Method and system for simulating and predicting intensity of slow positron source in research reactor

Abstract

The invention provides a method and a system for simulating and predicting the intensity of a slow positron source in a research reactor. The method comprises the following steps: S1, reading arrangement information of components in a reactor core of the research reactor; s2, constructing a research reactor core Monte Carlo model containing a slow positron source device, and obtaining neutron multi-group angle flux and photon multi-group angle flux information near a slow positron source generation device; s3, constructing a slow positron source Monte Carlo model; s4, performing energy and angle double sampling to obtain incident neutron energy probability density distribution functions fn, ig and ia, angle probability density distribution functions fn and ia, incident photon flux energy probability density distribution functions fg, ig and ia, angle probability density distribution functions fg and ia and neutron and photon weight factors; s5, function sampling of particle types, energy and angles is carried out; and S6, acquiring slow positron distribution information generated in the slow positron generation device. According to the method, the generation of the slow positron and the full life cycle of transportation are accurately considered through multi-stage coupling, and accurate prediction of the intensity of the slow positron source is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of research reactor slow positron source intensity prediction, and particularly relates to a slow positron source intensity simulation prediction method and system for a research reactor. BACKGROUND

[0002] In the prior art, research reactors use neutron, photon and other radiation beams generated by controllable chain fission reactions for fuel / material irradiation testing, radioisotope production, neutron analysis and other research and application work, and are important scientific research infrastructure for promoting the development of advanced nuclear energy and nuclear technology, and play a very important supporting role in advanced reactor technology research and development, medical and industrial isotope supply, nuclear medicine, material science and life science fields.

[0003] Among them, the plate-shaped fuel has a larger area-to-volume ratio and a larger heat exchange area, and is more suitable for research reactors that require high power density and high neutron flux.

[0004] As the antiparticle of electrons, positrons have the same charge, mass and spin as electrons, except that their charge is opposite. A positron beam system can achieve all the measurement and analysis methods and techniques of an electron beam system. At the same time, due to the special annihilation properties of positrons in matter, it can also obtain microscopic defect information that cannot be obtained by electron beam analysis techniques. The positron beam spectrometer can qualitatively or quantitatively analyze the information of the concentration and type of micro defects in the material, obtain the distribution of defect elements, and obtain the spatial distribution information of defect structure and characteristics from the surface to the interior of the material.

[0005] With the increasing demand for surface physics and thin film material characterization, the development of high-quality beams with sufficient beam intensity, single energy and good stability has become the development direction of experts and scholars at home and abroad. The intensity of the positron beam depends on the number of initial high-energy positrons and the slow-down efficiency of the high-energy positrons in the slow-down system. The slow positron beam generated by the slow positron source device has good consistency and strong energy adjustability, and has been widely used as a sensitive probe for detecting the surface of matter in surface physics and material science.

[0006] Compared with accelerator slow positron source devices, radioactive source slow positron source devices, etc., the slow positron source device in the research reactor is the best way to obtain high-intensity slow positron beams. The slow positron source device generates a positron beam with an intensity one order of magnitude higher than that of an accelerator, and only uses neutrons produced by a reactor to obtain a large number of positrons, which is more stable than an accelerator slow positron source.

[0007] Meanwhile, due to the complex environmental conditions in the heavy water tank of the research reactor, it is more difficult to simulate and predict the slow positron source intensity in the research reactor than in the accelerator and the slow positron source device of the radioactive source. Therefore, the slow positron source intensity simulation and prediction must be considered from the whole research reactor system, so as to accurately predict the slow positron source intensity.

[0008] Therefore, the present application designs a slow positron source intensity simulation and prediction method and system for a research reactor to overcome the above technical problems. SUMMARY

[0009] The technical problem to be solved by the present application is to overcome the defects that the slow positron source intensity simulation and prediction in the prior art is difficult and cannot accurately predict the slow positron source intensity, and to provide a slow positron source intensity simulation and prediction method and system for a research reactor.

[0010] The present application solves the above technical problems by the following technical scheme:

[0011] A slow positron source intensity simulation and prediction method for a research reactor, characterized in that the simulation and prediction method comprises the following steps:

[0012] S1, reading the arrangement information of the components in the reactor core of the research reactor;

[0013] S2, according to the arrangement information obtained in step S1, constructing a research reactor core Monte Carlo model containing a slow positron source device by using a constructed entity geometry method, solving a neutron-photon coupling transport equation by using a Monte Carlo method, and obtaining the neutron multi-group angular flux ig,ia and the photon multi-group angular flux igg,ia information near the slow positron source device as the interface parameters of the slow positron source device by dividing the incident particle angles of the statistical slow positron source device outer surface into a angles;

[0014] S3, according to the arrangement information obtained in step S1 and the information of the neutron-photon multi-group angular flux near the slow positron source device obtained in step S2, constructing a slow positron source Monte Carlo model by using a constructed entity geometry method;

[0015] S4, according to the neutron angular flux distribution information and the photon angular flux distribution information obtained in step S2, performing energy-angle double sampling to obtain the energy probability density distribution function f n,ig,ia , the angle probability density distribution function f n,ia , the energy probability density distribution function f g,igg,ia of the incident photon, the angle probability density distribution function f g,ia , and the neutron-photon weight factor;

[0016] S5, performing particle type function sampling according to the neutron photon weight factor obtained in step S4, performing particle angle function sampling according to the angle probability density function, and performing particle energy function sampling according to the energy probability density function;

[0017] S6, performing neutron-photon-electron coupling transport calculation by using the Monte Carlo method to obtain the slow positron distribution information generated by the slow positron generating device.

[0018] According to an embodiment of the present application, the component arrangement information in the reactor core in step S1 includes: geometric size and material information of different types of components, state parameter information, slow positron source device position information, and geometric size and material information of the slow positron source device.

[0019] According to an embodiment of the present application, the state parameter information includes material temperature, burnup depth, and nuclear density distribution.

[0020] According to an embodiment of the present application, the arrangement information in step S3 includes: geometric size volume and material information of the slow positron source device.

[0021] According to an embodiment of the present application, step S4 includes: performing energy angle double sampling according to the neutron angular flux distribution information near the slow positron source generating device obtained in step S2.

[0022] Performing normalization operation on the multi-group neutron flux in each angle direction to obtain the energy probability density distribution function f of the neutron in each angle n,ig,ia :

[0023]

[0024] Taking the sum of the neutron flux in each angle as the weight to obtain the angle probability density distribution function f of the neutron n,ia :

[0025]

[0026] According to an embodiment of the present application, step S4 further includes: performing energy angle double sampling according to the photon angular flux distribution information near the slow positron source generating device obtained in step S2.

[0027] Performing normalization operation on the multi-group photon flux in each angle direction to obtain the energy probability density distribution function f of the photon in each angle g,igg,ia :

[0028]

[0029] The angle probability density distribution function f of the photons is obtained by taking the sum of the photon fluxes in each angle as the weight g,ia :

[0030]

[0031] According to one embodiment of the present application, the step S4 further comprises: obtaining a neutron-photon weight factor according to the neutron-photon angle flux distribution information obtained in the step S2, the sum of the neutron and photon fluxes in each angle being taken as the weight, the neutron-photon weight factor c being defined as:

[0032]

[0033] According to one embodiment of the present application, the step S5 comprises:

[0034] If the sampling result is a neutron, the angle sampling is performed according to the angle probability density distribution function f of the neutron obtained in the step S4, if the sampling result is the ith angle, the neutron energy sampling is performed according to the energy probability density distribution function f of the neutron in the ith angle n,ia . n,ig,ia to obtain the initial neutron energy;

[0035] If the sampling result is a photon, the angle sampling is performed according to the angle probability density distribution function f of the photon obtained in the step S4, if the sampling result is the ith angle, the photon energy sampling is performed according to the energy probability density distribution function f of the photon in the ith angle g,ia . g,igg,ia to obtain the initial photon energy.

[0036] According to one embodiment of the present application, the step S6 is followed by the following steps:

[0037] S7, reading the electrode shape and voltage parameter information of the slow positron transport device, obtaining the slow positron position information, energy information and exit angle information generated in the slow positron generating device according to the step S6, sequentially solving the transport processes of each slow positron by using an electromagnetic simulation program of charged particle simulation, and recording as passing if the slow positron successfully transports to the tail end, and recording as failing otherwise.

[0038] S8, according to the slow positron transport results obtained in the step S7, counting the total number of slow positrons passing, and obtaining the final slow positron source intensity of the slow positron source device in the research reactor.

[0039] The present application also provides a simulation prediction system for the slow positron source intensity in a research reactor, characterized in that the simulation prediction system adopts the simulation prediction method for the slow positron source intensity in a research reactor as described above, and the simulation prediction system comprises:

[0040] A slow positron source device particle environment solving module is used for simulating a complex particle environment in a research reactor and obtaining neutron and photon angular flux distribution information of the slow positron source device accessory;

[0041] A slow positron generation simulation module is used for establishing a slow positron source generation device model and performing neutron, photon and electron coupling transport solving to obtain slow positron position, energy and angle information generated;

[0042] A slow positron transport simulation module is used for simulating a slow positron transport process to obtain a number of slow positrons passing through the slow positron source device finally;

[0043] An interaction module is used for reading component arrangement information in a research reactor core, performing data transmission of the slow positron source device particle environment solving module and the slow positron generation simulation module, and performing data transmission of the slow positron generation simulation module and the slow positron transport simulation module.

[0044] The application further provides an electronic device, characterized in that the electronic device comprises a processor and a memory, the memory stores programs or instructions executable on the processor, and the programs or instructions are executed by the processor to realize the method for simulating and predicting slow positron source intensity in a research reactor.

[0045] The application further provides a readable storage medium, characterized in that the readable storage medium stores programs or instructions, and the programs or instructions are executed by a processor to realize the method for simulating and predicting slow positron source intensity in a research reactor.

[0046] The positive progress effect of the application is that:

[0047] The application is a method and system for simulating and predicting slow positron source intensity in a research reactor, based on particle conversion and transport mechanism in a slow positron source device, coupling effects among neutrons, photons and electrons are considered by using multi-particle simulation, the whole life cycle of slow positron generation and transport is accurately considered by using multi-stage coupling, and finally, the slow positron source intensity is accurately predicted. BRIEF DESCRIPTION OF DRAWINGS

[0048] The above and other features, properties and advantages of the application will become more apparent through the following description with reference to the accompanying drawings and embodiments, wherein the same reference signs always denote the same features, and wherein:

[0049] Figure 1 The application is a method for simulating and predicting slow positron source intensity in a research reactor.

[0050] Figure 2This is a schematic diagram illustrating the slow positron generation and transport process in a reactor, used in the present invention for studying the intensity simulation and prediction method of slow positron sources in a reactor.

[0051] Figure 3 This is a schematic diagram of a simulation and prediction system for studying the intensity of slow positron sources in a reactor. Detailed Implementation

[0052] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0053] Embodiments of the invention will now be described in detail with reference to the accompanying drawings. Preferred embodiments of the invention will now be described in detail, examples of which are shown in the drawings. Wherever possible, the same reference numerals will be used in all the drawings to denote the same or similar parts.

[0054] Furthermore, although the terminology used in this invention is selected from commonly known and used terms, some terms mentioned in this specification may have been selected by the applicant in his or her judgment, and their detailed meanings are explained in the relevant sections of the description herein.

[0055] Furthermore, the invention should be understood not only through the actual terminology used, but also through the meaning implied by each term.

[0056] like Figure 1 and Figure 2 As shown, this invention discloses a method for simulating and predicting the intensity of slow positron sources in a reactor, which includes the following steps:

[0057] Step S1: Read the arrangement information of components in the core of the research reactor.

[0058] Preferably, the information on the arrangement of components in the reactor core studied in step S1 includes: geometric dimensions and material information of different types of components, state parameter information, location information of the slow positron source device, and geometric dimensions and material information of the slow positron source device.

[0059] The state parameter information includes material temperature, burn-out depth, nucleon density distribution, etc.

[0060] Step S2: Based on the layout information obtained in Step S1, the geometric dimensions and material information of different types of components, and state parameter information such as material temperature, burn-up depth, and nucleon density distribution, a Monte Carlo model of the research reactor core containing the slow positron source device is constructed using a solid geometry construction method. The neutron-photon coupling transport equation is solved using the Monte Carlo method. By dividing the incident particle angles on the outer surface of the statistical slow positron source device into 'a' angles, the neutron multigroup angular flux φ near the slow positron source device is obtained. ig,iaand photon multi-group angular flux φ igg,ia Information (for example, divided into g energy groups, a angular directions), taking the parameters as the interface parameters of the slow positron source device.

[0061] Here, the neutron and photon angular flux information on the surface of the slow positron source device is obtained by neutron-photon coupling transport calculation based on the research reactor core model containing the slow positron source device, and is taken as the interface parameter.

[0062] Step S3, according to the arrangement information obtained in step S1 and the information of the neutron-photon multi-group angular flux near the slow positron source device obtained in step S2, the slow positron source Monte Carlo model is constructed by using the entity geometry method.

[0063] Preferably, the arrangement information in step S3 includes the geometric size volume and material information of the slow positron source device.

[0064] Step S4, according to the neutron angular flux distribution information and the photon angular flux distribution information near the slow positron source device obtained in step S2, energy-angle double sampling is performed to obtain the energy probability density distribution function f n,ig,ia , the angle probability density distribution function f n,ia , the energy probability density distribution function f g,igg,ia , the angle probability density distribution function f g,ia of the incident photons, and the neutron-photon weight factor.

[0065] That is, the energy probability density distribution function, the angle probability density distribution function, and the neutron-photon weight factor of the neutrons and photons are obtained by using the neutron and photon angular flux information on the surface of the slow positron source device.

[0066] Preferably, the step S4 includes: performing energy-angle double sampling according to the neutron angular flux distribution information near the slow positron source device obtained in step S2.

[0067] First, the multi-group neutron flux in each angle direction is normalized to obtain the energy probability density distribution function f n,ig,ia of the neutrons in each angle:

[0068]

[0069] Then, taking the sum of the neutron flux in each angle as the weight, the angle probability density distribution function f n,ia of the neutrons is obtained:

[0070]

[0071] By the angle probability density function, the non-uniform distribution of particles in the angle is considered, and more accurate outgoing particle information can be obtained.

[0072] The step S4 further comprises: according to the photon angle flux distribution information near the slow positron source generating device obtained in the step S2, performing energy-angle double sampling.

[0073] Firstly, the multi-group neutron flux in each angle direction is normalized to obtain the energy probability density distribution function f g,igg,ia :

[0074]

[0075] Then, the sum of the photon flux in each angle is taken as the weight to obtain the angle probability density distribution function f g,ia :

[0076]

[0077] By the angle probability density function, the non-uniform distribution of particles in the angle is considered, and more accurate outgoing particle information can be obtained.

[0078] The step S4 further comprises: according to the neutron-photon angle flux distribution information near the slow positron source generating device obtained in the step S2, taking the sum of the neutron and photon flux in each angle as the weight to obtain a neutron-photon weight factor, and the neutron-photon weight factor c is defined as:

[0079]

[0080] The energy probability density distribution function, the angle probability density distribution function, and the neutron-photon weight factor obtained in the step S4 are obtained by full-process coupling simulation: firstly, the core Monte Carlo calculation is performed to obtain accurate interface information, and the multi-group angle flux information is used as the interface information, which is different from the common multi-group flux information, and the angle distribution information is increased to overcome the non-uniform effect of the angle distribution caused by the different relative positions and angles of the slow positron source device and the core. At the same time, the full-process coupling simulation accurately considers the accurate distribution of the neutron-photon on the outer surface of the slow positron source by double sampling of the flux and the angle.

[0081] The step S5 comprises: according to the neutron-photon weight factor obtained in the step S4, performing function sampling of the particle type, the energy, and the angle.

[0082] Preferably, the step S5 comprises:

[0083] If the sampling result is a neutron, the angle probability density distribution function f n,ia; angle sampling is performed, if the sampling result is the ith angle, then the energy probability density distribution function f n,ig,ia Neutron energy sampling is performed to obtain an initial neutron energy.

[0084] If the sampling result is a photon, then the angle probability density distribution function f g,ia ; angle sampling is performed, if the sampling result is the ith angle, then the energy probability density distribution function f g,igg,ia Photon energy sampling is performed to obtain an initial photon energy.

[0085] Step S6, according to the slow positron source generating device Monte Carlo model constructed in step S3, the initial neutron and photon energies and angles obtained in step S5, a neutron-photon-electron coupling transport calculation is performed by using a Monte Carlo method to obtain slow positron distribution information generated in the slow positron source generating device.

[0086] Here, the slow positron distribution information preferably includes slow positron generation position information, energy information, and emission angle information, and the parameters are used as slow positron transport device interface parameters.

[0087] Further preferably, the step S6 further includes the following steps:

[0088] Step S7, reading electrode shape and voltage parameter information of the slow positron transport device, according to the slow positron position information, energy information, and emission angle information generated in the slow positron source generating device obtained in step S6, the transport process of each slow positron is sequentially solved by using an electromagnetism simulation program of charged particle simulation; if the slow positron successfully transports to the tail end, it is recorded as passing, otherwise it is recorded as failing.

[0089] Step S8, according to the slow positron transport results obtained in step S7, the total number of slow positrons passing is counted to obtain the final slow positron source intensity of the slow positron source device in the research reactor.

[0090] As Figure 3 shown, the present application also provides a slow positron source intensity simulation prediction system for a research reactor, which adopts the slow positron source intensity simulation prediction method as described above, and the simulation prediction system comprises:

[0091] A slow positron source device particle environment solving module is configured to simulate a complex particle environment in the research reactor to obtain neutron and photon angle flux distribution information of the slow positron source device accessories.

[0092] A slow positron generation simulation module is used to establish a slow positron source generation device model and to solve neutron, photon and electron coupling transport to obtain slow positron position, energy and angle information generated.

[0093] A slow positron transport simulation module is used to simulate a slow positron transport process to obtain the number of slow positrons finally passing through the slow positron source device.

[0094] An interaction module is used to read component arrangement information in a research reactor core, geometric size and material information of different types of components, material temperature, burnup depth, nuclear density distribution and other state parameter information, slow positron source device position information, slow positron source device geometric size and material information, and electrode shape, voltage parameter information of the slow positron device.

[0095] The interaction module performs data transmission between the slow positron source device particle environment solving module and the positron generation simulation module, and between the slow positron generation simulation module and the slow positron transport simulation module.

[0096] The application further provides an electronic device, including a processor and a memory, wherein the memory stores programs or instructions executable on the processor, and the programs or instructions are executed by the processor to realize the slow positron source intensity simulation prediction method for a research reactor as described above.

[0097] The application further provides a readable storage medium, wherein the readable storage medium stores programs or instructions, and the programs or instructions are executed by a processor to realize the slow positron source intensity simulation prediction method for a research reactor as described above.

[0098] According to the above description, the slow positron source intensity simulation prediction method for a research reactor has the following characteristics:

[0099] Firstly, the application directly establishes a research reactor core Monte Carlo model containing a slow positron source device, adopts a neutron-photon coupling transport method, obtains accurate neutron-photon angular flux distribution near the slow positron source generation device, adopts angular flux distribution information as an interface parameter, retains particle energy angle information, and provides accurate input parameters for slow positron generation.

[0100] Secondly, the application adopts a multi-stage coupling simulation strategy: firstly, the generation of neutrons and photons in the core is accurately simulated to obtain accurate input parameters of the slow positron generating device; then, the neutron-photon-electron coupling transport is solved for the slow positron generating device to obtain accurate slow positron generation information; finally, the slow positron source intensity is obtained by accurately solving electromagnetism according to the slow positron generation information. The multi-stage coupling simulation strategy realizes accurate simulation of the whole life cycle of slow positron generation and transport, reduces the input and output uncertainty in each process, and greatly improves the prediction accuracy.

[0101] Thirdly, the application adopts multi-particle simulation to consider the coupling effect among neutrons, photons and electrons, adopts multi-stage coupling to accurately consider the whole life cycle of slow positron generation and transport, and finally realizes accurate prediction of the slow positron source intensity.

[0102] For those skilled in the art, the above-mentioned 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.

[0103] At the same time, 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" mean 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 refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be properly combined.

[0104] Aspects of the application can be implemented in, completely, in hardware, completely in software (including firmware, resident software, micro-code, etc.), or combinations thereof. The foregoing hardware or software can be referred to as a "data block", "module", "engine", "unit", "component", or "system". A processor can be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, or combinations thereof. Furthermore, aspects of the application can be presented in a computer program product, which can include a computer-readable medium having stored computer-readable program codes that can be executed by one or more computer processors. For example, the computer-readable medium can include, but is not limited to, magnetic storage devices (e.g., hard disk; floppy disk; magnetic strips...), optical disks (e.g., compact disk (CD); digital versatile disk (DVD)...), smart cards, and flash memory devices (e.g., card; stick; key drive...).

[0105] The computer readable medium can include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. The computer readable program code can be transmitted on a variety of mediums including, but not limited to, wireless, wireline, optical fiber cable, RF, etc., or any suitable combination thereof. A computer readable medium can be any medium that can be read by a computer processor, including, but not limited to, memory devices, optical storage devices, and any combination thereof. The computer readable program code can be downloaded over a network from a remote computer program product or from a server, or can be downloaded from another computer readable medium, such as a hard drive, floppy disk, or CD-ROM. The computer program product can comprise all the respective features enabling the implementation of the method described herein and which are, taken together, instrumental in transforming a computer readable medium.

[0106] It should also be noted that, while the foregoing description of the embodiments (and specific examples for the disclosure) has related to illustrating the illustrative aspects of an application and / or specific examples embodying the present application, it is not intended that the application be limited thereto. For example, the disclosure has been described with reference to a number of individual features or aspects. It should be noted that features described solely in the context of separate features can be provided on combined systems. For example, the features of the first aspect can be provided in combination with the features of the second aspect, and so on. Furthermore, where appropriate, aspects of the application incorporated in a patent litigation context can include a combination of features described in the specification, including combinations of features of the first aspect, the second aspect, and so on. The scope of the present application should be determined by reference to the appended claims, along with the full text of this disclosure, including the description.

[0107] Although the specific embodiments of the present application have been described above, it is understood by those skilled in the art that these are merely illustrative, and the scope of protection of the present application is defined by the appended claims. Those skilled in the art can make various changes or modifications to the embodiments without departing from the principles and the essence of the present application, and such changes and modifications fall within the scope of protection of the present application.

Claims

1. A method for analog prediction of slow positron source strength in a research reactor, characterized by, The simulation prediction method comprises the following steps: S1, reading the arrangement information of the assemblies in the core of the research reactor; S2, using the arrangement information obtained in step S1, constructing a research reactor core Monte Carlo model containing a slow positron source device using a constructive solid geometry method, solving a neutron-photon coupled transport equation using a Monte Carlo method, and obtaining neutron multi-group angular flux φ ig,ia and photon multi-group angular flux φ igg,ia information as interface parameters of the slow positron generating device; S3, constructing a slow positron source Monte Carlo model by using a constructive solid geometry method according to the arrangement information obtained in step S1 and the information of the neutron-photon multi-group angular flux near the slow positron source generating device obtained in step S2; S4, generating energy-angle double sampling based on the neutron angular flux distribution information and the photon angular flux distribution information obtained near the slow positron source generating device in step S2, and obtaining an energy probability density distribution function f of incident neutrons n,ig,ia , an angle probability density distribution function f n,ia , an energy probability density distribution function f of incident photons g,igg,ia , an angle probability density distribution function f g,ia , and a neutron-photon weight factor S5, performing function sampling of the particle type according to the neutron-photon weight factor obtained in step S4, performing function sampling of the particle angle according to the angular probability density function, and performing function sampling of the particle energy according to the energy probability density function; S6, performing neutron-photon-electron coupled transport calculation by using a Monte Carlo method to obtain the slow positron distribution information generated in the slow positron source generating device.

2. The method for the simulation prediction of the intensity of a slow positron source in a research reactor according to claim 1, characterized in that, The arrangement information of the assemblies in the core of the research reactor in step S1 comprises the geometric size and material information of assemblies of different types, state parameter information, slow positron source device position information, and the geometric size and material information of the slow positron source device.

3. The method for the simulation prediction of the intensity of a slow positron source in a research reactor according to claim 2, characterized in that, The state parameter information comprises material temperature, burnup depth, and nuclear density distribution.

4. The method for the simulation prediction of the strength of a slow positron source in a research reactor as claimed in claim 1, characterized in that, The arrangement information in step S3 comprises the geometric size volume and material information of the slow positron source device.

5. The method for the simulation prediction of the strength of a slow positron source in a research reactor as claimed in claim 1, characterized in that, In step S4, energy-angle double sampling is performed according to the neutron angular flux distribution information near the slow positron source generating device obtained in step S2; The multi-group neutron flux in each angular direction is normalized to obtain the energy probability density distribution function f of the neutrons in each angle n,ig,ia : The angular probability density distribution function f of the neutrons is obtained by using the sum of the neutron fluxes in the various angles as a weight n,ia :

6. The method for the simulation prediction of the strength of a slow positron source in a research reactor as claimed in claim 1, wherein In step S4, energy-angle double sampling is also performed according to the photon angular flux distribution information near the slow positron source generating device obtained in step S2; The multi-group neutron flux in each angular direction is normalized to obtain the energy probability density distribution function f of the photons in each angle g,igg,ia : Summing the photon fluxes in each angle as the weight, the angle probability density distribution function f of the photons is obtained g,ia :

7. The method for the simulation prediction of the strength of a slow positron source in a research reactor as claimed in claim 1, characterized in that, In step S4, the neutron-photon weight factor is obtained according to the neutron-photon angular flux distribution information near the slow positron source generating device obtained in step S2, with the sum of the neutron and photon fluxes at each angle as the weight, and the neutron-photon weight factor c is defined as:

8. The method for the simulation prediction of the strength of a slow positron source in a research reactor as claimed in claim 1, characterized in that, In step S5, the following steps are included: If the sampling result is a neutron, the angular probability density distribution function f of the neutron obtained according to step S4 is used to perform angular sampling, and if the sampling result is the ith angle, the energy probability density distribution function f of the neutron of the ith angle is used to perform energy sampling n,ia to obtain the initial neutron energy n,ig,ia to obtain the initial neutron energy If the sampling result is a photon, the angular probability density distribution function f of the photon obtained according to step S4 is used to perform angular sampling, and if the sampling result is the ith angle, the energy probability density distribution function f of the photon of the ith angle is used to perform energy sampling g,ia to obtain the initial photon energy. g,igg,ia to obtain the initial photon energy.

9. The method for the simulation prediction of the strength of a slow positron source in a research reactor as claimed in claim 1, characterized in that, After step S6, the following steps are further included: S7, reading the electrode shape and voltage parameter information of the slow positron transport device, and sequentially solving the transport processes of the slow positrons by using an electromagnetism simulation program for charged particles according to the slow positron position information, energy information, and exit angle information of the slow positrons generated in the slow positron generating device obtained in step S6; if the slow positrons are successfully transported to the tail end, it is recorded as passing, otherwise, it is recorded as failing; S8, according to the transport results of the slow positrons obtained in step S7, counting the total number of the slow positrons passing, and obtaining the final slow positron source intensity of the slow positron source device in the research reactor.

10. A system for analog prediction of slow positron source strength in a research reactor, characterized by, The simulation prediction system adopts the slow positron source intensity simulation prediction method for a research reactor according to any one of claims 1-9, and the simulation prediction system comprises: A slow positron source device particle environment solving module for simulating the complex particle environment in the research reactor to obtain the neutron and photon angular flux distribution information near the slow positron source device; A slow positron generation simulation module for establishing a slow positron source generating device model and performing neutron, photon, and electron coupled transport solving to obtain the slow positron position, energy, and angle information generated; A slow positron transport simulation module is configured to simulate a slow positron transport process to obtain a number of slow positrons finally passing through the slow positron source device; An interaction module is configured to read component arrangement information in a reactor core, and to perform data transmission between the particle environment solving module and the positron generation simulation module, and data transmission between the slow positron generation simulation module and the slow positron transport simulation module.

11. An electronic device, comprising: The electronic device comprises a processor and a memory, the memory stores programs or instructions executable on the processor, and the programs or instructions are executed by the processor to implement the method for simulating and predicting slow positron source intensity in a research reactor according to any one of claims 1-9.

12. A readable storage medium, characterized by, The readable storage medium stores programs or instructions, and the programs or instructions are executed by the processor to implement the method for simulating and predicting slow positron source intensity in a research reactor according to any one of claims 1-9.

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