Simulation prediction method and system for slow positron source intensity in research reactor

Abstract

The application provides a simulation prediction method and system for slow positron source intensity in a research reactor, comprising the following steps: S1, reading arrangement information of components in a reactor core of the research reactor; S2, constructing a Monte Carlo model of the reactor core containing a slow positron source device, and obtaining neutron multi-group angular flux and photon multi-group angular flux information near the slow positron source generating device; S3, constructing a slow positron Monte Carlo model; S4, performing energy-angle double sampling to obtain an incident neutron energy probability density distribution function f n,ig,ia , an angle probability density distribution function f n,ia , an incident photon flux energy probability density distribution function f g,ig,ia , an angle probability density distribution function f g,ia , and a neutron-photon weight factor; S5, performing function sampling of particle types, energy and angle; and S6, obtaining slow positron distribution information generated in the slow positron generating device. The application accurately considers the whole life cycle of slow positron generation and transportation through multi-stage coupling, and realizes accurate prediction of slow positron source intensity.

Description

Technical Field

[0001] This invention relates to the field of predicting the intensity of slow positron sources in research reactors, and particularly to a method and system for simulating and predicting the intensity of slow positron sources in research reactors. Background Technology

[0002] In existing technologies, research reactors utilize neutron and photon beams generated by controlled chain fission reactions for research and application work such as fuel / material irradiation testing, radioactive isotope production, and neutron analysis. They are important scientific research infrastructures for promoting the development of advanced nuclear energy and nuclear technology, and play a very important supporting role in the research and development of advanced reactor technology, medical and industrial isotope supply, nuclear medicine, materials science, and life sciences.

[0003] Plate-shaped fuel, with its larger area-to-volume ratio and larger heat exchange area, is more suitable for research reactors requiring high power density and high neutron flux. Based on the high neutron flux characteristics of research reactors, they are typically equipped with various neutron application devices.

[0004] As the antiparticle of the electron, the positron is identical to the electron in terms of charge, rest mass, and spin, except that its charge is opposite. Spectrometers developed using positron beam systems can implement all the measurement and analysis methods and techniques of electron beams. Furthermore, due to the unique annihilation properties of positrons in matter, they can also obtain microscopic defect information that is unavailable with electron beam analysis techniques. Positron beam spectrometers can qualitatively or quantitatively analyze the concentration and types of microscopic defects in materials, obtain the elemental distribution within defects, and acquire spatial distribution information of defect structure and properties from the material surface to the material interior with depth.

[0005] With the increasing demands for surface physics and thin film material characterization, developing high-quality beams with sufficiently high intensity, single energy, and good stability has become a key research direction pursued by experts and scholars both domestically and internationally. The intensity of a positron beam depends on the initial number of high-energy positrons and the slowing efficiency of the moderation system for these high-energy positrons. Slow positron source devices produce slow positron beams with good intensity consistency and strong energy tunability, and have been widely used as sensitive probes for probing material surfaces in surface physics and materials science.

[0006] Compared to accelerator-based slow positron source devices and radioactive source-based slow positron source devices, reactor-based slow positron source devices are currently the best way to obtain high-intensity slow positron beams. Slow positron source devices produce positron beams with an intensity an order of magnitude higher than accelerator-based positron beams, and obtain a large number of positrons simply by bombarding a target with neutrons generated in the reactor. This makes them more stable than accelerator-based slow positron sources.

[0007] Meanwhile, due to the complex environmental conditions in the heavy water tank of the research reactor, the simulation and prediction of the slow positron source intensity in the research reactor is more difficult than that of the slow positron source device in the accelerator and radioactive source. It is necessary to consider the slow positron source intensity simulation and prediction from the perspective of the entire research reactor system in order to accurately predict the slow positron source intensity.

[0008] In view of this, the inventors of this application have designed a method and system for simulating and predicting the intensity of slow positron sources in a reactor, in order to overcome the above-mentioned technical problems. Summary of the Invention

[0009] The technical problem to be solved by the present invention is to overcome the difficulty in simulating and predicting the intensity of slow positron sources in the research reactor and the inability to accurately predict the intensity of slow positron sources in the existing technology, and to provide a method and system for simulating and predicting the intensity of slow positron sources in the research reactor.

[0010] The present invention solves the above-mentioned technical problems through the following technical solution:

[0011] A simulation and prediction method for studying the intensity of slow positron sources in a reactor, characterized in that the simulation and prediction method includes the following steps:

[0012] S1. Read the arrangement information of components in the reactor core;

[0013] S2. Based on the layout information obtained in step S1, a Monte Carlo model of the research reactor core containing the slow positron source device is constructed using the 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,ia Photon multigroup angular flux φ igg,ia Information, serving as interface parameters for the slow positron generator;

[0014] S3. Based on the layout information obtained in step S1 and the information on the neutron-photon multigroup angular flux near the slow positron source generator obtained in step S2, construct a Monte Carlo model of the slow positron source using the solid geometry construction method.

[0015] S4. Based on the neutron angular flux distribution information and photon angular flux distribution information near the slow positron source generator obtained in step S2, perform double sampling of energy angle to obtain the energy probability density distribution function f of the incident neutron. n,ig,ia Angular probability density distribution function f n,ia The energy probability density distribution function f of the incident photon g,igg,ia Angular probability density distribution function f g,ia And neutron photon weighting factor;

[0016] S5. Based on the neutron photon weighting factor obtained in step S4, perform function sampling of particle type, function sampling of particle angle based on angle probability density function, and function sampling of particle energy based on energy probability density function.

[0017] S6. The Monte Carlo method is used to perform neutron-photon-electron coupling transport calculations to obtain the distribution information of slow positrons generated in the slow positron generator.

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

[0019] According to one embodiment of the present invention, the state parameter information includes material temperature, burn-out depth, and nucleon density distribution.

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

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

[0022] Normalizing the neutron flux of multiple groups at various angles yields the energy probability density distribution function f of neutrons at each angle. n,ig,ia :

[0023]

[0024] Using the sum of neutron flux at each angle as weights, the angular probability density distribution function f of neutrons is obtained. n,ia :

[0025]

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

[0027] Normalize the multi-group photon flux at each angle to obtain the energy probability density distribution function f of photons at each angle. g,igg,ia :

[0028]

[0029] Using the sum of photon flux at each angle as weights, the angular probability density distribution function f of photons is obtained. g,ia :

[0030]

[0031] According to an embodiment of the present invention, step S4 further includes: based on the neutron-photon angular flux distribution information near the slow positron source generator obtained in step S2, obtaining a neutron-photon weighting factor with the sum of neutron and photon fluxes at each angle as the weight, wherein the neutron-photon weighting factor c is defined as:

[0032]

[0033] According to an embodiment of the present invention, step S5 includes:

[0034] If the sampling result is a neutron, then according to the angular probability density distribution function f of the neutron obtained in step S4... n,ia Perform angle sampling. If the sampling result is the ia-th angle, then according to the energy probability density distribution function f of the neutrons at the ia-th angle... n,ig,ia The initial neutron energy is obtained by sampling the neutron energy.

[0035] If the sampling result is a photon, then according to the angular probability density distribution function f of the photon obtained in step S4... g,ia Perform angle sampling. If the sampling result is the ia-th angle, then according to the energy probability density distribution function f of the photon at the ia-th angle... g,igg,ia Initial photon energy is obtained by sampling photon energy.

[0036] According to one embodiment of the present invention, after step S6, the following step is further included:

[0037] S7. Read the electrode shape and voltage parameter information of the slow positron transport device. Based on the position information, energy information and emission angle information of the slow positrons generated in the slow positron generating device obtained in step S6, solve the transport process of each slow positron in sequence through the electromagnetic simulation program of charged particle simulation. If the slow positron is successfully transported to the tail end, it is recorded as a pass, otherwise it is recorded as a failure.

[0038] S8. Based on the slow positron transport results obtained in step S7, count the total number of slow positrons that pass through, and obtain the final slow positron source intensity of the slow positron source device in the research reactor.

[0039] This invention also provides a simulation and prediction system for studying the intensity of slow positron sources in a reactor, characterized in that the simulation and prediction system employs the simulation and prediction method for studying the intensity of slow positron sources in a reactor as described above, and the simulation and prediction system includes:

[0040] The particle environment solution module for the slow positron source device is used to simulate the complex particle environment inside the research reactor and obtain the neutron and photon angular flux distribution information of the slow positron source device.

[0041] The slow positron generation simulation module is used to build a model of the slow positron source generation device and solve for the coupled transport of neutrons, photons, and electrons to obtain the position, energy, and angle information of the generated slow positrons.

[0042] The slow positron transport simulation module is used to simulate the slow positron transport process and obtain the number of slow positrons that finally pass through the slow positron source device.

[0043] The interaction module is used to read the component layout information in the reactor core, and to perform data transfer between the particle environment solution module of the slow positron source device and the positron generation simulation module, and between the slow positron generation simulation module and the slow positron transport simulation module.

[0044] The present invention also provides an electronic device, characterized in that the electronic device includes: a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions being executed by the processor to implement the simulation and prediction method for studying the intensity of slow positron sources in a reactor as described above.

[0045] The present invention also provides a readable storage medium, characterized in that a program or instructions are stored on the readable storage medium, and when the program or instructions are executed by a processor, the above-described method for simulating and predicting the intensity of slow positron sources in a pile is implemented.

[0046] The positive and progressive effects of this invention are as follows:

[0047] This invention is used to study the simulation and prediction method and system of slow positron source intensity in a reactor. Based on the particle conversion and transport mechanism in the slow positron source device, it adopts multi-particle simulation to consider the coupling effect between neutrons, photons and electrons. Through multi-stage coupling, it accurately considers the entire life cycle of slow positron generation and transport, and finally realizes the accurate prediction of slow positron source intensity. Attached Figure Description

[0048] The above and other features, properties and advantages of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings and embodiments, in which the same reference numerals always denote the same features, wherein:

[0049] Figure 1 This is a flowchart of the method for simulating and predicting the intensity of slow positron sources in a reactor, which is the subject of this invention.

[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,iaPhoton multigroup angular flux φ igg,ia Information (e.g., divided into g energy groups and a angular directions) is used as the interface parameters for the slow positron generation device.

[0061] Here, a research reactor core model containing a slow positron source is used, and the neutron and photon angular flux information on the outer surface of the slow positron source generating device obtained through neutron-photon coupling transport calculations is used as interface parameters.

[0062] Step S3: Based on the layout information obtained in Step S1 and the information on the neutron-photon multigroup angular flux near the slow positron source generator obtained in Step S2, construct a Monte Carlo model of the slow positron source using a solid geometry construction method.

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

[0064] Step S4: Based on the neutron angular flux distribution information and photon angular flux distribution information near the slow positron source generator obtained in Step S2, perform double sampling of energy angle to obtain the energy probability density distribution function f of the incident neutron. n,ig,ia Angular probability density distribution function f n,ia The energy probability density distribution function f of the incident photon g,igg,ia Angular probability density distribution function f g,ia And neutron photon weighting factor;

[0065] In other words, by using the neutron and photon angular flux information on the outer surface of the slow positron source device, the energy probability density distribution function, angular probability density distribution function, and neutron-photon weighting factor of neutrons and photons can be obtained.

[0066] Preferably, step S4 includes: performing double sampling of energy angle based on the neutron angular flux distribution information near the slow positron source generator obtained in step S2.

[0067] First, the neutron flux of multiple groups at various angles is normalized to obtain the energy probability density distribution function f of neutrons at each angle. n,ig,ia :

[0068]

[0069] Then, using the sum of neutron flux at each angle as weights, the angular probability density distribution function f of neutrons is obtained. n,ia :

[0070]

[0071] By using the angular probability density function and considering the non-uniform distribution of particles at the angle, more accurate information about the emitted particles can be obtained.

[0072] Step S4 further includes: performing double sampling of energy angle based on the photon angular flux distribution information near the slow positron source generator obtained in step S2.

[0073] First, the multi-group neutron flux at each angle is normalized to obtain the energy probability density distribution function f of photons at each angle. g,igg,ia :

[0074]

[0075] Then, using the sum of photon flux at each angle as weights, the angular probability density distribution function f of the photons is obtained. g,ia :

[0076]

[0077] By using the angular probability density function and considering the non-uniform distribution of particles at the angle, more accurate information about the emitted particles can be obtained.

[0078] Step S4 further includes: based on the neutron-photon angular flux distribution information near the slow positron source generator obtained in step S2, using the sum of neutron and photon fluxes at each angle as weights, obtaining a neutron-photon weighting factor c, defined as:

[0079]

[0080] In step S4 above, the energy probability density distribution function, the angle probability density distribution function, and the neutron-photon weighting factor are obtained. A full-process coupled simulation is then employed: First, a Monte Carlo calculation of the reactor core is performed to obtain accurate interface information. Multi-group angular flux information is used as the interface information, which differs from common multi-group flux information by adding angle distribution information to overcome the non-uniform angle distribution effect caused by the different relative positions and angles between the slow positron source device and the reactor core. Simultaneously, the full-process coupled simulation accurately considers the precise distribution of neutrons and photons on the outer surface of the slow positron source in the reactor core through dual sampling of flux and angle.

[0081] Step S5: Based on the neutron photon weighting factor obtained in step S4, perform function sampling of particle type, energy, and angle.

[0082] Preferably, step S5 includes:

[0083] If the sampling result is a neutron, then according to the angular probability density distribution function f of the neutron obtained in step S4... n,iaPerform angle sampling. If the sampling result is the ia-th angle, then according to the energy probability density distribution function f of the neutrons at the ia-th angle... n,ig,ia The initial neutron energy is obtained by sampling the neutron energy.

[0084] If the sampling result is a photon, then according to the angular probability density distribution function f of the photon obtained in step S4... g,ia Perform angle sampling. If the sampling result is the ia-th angle, then according to the energy probability density distribution function f of the photon at the ia-th angle... g,igg,ia Initial photon energy is obtained by sampling photon energy.

[0085] Step S6: Based on the Monte Carlo model of the slow positron source generating device constructed in Step S3 and the initial neutron, photon energy, and angle obtained in Step S5, the Monte Carlo method is used to perform neutron-photon-electron coupling transport calculations to obtain the distribution information of slow positrons generated in the slow positron generating device.

[0086] Here, the slow positron distribution information preferably includes the slow positron generation location information, energy information, and emission angle information, and this parameter is used as the interface parameter of the slow positron transport device.

[0087] More preferably, the step S6 is followed by the following step:

[0088] Step S7: Read the electrode shape and voltage parameter information of the slow positron transport device. Based on the position information, energy information and emission angle information of the slow positrons generated in the slow positron generating device obtained in step S6, solve the transport process of each slow positron in sequence through the electromagnetic simulation program of charged particle simulation. If the slow positron is successfully transported to the tail end, it is recorded as a pass; otherwise, it is recorded as a failure.

[0089] Step S8: Based on the slow positron transport results obtained in step S7, count the total number of slow positrons that pass through, and obtain the final slow positron source intensity of the slow positron source device in the research reactor.

[0090] like Figure 3 As shown, the present invention also provides a simulation and prediction system for studying the intensity of slow positron sources in a reactor, which employs the simulation and prediction method for studying the intensity of slow positron sources in a reactor as described above. The simulation and prediction system includes:

[0091] The particle environment solution module for the slow positron source device is used to simulate the complex particle environment within the research reactor and obtain information on the neutron and photon angular flux distribution of the slow positron source device.

[0092] The slow positron generation simulation module is used to build a model of the slow positron source generation device and solve for the coupled transport of neutrons, photons, and electrons to obtain the position, energy, and angle information of the generated slow positrons.

[0093] The slow positron transport simulation module is used to simulate the slow positron transport process and obtain the number of slow positrons that ultimately pass through the slow positron source device.

[0094] The interactive module is used to read the component layout information in the reactor core, the geometric dimensions and material information of different types of components, the state parameter information such as material temperature, burn-up depth, and nucleon density distribution, the location information of the slow positron source device, the geometric dimensions and material information of the slow positron source device, and the electrode shape and voltage parameter information of the slow positron device.

[0095] The interaction module facilitates data transfer between the particle environment solution module of the slow positron source device and the positron generation simulation module, as well as data transfer between the slow positron generation simulation module and the slow positron transport simulation module.

[0096] The present invention also provides an electronic device comprising: a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions being executed by the processor to implement the simulation and prediction method described above for studying the intensity of slow positron sources in a reactor.

[0097] The present invention also provides a readable storage medium on which a program or instruction is stored, which, when executed by a processor, implements the method described above for simulating and predicting the intensity of slow positron sources in a reactor.

[0098] Based on the above description, the present invention is used to study a method for simulating and predicting the intensity of slow positron sources in a reactor, and has the following characteristics:

[0099] I. This invention establishes a Monte Carlo model of the core of a research reactor containing a slow positron source device by directly establishing such a model. Using a neutron-photon coupling transport method, it obtains the precise neutron-photon angular flux distribution near the slow positron source device. By using the angular flux distribution information as an interface parameter, it preserves the energy angle information of the particles, thus providing precise input parameters for the generation of slow positrons.

[0100] II. This invention employs a multi-stage coupled simulation strategy: First, the generation of neutrons and photons in the reactor core is accurately simulated to obtain precise input parameters for the slow positron generation device. Next, neutron-photon-electron coupled transport is solved for the slow positron generation device to obtain accurate slow positron generation information. Finally, based on the slow positron generation information, the final slow positron source intensity is obtained through precise electromagnetic solutions. This multi-stage coupled simulation strategy achieves accurate simulation of the entire lifecycle of slow positron generation and transport, reducing input-output uncertainties in each process and significantly improving prediction accuracy.

[0101] Third, this invention uses multi-particle simulation to consider the coupling effect between neutrons, photons, and electrons, and employs multi-stage coupling to accurately consider the entire life cycle of slow positron generation and transport, ultimately achieving accurate prediction of the intensity of the slow positron source.

[0102] 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.

[0103] 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.

[0104] Some aspects of this application can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The aforementioned hardware or software may be referred to as a "data block," "module," "engine," "unit," "component," or "system." The processor may 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, microcontrollers, microprocessors, or combinations thereof. Furthermore, aspects of this application may manifest as computer products residing in one or more computer-readable media, including computer-readable program code. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes, etc.), optical discs (e.g., compressed CDs, digital multifunction DVDs, etc.), smart cards, and flash memory devices (e.g., cards, sticks, key drives, etc.).

[0105] A computer-readable medium may contain a propagated data signal containing computer program code, for example, on baseband or as part of a carrier wave. This propagated signal may take various forms, including electromagnetic, optical, and so on, or suitable combinations thereof. A computer-readable medium can be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, apparatus, or device to enable communication, propagation, or transmission of a program for use. The program code located on the computer-readable medium can be propagated through any suitable medium, including radio, cable, fiber optic cable, radio frequency signals, or similar media, or any combination of the above media.

[0106] Similarly, it should be noted that, in order to simplify the description of the embodiments disclosed in this application and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of the embodiments of this 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 this application requires more features than those mentioned in the claims. In fact, the embodiments have fewer features than all the features of a single embodiment disclosed above. Some embodiments use numbers describing the number of components or attributes; it should be understood that such numbers used in the description of embodiments are modified in some examples by the terms "approximately," "about," or "generally."

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

Claims

1. A method for simulating and predicting the intensity of slow positron sources in a reactor, characterized in that, The simulation prediction method includes the following steps: S1. Read the arrangement information of components in the reactor core; S2. Based on the layout information obtained in step S1, a Monte Carlo model of the research reactor core containing the slow positron source device is constructed using the 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,ia Photon multigroup angular flux φ igg,ia Information, serving as interface parameters for the slow positron generator; S3. Based on the layout information obtained in step S1 and the information on the neutron-photon multigroup angular flux near the slow positron source generator obtained in step S2, construct a Monte Carlo model of the slow positron source using the solid geometry construction method. S4. Based on the neutron angular flux distribution information and photon angular flux distribution information near the slow positron source generator obtained in step S2, perform double sampling of energy angle to obtain the energy probability density distribution function f of the incident neutron. n,ig,ia Angular probability density distribution function f n,ia The energy probability density distribution function f of the incident photon g,igg,ia Angular probability density distribution function f g,ia and neutron photon weighting factor; S5. Based on the neutron photon weighting factor obtained in step S4, perform function sampling of particle type, function sampling of particle angle based on angle probability density function, and function sampling of particle energy based on energy probability density function. S6. The Monte Carlo method is used to perform neutron-photon-electron coupling transport calculations to obtain the distribution information of slow positrons generated in the slow positron generator.

2. The method for simulating and predicting the intensity of slow positron sources in a reactor as described in claim 1, characterized in that, The information on the arrangement of components in the reactor core studied in step S1 includes: the geometric dimensions and material information of different types of components, state parameter information, location information of the slow positron source device, and the geometric dimensions and material information of the slow positron source device.

3. The method for simulating and predicting the intensity of slow positron sources in a reactor as described in claim 2, characterized in that, The state parameter information includes material temperature, burn-out depth, and nucleon density distribution.

4. The method for simulating and predicting the intensity of slow positron sources in a reactor as described in claim 1, characterized in that, The arrangement information in step S3 includes: the geometric dimensions, volume, and material information of the slow positron source device.

5. The method for simulating and predicting the intensity of slow positron sources in a reactor as described in claim 1, characterized in that, Step S4 includes: performing double sampling of energy angle based on the neutron angular flux distribution information near the slow positron source generator obtained in step S2; Normalizing the neutron flux of multiple groups at various angles yields the energy probability density distribution function f of neutrons at each angle. n,ig,ia : Using the sum of neutron flux at each angle as weights, the angular probability density distribution function f of neutrons is obtained. n,ia :

6. The method for simulating and predicting the intensity of slow positron sources in a reactor as described in claim 1, characterized in that, Step S4 further includes: performing double sampling of energy angle based on the photon angular flux distribution information near the slow positron source generator obtained in step S2; Normalizing the multi-group neutron flux at various angles yields the energy probability density distribution function f of photons at each angle. g,igg,ia : Using the sum of photon flux at each angle as weights, the angular probability density distribution function f of photons is obtained. g,ia :

7. The method for simulating and predicting the intensity of slow positron sources in a reactor as described in claim 1, characterized in that, Step S4 further includes: based on the neutron-photon angular flux distribution information near the slow positron source generator obtained in step S2, using the sum of neutron and photon fluxes at each angle as weights, obtaining a neutron-photon weighting factor c, defined as:

8. The method for simulating and predicting the intensity of slow positron sources in a reactor as described in claim 1, characterized in that, Step S5 includes: If the sampling result is a neutron, then according to the angular probability density distribution function f of the neutron obtained in step S4... n,ia Perform angle sampling. If the sampling result is the ia-th angle, then according to the energy probability density distribution function f of the neutrons at the ia-th angle... n,ig,ia The initial neutron energy is obtained by sampling the neutron energy. If the sampling result is a photon, then according to the angular probability density distribution function f of the photon obtained in step S4... g,ia Perform angle sampling. If the sampling result is the ia-th angle, then according to the energy probability density distribution function f of the photon at the ia-th angle... g,igg,ia Initial photon energy is obtained by sampling photon energy.

9. The method for simulating and predicting the intensity of slow positron sources in a reactor as described in claim 1, characterized in that, Following step S6, the following steps are also included: S7. Read the electrode shape and voltage parameter information of the slow positron transport device. Based on the position information, energy information and emission angle information of the slow positrons generated in the slow positron generating device obtained in step S6, solve the transport process of each slow positron in sequence through the electromagnetic simulation program of charged particle simulation. If the slow positron is successfully transported to the tail end, it is recorded as a pass; otherwise, it is recorded as a failure. S8. Based on the slow positron transport results obtained in step S7, count the total number of slow positrons that pass through, and obtain the final slow positron source intensity of the slow positron source device in the research reactor.

10. A simulation and prediction system for studying the intensity of slow positron sources in a reactor, characterized in that, The simulation prediction system employs the simulation prediction method for studying the intensity of slow positron sources in a reactor as described in any one of claims 1-9, and the simulation prediction system includes: The particle environment solution module for the slow positron source device is used to simulate the complex particle environment inside the research reactor and obtain the neutron and photon angular flux distribution information of the slow positron source device. The slow positron generation simulation module is used to build a model of the slow positron source generation device and solve for the coupled transport of neutrons, photons, and electrons to obtain the position, energy, and angle information of the generated slow positrons. The slow positron transport simulation module is used to simulate the slow positron transport process and obtain the number of slow positrons that finally pass through the slow positron source device. The interaction module is used to read the component layout information in the reactor core, and to perform data transfer between the particle environment solution module of the slow positron source device and the positron generation simulation module, and between the slow positron generation simulation module and the slow positron transport simulation module.

11. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing programs or instructions that can run on the processor, the programs or instructions being executed by the processor to implement the simulation and prediction method for the intensity of slow positron sources in a reactor as described in any one of claims 1-9.

12. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions, which, when executed by a processor, implement the method for simulating and predicting the intensity of slow positron sources in a reactor as described in any one of claims 1-9.

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