Reactor prior reasoning method and system

Abstract

The invention provides a prior reasoning method and system for a reactor. The prior reasoning method comprises the following steps: obtaining a plurality of reactor parameters of the reactor; calculating a plurality of physical influence intensities among the plurality of reactor parameters according to a reactor state equation, wherein the plurality of physical influence intensities comprise a target physical influence intensity of at least one first reactor parameter on a second reactor parameter; calculating a deviation value of the at least one first reactor parameter; and calculating the conditional probability of the working condition related to the second reactor parameter under the deviation value according to the target physical influence intensity and the deviation value. According to the reactor prior reasoning method and system and the reactor applicable to the reactor prior reasoning method and system, the real-time working condition of the reactor can be accurately reasoned and monitored.

Description

TECHNICAL FIELD

[0001] The present application mainly relates to the field of reactor technology, and particularly relates to a reactor prior reasoning method and system. BACKGROUND

[0002] The safety problem of the reactor in the running process has been the focus of the industry, so the prior verification of the operation condition of the reactor and the subsequent reasoning of the possible operation condition are particularly important for the safety problem of the reactor operation. The static topology structure of the reactor in the running process cannot adapt to the accident evolution process. In the static topology structure, only the fixed reasoning link is included, and the new influence and causality relationship cannot be reasoned. For example, the static topology structure only includes the reasoning link of the main pump rotating speed -> coolant flow -> wall surface temperature -> pressure, but does not preset the reasoning link of "core melt -> containment damage -> hydrogen explosion" in some accidents, which means that the fixed reasoning link in the static topology structure cannot estimate the influence factors that may occur in the accident condition other than the experience. SUMMARY

[0003] The prior method and the applicable reactor provided by the present application can accurately reason and monitor the real-time condition of the reactor.

[0004] To solve the above technical problems, the present application provides a reactor prior reasoning method.

[0005] Optionally, the plurality of reactor parameters are any combination of reactor core temperature, reactor wall surface temperature, reactor pressure, fuel rod axial power density and reactor flow.

[0006] Optionally, the reactor state equation comprises one or any combination of coolant energy conservation equation, turbine efficiency correlation equation, containment thermal hydraulic equation, loss correlation equation and hot spot temperature equation.

[0007] Optionally, the coolant energy conservation equation comprises:

[0008] Wherein, p is the reactor pressure, T wall is the reactor wall surface temperature, q m is the fuel rod axial power density, T is the coolant temperature, t is the reactor running time, and ε is the loss energy.

[0009] Optionally, after obtaining the plurality of reactor parameters of the reactor, the plurality of reactor parameters are further subjected to denoising processing, and the denoising processing comprises one or any combination of parameter noise elimination, parameter abnormal value marking, parameter repair and parameter abnormal value processing.

[0010] Optionally, calculating the plurality of physical influence strengths between the plurality of reactor parameters according to the reactor state equation comprises the following steps: determining an independent reactor parameter and a dependent reactor parameter in the plurality of reactor parameters; and calculating a partial derivative of the dependent reactor parameter with respect to the independent reactor parameter.

[0011] Optionally, calculating the conditional probability of the working condition related to the second reactor parameter at the deviation value according to the target physical influence strength and the deviation value comprises: converting the deviation value into the conditional probability using a connection function according to the target physical influence strength.

[0012] Optionally, the priori reasoning method further comprises dynamically adjusting the weights of the plurality of reactor parameters using a time decay function.

[0013] Optionally, the priori reasoning method further comprises: establishing a causal graph according to the plurality of reactor parameters and the plurality of physical influence strengths; and judging whether the physical influence strength value is less than or equal to a preset threshold value, and if so, eliminating a causal path corresponding to the physical influence strength value in the causal graph.

[0014] Optionally, the preset threshold value ranges from 0.73 to 0.75.

[0015] To solve the above technical problems, the present application provides a priori reasoning system, comprising: a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the method as described above.

[0016] To solve the above technical problems, the present application provides a computer readable medium storing computer program codes, which, when executed by a processor, implement the method as described above.

[0017] Compared with the prior art, the present application can fully reflect the working condition influence relationship between different reactor structures by calculating the influence strength between a plurality of real-time reactor parameters, and is not limited to the existing working condition reasoning link. The priori reasoning is performed on the influence factors that may cause accidents other than experience, and the real-time working condition of the reactor can be accurately reasoned and monitored. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings are included to provide a further understanding of the present application, and are incorporated and constitute a part of the present application. The drawings illustrate embodiments of the present application and, together with the description, serve to explain the principles of the present application. In the drawings: Figure 1 is a flowchart of a priori reasoning method in an embodiment of the present application; Figure 2is a flow diagram of a priori reasoning method in an embodiment of the present application; Figure 3 is a system module diagram of a priori reasoning system in an embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some examples or embodiments of the present application, and for those skilled in the art, the present application can also be applied to other similar scenarios without creative labor on the basis of these drawings. Unless it is clear from the language context or otherwise indicated, the same reference numbers in the drawings represent the same structures or operations.

[0020] As shown in the present application and claims, unless the context clearly indicates otherwise, the words "one", "an", "a", and / or "the" do not specify a singular form, but also include a plural form. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements explicitly identified, and these steps and elements do not constitute an exclusive list, and the method or device can also include other steps or elements.

[0021] Unless otherwise specifically indicated, the relative arrangement of the components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application. At the same time, it should be understood that the sizes of the various parts shown in the drawings are not drawn in proportion to the actual proportions. The technology, methods and devices known to those skilled in the relevant art can not be discussed in detail, but under appropriate circumstances, the technology, methods and devices should be considered as part of the authorized description. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary, and not as a limitation. Therefore, other examples of exemplary embodiments can have different values. It should be noted that similar reference numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0022] In the description of the present application, it should be understood that the orientation words such as "front, back, up, down, left, right", "horizontal, vertical, perpendicular, horizontal" and "top, bottom" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and in the absence of contrary indications, these orientation words do not indicate and imply that the indicated device or element must have a particular orientation or be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the scope of protection of the present application; the orientation words "inner, outer" refer to the inner and outer relative to the contour of the parts themselves.

[0023] For purposes of the description hereinafter, spatial

[0024] In addition, it is to be noted that the terms "first", "second", and the like, used herein do not necessarily have an ordinal meaning. Rather, such terms are used to distinguish a different structure or action from another structure or action. It is also to be understood that the terms "left", "right", "back", "front", "top", "bottom", "over", "under", and the like as can be used herein are used for description purposes only and are not to be interpreted in a limiting sense.

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

[0026] The present application is directed to Figure 1A priori reasoning method 10 (hereinafter referred to as "reasoning method 10") is proposed. Flowcharts are used in the present application to illustrate the operations performed by the system according to embodiments of the present application. It should be understood that the foregoing or the following operations are not necessarily performed in sequence. On the contrary, various steps can be processed in reverse order or simultaneously. Meanwhile, other operations can be added to these processes, or one or more steps can be removed from these processes. The reasoning method 10 includes steps S1-S4. The prior method proposed in the present application and the reactor to which it is applicable can accurately reason and monitor the real-time operating conditions of the reactor.

[0027] Specifically, step S1 includes obtaining a plurality of reactor parameters of the reactor. In the present embodiment, the real-time reactor parameters include one or any combination of the reactor core temperature, the reactor wall surface temperature, the reactor pressure, the fuel rod axial power density, and the reactor flow. Preferably, after obtaining the real-time reactor parameters of the reactor, the real-time reactor parameters are subjected to denoising processing, which includes one or any combination of parameter noise elimination, parameter outlier marking, parameter repair, and parameter outlier processing. In other embodiments of the present application, the denoising processing can also include the operation of smoothing and enhancing the parameters, which is not limited in the present application. By denoising the real-time reactor parameters, it can be ensured that the real-time reactor parameters are accurate and available, which can further improve the reasoning accuracy of the prior reasoning method 10.

[0028] In the present embodiment, step S2 includes calculating a plurality of physical influence strengths between the plurality of reactor parameters according to a reactor state equation, the plurality of physical influence strengths including at least one target physical influence strength of a first reactor parameter on a second reactor parameter. Further, the reactor state equation includes one or any combination of a coolant energy conservation equation, a turbine efficiency correlation equation, a containment thermal-hydraulic equation, a loss correlation equation, and a hot spot temperature equation. For example, if the heat exchange scenario between the fuel rod and the coolant needs to be reasoned a priori, the coolant energy conservation equation can be used at this time. First, the coolant energy conservation equation includes: ε where p is the reactor pressure, T wall is the reactor wall surface temperature, q m is the fuel rod axial power density, T is the coolant temperature, t is the reactor operating time, and ε is the loss energy. That is, the real-time reactor parameters obtained in step S1 are brought into the coolant energy conservation equation to obtain the correlation mapping relationship among the reactor pressure, the reactor wall surface temperature, and the fuel rod axial power density, i.e. the increase of the fuel rod axial power density will cause the wall surface temperature to rise, and the rise of the wall surface temperature will cause the reactor pressure to increase.

[0029] Further, for example, when the axial power density of the fuel rod increases, the wall surface temperature of the reactor will rise according to the correlation mapping relationship obtained above, and the rise in the wall surface temperature will cause the pressure in the reactor to increase, so when the axial power density of the fuel rod is detected to increase, the staff needs to pay special attention to the situation of the internal pressure of the reactor at this time, and take safety measures according to the pressure change. On the other hand, in other embodiments of the present application, the change in the pressure of the reactor will also affect the cooling flow and other relationships, thereby further obtaining the influence relationship of the heat exchange efficiency. Therefore, the staff can perform real-time prior reasoning on the working condition of the heat exchange scene of the fuel rod and the coolant through the above relationship, and the correlation mapping relationship of multiple real-time reactor parameters can be clearly obtained through the above setting, avoiding the "black box" defect, and the safety and reliability of the reactor during operation can be further improved.

[0030] On the other hand, step S3 includes calculating a deviation value of the at least one first reactor parameter. Referring to Figure 2 , calculating the plurality of physical influence strengths between the plurality of reactor parameters according to the reactor state equation includes steps S11-S12. Step S11 includes determining an independent reactor parameter and a dependent reactor parameter in the plurality of reactor parameters; and step S12 includes calculating a partial derivative of the dependent reactor parameter with respect to the independent reactor parameter.

[0031] In the present embodiment, for example, it is desired to know the influence strength between the reactor temperature T and the reactor pressure p, first, the parameter function relationship p=f(T) between the reactor temperature T and the reactor pressure p needs to be constructed. At this time, T is selected as the independent real-time reactor parameter, and p is selected as the dependent real-time reactor parameter. Further, at this time, other parameters involved in the parameter function relationship p=f(T) are kept unchanged, only the reactor temperature T is changed, and the change rate of the reactor pressure p corresponding to different reactor temperatures T is calculated through the parameter function relationship, that is, the partial derivative is calculated. Exemplarily, the greater the value of the change rate (i.e., the partial derivative) , the stronger the influence of temperature change on pressure, and the smaller the value of the change rate , the weaker the influence of temperature change on pressure.

[0032] In the present embodiment, step S4 includes calculating a conditional probability of a working condition related to the second reactor parameter at the deviation value according to the target physical influence strength and the deviation value. Specifically, calculating the conditional probability of the working condition related to the second reactor parameter at the deviation value according to the target physical influence strength and the deviation value includes: using a connection function to convert the deviation value into the conditional probability according to the target physical influence strength. In the present embodiment, the Sigmoid function can be used to calculate the conditional probability.

[0033] Further, taking the coolant temperature T1 as an example, the following table shows the probability distribution of the coolant temperature T1 under the condition that both the flow rate and the neutron flux have deviations, which can help the staff accurately monitor and predict the coolant temperature T1 under the condition that both the flow rate and the neutron flux have deviations, so as to better control the coolant temperature T1. The following table lists the dynamic conditional probability table (CPT) obtained by using the reasoning method 10

[0034] Firstly, the deviation value of the real-time reactor parameter needs to be determined, that is, the deviation value of the reactor flow rate and the deviation value of the neutron flux are calculated in this embodiment. For example, the calculation of the deviation value of the reactor flow rate can be calculated according to the real-time reactor flow rate and the rated reactor flow rate. The calculation method can refer to the existing method, and since it is not the focus of the present application, it will not be described here.

[0035] Further, in this embodiment, the deviation value is converted into a conditional probability P using a connection function according to the target physical influence intensity. The specific calculation steps can refer to the existing calculation method of the Sigmoid function, and since it is not the focus of the present application, it will not be described here.

[0036]

[0037] As can be seen from the above table, -0.1≤ΔQ<0 means that the reactor flow rate is slightly low at this time, -5%≤ΔΦ<0% means that the reactor neutron flux is slightly low at this time, and then the probability of the coolant temperature T1 being normal is 0.85, the probability of being high is 0.12, and the probability of being dangerous is 0.03. Therefore, no special attention needs to be paid to the coolant temperature T1 at this time.

[0038] When -0.5≤ΔQ<-0.1 and 0%≤ΔΦ<5%, it means that the reactor flow rate is moderately low and the neutron flux is slightly high at this time. Then the probability of the coolant temperature T1 being normal is 0.6, the probability of being high is 0.3, and the probability of being dangerous is 0.1. Therefore, further attention needs to be paid to the coolant temperature T1 at this time.

[0039] When ΔQ<-0.5 and ΔΦ≥5%, it means that the flow rate of the reactor is significantly low and the neutron flux is significantly high at this time. The low flow rate means that the cooling capacity of the coolant to carry away the heat of the core is weaker, and the higher neutron flux means that the heat released by the fuel rod is more. Then it can be seen that the probability of the coolant temperature T1 being normal is 0.2, the probability of being high is 0.5, and the probability of being dangerous is 0.3. It can be seen that the probability of danger is 30% at this time, so special attention needs to be paid to the coolant temperature T1 at this time.

[0040] On the other hand, the reasoning method 10 also includes dynamically adjusting the weights of multiple reactor parameters using a time decay function. The time decay function includes: ,in, β is the initial weight, t is the real-time reactor parameter decay coefficient, and w is the timeout period. t This refers to real-time weighting. For example, the real-time reactor parameter decay coefficient can be obtained through calculation; for instance, after the main pump shuts down, the coolant flow rate decay coefficient β = 0.02s. -1 Since the calculation method is not the focus of this application, it will not be elaborated here.

[0041] In this embodiment, the real-time reactor parameters obtained by sensors are reliable for a certain period after acquisition, but beyond that time, the accuracy of prediction and inference decreases. Therefore, time-sensing processing of real-time reactor parameters ensures that the parameters used in subsequent steps are those within a certain reliable timeframe. For example, coolant temperature is affected by the reactor's neutron flux and reactor flow rate. In actual prediction, there may be situations where real-time neutron flux data is updated but real-time reactor flow rate data is not, thus reducing the weight of reactor flow rate. This means that when real-time reactor flow rate data is not updated, its importance in predicting subsequent coolant temperature conditions decreases. For example, if the preset reliable time is 60 seconds, the higher the timeout period, the lower the weight of the real-time reactor parameter. This ensures that older data has a lower weight but is not completely discarded, retaining a small amount of historical reference value while maintaining accuracy.

[0042] On the other hand, the reasoning method 10 also includes establishing a causal graph based on multiple reactor parameters and multiple physical influence intensities; determining whether the physical influence intensity value is less than or equal to a preset threshold; if so, removing the causal path corresponding to the physical influence intensity value from the causal graph. For example, the preset threshold ranges from 0.73 to 0.75.

[0043] Furthermore, for example, regarding reactor pressure p and reactor wall temperature T wall The reactor pressure p and reactor wall temperature T can be obtained first through the coolant energy conservation equation. wall The influence strength between them. At this point, a preset threshold of 0.75 is selected. If the calculated reactor pressure p and reactor wall temperature T... wall If the influence strength value is greater than 0.75, then it will affect the reactor wall temperature T. wall When performing predictive inference, the influence of reactor pressure p can be retained. If the influence strength value is less than or equal to 0.75, reactor pressure p can be removed and not used as an influencing factor in predictive inference.

[0044] An embodiment of this application also proposes a method such as Figure 3 The prior reasoning system 30 shown. According to...Figure 3 The a priori reasoning system 30 can include an internal communication bus 31, a processor 32, a read only memory (ROM) 33, a random access memory (RAM) 34, and a communication port 35. When implemented on a personal computer, the a priori reasoning system 30 can also include a hard disk 36.

[0045] The internal communication bus 31 can enable data communication among the components of the a priori reasoning system 30. The processor 32 can make decisions and issue prompts. In some embodiments, the processor 32 can be composed of one or more processors. The communication port 35 can enable data communication of the a priori reasoning system 30 with the outside. In some embodiments, the a priori reasoning system 30 can send and receive information and data from a network through the communication port 33.

[0046] The a priori reasoning system 30 can also include different forms of program storage units and data storage units, such as the hard disk 36, the read only memory (ROM) 33 and the random access memory (RAM) 34, which can store various data files used by the computer processing and / or communication, and possible program instructions executed by the processor 32. The processor executes these instructions to implement the main part of the method. The results of the processor processing are transmitted to the user equipment through the communication port, and displayed on the user interface.

[0047] In addition, another aspect of the present application provides a computer readable medium storing computer program codes, which, when executed by a processor, implement the a priori reasoning system method described above.

[0048] The above has described the basic concepts. It is obvious that the above application disclosure is only as an example, and does not constitute a limitation on the present application. Although it is not explicitly stated here, those skilled in the art can make various modifications, improvements and corrections to the present application. Such modifications, improvements and corrections are suggested in the present application, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of the present application.

[0049] Meanwhile, specific words are used in the present application to describe the embodiments of the present application. As "one embodiment", "an embodiment", and / or "some embodiments" means a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that the "an embodiment" or "one embodiment" or "an alternative embodiment" mentioned in different places in the specification does not necessarily mean the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be properly combined.

[0050] Aspects of the application can be implemented in hardware, software (including firmware, resident software, micro-code, etc.), or a combination thereof. The foregoing flow diagrams can be implemented in hardware, software (including firmware, resident software, micro-code, etc.), or a combination thereof. The various hardware and software components can be implemented within one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, a combination thereof, or the like. With respect to the various functions performed in the description above, the functions can be described in terms of a specific sequence or order of operations, but this description is not necessarily a limiting factor. Some of these operations can be combined into a single operation, further divided into multiple operations, performed at the same time, performed at different times, or performed in a different order or sequence, unless otherwise specified or implicit from the context. The above description is thus provided as an example, and not provided to limit or restrict the scope of the application.

[0051] Computer readable media can include a propagated data signal with computer program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal can take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any combination thereof. Computer readable media can be any media that can be accessed by a computer. By way of example, and not limitation, such computer readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired computer program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or any other medium, the coaxial cable, fiber optic cable, twisted pair, DSL, or any other medium is included in the definition of medium. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), and floppy disk where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer readable media.

[0052] In this respect, it should be noted that, in describing the embodiments of the application, the specification can have presented the application in a form that can highlight its preferred embodiments, but other embodiments may, however, be made without departing from the spirit of the application. Accordingly, no limitation should be imposed on the scope of the application with respect to its printed description and illustrated embodiments.

[0053] 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.

[0054] 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 of a priori reasoning for a reactor, characterized by, comprising the steps of: obtaining a plurality of reactor parameters of the reactor; calculating a plurality of physical influence strengths between the plurality of reactor parameters according to a reactor state equation, the plurality of physical influence strengths comprising at least one target physical influence strength of a first reactor parameter on a second reactor parameter; calculating a bias value of the at least one first reactor parameter; and calculating a conditional probability of an operating condition related to the second reactor parameter at the bias value according to the target physical influence strength and the bias value. The plurality of reactor parameters are any combination of reactor core temperature, reactor wall surface temperature, reactor pressure, fuel rod axial power density, and reactor flow rate.

2. The a priori reasoning method of claim 1, wherein, The reactor state equation comprises one or any combination of coolant energy conservation equation, turbine efficiency correlation equation, containment thermal-hydraulic equation, loss correlation equation, and hot spot temperature equation.

3. The a priori reasoning method of claim 2, wherein, The coolant energy conservation equation comprises:

4. The a priori reasoning method of claim 3, wherein, After obtaining the plurality of reactor parameters of the reactor, further comprising denoising the plurality of reactor parameters, the denoising comprising one or any combination of outlier rejection, outlier labeling, parameter repair, and outlier handling. where p is the reactor pressure, T wall is the reactor wall temperature, q m is the fuel rod axial power density, T is the coolant temperature, t is the reactor operating time, and ε is the energy loss.

5. The a priori reasoning method of claim 1, wherein, The calculating a plurality of physical influence strengths between the plurality of reactor parameters according to a reactor state equation comprises the steps of:

6. The a priori reasoning method of claim 1, wherein, determining an independent reactor parameter and a dependent reactor parameter in the plurality of reactor parameters; calculating a partial derivative of the dependent reactor parameter with respect to the independent reactor parameter. The calculating a conditional probability of an operating condition related to the second reactor parameter at the bias value according to the target physical influence strength and the bias value comprises converting the bias value to the conditional probability using a link function according to the target physical influence strength.

7. The a priori reasoning method of claim 1, wherein, Further comprising dynamically adjusting weights of the plurality of reactor parameters using a time decay function.

8. The a priori reasoning method of claim 1, wherein, Further comprising:

9. The a priori reasoning method of claim 1, wherein, establishing a causal graph according to the plurality of reactor parameters and the plurality of physical influence strengths; determining whether the physical influence strength value is less than or equal to a preset threshold value, and if so, rejecting a causal path corresponding to the physical influence strength value in the causal graph. The preset threshold value ranges from 0.73 to 0.

75.

10. The a priori reasoning method of claim 9, wherein, 11. A priori reasoning system, comprising: a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the method of any one of claims 1-10.

12. A computer readable medium having stored thereon computer program code which, when executed by a processor, implements the method of any one of claims 1-10. ​

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