Method for evaluating reliability of high-temperature alkali metal heat pipe

Abstract

The application provides a high-temperature alkali metal heat pipe reliability evaluation method, which comprises the following steps: obtaining failure modes of the high-temperature alkali metal heat pipe; calculating failure probabilities of the high-temperature alkali metal heat pipe corresponding to each failure mode respectively; in response to a failure mechanism of the failure mode being mechanical failure, constructing a structure fracture propagation model by using a probabilistic fracture mechanics analysis method, and calculating the failure probability of the high-temperature alkali metal heat pipe based on the structure fracture propagation model; in response to the failure mechanism of the failure mode being heat transfer failure, constructing a proxy model mapped from a working condition variable to each failure parameter by using a high-temperature alkali metal heat pipe transient working condition simulation model, and calculating the failure probability of the high-temperature alkali metal heat pipe based on the proxy model; and coupling the failure probabilities of the high-temperature alkali metal heat pipe of each failure mode to obtain a total failure probability of the high-temperature alkali metal heat pipe.

Description

Technical Field

[0001] This application relates primarily to the field of reactor technology, and in particular to a method for assessing the reliability of high-temperature alkali metal heat pipes. Background Technology

[0002] High-temperature alkali metal heat pipes (HTLMs) are the core components for heat transfer in HTLM-cooled reactors, efficiently transferring core fission heat to the energy conversion system. To ensure safe reactor operation, HTLMs must possess the ability to withstand extreme environments (high temperatures of 1000K-1800K, irradiation exposure) and long-term operational reliability (e.g., over 10 years of service life) to reliably transfer heat generated by the reactor core under both normal and accident conditions. Therefore, establishing a reliability assessment method for HTLMs is a crucial prerequisite for the transition from design to engineering verification of HTLM-cooled reactors.

[0003] However, the fabrication process of high-temperature alkali metal heat pipes is complex and difficult to manufacture. Furthermore, the test conditions for performance tests, such as heat transfer limits, start-up and transient tests, and long-term life tests, are stringent. Test-based reliability assessment methods for high-temperature alkali metal heat pipes are costly and time-consuming, and a scientific assessment method has not yet been established. In addition, long-term operational data for high-temperature alkali metal heat pipes are lacking, especially for high-aspect-ratio, gravity-free, and high-power-density heat pipes, which are newly developed equipment with limited industry experience. This makes it difficult for existing methods to effectively and quantitatively assess the reliability of high-temperature alkali metal heat pipes.

[0004] Therefore, there is an urgent need in this field for a reliability assessment method for high-temperature alkali metal heat pipes to quantitatively evaluate their reliability. Summary of the Invention

[0005] The technical problem to be solved by this application is to provide a reliability assessment method for high-temperature alkali metal heat pipes, which can quantitatively calculate the failure probability of high-temperature alkali metal heat pipes, thereby scientifically assessing the reliability of high-temperature alkali metal heat pipes.

[0006] To address the aforementioned technical problems, this application provides a reliability assessment method for high-temperature alkali metal heat pipes, comprising: acquiring the failure modes of the high-temperature alkali metal heat pipe; calculating the failure probability of the high-temperature alkali metal heat pipe corresponding to each failure mode; in response to the failure mechanism of the failure mode being mechanical failure, constructing a structural fracture propagation model using probabilistic fracture mechanics analysis, and calculating the failure probability of the high-temperature alkali metal heat pipe based on the structural fracture propagation model; in response to the failure mechanism of the failure mode being heat transfer failure, constructing a surrogate model mapping operating variables to each failure parameter using a transient operating condition simulation model of the high-temperature alkali metal heat pipe, and calculating the failure probability of the high-temperature alkali metal heat pipe based on the surrogate model; and coupling the failure probability of the high-temperature alkali metal heat pipe for each failure mode to obtain the total failure probability of the high-temperature alkali metal heat pipe.

[0007] In one embodiment of this application, the failure mode includes at least one of the following: shell rupture failure mode, wick deformation failure mode, working fluid degradation failure mode, and non-condensable gas accumulation failure mode.

[0008] In one embodiment of this application, the step of coupling the failure probability of the high-temperature alkali metal heat pipe for each failure mode to obtain the total failure probability of the high-temperature alkali metal heat pipe includes: obtaining the failure probability density function of each failure mode based on the failure probability of the high-temperature alkali metal heat pipe, and obtaining the total failure probability density function of the high-temperature alkali metal heat pipe by sampling and coupling the failure probability density function of each failure mode.

[0009] In one embodiment of this application, the step of calculating the failure probability of the high-temperature alkali metal heat pipe based on the structural fracture propagation model includes: obtaining the operating parameters of the high-temperature alkali metal heat pipe; randomly selecting initial crack parameters according to the probability density function to form a crack sample; and calculating the crack propagation of the crack sample caused by at least one of fatigue, stress corrosion cracking, and high-temperature creep according to the structural fracture propagation model. The structural fracture propagation model includes a fatigue crack propagation sub-model, a stress corrosion crack propagation sub-model, and a high-temperature creep crack propagation sub-model. Calculating the crack propagation of the crack sample includes: fitting the failure probability caused by fatigue based on the fatigue crack propagation sub-model. The crack propagation rate corresponding to the number of cycles is used to obtain the crack propagation rate at the corresponding time caused by stress corrosion cracking based on the stress corrosion crack propagation sub-model, and the creep fracture time caused by high temperature creep is obtained based on the high temperature creep crack propagation sub-model. Based on the crack propagation rate corresponding to the number of cycles and the crack propagation rate at the corresponding time, the crack propagation depth of the crack sample at the simulated time point is calculated. The number of failure samples is counted based on whether the crack propagation depth is greater than the wall thickness of the high-temperature alkali metal heat pipe or whether the creep fracture time is less than the simulated time point. Finally, the failure probability of the high-temperature alkali metal heat pipe is calculated based on the number of failure samples.

[0010] In one embodiment of this application, the step of constructing a surrogate model mapping operating condition variables to each failure parameter using a high-temperature alkali metal heat pipe transient operating condition simulation model includes: randomly sampling the operating condition variables to obtain sampling data corresponding to each failure parameter; using the high-temperature alkali metal heat pipe transient operating condition simulation model to calculate the simulated value of the failure parameter under the operating condition corresponding to the sampling data; and fitting the surrogate model corresponding to each failure parameter based on the sampling data and the simulated value of the failure parameter.

[0011] In one embodiment of this application, the failure parameters include at least one of pipe strength failure parameters, capillary limit failure parameters, and entrainment limit failure parameters.

[0012] In one embodiment of this application, the operating condition variables include at least one of power, operating angle, working fluid purity, liquid core deformation, non-condensable gas content, and running time.

[0013] In one embodiment of this application, the surrogate model includes a polynomial function that maps the operating condition variables to the failure parameters, the polynomial function being: In the formula, The failure parameters; : constant term; The number of the aforementioned operating condition variables; The operating condition variables form a one-dimensional vector; : A one-dimensional vector formed by the second-order expansion of the operating condition variables; : A one-dimensional vector formed by the third-order expansion of the operating condition variables; : A one-dimensional vector formed by the Nth-order expansion of the operating condition variables; , , , , : Coefficient vector.

[0014] In one embodiment of this application, the step of calculating the failure probability of the high-temperature alkali metal heat pipe based on the surrogate model includes: sampling each surrogate model corresponding to each failure parameter to obtain a frequency distribution histogram; obtaining a corresponding first probability density distribution function based on the frequency distribution histogram; calculating the overlap area between the probability density curve corresponding to the first probability density distribution function and the probability density curve corresponding to the second probability density distribution function, wherein the overlap area is used as the failure probability corresponding to each failure parameter, and the second probability density distribution function corresponds to the baseline operating condition; summing the failure probabilities corresponding to the failure parameters to obtain the failure probability of the high-temperature alkali metal heat pipe.

[0015] This application also proposes an electronic device comprising: a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the method described above.

[0016] This application also proposes a computer storage medium storing computer program code that, when executed by a processor, implements the method described above.

[0017] This application also proposes a computer program product including computer program code, which, when executed by one or more processors, implements the steps described above.

[0018] Compared with the prior art, this application has the following advantages: by obtaining the failure modes of high-temperature alkali metal heat pipes and calculating the failure probability of each failure mode using a quantitative evaluation method based on failure mechanism, the total failure probability of high-temperature alkali metal heat pipes is obtained by coupling, which solves the problem of difficult reliability evaluation of high-temperature alkali metal heat pipes, forms a quantitative evaluation paradigm for the reliability of high-temperature alkali metal heat pipes, and improves the efficiency of quantitative reliability evaluation of high-temperature alkali metal heat pipes. Attached Figure Description

[0019] The accompanying drawings are included to provide a further understanding of this application; they are incorporated into and constitute a part of this application. The drawings illustrate embodiments of this application and, together with this specification, serve to explain the principles of this application. In the drawings: Figure 1 This is a flowchart illustrating a method for evaluating the reliability of high-temperature alkali metal heat pipes according to an embodiment of this application. Figure 2 This is a flowchart illustrating a method for calculating the failure probability of a high-temperature alkali metal heat pipe based on a structural fracture propagation model according to an embodiment of this application. Figure 3 This is a flowchart illustrating a method for constructing a proxy model according to an embodiment of this application; Figure 4 This is a flowchart illustrating a method for calculating the failure probability of a high-temperature alkali metal heat pipe based on a surrogate model according to an embodiment of this application. Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0020] Reference numerals: Electronic device 500, communication bus 501, processor 502, read-only memory 503, random access memory 504, communication port 505, hard disk 506. Detailed Implementation

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this application. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0022] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not specifically singular and may include plural forms. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0023] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following drawings denote similar items; therefore, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.

[0024] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, these terms have no special meaning and therefore should not be construed as limiting the scope of protection of this application. In addition, although the terminology used in this application is selected from commonly known and used terms, some terms mentioned in this application's specification may have been chosen by the applicant according to his or her judgment, and their detailed meanings are explained in the relevant sections of this description. Moreover, this application should be understood not only through the actual terms used, but also through the meaning implied by each term.

[0025] It should be understood that when a component is referred to as "on another component," "connected to another component," "coupled to another component," or "in contact with another component," it can be directly on, connected to, coupled to, or in contact with that other component, or there may be an intervening component. In contrast, when a component is referred to as "directly on another component," "directly connected to," "directly coupled to," or "directly in contact with" another component, there is no intervening component. Similarly, when a first component is referred to as "electrically contacting" or "electrically coupled to" a second component, there is an electrical path between the first and second components that allows current to flow. This electrical path may include capacitors, coupled inductors, and / or other components that allow current to flow, even if there is no direct contact between the conductive components.

[0026] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more steps may be removed from these processes.

[0027] The reliability assessment method for high-temperature alkali metal heat pipes of this application will be described below through specific embodiments.

[0028] refer to Figure 1 The flowchart shown is a schematic diagram of a high-temperature alkali metal heat pipe reliability assessment method according to an embodiment. The assessment method includes... Figure 1 Steps S110 to S130 will be explained in detail below.

[0029] In step S110, the failure mode of the high-temperature alkali metal heat pipe is obtained.

[0030] In specific implementation, the failure modes of the high-temperature alkali metal heat pipe are obtained based on empirical settings. In some embodiments, the failure modes of the high-temperature alkali metal heat pipe obtained in step S110 include at least one of the following: shell rupture failure mode, wick deformation failure mode, working fluid degradation failure mode, and non-condensable gas accumulation failure mode.

[0031] The failure modes of high-temperature alkali metal heat pipes, defined based on experience, refer to the analysis and summarization of failure modes that lead to partial or complete failure of high-temperature alkali metal heat pipes, based on research into relevant data and failure problems encountered during actual manufacturing and testing. Considering the working fluid, the heat pipe shell, and the wick, the failure modes defined based on experience include the following: shell rupture failure mode, wick deformation failure mode, working fluid degradation failure mode, and non-condensable gas accumulation failure mode.

[0032] Specifically, the shell rupture failure mode refers to the pitting corrosion of the high-temperature alkali metal heat pipe shell caused by chemical corrosion and stress cracking, which expands into perforation and ultimately leads to the sealing failure of the high-temperature alkali metal heat pipe. The wick deformation failure mode refers to assembly defects or high-temperature corrosion causing poor contact between the wick and the pipe wall, or wick structural collapse, affecting the refrigerant return and leading to heat transfer failure. The refrigerant degradation failure mode refers to the incompatibility between the high-temperature alkali metal heat pipe material and the alkali metal refrigerant, or contamination by corrosion products, resulting in reduced refrigerant purity, increased thermal resistance, and ultimately heat transfer failure. The non-condensable gas accumulation failure mode refers to the accumulation of gases such as hydrogen, nitrogen, and oxygen released during corrosion of the high-temperature alkali metal heat pipe in the condensation section, leading to a reduction in heat exchange area, increased thermal resistance, and ultimately heat transfer failure.

[0033] In step S120, the failure probability of the high-temperature alkali metal heat pipe corresponding to each failure mode is calculated respectively: in response to the failure mechanism of the failure mode being mechanical failure, a structural fracture propagation model is constructed using probabilistic fracture mechanics analysis, and the failure probability of the high-temperature alkali metal heat pipe is calculated based on the structural fracture propagation model; in response to the failure mechanism of the failure mode being heat transfer failure, a surrogate model is constructed using a transient operating condition simulation model of the high-temperature alkali metal heat pipe, which maps operating condition variables to each failure parameter, and the failure probability of the high-temperature alkali metal heat pipe is calculated based on the surrogate model.

[0034] Specifically, based on the acquired failure modes, the failure mechanisms of these modes are analyzed. For example, the failure mechanism of the shell rupture failure mode is mechanical failure, while the failure mechanisms of the wick deformation failure mode, working fluid degradation failure mode, and non-condensable gas accumulation failure mode are heat transfer failures. Quantitative calculation methods corresponding to different failure mechanisms are then used to calculate the failure probability of the high-temperature alkali metal heat pipe for each failure mode.

[0035] When the failure mechanism is mechanical failure, the crack depth gradually increases over time. When the crack penetrates the wall of the high-temperature alkali metal heat pipe, the heat pipe is considered to have failed. A structural fracture propagation model is constructed to simulate the crack development process of the high-temperature alkali metal heat pipe from the appearance of a crack to its propagation over a preset time, thereby quantitatively assessing the failure probability of the high-temperature alkali metal heat pipe at the preset time. The preset time can be set according to actual conditions.

[0036] When the failure mechanism of the failure mode is heat transfer failure, the fitting data is collected through the transient operating condition simulation model of the high-temperature alkali metal heat pipe, and the fitting data is used to construct a surrogate model to simulate the mapping relationship between the operating condition variables and each failure parameter that causes the heat transfer failure of the high-temperature alkali metal heat pipe, so as to quantitatively assess the failure probability of the high-temperature alkali metal heat pipe at a preset time.

[0037] refer to Figure 2 The flowchart shown is a schematic diagram of a method for calculating the failure probability of a high-temperature alkali metal heat pipe based on a structural fracture propagation model, according to one embodiment. In one embodiment, the method for calculating the failure probability of a high-temperature alkali metal heat pipe based on a structural fracture propagation model includes... Figure 2 Steps S210 to S260 will be described in detail below.

[0038] In step S210, the operating parameters of the high-temperature alkali metal heat pipe are obtained.

[0039] Specifically, the operating parameters of high-temperature alkali metal heat pipes include operating temperature, material properties of high-temperature alkali metal heat pipes, coefficient of thermal expansion, internal compressive stress, thermal expansion stress, and self-weight stress.

[0040] In step S220, initial crack parameters are randomly selected according to the probability density function to form a crack sample.

[0041] Specifically, assuming that the geometry of the surface crack in the high-temperature alkali metal heat pipe remains unchanged during the propagation process, and only extends in crack depth, the initial geometric dimensions of the crack are determined by... and The probability density function is defined as follows:

[0042] In the formula, The crack depth. For half the length of the crack, For high-temperature alkali metal heat pipes with thick walls and The thickness of the high-temperature alkali metal heat pipe wall is a known value. A crack depth is randomly selected based on the probability density function. ,according to The probability density function yields the crack half-length. This allows for the random selection of initial crack parameters to form a crack sample.

[0043] In this step, sampling methods include, but are not limited to, simple random sampling, Latin hypercube sampling, stratified sampling, subset simulation, and directional sampling. In some embodiments, stratified sampling or importance sampling is used to balance computational accuracy and numerical stability under different operating parameters, thereby adapting to the analysis needs of high-dimensional random variables, nonlinear limit states, and low failure probability scenarios.

[0044] In some embodiments, to improve the accuracy of calculating the failure probability of high-temperature alkali metal heat pipes, a sufficient number of crack samples are extracted, for example, at least 300,000 crack samples are extracted in step S220.

[0045] In step S230, based on the structural fracture propagation model, the crack propagation of the crack sample caused by at least one of fatigue, stress corrosion cracking, and high-temperature creep is calculated. The structural fracture propagation model includes a fatigue crack propagation sub-model, a stress corrosion crack propagation sub-model, and a high-temperature creep crack propagation sub-model. The calculation of the crack propagation of the crack sample includes: fitting the crack propagation rate corresponding to the number of cycles caused by fatigue based on the fatigue crack propagation sub-model; fitting the crack propagation rate corresponding to the time caused by stress corrosion cracking based on the stress corrosion crack propagation sub-model; and fitting the creep fracture time caused by high-temperature creep based on the high-temperature creep crack propagation sub-model.

[0046] Specifically, based on the crack propagation caused by fatigue, stress corrosion cracking (SCC), and high-temperature creep, fatigue crack propagation sub-model, stress corrosion crack propagation sub-model, and high-temperature creep crack propagation sub-model are constructed to form a structural fracture propagation model under the mechanical failure mechanism.

[0047] A fatigue crack propagation sub-model simulates crack propagation caused by fatigue, and the crack propagation rate for the corresponding number of cycles is obtained by fitting the fatigue crack propagation sub-model. The expression of the fatigue crack propagation sub-model is:

[0048] In the formula, The crack depth. The number of loops. This represents the crack propagation rate corresponding to the number of cycles. and It is an empirical constant. Stress intensity factor For load ratio, , The maximum stress intensity factor, It is the minimum stress intensity factor. The effective stress intensity factor is calculated based on the operating temperature obtained in step S210. .

[0049] A stress corrosion crack propagation sub-model simulates crack propagation caused by stress corrosion cracking. The crack propagation rate at corresponding time points is obtained by fitting the stress corrosion crack propagation sub-model. The expression for the stress corrosion crack propagation sub-model is:

[0050] In the formula, The crack propagation rate is given over time and is expressed in millimeters per second (mm / sec). This is the stress intensity factor.

[0051] In some embodiments, the stress intensity factor is calculated using the weighted function method based on the operating temperature and shell material properties obtained in step S210. The formula for calculating the stress intensity factor is:

[0052] In the formula, , , , , It is a constant. , , , , , The sum of thermal expansion stress, compressive stress, and self-weight stress obtained in step S210. The crack depth. The wall thickness of the high-temperature alkali metal heat pipe is [not specified].

[0053] A high-temperature creep crack propagation sub-model simulates crack propagation caused by high-temperature creep, and the creep fracture time is obtained by fitting the model. The expression for the high-temperature creep crack propagation sub-model is:

[0054] In the formula, Larsson-Miller parameters are characteristic constants of a material under constant stress. Under the same material and stress level, For a constant value, For temperature, The creep buckling failure time. Let be the Larsson-Miller constant based on material properties. According to the above expression, the formula for calculating the creep rupture time after deformation is:

[0055] In step S240, the crack propagation depth of the crack sample at the simulated time point is calculated based on the crack propagation rate of the corresponding number of cycles and the crack propagation rate of the corresponding time.

[0056] Specifically, the crack propagation rate corresponding to the number of cycles obtained by fitting in step S230 is used. and the crack propagation rate over the corresponding time The crack propagation depth of the crack sample at each simulated time point (e.g., 1 year, 2 years, ..., 10 years) is obtained by performing multiplication operations with the simulated time points. .

[0057] In step S250, the number of failure samples is counted based on whether the crack propagation depth is greater than the wall thickness of the high-temperature alkali metal heat pipe or whether the creep fracture time is less than the simulated time point.

[0058] Specifically, the crack propagation depth at the simulation time point is calculated based on the crack propagation rate of the corresponding number of cycles. Greater than the wall thickness of high-temperature alkali metal heat pipes If the value is positive, it indicates that the high-temperature alkali metal heat pipe failed due to fatigue at the simulated time point, and this is recorded as a failed sample at the simulated time point; otherwise, it is recorded as a non-failed sample at the simulated time point. The crack propagation depth at the simulated time point is calculated based on the crack propagation rate at the corresponding time. Greater than the wall thickness of high-temperature alkali metal heat pipes If the time to failure is less than the simulation time, it indicates that the high-temperature alkali metal heat pipe failed due to stress corrosion cracking at the simulation time point, and this is recorded as a failed sample at the simulation time point; otherwise, it is recorded as a non-failed sample at the simulation time point. If the creep rupture time is less than the simulation time point, it indicates that the high-temperature alkali metal heat pipe failed due to high-temperature creep at the simulation time point, and this is recorded as a failed sample at the simulation time point; otherwise, it is recorded as a non-failed sample at the simulation time point. Count the number of failure samples caused by at least one of fatigue, stress corrosion cracking, or high-temperature creep at the simulation time point.

[0059] In step S260, the failure probability of the high-temperature alkali metal heat pipe is calculated based on the number of failure samples.

[0060] Specifically, the ratio of the number of failed samples to the total number of cracked samples is calculated to assess the failure probability of high-temperature alkali metal heat pipes. The formula for calculating the failure probability of high-temperature alkali metal heat pipes is as follows:

[0061] In the formula, To simulate time points The failure probability of high-temperature alkali metal heat pipes To simulate time points The number of failure samples, This represents the total number of crack samples.

[0062] According to the above embodiments, when the failure mechanism of the failure mode is mechanical failure, then based on Figure 2 Steps S210 to S260 shown calculate the failure probability of the high-temperature alkali metal heat pipe at the simulation time point.

[0063] During the service life of high-temperature alkali metal heat pipes, the operating limits of these heat pipes include capillary limit, viscous limit, sonic limit, entrainment limit, and boiling limit. Triggering the capillary limit and triggering the entrainment limit directly leads to heat transfer failure. Furthermore, heat transfer failure in high-temperature alkali metal heat pipes can also manifest as failure due to stress exceeding the operating limit caused by the high-temperature environment. This differs from the mechanical failure caused by crack propagation in the previous embodiment; its failure mechanism is heat transfer failure. In step S120, for failure modes with heat transfer failure as the failure mechanism, failure parameters leading to heat transfer failure of the high-temperature alkali metal heat pipe are set based on the aforementioned experience.

[0064] In some embodiments, the failure parameters include at least one of the pipe strength failure parameters, capillary limit failure parameters, and entrainment limit failure parameters. The pipe strength failure parameter refers to the heat transfer failure of the high-temperature alkali metal heat pipe caused by the pipe wall stress exceeding the limit stress. The capillary limit failure parameter refers to the heat transfer failure of the high-temperature alkali metal heat pipe caused by triggering the capillary limit. The entrainment limit failure parameter refers to the heat transfer failure of the high-temperature alkali metal heat pipe caused by triggering the entrainment limit.

[0065] In some embodiments, operating condition variables include at least one of power, operating angle, working fluid purity, wick deformation, non-condensable gas content, and operating time. Considering the acquired working fluid degradation failure mode, wick deformation failure mode, and non-condensable gas accumulation failure mode, working fluid purity, wick deformation, and non-condensable gas content are set as operating condition variables affecting failure parameters. Similarly, considering that the power and operating angle of the high-temperature alkali metal heat pipe are also factors influencing failure parameters, power and operating angle are set as operating condition variables. Furthermore, operating time is set as an operating condition variable to provide a means of determining the failure probability of the high-temperature alkali metal heat pipe at the simulated time point. For example, operating condition variables include power, operating angle, working fluid purity, wick deformation, non-condensable gas content, and operating time.

[0066] In one embodiment, the following is employed: Figure 3 Steps S310 to S330, as shown, construct a surrogate model that maps operating condition variables to each failure parameter, for subsequent calculation of the failure probability of high-temperature alkali metal heat pipes with heat transfer failure as the failure mechanism. Steps S310 to S330 will be described in detail below.

[0067] In step S310, the operating condition variables are randomly sampled to obtain sampling data corresponding to each failure parameter.

[0068] Specifically, based on relevant data, a reasonable mathematical distribution of the operating condition variables is assumed, as shown in Table 1, which illustrates the mathematical distribution of operating condition variables and the reasons for failure in one embodiment. Based on this mathematical distribution, sampling is performed on the operating condition variables to obtain sampling data corresponding to different failure parameters. As an example, the Latin hypercube sampling method is used to ensure that the sampled operating condition variables are uniformly distributed throughout the variable space and cover the maxima and minima of the operating condition variables. In addition, other sampling methods such as simple random sampling, stratified sampling, importance sampling, or subset simulation can also be used.

[0069] Table 1: Mathematical distribution of operating condition variables and reasons for failure in an embodiment.

[0070]

[0071] Each failure parameter corresponds to a sampling data set containing multiple sets of operating condition variable values. To improve the accuracy of the surrogate model, in some embodiments, at least 50 sampling data points are obtained for each failure parameter. It can be understood that when the failure parameters include pipe strength failure parameters, capillary limit failure parameters, and entrainment limit failure parameters, after step S310, at least 50 sampling data points are obtained for each failure parameter, resulting in at least 150 sampling data points for the three types of failure parameters. The sampling data for each failure parameter may differ.

[0072] In step S320, a high-temperature alkali metal heat pipe transient operating condition simulation model is used to calculate the simulated values ​​of failure parameters under the corresponding operating conditions of the sampled data.

[0073] Specifically, the transient operating condition simulation model for high-temperature alkali metal heat pipes is used to simulate the actual transient operating conditions of various high-temperature alkali metal heat pipes, in order to solve for data such as temperature, pressure, flow rate, and heat flux at different stages of the high-temperature alkali metal heat pipe. Then, based on the output data of the high-temperature alkali metal heat pipe transient operating condition simulation model, the simulated values ​​of failure parameters are calculated. The high-temperature alkali metal heat pipe transient operating condition simulation model includes, but is not limited to, the one-dimensional simplified thermal resistance network method, the two-dimensional refined core-thermal coupling flow model, and the three-dimensional core-thermal-mechanical multiphysics coupling model.

[0074] For example, the inputs to the transient operating condition simulation model of a high-temperature alkali metal heat pipe include operating condition variables and other parameters required for modeling the high-temperature alkali metal heat pipe, such as the geometric parameters of the high-temperature alkali metal heat pipe, the operating condition parameters of the heat exchange interface on the outer wall of the condensing section, and the vapor flow transition temperature parameters. The transient operating condition simulation model of a high-temperature alkali metal heat pipe can be implemented using conventional methods, which will not be elaborated here.

[0075] In step S330, a surrogate model corresponding to each failure parameter is fitted based on the sampling data and the simulated values ​​of the failure parameters.

[0076] Specifically, for each failure parameter, a surrogate model expression containing undetermined parameters is constructed. Based on sampled data and simulated values ​​of the failure parameters, the undetermined parameters in the surrogate model expression are determined through fitting / training to obtain the surrogate model corresponding to each failure parameter. The surrogate model includes the mapping relationship from operating condition variables to failure parameters, so as to output the fitted value of the failure parameter according to the input operating condition variables.

[0077] In some embodiments, the surrogate model includes a polynomial function that maps condition variables to failure parameters, the expression of which is:

[0078] In the formula, For failure parameters, For constant terms, The number of operating condition variables, A one-dimensional vector composed of operating condition variables. Let be a one-dimensional vector formed by the second-order expansion of the operating condition variables. Let be a one-dimensional vector formed by the third-order expansion of the operating condition variables. Let be a one-dimensional vector formed by the Nth-order expansion of the operating condition variables. , , , , This is the coefficient vector.

[0079] As an example, failure parameters include pipe strength failure parameters, capillary limit failure parameters, and entrainment limit failure parameters; operating condition variables include power. From a working perspective Sodium purity of working fluid Deformation of the wick Non-condensable gas content Running time The surrogate model is constructed as a polynomial function mapping the aforementioned operating condition variables to each of the aforementioned failure parameters. Taking insufficient pipe strength as an example, the expression of the polynomial function of the corresponding surrogate model is as follows:

[0080] In the formula, It is a one-dimensional vector consisting of six operating condition variables, with a dimension of 6; The second-order expansion of the six operating condition variables The resulting one-dimensional vector has a dimension of 21. The third-order expansion of the six operating condition variables The resulting one-dimensional vector has a dimension of 56. The fourth-order expansion of the six operating condition variables The resulting one-dimensional vector has a dimension of 126; The fifth-order expansion of the six operating condition variables The resulting one-dimensional vector has a dimension of 252; The sixth-order expansion of the six operating condition variables The resulting one-dimensional vector has a dimension of 462.

[0081] In other embodiments, when performing such Figure 3Before steps S310 to S330, the process includes: conducting a sensitivity analysis of the operating condition variables for each failure parameter, and selecting the operating condition variables with higher sensitivity as sensitive operating condition variables based on the sensitivity analysis results. Accordingly, in step S310, for each failure parameter, random sampling is performed on the sensitive operating condition variables corresponding to the failure parameter to obtain sampling data; in step S320, a high-temperature alkali metal heat pipe transient operating condition simulation model is used to calculate the simulated values ​​of the failure parameters; in step S330, based on the sampling data and the simulated values ​​of the failure parameters, a surrogate model mapping the sensitive operating condition variables to the corresponding failure parameters is fitted.

[0082] Compared to the time-consuming transient operating condition simulation model of high-temperature alkali metal heat pipes, this application constructs a surrogate model by sampling data, which maps operating condition variables to each failure parameter. This allows the surrogate model to quickly respond to operating condition variables and output the corresponding failure parameters, thereby improving the efficiency of transient operating condition simulation.

[0083] For reference Figure 4 The flowchart shown is a schematic diagram of a method for calculating the failure probability of a high-temperature alkali metal heat pipe based on a surrogate model, according to one embodiment. In one embodiment, the method for calculating the failure probability of a high-temperature alkali metal heat pipe includes, as follows: Figure 4 Steps S410 to S440 are shown below. Steps S410 to S440 will be explained in detail below.

[0084] In step S410, sampling is performed on each surrogate model corresponding to each failure parameter to obtain a frequency distribution histogram.

[0085] Under the coupling of multiple operating condition variables, the probability density distribution function of each failure parameter is obtained by sampling from the surrogate model. Step S410 specifically involves using the Monte Carlo sampling method to sample the surrogate model corresponding to each failure parameter, generating a large number of random samples, and obtaining the frequency distribution histogram of the surrogate model by statistically analyzing the probability distribution of the samples. It can be understood that the Monte Carlo sampling method is only one example; other sampling schemes can also be used to obtain the frequency distribution histogram.

[0086] In step S420, the corresponding first probability density distribution function is obtained based on the frequency distribution histogram.

[0087] Specifically, the implementation employs a kernel density estimation method, using a kernel function to smooth a set of sample points in the frequency distribution histogram, and constructs a continuous probability density function estimate as the first probability density distribution function. It is understood that other methods for smoothing and making the frequency distribution histogram continuous are also within the scope of this application.

[0088] In step S430, the overlapping area of ​​the probability density curve corresponding to the first probability density distribution function and the probability density curve corresponding to the second probability density distribution function is calculated. The overlapping area is used as the failure probability corresponding to each failure parameter, wherein the second probability density distribution function corresponds to the baseline operating condition.

[0089] Specifically, based on stress interference theory, the probability density curve corresponding to the first probability density distribution function generated by the surrogate model overlaps with the probability density curve corresponding to the second probability density distribution function under the baseline condition. Within this overlapping region, the fitted value of the failure parameter by the surrogate model is greater than the theoretical value. Therefore, calculating the area of ​​this overlapping region can quantify the failure probability. The formula for calculating the overlapping area is:

[0090] In the formula, Let be the first probability density distribution function. The second probability density distribution function, This represents the failure probability corresponding to the failure parameter.

[0091] Based on the above calculation formula, the overlap area between the surrogate model and the baseline operating condition corresponding to each failure parameter is calculated to obtain the failure probability corresponding to each failure parameter.

[0092] In step S440, the failure probabilities corresponding to the failure parameters are summed to obtain the failure probability of the high-temperature alkali metal heat pipe. Specifically, the operating condition variables of the surrogate model include the running time. In step S410, the frequency distribution histogram at the simulation time points is sampled, and in step S440, the failure probabilities corresponding to each failure parameter are summed to obtain the failure probability of the high-temperature alkali metal heat pipe with heat transfer failure as the failure mechanism.

[0093] As an example, the failure modes of high-temperature alkali metal heat pipes include wick deformation failure, working fluid degradation failure, and non-condensable gas accumulation failure. The failure mechanism of all three modes is heat transfer failure. Based on... Figure 3 and Figure 4 The embodiments shown calculate the failure probability of high-temperature alkali metal heat pipes at simulated time points (e.g., 1 year, 2 years, ..., 10 years) for three failure modes.

[0094] Next, refer to Figure 1 In step S130, the failure probability of the high-temperature alkali metal heat pipe for each failure mode is coupled to obtain the total failure probability of the high-temperature alkali metal heat pipe.

[0095] In some embodiments, step S130 includes: obtaining the failure probability density function of each failure mode based on the failure probability of the high-temperature alkali metal heat pipe, and obtaining the total failure probability density function of the high-temperature alkali metal heat pipe by sampling and coupling the failure probability density function of each failure mode.

[0096] Specifically, based on the failure probability of the high-temperature alkali metal heat pipe for each failure mode at the simulated time point, a mathematical method is used to obtain the failure probability density function for each failure mode. Then, a sampling coupling method (such as Monte Carlo sampling) is used to obtain the total failure probability density function. Based on the total failure probability density function, the failure probability of the high-temperature alkali metal heat pipe at the desired time point can be obtained.

[0097] For example, taking the shell rupture failure mode, wick deformation failure mode, working fluid degradation failure mode, and non-condensable gas accumulation failure mode as examples, the failure probability density function of the shell rupture failure mode is obtained based on the heat pipe failure probability of each failure mode at the simulation time point obtained in step S120. Failure probability density function of the wick deformation failure mode Failure probability density function of working fluid degradation failure mode Failure probability density function of non-condensable gas aggregation failure mode Combining optimal estimation and uncertainty analysis methods, from , , , A certain number of data samples are extracted from the data to construct the total failure probability density function. .

[0098] The reliability assessment method for high-temperature alkali metal heat pipes in this application obtains the failure modes of the high-temperature alkali metal heat pipes. When the failure mechanism of the failure mode is mechanical failure, a structural fracture propagation model is used to quantitatively calculate the failure probability of the high-temperature alkali metal heat pipe. When the failure mechanism of the failure mode is heat transfer failure, a surrogate model that maps operating condition variables to each failure parameter is used to calculate the failure probability of the high-temperature alkali metal heat pipe. The failure probabilities of the high-temperature alkali metal heat pipe under each failure mode are coupled to obtain the total failure probability. This forms a systematic, comprehensive, and scientific quantitative assessment paradigm for the reliability of high-temperature alkali metal heat pipes, providing a highly feasible quantitative assessment scheme for the reliability of high-temperature alkali metal heat pipes.

[0099] An embodiment of this application also proposes a method such as Figure 5 The electronic device 500 is shown. According to... Figure 5The electronic device 500 may include an internal communication bus 501, a processor 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, and a communication port 505. When used in a personal computer, the electronic device may also include a hard disk 506.

[0100] The internal communication bus 501 enables data communication between components of the electronic device 500. The processor 502 can perform judgments and issue prompts. In some embodiments, the processor 502 may consist of one or more processors. The communication port 505 enables data communication between the electronic device 500 and external devices. In some embodiments, the electronic device 500 can send and receive information and data from a network through the communication port 505.

[0101] Electronic device 500 may also include different forms of program storage units and data storage units, such as hard disk 506, read-only memory (ROM) 503, and random access memory (RAM) 504, capable of storing various data files used for computer processing and / or communication, as well as possible program instructions executed by processor 502. The processor executes these instructions to implement the main parts of the methods described above. The results of processor processing are transmitted to user equipment via a communication port and displayed on a user interface.

[0102] This application also proposes a computer-readable medium storing computer program code that, when executed by a processor, implements the method described above.

[0103] In addition, this application also proposes a computer program product, including computer program code, which, when executed by one or more processors, enables the implementation of the steps described above.

[0104] The basic concepts have been described above. Obviously, for those skilled in the art, the above disclosure is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore remain within the spirit and scope of the exemplary embodiments of this application.

[0105] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.

[0106] Similarly, it should be noted that, in order to simplify the description of the present application and thus aid in the understanding of one or more embodiments, the foregoing description of the embodiments of the present application sometimes combines multiple features into a single embodiment, drawing, or description thereof. However, this disclosure method does not imply that the subject matter of the present application requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of the single embodiments disclosed above.

[0107] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of scope in some embodiments of this application are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0108] Although this application has been described with reference to specific embodiments, those skilled in the art should recognize that the above embodiments are only used to illustrate this application, and various equivalent changes or substitutions can be made without departing from the spirit of this application. Therefore, any changes or modifications to the above embodiments within the essential spirit of this application will fall within the scope of the claims of this application.

Claims

1. A method for evaluating the reliability of high-temperature alkali metal heat pipes, characterized in that, include: To obtain the failure modes of high-temperature alkali metal heat pipes; The failure probability of the high-temperature alkali metal heat pipe corresponding to each failure mode is calculated separately: In response to the failure mechanism of the failure mode being mechanical failure, a structural fracture propagation model is constructed using probabilistic fracture mechanics analysis, and the failure probability of the high-temperature alkali metal heat pipe is calculated based on the structural fracture propagation model; In response to the failure mechanism of the failure mode being heat transfer failure, a transient operating condition simulation model of the high-temperature alkali metal heat pipe is used to construct a surrogate model that maps operating condition variables to each failure parameter preset according to the heat transfer failure mechanism, and the failure probability of the high-temperature alkali metal heat pipe is calculated based on the surrogate model, wherein the surrogate model is used to output the fitted value of each failure parameter according to the input value of the operating condition variables; as well as The failure probability of the high-temperature alkali metal heat pipe is coupled with the failure mode of each of the aforementioned failure modes to obtain the total failure probability of the high-temperature alkali metal heat pipe.

2. The reliability assessment method for high-temperature alkali metal heat pipes as described in claim 1, characterized in that, The failure modes include at least one of the following: shell rupture failure mode, wick deformation failure mode, working fluid degradation failure mode, and non-condensable gas accumulation failure mode.

3. The reliability assessment method for high-temperature alkali metal heat pipes as described in claim 2, characterized in that, The step of coupling the failure probability of each failure mode of the high-temperature alkali metal heat pipe to obtain the total failure probability of the high-temperature alkali metal heat pipe includes: obtaining the failure probability density function of each failure mode based on the failure probability of the high-temperature alkali metal heat pipe, and obtaining the total failure probability density function of the high-temperature alkali metal heat pipe by sampling and coupling the failure probability density function of each failure mode.

4. The reliability assessment method for high-temperature alkali metal heat pipes as described in claim 1, characterized in that, The steps for calculating the failure probability of the high-temperature alkali metal heat pipe based on the structural fracture propagation model include: Obtain operating parameters of high-temperature alkali metal heat pipes; Initial crack parameters are randomly selected based on the probability density function to form crack samples; Based on the structural fracture propagation model, the crack propagation of the crack sample caused by at least one of fatigue, stress corrosion cracking, and high-temperature creep is calculated. The structural fracture propagation model includes a fatigue crack propagation sub-model, a stress corrosion crack propagation sub-model, and a high-temperature creep crack propagation sub-model. Calculating the crack propagation of the crack sample includes: fitting the crack propagation rate corresponding to the number of cycles caused by fatigue based on the fatigue crack propagation sub-model; fitting the crack propagation rate corresponding to the time caused by stress corrosion cracking based on the stress corrosion crack propagation sub-model; and fitting the creep fracture time caused by high-temperature creep based on the high-temperature creep crack propagation sub-model. Based on the crack propagation rate of the corresponding number of cycles and the crack propagation rate of the corresponding time, the crack propagation depth of the crack sample at the simulated time point is calculated respectively. Based on whether the crack propagation depth is greater than the wall thickness of the high-temperature alkali metal heat pipe or whether the creep rupture time is less than the simulated time point, the number of failure samples is counted; and Based on the number of failed samples, the failure probability of the high-temperature alkali metal heat pipe is calculated.

5. The reliability assessment method for high-temperature alkali metal heat pipes as described in claim 1, characterized in that, The steps for constructing a surrogate model that maps operating condition variables to each failure parameter using a high-temperature alkali metal heat pipe transient operating condition simulation model include: Random sampling is performed on the operating condition variables to obtain sampling data corresponding to each failure parameter; A high-temperature alkali metal heat pipe transient operating condition simulation model was used to calculate the simulated values ​​of failure parameters under the operating conditions corresponding to the sampled data. Based on the sampling data and the simulated values ​​of the failure parameters, a surrogate model corresponding to each failure parameter is fitted.

6. The reliability assessment method for high-temperature alkali metal heat pipes as described in claim 1, characterized in that, The failure parameters include at least one of the following: pipe strength failure parameters, capillary limit failure parameters, and entrainment limit failure parameters.

7. The reliability assessment method for high-temperature alkali metal heat pipes as described in claim 1, characterized in that, The operating variables include at least one of the following: power, operating angle, working fluid purity, liquid core deformation, non-condensable gas content, and operating time.

8. The reliability assessment method for high-temperature alkali metal heat pipes as described in claim 1, characterized in that, The surrogate model includes a polynomial function that maps the operating condition variables to the failure parameters, wherein the polynomial function is: In the formula, The failure parameters; : constant term; The number of the aforementioned operating condition variables; The operating condition variables form a one-dimensional vector; : A one-dimensional vector formed by the second-order expansion of the operating condition variables; : A one-dimensional vector formed by the third-order expansion of the operating condition variables; : A one-dimensional vector formed by the Nth-order expansion of the operating condition variables; , , , , : Coefficient vector.

9. The reliability assessment method for high-temperature alkali metal heat pipes as described in claim 1, characterized in that, The step of calculating the failure probability of the high-temperature alkali metal heat pipe based on the surrogate model includes: Sampling is performed on each of the surrogate models corresponding to each of the aforementioned failure parameters to obtain a frequency distribution histogram; Based on the frequency distribution histogram, the corresponding first probability density distribution function is obtained; Calculate the area of ​​overlap between the probability density curve corresponding to the first probability density distribution function and the probability density curve corresponding to the second probability density distribution function. The area of ​​overlap is used as the failure probability corresponding to each failure parameter, wherein the second probability density distribution function corresponds to the baseline operating condition. The failure probability of the high-temperature alkali metal heat pipe is obtained by summing the failure probabilities corresponding to the failure parameters.

10. An electronic device, comprising: Memory is used to store instructions that can be executed by the processor; as well as A processor for executing the instructions to implement the method as described in any one of claims 1-9.

11. A computer storage medium storing computer program code, said computer program code implementing the method as claimed in any one of claims 1-9 when executed by a processor.

12. A computer program product comprising computer program code, wherein when the computer program code is executed by one or more processors, the one or more processors implement the steps of the method as described in any one of claims 1-9.

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