Coupling calculation method and device for reactor core and heat pipe of heat pipe reactor and storage medium

Abstract

The invention provides a coupling calculation method of a heat pipe reactor core and a heat pipe, calculation equipment and a storage medium, and relates to the technical field of nuclear reactors. The virtual fluid is introduced, the coupling variable is mapped to the virtual fluid, coupling of the reactor core model and the heat pipe model is achieved, only respective coupling interfaces of the reactor core module and the heat pipe module need to be developed, and the coupling interface of the other module does not need to be modified when any module is replaced. And the flexibility and the expandability of safety analysis of the heat pipe reactor system are improved.

Description

Technical Field

[0001] The present application relates to the technical field of nuclear reactors, and in particular to a coupling calculation method, a calculation device and a storage medium for a heat pipe reactor core and a heat pipe. Background Art

[0002] As countries around the world continue to increase their exploration missions to special physical spaces such as deep space, deep sea, and isolated islands, the demand for power is also growing. Compared with traditional power sources, nuclear power sources with higher energy density, greater reliability and sustainability are the first choice for special physical space exploration missions. Heat pipe reactors have outstanding advantages such as simple structure, high inherent safety, and simple operating characteristics. The core advantage of heat pipe reactors is that they use non-passive component heat pipes rather than a coolant loop arrangement to remove heat from the core, and transfer heat from the core to the heat pipes by heat conduction.

[0003] The coupling calculation of the core and heat pipe is an important part of the safety analysis process of the heat pipe reactor system. The core of the heat pipe reactor can be solved by various finite element software such as ANSYS and COMSOL, and the heat pipe itself can be calculated by various models such as one to three dimensions. When replacing either the core module or the heat pipe module, the coupling interface of the other module needs to be modified. Summary of the invention

[0004] In order to alleviate, mitigate or eliminate the above-mentioned technical problems, the present application provides a coupling calculation method, a computing device and a storage medium for a heat pipe stack core and a heat pipe, which can improve the flexibility and scalability of the safety analysis of the heat pipe stack system.

[0005] In a first aspect, the present application provides a coupling calculation method for a heat pipe reactor core and a heat pipe, characterized by comprising:

[0006] Step S1: acquiring a first model and a second model, wherein the first model is one of a core model and a heat pipe model, and the second model is the other of the core model and the heat pipe model;

[0007] Step S2: obtaining initial boundary conditions, wherein the initial boundary conditions include initial values ​​of the first iteration variable and the second iteration variable;

[0008] Step S3: Based on the first model, taking the first iterative variable as a boundary condition, calculating a second coupling variable, and mapping the second coupling variable from the first model to the imaginary fluid to obtain a new second iterative variable;

[0009] Step S4: Based on the second model, taking the second iterative variable as a boundary condition, calculating a first coupling variable, and mapping the first coupling variable from the second model to the imaginary fluid to obtain a new first iterative variable;

[0010] Step S5: Determine whether the output condition is met;

[0011] Step S6: If the output condition is not met, repeat steps S3-S5 until the output condition is met and output the calculation result.

[0012] In a possible implementation, the core model is a three-dimensional core model having a two-dimensional boundary surface; the heat pipe model is a two-dimensional heat pipe model having a one-dimensional boundary surface; and the imaginary fluid is a one-dimensional imaginary fluid.

[0013] In a possible implementation, mapping the second coupling variable from the first model to the imaginary fluid to obtain a new second iterative variable includes:

[0014] Obtaining mesh divisions of the first model boundary surface and the imaginary fluid;

[0015] Acquire a first mesh correspondence between the first model boundary surface and the imaginary fluid;

[0016] Based on the first grid correspondence, the second coupling variable is mapped from the first model to the imaginary fluid, and then the mapped data is interpolated to obtain a new second iterative variable.

[0017] In a possible implementation, mapping the second coupling variable from the first model to the imaginary fluid based on the first grid correspondence includes:

[0018] Based on the first grid correspondence, the second coupling variable is averaged using the area of ​​the imaginary fluid grid as a weighting factor.

[0019] In a possible implementation, mapping the first coupling variable from the second model to the imaginary fluid to obtain a new first iteration variable includes:

[0020] Obtaining mesh divisions of the second model boundary surface and the imaginary fluid;

[0021] Acquire a second mesh correspondence between the second model boundary surface and the imaginary fluid;

[0022] Based on the second grid correspondence, the first coupling variable is mapped from the second model to the imaginary fluid, and then the mapped data is interpolated to obtain a new first iteration variable.

[0023] In a possible implementation, mapping the first coupling variable from the second model to the imaginary fluid based on the second grid correspondence includes:

[0024] Based on the second grid correspondence, the first coupling variable is averaged using the area of ​​the imaginary fluid grid as a weighting factor.

[0025] In a possible implementation, the first iteration variable includes wall temperature, and the second iteration variable includes heat flux density.

[0026] In a possible implementation, step S5 includes:

[0027] Step S51: determine whether the iteration variable group of the current time step meets the convergence condition, if yes, execute step S52, if no, repeat steps S3-S4, wherein the iteration variable group includes the first iteration variable and the second iteration variable, and the convergence condition is that the deviation between the iteration variable groups calculated twice adjacently is less than a preset threshold;

[0028] Step S52: Determine whether the current time step reaches the preset simulation time. If yes, the output condition is met; if not, the output condition is not met and the time step is advanced.

[0029] In a second aspect, the present application provides a computing device, including:

[0030] at least one processor; and

[0031] At least one memory having instructions stored thereon, which, when executed individually or collectively by the at least one processor, cause the computing device to perform the method according to the first aspect.

[0032] In a third aspect, the present application provides a computer storage medium having instructions stored thereon, which, when executed individually or collectively by at least one processor of a computing device, causes the computing device to execute the method described in the first aspect.

[0033] Compared with the prior art, this application has the following advantages:

[0034] The present application realizes the coupling of the core model and the heat pipe model by introducing a hypothetical fluid and mapping the coupling variables to the hypothetical fluid. It only requires developing the coupling interfaces of the core module and the heat pipe module respectively. When replacing any of the modules, there is no need to modify the coupling interface of the other module, thereby improving the flexibility and scalability of the safety analysis of the heat pipe reactor system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings are included to provide a further understanding of the present application. They are included and constitute a part of the present application. The accompanying drawings illustrate embodiments of the present application and together with the present specification serve to explain the principles of the present application. In the accompanying drawings:

[0036] Figure 1It is a schematic diagram of a coupling method between a heat pipe stack core and a heat pipe provided in an embodiment of the present application;

[0037] Figure 2 It is a flow chart of a coupling calculation method of a heat pipe stack core and a heat pipe provided in an embodiment of the present application;

[0038] Figure 3 It is a schematic diagram of a grid mapping relationship between a heat pipe stack core and a heat pipe provided in an embodiment of the present application;

[0039] Figure 4 It is a schematic diagram of an iterative variable and its solution method provided in an embodiment of the present application;

[0040] Figure 5 It is a structural diagram of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] The principle of the present application will now be described with reference to some embodiments. It should be understood that the description of these embodiments is only for illustrative purposes, and helps those skilled in the art to understand and implement the present application, without any limitation to the scope of the present application. The disclosure described herein can be implemented in a manner different from that described below.

[0042] In the following description, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0043] References in this application to "one embodiment," "an embodiment," "an exemplary embodiment," etc. indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment necessarily includes the particular feature, structure, or characteristic. Moreover, such phrases do not necessarily refer to the same embodiment. In addition, when a particular feature, structure, or characteristic is described in conjunction with an exemplary embodiment, whether or not explicitly described, those skilled in the art will recognize that such feature, structure, or characteristic may affect incorporation into other embodiments.

[0044] The terms used herein are only for describing specific embodiments, rather than for limiting exemplary embodiments. The singular forms "one", "an", and "the" used herein also include plural forms, unless the context clearly indicates otherwise. "A group of elements" or "element set" used herein is intended to include one or more elements. It should also be understood that the terms "include", "comprise", "have", "have", "include" and / or "include", when used herein, specify the presence of the features, elements and / or parts, etc., but do not exclude the presence or addition of one or more other features, elements, parts and / or combinations thereof.

[0045] In addition, it should be noted that the use of words such as "first" and "second" to limit objects is only to facilitate the distinction between corresponding objects. Unless otherwise stated, the above words have no special meaning and therefore cannot be understood as limiting the scope of protection of the present invention.

[0046] Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps may be processed in reverse order or simultaneously. At the same time, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0047] In the numerical simulation analysis of heat pipe reactors, the core part usually adopts the three-dimensional finite element modeling method to accurately simulate the complex geometry, material properties and heat conduction process inside the core. For heat pipes, because the radial thickness of the tube wall and the wick is very small and the steam core is isothermal after the heat pipe is started, the circumferential distribution of the heat pipe is uniform, and the use of a two-dimensional axisymmetric model for analysis is more intuitive, efficient and the calculation accuracy can be guaranteed. Therefore, the core model and the heat pipe model do not match in dimension.

[0048] In existing analysis, the coupling between the core and the heat pipe usually adopts a compromise solution, that is, the heat pipe is also modeled in three dimensions, and the coupling between the heat pipe and the core is solved in a unified way to perform thermal analysis of the heat pipe reactor. However, the core heat conduction equation discretized by the finite element method has excellent characteristics, and there is an extremely efficient JFNK (Jacobi-free Newtow-krylov) solution algorithm. For the heat pipe control equation, due to the fluid characteristics of the heat pipe core steam, its control equation has a great difference from the characteristics of the core heat conduction equation. If the heat pipe control equation and the core heat conduction control equation are solved directly together, the core heat conduction equation itself will be destroyed. The characteristics of easy solution and multi-core parallelism will be destroyed.

[0049] The embodiment of the present application introduces a hypothetical fluid, through which data interaction and collaborative work are performed to achieve coupling between the core and the heat pipe, such as Figure 1 Specifically, an imaginary fluid 103 with a density of 0 and a heat capacity of 0 is introduced between the core 101 and the heat pipe 102 to efficiently couple the core 101 and the heat pipe 102. The contact interface between the core 101 and the heat pipe 102 adopts a convection heat transfer model, and the convection heat transfer coefficient reflects the contact thermal resistance.

[0050] In some embodiments, the contact thermal resistance R between the core 101 and the heat pipe 102 can be characterized by setting an equivalent heat transfer coefficient h between the imaginary fluid 103 and the core 101 tThe solid core and the heat pipe evaporator are nominally in contact, but in fact they are only in contact at discrete points. The air in the gap causes the heat to be conducted through the air gap layer, thus forming contact thermal resistance. The heat pipe cooling reactor has no liquid or gas medium, and the solid-solid contact makes the contact thermal resistance more significant. In order to reflect the contact thermal resistance R t To simplify the coupling, a hypothetical fluid 103 is introduced between the core 101 and the heat pipe 102, and its equivalent convection heat transfer coefficient h can be used to represent the contact thermal resistance between the core 101 and the heat pipe 102. Therefore, the hypothetical fluid 103 satisfies the following relationship:

[0051]

[0052] Where, Ф is the heat flux between the core and the heat pipe (W); R t is the contact thermal resistance (m 2 ·K·W -1 );T w is the temperature of the core and heat pipe coupling (K); T s is the core boundary temperature (K); h is the equivalent convection heat transfer coefficient (W / m 2 K); A is the contact area (m 2 ).

[0053] In some embodiments, the core heat flux and the heat pipe wall temperature are selected as the iterative variable group. The temperature of the imaginary fluid 103 in the iterative variable group is used as the wall temperature. The core module calculates the distribution of the heat flux on the outer surface of the core based on the core model and takes the wall temperature as the boundary condition, and obtains the heat flux at the imaginary fluid through mapping. The heat pipe module calculates the heat pipe wall temperature distribution based on the heat pipe model and takes the heat flux as the boundary condition, and then maps it back to the imaginary fluid 103. Thus, the coupled calculation of the core and the heat pipe is realized by iterating the iterative variable group composed of the heat flux and the wall temperature.

[0054] It should be noted that in some other embodiments, the iterative variable group can be adjusted according to the design requirements of the heat pipe stack and the characteristics of the core and heat pipe analysis program, such as using the core wall temperature and the heat flux density of the heat pipe, etc. The embodiments of the present application do not limit the iterative variable group.

[0055] Unlike the traditional direct coupling of the core grid and the heat pipe grid, the embodiment of the present application introduces an imaginary fluid, and the core module and its grid and the heat pipe module and its grid only need to be coupled with the imaginary fluid. The core module and its grid and the heat pipe module and its grid are no longer constrained to each other. That is, when the heat pipe module and its grid are changed, since the core is directly coupled with the imaginary fluid instead of the heat pipe, the core coupling interface is still applicable, and there is no need to develop a new coupling interface for the new heat pipe module. Similarly, there is no need to develop a new heat pipe module coupling interface for each core module, thereby realizing the versatility of the coupling interface.

[0056] In some embodiments, the core model is a three-dimensional core model, and the three-dimensional core model has a two-dimensional boundary surface. The heat pipe model is a two-dimensional heat pipe model, and the two-dimensional heat pipe model has a one-dimensional boundary surface. The hypothetical fluid is a one-dimensional hypothetical fluid. It effectively solves the problem of dimensional mismatch between the three-dimensional core model and the two-dimensional heat pipe model, realizes the deep integration of the advantages of the two, and ensures the balance between the calculation accuracy and calculation time of the safety analysis of the heat pipe stack system. And while ensuring that the excellent characteristics of the core heat conduction control equation are not affected by the heat pipe control equation, it satisfies the efficient simulation of the steam core working fluid flow by the two-dimensional heat pipe model, thereby improving the overall calculation efficiency.

[0057] Figure 2 FIG. 1 is a flow chart of a method for calculating the coupling between a heat pipe stack core and a heat pipe provided in an embodiment of the present application. Figure 2 As shown in the figure, the coupling calculation method of the heat pipe reactor core and the heat pipe includes the following contents:

[0058] Step S1: Obtain a first model and a second model.

[0059] In some embodiments, the first model is a core model and the second model is a heat pipe model. In some other embodiments, the first model is a heat pipe model and the second model is a core model.

[0060] Step S2: Acquire initial boundary conditions, wherein the initial boundary conditions include initial values ​​of the first iteration variable and the second iteration variable.

[0061] It should be understood that step S1 may be performed first, and then step S2. Step S2 may also be performed first, and then step S1. Alternatively, step S1 and step S2 may be performed in parallel.

[0062] For example, the analysis object is first determined, the heat pipe input parameters are sorted, and the geometric dimensions of the solid core and heat pipe, the material thermophysical parameters (such as thermal conductivity, heat capacity, density, etc.) and the initial boundary conditions are set. Then, the core model of the core three-dimensional finite element analysis module and the heat pipe model of the heat pipe two-dimensional analysis module are constructed and the initial solution settings are set.

[0063] Step S3: Based on the first model and taking the first iterative variable as a boundary condition, a second coupling variable is calculated, and the second coupling variable is mapped from the first model to the hypothetical fluid to obtain a new second iterative variable.

[0064] Step S4: Based on the second model and taking the second iterative variable as a boundary condition, a first coupling variable is calculated, and the first coupling variable is mapped from the second model to the hypothetical fluid to obtain a new first iterative variable.

[0065] It should be understood that step S3 may be performed first, and then step S4, then the first iteration variable in the initial boundary condition is used when step S3 is performed for the first time, and the second iteration variable calculated in step S3 is used when step S4 is performed for the first time. Step S4 may also be performed first, and then step S3, then the second iteration variable in the initial boundary condition is used when step S4 is performed for the first time, and the first iteration variable calculated in step S4 is used when step S3 is performed for the first time. Alternatively, step S3 and step S4 are performed in parallel, then when step S3 and step S4 are performed for the first time, both use the corresponding iteration variables in the initial boundary condition.

[0066] In some embodiments, a partitioned grid mapping strategy may be used to ensure efficient and accurate transmission of coupling variables. The grid is used as a data carrier, and data transmission is achieved by a partitioned grid mapping method. Specifically, in step S3, mapping the second coupling variable from the first model to the imaginary fluid to obtain a new second iteration variable includes:

[0067] Obtain the grid division of the first model boundary surface and the imaginary fluid, obtain the first grid correspondence between the first model boundary surface and the imaginary fluid, map the second coupling variable from the first model to the imaginary fluid based on the first grid correspondence, and then interpolate the mapped data to obtain a new second iterative variable.

[0068] Mapping the first coupling variable from the second model to the imaginary fluid to obtain a new first iteration variable in step S4 includes:

[0069] Obtain the grid division of the second model boundary surface and the imaginary fluid, obtain the second grid correspondence between the second model boundary surface and the imaginary fluid, map the first coupling variable from the second model to the imaginary fluid based on the second grid correspondence, and then interpolate the mapped data to obtain a new first iterative variable.

[0070] In order to better understand the present application, the mapping of data is further explained below by taking the first model as a three-dimensional core model, the second model as a two-dimensional heat pipe model, the first iteration variable as the wall temperature, and the second iteration variable as the heat flux density as an example.

[0071] The boundary of the 3D core model is a 2D boundary surface, the boundary of the 2D heat pipe model is a 1D boundary surface, and the imaginary fluid is a 1D imaginary fluid. During the coupling analysis, the system is subdivided into multiple independent sub-regions, and all the grids in each sub-region are lumped as a heat transfer unit.

[0072] Please refer to Figure 3, the core two-dimensional boundary surface 301 is divided into M+1 grids in the longitudinal direction and 3 grids in the transverse direction. The heat pipe one-dimensional boundary surface 302 is divided into K+1 grids in the longitudinal direction. The one-dimensional imaginary fluid 303 is divided into N+1 grids in the longitudinal direction. Due to the longitudinal dimensions of the core two-dimensional boundary surface 301, the heat pipe one-dimensional boundary surface 302 and the one-dimensional imaginary fluid 303, the grids of the core two-dimensional boundary surface 301 and the one-dimensional imaginary fluid 303, and the grids of the heat pipe one-dimensional boundary surface 302 and the one-dimensional imaginary fluid 303 in the longitudinal direction may not correspond one to one.

[0073] For example, for the nth grid of the one-dimensional imaginary fluid 303, the decoupled heat flux density data obtained from the core module is q n . Assume that the grids of the two-dimensional boundary surface 301 of the core corresponding to the nth grid of the one-dimensional imaginary fluid 303 are the mth and m-1th. Based on the first grid correspondence, the second coupling variable calculated by the core module is mapped from the three-dimensional core model to the one-dimensional imaginary fluid. For example, the second coupling variable is averaged with the area of ​​the imaginary fluid grid in the heat transfer unit as a weighting factor, and the average heat flux density of the heat transfer unit is obtained based on this, as shown in formula (2). The average heat flux density of the heat transfer units of all partitions can be further obtained, and then a piecewise continuous interpolation function can be constructed with the discrete heat flux density data to obtain the iterative variable group heat flux density, thereby realizing the data mapping from the core to the imaginary fluid.

[0074]

[0075] Among them, q m is the total heat flux of the m-th core two-dimensional boundary surface grid, q m-1 is the total heat flux of the m-1th core two-dimensional boundary surface grid, S i,j is the area of ​​the jth imaginary fluid grid corresponding to the i-th core two-dimensional boundary surface grid, q n is the heat flux density of the nth hypothetical fluid grid. It should be understood that the i-th core two-dimensional boundary surface grid mentioned here includes all grids in the i-th row in the vertical direction, such as the m-th core two-dimensional boundary surface grid includes three grids m1, m2 and m3.

[0076] Similarly, data mapping from heat pipe to imaginary fluid can be realized. Assume that the grids of the heat pipe one-dimensional boundary surface 301 corresponding to the n-th grid of the one-dimensional imaginary fluid 303 are the k-th and k+1-th. Based on the second grid correspondence, the first coupling variable calculated by the heat pipe module is mapped from the two-dimensional heat pipe model to the one-dimensional imaginary fluid. For example, the first coupling variable is averaged with the area of ​​the imaginary fluid grid in the heat transfer unit as a weighting factor, and the average wall temperature of the heat transfer unit is obtained based on this, as shown in formula (3). The average wall temperature of the heat transfer unit in all partitions can be further obtained, and then a piecewise continuous interpolation function can be constructed with the discrete wall temperature data to obtain the wall temperature of the iterative variable group.

[0077]

[0078] Among them, T k is the wall temperature of the kth heat pipe grid, T k+1 is the wall temperature of the k+1th heat pipe grid, S i,j is the area of ​​the jth imaginary fluid grid corresponding to the i-th heat pipe grid, T n is the wall temperature of the nth imaginary fluid grid.

[0079] It should be noted that the grid mapping mechanism in the above embodiment adopts free grid division and linear interpolation algorithm. In some other embodiments, the grid mapping can adopt other algorithms such as nearest neighbor algorithm, and the interpolation algorithm can adopt high-order interpolation algorithm (such as bilinear, bicubic interpolation) and the like.

[0080] Step S5: Determine whether the output condition is met.

[0081] Specifically, the output conditions of the calculation results can be set according to actual needs, such as the number of iterations reaches a preset value, the iteration time reaches a preset time, the deviation between two adjacent calculation results is less than a preset threshold, etc.

[0082] In some embodiments, step S5 includes:

[0083] Step S51: Determine whether the iteration variable group of the current time step meets the convergence condition. If yes, execute step S52. If no, repeat steps S3-S4, i.e. continue to iterate the current time step. The iteration variable group includes the first iteration variable and the second iteration variable, and the convergence condition is that the deviation between the iteration variable groups calculated twice adjacently is less than a preset threshold.

[0084] The iteration method between the core and the heat pipe can be selected from a variety of iteration methods. For example, the iteration method between the core and the heat pipe adopts Gauss-Seidel iteration, such as Figure 4 As shown. Let the wall temperature and heat flux density of the iteration variable group be T wand q w The core module wall temperature is T w As the boundary condition, the average heat flux density is calculated, and the heat flux density q of the iterative variable group is obtained after data mapping w , denoted as q w =Core(T w ). The heat pipe module takes the heat flux density q w As the boundary condition, the average wall temperature is calculated, and the wall temperature T of the iterative variable group is obtained after data mapping. w , denoted as T w =HP(q w ). The specific Gauss-Seidel iteration process is as follows:

[0085]

[0086] In the above formula, ω q ,ω T ∈(0,1) are the iteration factors of heat flux density and wall temperature respectively, and the superscript n is the number of iterations. Repeated iterations are performed until the preset convergence conditions are met, thus completing the coupled calculation of this time step.

[0087] Step S52: Determine whether the current time step reaches the preset simulation time. If so, the output condition is met; if not, the output condition is not met and the time step is advanced.

[0088] According to actual needs, a suitable time step and simulation time can be set. In each time step, the calculation process from step S3 to step S51 is repeated until the required simulation time is reached or a specific termination condition is met.

[0089] Step S6: If the output condition is not met, repeat steps S3-S5 until the output condition is met and output the calculation result.

[0090] Specifically, the calculation result files of each time step can be collated and output, and the calculation results can be analyzed through visualization software.

[0091] Figure 5 Schematic diagram of a computing device provided in an embodiment of the present application. Figure 5 As shown, computing device 500 includes one or more processors 510 , one or more memories 520 coupled to processor 510 , and one or more communication modules 540 coupled to processor 510 .

[0092] The communication module 540 is used for two-way communication. The communication module 540 has at least one antenna to facilitate communication. The communication interface may represent any interface necessary for communicating with other network elements.

[0093] Processor 510 may be of any type suitable for the local technology network, and may include, as non-limiting examples, one or more of: a general purpose computer, a special purpose computer, a microprocessor, a digital signal processor (DSP), and a processor based on a multi-core processor architecture. Computing device 500 may have multiple processors, such as application specific integrated circuit chips, which are driven in time to a clock that synchronizes a master processor.

[0094] The memory 520 may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, read-only memory (ROM) 524, electrically programmable read-only memory (EPROM), flash memory, hard disk, compact disk (CD), digital video disk (DVD), and other magnetic and / or optical memories. Examples of volatile memories include, but are not limited to, random access memory (RAM) 522 and other volatile memories that do not persist during the duration of a power outage.

[0095] Computer program 530 includes computer executable instructions executed by associated processor 510. Program 530 may be stored in ROM 524. Processor 510 may perform any appropriate actions and processes by loading program 530 into RAM 522.

[0096] The embodiment of the present application can be implemented by program 530, so that the computing device 500 can execute the reference Figure 2 Any process disclosed in the discussion. The embodiments of the present application may also be implemented by hardware or by a combination of software and hardware.

[0097] In some embodiments, program 530 may be tangibly embodied in a computer-readable medium, which may be contained in computing device 500 (e.g., memory 520) or other storage devices accessible to computing device 500. Computing device 500 may load program 530 from the computer-readable medium to RAM 522 for execution. The computer-readable medium may include any type of tangible non-volatile memory, such as ROM, EPROM, flash memory, hard disk, CD, DVD, etc. The computer-readable medium has program 530 stored thereon.

[0098] Generally, various embodiments of the present application may be implemented in hardware or dedicated circuits, software, logic, or any combination thereof. Certain aspects may be implemented in hardware, while other aspects may be implemented in firmware or software, which may be performed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of the present application are shown and described as block diagrams, flow charts, or using some other graphical representations, it should be understood that, as non-limiting examples, the blocks, devices, systems, techniques, or methods described herein may be implemented in hardware, software, firmware, dedicated circuits or logic, general hardware or controllers or other computing devices, or some combination thereof.

[0099] The present application also provides at least one computer program product tangibly stored on a non-transitory computer readable storage medium. The computer program product includes computer executable instructions, such as instructions included in program modules, which are executed in a device on a target real or virtual processor to perform the above-mentioned reference Figure 2 The method described. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform specific tasks or implement specific abstract data types. In various embodiments, the functions of program modules can be combined or separated between program modules as needed. Machine executable instructions for program modules can be executed in local or distributed devices. In distributed devices, program modules can be located in local and remote storage media.

[0100] The program code for executing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing equipment so that when the program code is executed by the processor or controller, the function / operation specified in the flow chart and / or the block diagram is realized. The program code can be executed completely on the machine as an independent software package, partially on the machine, partially on the machine, partially on a remote machine, partially on a remote machine, or all on a remote machine or server.

[0101] In the context of this application, computer program codes or related data may be carried by any appropriate carrier to enable a device, apparatus or processor to perform various processes and operations as described above. Examples of carriers include signals, computer readable media, etc.

[0102] The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or apparatuses, or any suitable combination of the foregoing. More specific examples of computer readable storage media include an electrical connection with one or more wires, a portable computer floppy disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0103] In addition, although the operations are described in a specific order, this should not be construed as requiring to perform these operations in the specific order or sequence shown, or to perform all the operations shown, to obtain the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the above discussion, these details should not be interpreted as limiting the scope of the application, but can be interpreted as a description of the specific features of a particular embodiment. Some of the features described in the context of a separate embodiment may also be implemented in combination in a single embodiment. On the contrary, the various features described in the context of a single embodiment may also be implemented in multiple embodiments individually or in any suitable sub-combination.

[0104] Although the present application has been described in language specific to structural features and / or methodological acts, it should be understood that the present application defined in the appended claims is not necessarily limited to the specific features or acts described above. Instead, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

1. A coupling calculation method for a heat pipe reactor core and a heat pipe, characterized in that: include: Step S1: acquiring a first model and a second model, wherein the first model is one of a core model and a heat pipe model, and the second model is the other of the core model and the heat pipe model; Step S2: obtaining initial boundary conditions, wherein the initial boundary conditions include initial values ​​of the first iteration variable and the second iteration variable; Step S3: Based on the first model, taking the first iterative variable as a boundary condition, calculating a second coupling variable, and mapping the second coupling variable from the first model to the imaginary fluid to obtain a new second iterative variable; Step S4: Based on the second model, taking the second iterative variable as a boundary condition, calculating a first coupling variable, and mapping the first coupling variable from the second model to the imaginary fluid to obtain a new first iterative variable; Step S5: Determine whether the output condition is met; Step S6: If the output condition is not met, repeat steps S3-S5 until the output condition is met and output the calculation result.

2. The method according to claim 1, characterized in that The core model is a three-dimensional core model having a two-dimensional boundary surface; the heat pipe model is a two-dimensional heat pipe model having a one-dimensional boundary surface; and the imaginary fluid is a one-dimensional imaginary fluid.

3. The method according to claim 2, characterized in that Mapping the second coupling variable from the first model to the imaginary fluid to obtain a new second iterative variable comprises: Obtaining mesh divisions of the first model boundary surface and the imaginary fluid; Acquire a first mesh correspondence between the first model boundary surface and the imaginary fluid; Based on the first grid correspondence, the second coupling variable is mapped from the first model to the imaginary fluid, and then the mapped data is interpolated to obtain a new second iterative variable.

4. The method according to claim 3, characterized in that The mapping of the second coupling variable from the first model to the imaginary fluid based on the first grid correspondence includes: Based on the first grid correspondence, the second coupling variable is averaged using the area of ​​the imaginary fluid grid as a weighting factor.

5. The method according to claim 2, characterized in that Mapping the first coupling variable from the second model to the imaginary fluid to obtain a new first iteration variable comprises: Obtaining mesh divisions of the second model boundary surface and the imaginary fluid; Acquire a second mesh correspondence between the second model boundary surface and the imaginary fluid; Based on the second grid correspondence, the first coupling variable is mapped from the second model to the imaginary fluid, and then the mapped data is interpolated to obtain a new first iteration variable.

6. The method according to claim 5, characterized in that The mapping of the first coupling variable from the second model to the imaginary fluid based on the second grid correspondence includes: Based on the second grid correspondence, the first coupling variable is averaged using the area of ​​the imaginary fluid grid as a weighting factor.

7. The method according to claim 1, characterized in that The first iteration variable includes wall temperature, and the second iteration variable includes heat flux density.

8. The method according to claim 1, characterized in that Step S5 includes: Step S51: determine whether the iteration variable group of the current time step meets the convergence condition, if yes, execute step S52, if no, repeat steps S3-S4, wherein the iteration variable group includes the first iteration variable and the second iteration variable, and the convergence condition is that the deviation between the iteration variable groups calculated twice adjacently is less than a preset threshold; Step S52: Determine whether the current time step reaches the preset simulation time. If so, the output condition is met; if not, the output condition is not met and the time step is advanced.

9. A computing device, characterized in that include: at least one processor; as well as At least one memory having instructions stored thereon, which, when executed individually or collectively by the at least one processor, cause the computing device to perform the method according to any one of claims 1-8.

10. A computer storage medium, characterized in that: The computer storage medium stores instructions, which, when executed individually or collectively by at least one processor of a computing device, cause the computing device to perform the method according to any one of claims 1-8.

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