematic diagram of the geometric structure of the spiral groove suction core; Figure 7 This is a schematic diagram of the multi-physics field pressure drop distribution of a heat pipe. Figure 8 A schematic diagram of a computer device provided in an embodiment of the present invention; Figure 9 This is a block diagram of a chip provided according to an embodiment of the present invention.

[0033] Among them, 60. Computer equipment; 61. Processor; 62. Memory; 63. Computer program; 600. Electronic device; 610. Processing unit; 620. Storage unit; 6201. Random access memory unit; 6202. Cache memory unit; 6203. Read-only memory unit; 6204. Program / utility; 6205. Program module; 630. Bus; 640. Display unit; 650. Input / output interface; 660. Network adapter; 700. External device. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0036] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0037] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0038] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0039] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0040] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0041] This invention provides a method for performance analysis and optimization of heat pipes with multi-working-fluid and multi-wick structures. It constructs a modular, end-to-end analysis framework adaptable to five working fluids (lithium, sodium, potassium, mercury, and water) covering a full temperature range of -50 to 1200°C, and compatible with five types of wick structures: coreless, circular channel, annular channel, spiral groove, and uniform wick. Through multi-physics coupled pressure drop calculation, solution of compressible flow effects in the adiabatic section, quantitative analysis of sound velocity and carryover limits, and multi-strategy iterative optimization logic, it achieves accurate calculation and targeted optimization of heat pipe performance. This invention can be widely applied to heat pipe design, performance verification, and optimization in scenarios such as spacecraft thermal control, high-end electronic equipment heat dissipation, and nuclear energy device thermal management. It provides accurate multi-physics parameter calculation and quantitative performance optimization guidance for heat pipe design and performance verification in various scenarios such as spacecraft thermal control, high-end electronic equipment heat dissipation, and industrial waste heat recovery.

[0042] Please see Figure 1 This invention discloses a performance analysis and optimization method for heat pipes with multi-working-medium and multi-absorbent core structures. Based on a modular computational model, it constructs a comprehensive analysis system encompassing parameter initialization, calculation of multi-working-medium thermophysical properties, calculation of multi-absorbent core hydraulic characteristics, calculation of multi-physics field coupling pressure drop, calculation of failure limit threshold, multi-strategy iterative optimization, and data output. To facilitate engineering calculations, this invention builds a computational framework based on the centimeter-gram-second (CGS) unit system. Utilizing a saturation temperature quantization calculation model and a Mach number iterative solution model, it achieves high-precision coupling of multi-physics fields. Simultaneously, it designs multi-strategy iterative logic for linear interpolation correction, divergence suppression, and physical constraints to address the slow convergence and divergence issues of traditional analysis methods. The specific calculation steps of this invention are as follows: S1, Calculation of heat pipe characteristic parameters To achieve universal calculation of the heat pipe model, the core input parameters of the heat pipe are first standardized and defined into three categories: geometric parameters, operating condition parameters, and calculation control parameters, and parameter initialization and basic geometric quantity calculation are completed.

[0043] All parameters in this invention are expressed in centimeter-gram-second (CGS) units. The input parameters include 24 core characteristic parameters, specifically: operating temperature, total heat transfer, evaporation section length, adiabatic section length, condensation section length, pipe cross-sectional area, heat pipe inclination angle, pipe radius, wick thickness / porosity, channel wall thickness / maximum channel spacing / wall thickness / torsional curvature, channel size, geometric parameters, number of channels, number of auxiliary channels, wick type, number of spiral groove turns, working fluid type, flow state, cycle start value, cycle end value, cycle step size, calculation type, wall thickness, and mesh count of the wire mesh wick.

[0044] Based on the input parameters, the basic geometric quantities of the heat pipe are calculated. The core formula is as follows: Total length of heat pipe:

[0045] Effective length on the liquid side:

[0046] Effective length on the steam side:

[0047] in, , where is the length of the evaporation section, in cm; The length of the insulation section is in cm; , where is the length of the condensation section, in cm.

[0048] Simultaneously, the initialization of fundamental physical constants and calculation thresholds is completed, including pi (π), gravitational acceleration g = 980 cm / s², universal gas constant R, and iterative convergence threshold 1 × 10⁻⁶. -5 Minimum heat transfer threshold 1×10 -5 erg / s.

[0049] S2, Calculation of thermophysical properties of multiple working fluids Based on the initialized working fluid type parameters and the experimental fitting formula for the corresponding working fluid, the core thermophysical parameters of the working fluid at the current operating temperature are automatically calculated, providing basic physical property inputs for subsequent hydraulic calculations and pressure drop coupling calculations. This invention is compatible with five typical working fluids, covering the entire temperature range of -50 to 1200℃. The calculation formulas for the core parameters of each working fluid are as follows: (1) Lithium working medium (IFLUID=1, suitable for high temperature scenarios 500~1200℃) Saturation pressure: The unit is Pa; Molar mass: Unit: g / mol; Liquid density: Unit: g / cm³; Liquid viscosity: The unit is Pa·s; Latent heat of vaporization: Unit: J / kg; Surface tension: Unit: N / m; Specific heat ratio: .

[0050] (2) Sodium working medium (IFLUID=2, suitable for medium and high temperature scenarios 300~1000℃) Saturation pressure: The unit is Pa; Molar mass: Unit: g / mol; Liquid density: Unit: g / cm³; Liquid viscosity: The unit is Pa·s; Latent heat of vaporization: Unit: J / kg; Surface tension: Unit: N / m; Specific heat ratio: .

[0051] (3) Potassium working medium (IFLUID=3, suitable for medium temperature scenarios 200~800℃) Saturation pressure: The unit is Pa; Molar mass: Unit: g / mol; Liquid density: Unit: g / cm³; Liquid viscosity: The unit is Pa·s; Latent heat of vaporization: Unit: J / kg; Surface tension: Unit: N / m; Specific heat ratio: .

[0052] (4) Mercury working medium (IFLUID=4, suitable for medium and low temperature scenarios -50~300℃) Saturation pressure: The unit is Pa; Molar mass: Unit: g / mol; Liquid density: Unit: g / cm³; Liquid viscosity: The unit is Pa·s; Latent heat of vaporization: Unit: J / kg; Surface tension: Unit: N / m; Specific heat ratio: (constant).

[0053] (5) Water medium (IFLUID=5, suitable for normal temperature scenarios 0~150℃) Saturation pressure: The unit is Pa; Molar mass: Unit: g / mol; Liquid density: Unit: g / cm³; Liquid viscosity: The unit is Pa·s; Latent heat of vaporization: Unit: J / kg; Surface tension: Unit: N / m; Specific heat ratio: (constant).

[0054] The vapor density of all working fluids is calculated uniformly using the ideal gas law:

[0055] in, The density of the working fluid vapor is expressed in g / cm³. The universal gas constant is 8.314 × 10⁻⁶. 7 erg / (mol·K); The operating temperature of the heat pipe is K.

[0056] S3, Calculation of Hydraulic Characteristics of Multiple Types of Suction Cores Based on the initialized suction core type parameters, and using the corresponding structure's dedicated hydraulic calculation model, the liquid flow area is calculated. Steam circulation area Hydraulic radius coefficient of friction Four core hydraulic characteristic parameters provide hydraulic parameter inputs for subsequent pressure drop coupling calculations. This invention is compatible with five types of liquid-absorbing core structures, and the core calculation logic for each structure is as follows: (1) Coreless structure (ARTG=0) The coreless structure relies on gravity or centrifugal force to drive the liquid film recirculation. The liquid film thickness is calculated using the liquid film Reynolds number, and then the hydraulic parameters of the annular flow channel are derived. Liquid film Reynolds number:

[0057] in, For the working fluid mass flow rate, , kg / s; Where is the radius of the heat pipe, in cm.

[0058] Laminar friction coefficient: ( ); Turbulent friction coefficient: ( ); Liquid film thickness: ; Liquid flow area: The unit is cm². Steam flow area: The unit is cm². Hydraulic radius: , unit cm.

[0059] (2) Circular channel suction core (ARTG=1) The circular channel liquid suction core has a multi-channel parallel flow channel structure. Considering the influence of channel wall thickness on the vapor flow area, the core calculation formula is as follows: Single-channel liquid flow area: The unit is cm²; in the formula The radius of the channel is in cm; Steam side radius: The unit is cm; where $TSD$ is the thickness of the absorbent core, in cm. Steam flow area: The unit is cm². in, For the number of channels, The auxiliary channel number is $TSA$, which represents the channel wall thickness in cm. Hydraulic radius: The unit is cm; Laminar friction coefficient: ; (3) Annular channel suction core (ARTG=2) The annular channel liquid suction core is calculated approximately based on a rectangular annular flow channel. The friction coefficient is corrected according to the channel size ratio. The core calculation formula is as follows: Channel height: The unit is cm; Where TBA is the maximum channel spacing, in cm; Unit: cm Width of the annular channel, in cm Single-channel liquid flow area: The unit is cm². Steam flow area: The unit is cm². Hydraulic radius: The unit is cm; Size ratio: ; coefficient of friction: The friction coefficient is corrected to be in single-channel mode. .

[0060] (4) Spiral groove suction core (ARTG=3) The spiral groove liquid suction core needs to first calculate the spiral angle and the effective length of the spiral unfolding, correct for the tilt effect of the steam flow area, and then reuse the hydraulic calculation logic of the annular channel. The core calculation formula is as follows: Circumference of a single turn of the spiral: The unit is cm; Effective length of spiral unfolding: The unit is cm; in, The number of spiral groove turns; Helix angle: The unit is rad; Spiral groove inner diameter: The unit is cm; Steam flow area: The unit is cm². Where GH is the groove width, WS is the wall thickness, and TMG is the groove depth, all in cm; Steam-side equivalent radius: The unit is cm; Channel height: The unit is cm; The subsequent hydraulic radius and friction coefficient were solved using the same calculation formula for the annular channel.

[0061] (5) Uniform liquid aspiration core (ARTG=4) The uniform liquid-absorbing core has a porous media structure. Considering the influence of porosity and tortuosity on flow resistance, the core calculation formula is as follows: Liquid flow area: The unit is cm². in, Where is the thickness of the absorbent core, in cm; $PORO$ is the porosity of the absorbent core. Hydraulic radius: The unit is cm; Where RMESH is the mesh count and WS is the wire diameter, in cm; when At that time, take Effective capillary radius Steam side radius: The unit is cm; Steam flow area: The unit is cm². coefficient of friction: In the formula, TORT represents the tortuosity of the absorbent core; After completing the hydraulic parameter calculations, the steam side perimeter is calculated simultaneously. This provides parameter input for subsequent calculations of steam friction pressure drop.

[0062] S4. Calculation of multiphysics coupling voltage drop throughout the heat pipe process. This step is the core calculation process, which couples the calculation of five types of core pressure drops throughout the heat pipe process. At the same time, for heat pipes with adiabatic sections, the compressible flow effect of the adiabatic section is incorporated to complete the bidirectional coupled calculation of the pressure field and temperature field.

[0063] (1) Calculation of voltage drop in five types of cores 1. Fluid frictional pressure drop Based on the Hagen-Poiseuille formula, considering the number of channels, hydraulic radius, and flow state, the core formula is as follows:

[0064] in, The working fluid mass flow rate is expressed in kg / s. The total heat transfer of the heat pipe is expressed in erg / s.

[0065] 2. Steam friction pressure drop Based on the formula for frictional pressure drop in circular pipe flow, the core formula is as follows:

[0066] When the flow state is laminar or mixed, the steam friction pressure drop can be simplified for calculation.

[0067] 3. Inertial pressure drop Based on the derivation of steam momentum changes, the core formula is as follows:

[0068] in, Where is the cross-sectional area of ​​the heat pipe, cm²; during length optimization calculations, the inertial pressure drop is corrected in segments according to the length derivative.

[0069] 4. Static pressure drop Considering the gravitational influence of the heat pipe tilt angle, the core formula is as follows:

[0070] in, The heat pipe tilt angle is in degrees; when At that time, static pressure drop .

[0071] 5. Capillary pressure drop Based on the Young-Laplace equation, the core formula is as follows: When there is a wick structure:

[0072] In the case of a coreless structure:

[0073] in, The effective capillary radius of the suction core is denoted in cm.

[0074] (2) Calculation of compressible flow pressure drop in the adiabatic section When the length of the insulation section When the compressible flow effect of steam is incorporated, the pressure drop and temperature field of the adiabatic section are solved by Mach number iteration and coupled calculation with saturated temperature-pressure. The specific steps are as follows: 1. Calculate the Mach number at the evaporator outlet:

[0075] 2. Calculate the Reynolds number on the steam side:

[0076] Determine the coefficient of friction (Laminar flow) turbulence ).

[0077] 3. Calculate the flow function:

[0078] Maximum flow function:

[0079] 4. Iteratively solve for the Mach number at the outlet of the adiabatic section. :like It was determined to be sound velocity flow. Otherwise, solve using Newton's iteration method. .

[0080] 5. Calculate the pressure ratio:

[0081] Among them, the pressure ratio function The upper limit of the pressure ratio is revised to

[0082] 6. Calculate the outlet pressure of the adiabatic section: Pressure drop in the adiabatic section: .

[0083] 7. According to Solve for the saturation temperature at the outlet of the adiabatic section. This completes the coupling of the pressure field and the temperature field.

[0084] S5. Calculation of heat pipe failure threshold We constructed two core failure models: the sound speed limit and the carrying capacity limit, and calculated the maximum safe heat transfer threshold of the heat pipe, providing a quantitative basis for predicting the failure risk of the heat pipe.

[0085] (1) Calculation of the speed of sound The speed limit of sound is when the steam flow velocity reaches the speed of sound. The upper limit of heat transfer at this time is calculated in two scenarios: 1. Scenarios without an adiabatic section ( ) Sound stagnation pressure:

[0086] according to Solve for the corresponding saturation temperature ; The maximum heat transfer at the speed of sound:

[0087] 2. Scenarios with adiabatic sections ( ) Calculate the friction loss of the adiabatic section The Mach number at the evaporator outlet is solved using Newton's iterative method. ,satisfy

[0088] Calculate the steam velocity at the evaporator outlet:

[0089] Iterate twice to correct the inertia coefficient $AB$ and calculate the viscous pressure drop. Inertial pressure drop With stagnation pressure

[0090] Solving based on the saturation temperature calculation model Finally, the heat transfer limit at the speed of sound is calculated:

[0091] in, The stabilizing pressure ratio.

[0092] (2) Carrying limit calculation The carry-over limit is the upper limit of heat transfer caused by high-speed steam flow carrying liquid, leading to the drying of the wick. It is calculated in two scenarios: 1. It has a liquid-absorbing core structure (ARTG≠0) Feature length:

[0093] Scenario without adiabatic section:

[0094] In scenarios with an adiabatic section: iteratively calculate the outlet pressure, temperature, and steam density of the adiabatic section; after iterative convergence, calculate the maximum heat transfer capacity. ,in This represents the steam density at the outlet of the adiabatic section.

[0095] 2. Coreless structure (ARTG=0) Calculate the Potentstein number:

[0096] Correction factor:

[0097] Carrying the limit of heat transfer:

[0098] After completing the ultimate heat transfer calculation, the current heat transfer is determined by the marker bit to determine whether it exceeds the speed of sound limit, providing a quantitative basis for the design of heat pipe safety conditions.

[0099] S6, Multi-strategy Iterative Optimization Calculation For four optimization objectives—capillary radius, temperature, length, and channel size—a multi-strategy iterative convergence logic combining linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation is employed to achieve targeted optimization of heat pipe parameters. The specific steps are as follows: 1. Iterative initialization: In the first iteration, the optimization variables are amplified by 1.1 times to quickly approach the target value. The convergence baseline CONVB=1.0 and the convergence deviation CONV=1.0 are initialized. 2. Convergence judgment: Calculate the relative deviation. In the formula The parameter value for the current iteration step. The parameter value is the value of the previous iteration step; when If the iteration is successful, stop the iteration; otherwise, proceed to the correction step. 3. Linear interpolation correction: Calculate the iterative slope In the formula To adjust the optimization variables for convergence criteria (such as pressure drop difference). The goal is To achieve parameter matching; 4. Divergence Suppression Strategy: The minimum convergence deviation CONVB is updated in real time. When this occurs, it is determined to be iterative divergence, and the optimization variables are forcibly corrected. To suppress the expansion of deviation; the upper limit of the number of iterations is set to 100, and when the limit is exceeded, forced convergence is performed and the gravity-assisted adaptation judgment is entered. 5. Physical constraint correction: If the optimization variables (Without physical meaning, such as a negative capillary radius), reset to This ensures both computational continuity and physical plausibility. 6. Gravity-assisted adaptation: If the liquid friction pressure drop Furthermore, gravity assistance is present. By disabling the gravity assistance flag, resetting the iteration counter, and recompleting the iteration calculation, the accuracy of the calculation under inclined conditions can be ensured.

[0100] S7, Heat Pipe Performance Analysis The quantitative performance curves and data obtained by the optimization objectives include capillary pressure drop-channel number curve, heat transfer-sound velocity limit-temperature curve, saturation temperature-length distribution curve, heat transfer-channel size curve, etc., which directly provide practical quantitative guidance for heat pipe design.

[0101] Meanwhile, this method supports receiving feedback data on heat pipe deformation, working fluid property shifts, and changes in operating parameters, and recompiles the heat pipe model and recalculates its performance according to steps S1 to S6, thereby realizing dynamic analysis of thermo-mechanical coupling under varying operating conditions of the heat pipe.

[0102] In another embodiment of the present invention, a performance analysis and optimization system for heat pipes with multi-working-medium and multi-absorbent core structures is provided. This system can be used to implement the above-mentioned performance analysis and optimization method for heat pipes with multi-working-medium and multi-absorbent core structures. Specifically, the performance analysis and optimization system for heat pipes with multi-working-medium and multi-absorbent core structures includes a parameter module, a physical property module, a hydraulic module, a coupling module, a calculation module, an optimization module, and an output module.

[0103] Among them, the parameter module uses the centimeter-gram-second unit system to standardize and initialize the geometric parameters, operating parameters, and calculation control parameters of the heat pipe, and completes the setting of basic physical constants, calculation thresholds, and calculation of basic geometric quantities of the heat pipe. The physical properties module calculates the thermophysical parameters of the working fluid at the current operating temperature using the corresponding experimental fitting formula, based on the working fluid type determined during initialization. The hydraulic module, based on the type of liquid suction core determined during initialization, uses a dedicated hydraulic calculation model corresponding to the structure to calculate the liquid flow area, steam flow area, hydraulic radius, and friction coefficient. The coupling module, based on the thermophysical parameters of the working fluid obtained from the physical properties module and the liquid flow area, steam flow area, hydraulic radius, and friction coefficient obtained from the hydraulic module, performs coupled calculations of liquid friction pressure drop, steam friction pressure drop, inertial pressure drop, hydrostatic pressure drop, and capillary pressure drop. For heat pipes containing adiabatic sections, the compressible flow effect of the adiabatic section is incorporated into the pressure drop calculation, thus completing the coupled calculation of the pressure field and temperature field. The calculation module, based on the pressure field and temperature field parameters obtained by the coupling module, constructs a calculation model for the sound speed limit and the carrying limit, and obtains the maximum safe heat transfer threshold of the heat pipe. The optimization module uses capillary radius, operating temperature, heat pipe length, and channel size as optimization targets. Based on the coupling calculation results of the coupling module and the maximum safe heat transfer threshold obtained by the calculation module, it adopts iterative convergence logic with linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation to complete the targeted iterative optimization of capillary radius, operating temperature, heat pipe length, or channel size. The output module is used to output the optimized heat pipe performance parameters obtained by the optimization module.

[0104] This invention provides a terminal device comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or corresponding function. The processor described in this embodiment can be used in the operation of a performance analysis and optimization method for heat pipes with multi-working-medium and multi-absorbent core structures, including: The geometric parameters, operating parameters, and computational control parameters of the heat pipe are standardized and initialized using a centimeter-gram-second (cm·g·s) unit system. This includes setting basic physical constants, computational thresholds, and calculating the basic geometric quantities of the heat pipe. Based on the initialized working fluid type, the thermophysical parameters of the working fluid at the current operating temperature are calculated using corresponding experimental fitting formulas. Based on the initialized wick type, a dedicated hydraulic calculation model for the corresponding structure is used to calculate the liquid flow area, vapor flow area, hydraulic radius, and friction coefficient. Based on the obtained thermophysical parameters of the working fluid and the liquid flow area, vapor flow area, hydraulic radius, and friction coefficient, the liquid frictional pressure drop, vapor frictional pressure drop, and inertial pressure are coupled and calculated. For heat pipes containing an adiabatic section, the pressure drop, hydrostatic pressure drop, and capillary pressure drop are calculated by incorporating the compressible flow effect of the adiabatic section into the pressure drop calculation, thus completing the coupled calculation of the pressure field and temperature field. Based on the pressure field and temperature field parameters obtained from the coupled calculation, a calculation model for the sound velocity limit and the carry-over limit is constructed to obtain the maximum safe heat transfer threshold of the heat pipe. Using the capillary radius, operating temperature, heat pipe length, and channel size as optimization targets, and based on the coupled calculation results and the maximum safe heat transfer threshold, an iterative convergence logic consisting of linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation is used to complete the directional iterative optimization of the capillary radius, operating temperature, heat pipe length, or channel size, and output the optimized heat pipe performance parameters.

[0105] Please see Figure 8 The terminal device is a computer device. In this embodiment, the computer device 60 includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When executed by the processor 61, the computer program 63 implements the performance analysis and optimization method for the multi-working-medium multi-absorbent core structure heat pipe in this embodiment. To avoid repetition, these details are not elaborated here. Alternatively, when executed by the processor 61, the computer program 63 implements the functions of each model / unit in the performance analysis and optimization system for the multi-working-medium multi-absorbent core structure heat pipe in this embodiment. To avoid repetition, these details are not elaborated here.

[0106] Computer device 60 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 8 This is merely an example of computer device 60 and does not constitute a limitation on computer device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0107] The processor 61 may be a Central Processing Unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0108] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on the computer device 60.

[0109] Furthermore, the memory 62 may include both internal storage units of the computer device 60 and external storage devices. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0110] Please see Figure 9 The terminal device is an electronic device 600, which is manifested in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including storage unit 620 and processing unit 610), a display unit 640, etc.

[0111] The storage unit stores program code, which can be executed by the processing unit 610 to perform the steps described in the method section of this specification according to various exemplary embodiments of the present invention. For example, the processing unit 610 can perform actions such as... Figure 1 The steps are shown in the figure.

[0112] Storage unit 620 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 6201 and / or cache memory 6202, and may further include a read-only memory (ROM) 6203.

[0113] Storage unit 620 may also include a program / utility 6204 having a set (at least one) program module 6205, such program module 6205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0114] Bus 630 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the multiple bus structures.

[0115] Electronic device 600 can also communicate with one or more external devices 700 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 600, and / or with any device that enables electronic device 600 to communicate with one or more other computing devices (e.g., router, modem). This communication can be performed via input / output interface 650. Furthermore, electronic device 600 can also communicate with one or more networks (e.g., local area network, wide area network, and / or public network, such as the Internet) via network adapter 660. Network adapter 660 can communicate with other modules of electronic device 600 via bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0116] This invention also provides a storage medium, specifically a computer-readable storage medium, which is a memory device in a terminal device for storing programs and data. It is understood that the computer-readable storage medium here can include both built-in storage media in the terminal device and extended storage media supported by the terminal device; it can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor, which can be one or more computer programs (including program code). More specific examples of the computer-readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical fiber, portable compact disk read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0117] Computer-readable storage media also include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium can also be any readable medium other than a readable storage medium that can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency, etc., or any suitable combination thereof.

[0118] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0119] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the heat pipe performance analysis and optimization method for multi-working-fluid multi-absorbent core structures in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor in the following steps: The geometric parameters, operating parameters, and computational control parameters of the heat pipe are standardized and initialized using a centimeter-gram-second (cm·g·s) unit system. This includes setting basic physical constants, computational thresholds, and calculating the basic geometric quantities of the heat pipe. Based on the initialized working fluid type, the thermophysical parameters of the working fluid at the current operating temperature are calculated using corresponding experimental fitting formulas. Based on the initialized wick type, a dedicated hydraulic calculation model for the corresponding structure is used to calculate the liquid flow area, vapor flow area, hydraulic radius, and friction coefficient. Based on the obtained thermophysical parameters of the working fluid and the liquid flow area, vapor flow area, hydraulic radius, and friction coefficient, the liquid frictional pressure drop, vapor frictional pressure drop, and inertial pressure are coupled and calculated. For heat pipes containing an adiabatic section, the pressure drop, hydrostatic pressure drop, and capillary pressure drop are calculated by incorporating the compressible flow effect of the adiabatic section into the pressure drop calculation, thus completing the coupled calculation of the pressure field and temperature field. Based on the pressure field and temperature field parameters obtained from the coupled calculation, a calculation model for the sound velocity limit and the carry-over limit is constructed to obtain the maximum safe heat transfer threshold of the heat pipe. Using the capillary radius, operating temperature, heat pipe length, and channel size as optimization targets, and based on the coupled calculation results and the maximum safe heat transfer threshold, an iterative convergence logic consisting of linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation is used to complete the directional iterative optimization of the capillary radius, operating temperature, heat pipe length, or channel size, and output the optimized heat pipe performance parameters.

[0120] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0121] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention 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 the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0122] Preferably, in step S3, a unique calculation logic based on the "effective length of spiral unfolding" is used for the spiral groove liquid suction core (ARTG=3).

[0123] The actual flow channel length of the spiral groove is much larger than the axial length of the heat pipe, and the steam flow cross-section is inclined. This embodiment first calculates the effective length on the liquid side based on the circumference and number of turns of the spiral, and then calculates the correction factor for the steam flow area based on the spiral angle. By reusing the annular channel model but substituting the corrected effective length and area, this invention accurately reproduces the true flow resistance and steam flow capacity of the spiral groove, solving the problem of high-precision calculation for complex structures.

[0124] In step S4, a compressible flow model was established for the case where the length of the adiabatic section is greater than 0.

[0125] In high-temperature heat pipes or long adiabatic sections, the steam velocity is extremely high, and the density changes significantly. This embodiment determines whether a critical state has been reached by calculating the ratio of the flow rate function to the maximum flow rate function. If not, Newton's iteration method is used to solve for the Mach number at the outlet of the adiabatic section, rather than a simple empirical formula. This setup can accurately calculate the expansion and cooling process of steam within the adiabatic section, correcting the deficiency of traditional methods that overestimate the heat transfer limit of the speed of sound, resulting in a very high degree of agreement between the pressure field calculation results and actual physical experimental data (error ≤ 10%).

[0126] In step S6, a closed-loop logic was designed that includes initial amplification, linear interpolation, divergence forced correction, and physical constraint reset.

[0127] In this embodiment, the variables are amplified by a factor of 1.1 at the start of the iteration to accelerate the approximation; the relative deviation is monitored in real time during the iteration process. Once the detected deviation exceeds the minimum convergence deviation (i.e., divergence is determined), the system does not exit with an error, but immediately forces the correction and optimization of the variables; if the variables have negative values ​​or other physically meaningless conditions, they are reset to reasonable initial values. This robust design ensures that the algorithm can still converge stably and output the optimal solution when facing extreme parameter combinations across the entire temperature range and all structures, greatly improving the software's engineering practicality.

[0128] To verify the correctness of the method of the present invention, the method was used to simulate the performance test experiment of the international standard heat pipe, and the calculation results were compared with the data in the literature.

[0129] The standard experimental heat pipe used in this verification is a potassium working fluid circular channel wick high-temperature heat pipe. The core parameters of the heat pipe are as follows: evaporation section length 35cm, adiabatic section length 0cm, condensation section length 450cm, pipe radius 1.85cm, wick thickness 0.03048cm, number of channels 3, channel radius 0.125cm, operating temperature 775K, total heat transfer 12500erg / s, and heat pipe tilt angle 0°.

[0130] Input the above parameters into the calculation model of this invention, and after completing the performance calculation, compare the calculated values ​​of the core parameters with the values ​​in the literature. The calculation results of the capillary radius optimization mode are as follows: Figure 2 As shown, the trend of capillary pressure drop in the heat pipe with the number of wick channels is revealed; the calculation results of the heat pipe operating temperature optimization mode are as follows: Figure 3 Figures 1 and 4 show the trends in heat transfer and sound velocity limit of the heat pipe with temperature; the calculation results for the heat pipe are as follows: Figure 5 This reveals the variation of heat pipe operating temperature with heat pipe length; the implementation results of channel size optimization calculation are as follows: Figure 6 Figure 7 This study revealed how the heat transfer capacity and sound velocity limit of a heat pipe vary with the channel size.

[0131] The comparison results show that the heat pipe performance analysis and optimization method developed in this invention, applicable to heat pipes with multiple working fluids and multiple wicking structures, can accurately model and calculate the performance of heat pipes with different working fluids and different wicking structures, meeting the accuracy requirements of engineering design. It can be directly applied to the design, performance verification and structural optimization of various heat pipes.

[0132] The present invention has the following beneficial effects: 1. Universally adaptable across all temperature ranges and structures, with strong reusability across different scenarios. This invention supports automatic calculation of the thermophysical properties of five typical working fluids: lithium, sodium, potassium, mercury, and water. It covers the entire temperature range from -50 to 1200℃, including low, medium, and high temperatures, and can be directly adapted to the heat pipe design requirements of different scenarios such as high-temperature thrusters in spacecraft, room-temperature heat dissipation in electronic devices, and high-temperature waste heat recovery in industrial metallurgy. At the same time, it is compatible with five types of liquid wicking structures: coreless, circular channel, annular channel, spiral groove, and uniform core. It designs a dedicated hydraulic characteristic calculation model for complex structures such as spiral grooves, eliminating the need to redevelop the core calculation logic and enabling model reuse across structures and scenarios, which significantly reduces the development cost of heat pipe design in multiple scenarios.

[0133] 2. High accuracy in multiphysics coupling calculations This invention breaks through the limitations of the incompressible flow assumption in traditional methods by incorporating the compressible flow effect of the adiabatic section into the core calculation framework. It achieves accurate Mach number calculation through Newton's iteration method and combines the fully coupled calculation of five types of pressure drops: liquid friction pressure drop, vapor friction pressure drop, inertial pressure drop, hydrostatic pressure drop, and capillary pressure drop, thereby controlling the calculation error of the heat pipe pressure field to ≤10%. At the same time, it fully considers the gravity-assisted effect brought about by the heat pipe tilt angle, corrects the pressure balance calculation in the tilted installation scenario, and significantly improves the accuracy of heat pipe performance prediction under complex operating conditions.

[0134] 3. Quantitative Analysis of Extreme Operating Conditions This invention integrates physical calculation models for the two core failure limits: the speed of sound limit and the carry-over limit. Through the collaborative calculation of the saturated temperature-pressure coupling model and the Mach number iterative solution model, it achieves accurate quantification of the ultimate heat transfer. It can directly determine the failure risks of heat pipes under high power and high load conditions, such as heat transfer interruption and wick drying. This provides accurate quantitative basis for the design of heat pipe safety thresholds and avoids overheating damage to equipment caused by heat pipe failure in the thermal management system.

[0135] 4. Improved efficiency through iterative optimization This invention designs a multi-strategy iterative convergence logic of "linear interpolation correction + divergence suppression + physical constraints + gravity-assisted adaptation", which can perform targeted optimization for four core design parameters: capillary radius, operating temperature, heat pipe length, and channel size. This solves the problems of slow iterative convergence and easy divergence in traditional methods. At the same time, for new working fluids and new liquid wick structures, only the fitting formula and structural calculation logic need to be added to the corresponding modules, without the need to reconstruct the overall calculation framework, thus improving R&D efficiency.

[0136] 5. Highly practical engineering applications This invention can automatically output quantitative performance curves such as temperature-length, heat transfer-sound speed limit, and capillary pressure drop-number of channels according to the optimization target, directly providing practical design guidance such as the optimal parameter range, extreme operating condition threshold, and structural size range for heat pipe structure design, with strong engineering adaptability.

[0137] In summary, this invention presents a method and system for performance analysis and optimization of heat pipes with multi-working-fluid and multi-wick structures. By establishing a standardized computational framework based on the centimeter-gram-second (CGS) unit system, this invention successfully integrates calculation models for the thermophysical properties of five typical working fluids: lithium, sodium, potassium, mercury, and water, covering the entire temperature range from -50℃ to 1200℃. Simultaneously, the algorithm is compatible with five mainstream wick structures: coreless, circular channel, annular channel, spiral groove, and uniform core. This fully parameterized adaptability allows the same code to be used for liquid metal heat pipe design in high-temperature spacecraft thrusters as well as for water heat pipe heat dissipation analysis in room-temperature electronic devices, completely breaking the limitation of traditional software requiring a separate algorithm for each working fluid and significantly reducing the R&D costs of multi-scenario thermal control design. Furthermore, this invention achieves a significant breakthrough in the accuracy of physical field coupling calculations. To address the shortcomings of traditional methods that neglect the compressible flow effect in the adiabatic section, leading to high-pressure errors, this invention introduces a Mach number solution model based on Newton's iterative method. This model precisely couples the pressure and temperature fields, controlling the pressure drop calculation error throughout the heat pipe process to within 10%. Simultaneously, by establishing a correction model based on the effective length of the spiral unfolding, the invention accurately solves the problem of hydraulic characteristic calculation distortion caused by the geometric tilt effect of the spiral groove wick. This high-precision physical modeling allows the invention to accurately predict the true performance boundaries of the heat pipe under extreme conditions. Finally, this invention designs a multi-strategy iterative optimization logic with adaptive capabilities. By introducing an algorithm combination of linear interpolation correction, divergence suppression, and physical constraints, it effectively solves the common problems of slow convergence and easy divergence in solving nonlinear equations. It can not only perform performance verification but also automatically optimize core parameters such as capillary radius, channel size, and heat pipe length based on the quantitative constraints of the sound velocity limit and the carry capacity limit. This not only significantly shortens the heat pipe development cycle but also provides a safe and reliable quantitative design basis for thermal management systems, possessing extremely high engineering practical value.

[0138] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0139] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0140] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0141] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0142] 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 network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0143] Furthermore, the functional units in the various embodiments of the present invention 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.

[0144] If the integrated module / 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, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random-access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0145] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus, and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0146] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0147] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0148] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for performance analysis and optimization of heat pipes with multi-working-fluid and multi-absorbent core structures, characterized in that, Includes the following steps: S1. The geometric parameters, operating parameters, and calculation control parameters of the heat pipe are standardized and initialized using the centimeter-gram-second unit system, and the basic physical constants, calculation thresholds and basic geometric quantities of the heat pipe are set. S2. Based on the type of working fluid determined in the initialization, calculate the thermophysical parameters of the working fluid at the current working temperature using the corresponding experimental fitting formula; S3. Based on the type of liquid-absorbing core determined in the initialization, the corresponding hydraulic calculation model is used to calculate the liquid flow area, steam flow area, hydraulic radius and friction coefficient. S4. Based on the thermophysical parameters of the working fluid obtained in S2 and the liquid flow area, steam flow area, hydraulic radius, and friction coefficient obtained in S3, couple the calculation of liquid friction pressure drop, steam friction pressure drop, inertial pressure drop, hydrostatic pressure drop, and capillary pressure drop. For heat pipes containing adiabatic sections, incorporate the compressible flow effect of the adiabatic section into the pressure drop calculation to complete the coupled calculation of the pressure field and temperature field. S5. Based on the pressure field and temperature field parameters obtained from the coupling calculation in S4, construct the calculation model of the sound speed limit and the carrying limit to obtain the maximum safe heat transfer threshold of the heat pipe. S6. Using capillary radius, operating temperature, heat pipe length, and channel size as optimization targets, based on the coupling calculation results of S4 and the maximum safe heat transfer threshold obtained in S5, it uses iterative convergence logic with linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation to complete the directional iterative optimization of capillary radius, operating temperature, heat pipe length, or channel size, and outputs the optimized heat pipe performance parameters.

2. The method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures according to claim 1, characterized in that, In S1, the calculation control parameters include the loop start value, loop end value, loop step size, and calculation type; the basic physical constants include pi and gravitational acceleration g = 980 cm / s². 2 The universal gas constant R; the calculation threshold includes an iterative convergence threshold of 1×10⁻⁶. -5 Minimum heat transfer threshold 1×10 -5 erg / s.

3. The method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures according to claim 1, characterized in that, In S2, the working fluid types include lithium, sodium, potassium, mercury, or water; the thermophysical parameters of the working fluid include saturation pressure, molar mass, liquid density, liquid viscosity, latent heat of vaporization, surface tension, and specific heat ratio.

4. The method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures according to claim 1, characterized in that, In S3, the liquid suction core types include coreless, circular channel, annular channel, spiral groove, or uniform core; the dedicated hydraulic calculation model includes a coreless structure model based on liquid film Reynolds number, a circular channel model based on multi-channel parallel flow channel, an annular channel model based on rectangular annular flow channel approximation, a spiral groove model based on the effective length of spiral expansion, and a uniform liquid suction core model based on porous media.

5. The method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures according to claim 1, characterized in that, In S4, the compressible flow effect in the adiabatic section specifically includes: When the length of the adiabatic section is greater than 0, calculate the Mach number at the evaporator outlet and the Reynolds number on the steam side; determine the friction coefficient, and calculate the flow function and the maximum flow function; if the flow function is less than the maximum flow function, it is determined to be sonic flow; otherwise, solve for the Mach number at the outlet of the adiabatic section using the Newton-Raphson iteration method; calculate the pressure ratio based on the pressure ratio function, and then solve for the outlet pressure and pressure drop of the adiabatic section; solve for the outlet saturation temperature of the adiabatic section based on the outlet pressure of the adiabatic section, thus completing the coupling of the pressure field and the temperature field.

6. The method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures according to claim 1, characterized in that, In S5, the specific steps for constructing the calculation models for the speed of sound and the carry-over limit include: For the sound speed limit, the heat transfer limit of the sound speed limit is calculated based on the relationship between the stagnation pressure and the saturation temperature when the steam flow rate reaches the sound speed; for the carry-over limit, the heat transfer limit of the carry-over limit is calculated based on the Podenstein number and correction factor of the steam flowing at high speed carrying the liquid.

7. The method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures according to claim 1, characterized in that, In S6, the iterative convergence logic employing linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation specifically includes: In the first iteration, the optimization variables are amplified by 1.1 times, and the convergence benchmark and convergence deviation are initialized. The relative deviation is calculated. If the relative deviation is less than the convergence threshold, the iteration is considered to have converged; otherwise, the correction step is initiated. The iteration slope is calculated, and the optimization variables are corrected. If the relative deviation is greater than the minimum convergence deviation, the iteration is considered to be diverging, and the optimization variables are forcibly corrected. If the optimization variables have no physical meaning, the optimization variables are reset. If gravity assistance exists and the liquid friction pressure drop meets specific conditions, the gravity assistance flag is turned off and the iteration counter is reset.

8. The method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures according to claim 1, characterized in that, In S6, the optimized heat pipe performance parameters output specifically include: Output capillary pressure drop-channel number curve, heat transfer-sound velocity limit-temperature curve, saturation temperature-length distribution curve, or heat transfer-channel size curve.

9. The method for performance analysis and optimization of heat pipes with multi-working-medium and multi-absorbent core structures according to claim 1, characterized in that, The geometric parameters include at least one of the following: evaporation section length, adiabatic section length, condensation section length, pipe cross-sectional area, heat pipe inclination angle, pipe radius, wick thickness, porosity, channel wall thickness, maximum channel spacing, wall thickness, tortuosity, channel size, number of channels, number of auxiliary channels, number of spiral groove turns, mesh count of the wire wick, and wire diameter.

10. A system for performance analysis and optimization of heat pipes with multi-working-fluid and multi-absorbent core structures, characterized in that, include: The parameter module uses a centimeter-gram-second unit system to standardize and initialize the geometric parameters, operating parameters, and calculation control parameters of the heat pipe, and completes the setting of basic physical constants, calculation thresholds, and calculation of basic geometric quantities of the heat pipe. The physical properties module calculates the thermophysical parameters of the working fluid at the current operating temperature using the corresponding experimental fitting formula, based on the working fluid type determined during initialization. The hydraulic module, based on the type of liquid suction core determined during initialization, uses a dedicated hydraulic calculation model corresponding to the structure to calculate the liquid flow area, steam flow area, hydraulic radius, and friction coefficient. The coupling module, based on the thermophysical parameters of the working fluid obtained from the physical properties module and the liquid flow area, steam flow area, hydraulic radius, and friction coefficient obtained from the hydraulic module, performs coupled calculations of liquid friction pressure drop, steam friction pressure drop, inertial pressure drop, hydrostatic pressure drop, and capillary pressure drop. For heat pipes containing adiabatic sections, the compressible flow effect of the adiabatic section is incorporated into the pressure drop calculation, thus completing the coupled calculation of the pressure field and temperature field. The calculation module, based on the pressure field and temperature field parameters obtained by the coupling module, constructs a calculation model for the sound speed limit and the carrying limit, and obtains the maximum safe heat transfer threshold of the heat pipe. The optimization module uses capillary radius, operating temperature, heat pipe length, and channel size as optimization targets. Based on the coupling calculation results of the coupling module and the maximum safe heat transfer threshold obtained by the calculation module, it adopts iterative convergence logic with linear interpolation correction, divergence suppression, physical constraints, and gravity-assisted adaptation to complete the targeted iterative optimization of capillary radius, operating temperature, heat pipe length, or channel size. The output module is used to output the optimized heat pipe performance parameters obtained by the optimization module.

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