Modular computing system and method for high-purity germanium detector

Abstract

The embodiment of the invention relates to the technical field of high-purity germanium detectors, and discloses a modular computing system and method of a high-purity germanium detector. According to the characteristics of a Monte Carlo input file, the input file is divided into a detector module, a sample rack module, a sample container module, a sample source module and a calculation module; compiling and freely combining codes of each module to generate a Monte Carlo calculation file; wherein each module comprises a detector module used for defining and modifying a geometric model and physical attributes of the high-purity germanium detector; the sample holder module is used for defining and modifying a geometric model and physical attributes of a sample holder; the sample container module is used for defining and modifying a geometric model and physical attributes of a sample container; the sample source module is used for defining and modifying a geometric model and physical attributes of a radioactive source; and the calculation module is used for generating and calculating an efficiency curve of the high-purity germanium detector according to the selected module, and outputting a related calculation result. The technical problem of complex Monte Carlo file design of the high-purity germanium detector can be solved at least.

Description

Technical Field

[0001] This application relates to the technical field of high-purity germanium detectors, and particularly to a modular computing system and method for high-purity germanium detectors. Background Art

[0002] High-purity germanium (HPGe) detectors are important radiation detectors widely used in the measurement of γ-rays and X-rays. Due to their high energy resolution, high detection efficiency, and wide range of ray detection (from a few keV to a few MeV), HPGe detectors have been widely used in many fields such as nuclear physics, radiation safety, environmental monitoring, medical imaging, and material analysis. Especially in precise radiation energy measurement and material composition analysis, HPGe detectors are often regarded as the preferred equipment.

[0003] During the use of high-purity germanium detectors, the detection efficiency is a crucial technical indicator, which directly affects the accuracy of physical quantity measurement results. The detection efficiency refers to the ability of the detector to effectively detect the rays emitted by the radiation source and convert them into electrical signals. To improve the reliability and accuracy of measurement results, accurately calibrating the detection efficiency has become a key step in the performance evaluation of HPGe detectors.

[0004] Currently, there are mainly two common efficiency calibration methods: the experimental calibration method and the passive efficiency calibration method based on the Monte Carlo (MC) method. The experimental calibration method usually requires the use of prepared standard sources for experimental measurement, and the detector efficiency is calibrated according to the actual measurement results under different conditions. However, this method is complex to operate, time-consuming, and requires high-quality standard sources, and it cannot flexibly handle the efficiency evaluation of different detection environments or unknown radiation sources.

[0005] In contrast, the Monte Carlo passive efficiency calibration method uses computer simulation technology. Based on the geometric model and physical parameters of the high-purity germanium detector, the interaction between rays and the detector is simulated by the Monte Carlo method, and then the detection efficiency is calculated. This method can not only overcome the limitations of the experimental method but also perform efficient detector efficiency evaluation without a standard source. With the popularization of the Monte Carlo passive efficiency calibration method, the efficiency calibration of HPGe detectors has become more convenient, fast, and accurate.

[0006] However, despite the many advantages of the Monte Carlo method, its calculation process is relatively complex. The calculation files need to be written manually and contain a large number of parameters such as geometric models, physical material properties, and radiation source information. Each detector, sample rack, sample container, radiation source, etc. corresponds to a complete calculation file, and the code logic in it needs to be accurate. A slight error may lead to deviations in the simulation results. Since each model requires a separate file and these files are interrelated, manually writing and maintaining these calculation files is time-consuming and laborious, and prone to human errors. Therefore, how to generate and manage these calculation files efficiently and accurately has become a major challenge in the current application of the Monte Carlo method. Summary of the Invention

[0007] An object of the present application is to provide a modular calculation system and method for high-purity germanium detectors to solve the technical problem of the complex design of Monte Carlo files for high-purity germanium detectors.

[0008] To achieve the above object, some embodiments of the present application provide the following aspects:

[0009] In a first aspect, some embodiments of the present application further provide a modular calculation system for high-purity germanium detectors, which includes dividing the input file into a detector module, a sample rack module, a sample container module, a sample source module, and a calculation module according to the characteristics of the Monte Carlo input file; writing and freely combining the codes of each module to generate a Monte Carlo calculation file; wherein, each module includes: a detector module for defining and modifying the geometric model and physical properties of the high-purity germanium detector; a sample rack module for defining and modifying the geometric model and physical properties of the sample rack; a sample container module for defining and modifying the geometric model and physical properties of the sample container; a sample source module for defining and modifying the geometric model and physical properties of the radiation source; a calculation module for generating and calculating the efficiency curve of the high-purity germanium detector and outputting relevant calculation results according to the selected modules.

[0010] In a second aspect, some embodiments of the present application further provide a modular calculation method for high-purity germanium detectors, which includes selecting and configuring a detector module, a sample rack module, a sample container module, a sample source module, and a calculation module according to the application requirements of the high-purity germanium detector, and setting corresponding parameters according to the predetermined geometric model and physical properties; freely combining the parameters of each module to generate a Monte Carlo calculation file, and generating a complete calculation file by writing the codes of each module to combine the modular parameters; in the calculation module, running the calculation and outputting the efficiency curve and relevant calculation results of the high-purity germanium detector according to the Monte Carlo calculation file and loading the energy test file.

[0011] In a third aspect, some embodiments of the present application further provide an electronic device, which includes: one or more processors; and a memory storing computer program instructions, and when the computer program instructions are executed, the processors perform the steps of the method as described above.

[0012] In a fourth aspect, some embodiments of the present application further provide a computer-readable medium, on which computer program instructions are stored, and the computer program instructions can be executed by a processor to implement the method as described above.

[0013] Compared with the related art, in the solution provided by the embodiments of the present application, based on the modular structure of the Monte Carlo calculation system, by modularizing detectors, sample holders, sample containers, sample sources, etc., users can conveniently define and modify the parameters of each module, and then automatically generate the efficiency calculation file of the high-purity germanium detector through module combination, thereby reducing the complexity of manually writing code and the possibility of errors. This method not only simplifies the implementation process of Monte Carlo simulation, but also improves the accuracy and efficiency of the simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] One or more embodiments are exemplarily illustrated by the pictures in the corresponding drawings. These exemplary illustrations do not limit the embodiments. Elements with the same reference numerals in the drawings are represented as similar elements, unless otherwise stated, and the drawings in the drawings do not constitute a proportional limitation.

[0015] Figure 1 FIG. is a schematic flow chart of a modular calculation system for a high-purity germanium detector provided according to an embodiment of the present application;

[0016] Figure 2 FIG. is a schematic flow chart of a modular calculation method for a high-purity germanium detector provided according to an embodiment of the present application;

[0017] Figure 3 FIG. is a schematic structural diagram of an exemplary electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art without making creative efforts based on the embodiments of the present application belong to the scope of protection of the present application.

[0019] First Embodiment

[0020] The first embodiment of this application relates to a modular computing system for a high-purity germanium detector. The system may include:

[0021] According to the characteristics of the Monte Carlo input file, the input file is divided into a detector module, a sample rack module, a sample container module, a sample source module, and a calculation module; the codes for each module are written and freely combined to generate a Monte Carlo calculation file;

[0022] Among them, each module includes:

[0023] A detector module, which is used to define and modify the geometric model and physical properties of the high-purity germanium detector;

[0024] A sample rack module, which is used to define and modify the geometric model and physical properties of the sample rack;

[0025] A sample container module, which is used to define and modify the geometric model and physical properties of the sample container;

[0026] A sample source module, which is used to define and modify the geometric model and physical properties of the radiation source;

[0027] A calculation module, which is used to generate and calculate the efficiency curve of the high-purity germanium detector according to the selected modules and output relevant calculation results.

[0028] The system divides and combines the various calculation tasks in the Monte Carlo calculation file in a modular manner, which can simplify the calculation process of the high-purity germanium detector efficiency calibration and improve the accuracy and flexibility of the calculation.

[0029] The detector module is used to define and modify the geometric model and physical properties of the high-purity germanium detector. Specifically, the detector module can set various parameters of the detector, such as the name, shape, size, material type, crystal thickness, etc. of the detector. Through this module, the user can modify the geometric structure of the detector according to different experimental requirements, such as changing the height, radius, end window thickness, and bracket of the detector, so as to accurately model different types of detectors. This module plays a crucial role in the calculation. It ensures that the detector model used in the calculation matches the actual detector, guaranteeing the reliability of the simulation results. It provides a detailed geometric model and physical properties of the high-purity germanium detector, enabling the system to accurately simulate the response of the detector and ensuring that the simulation results can be consistent with the actual detector, avoiding unnecessary errors.

[0030] The sample holder module is used to define and modify the geometric model and physical properties of the sample holder. The design of the sample holder directly affects the way the samples are placed and the working efficiency of the detector. Through this module, users can set the parameters of the sample holder, such as the height of the support, outer radius, wall thickness, hole radius, and the material of the support, etc. The coordination between the geometric parameters of the sample holder and the sample container is very important, which affects the distance between the radiation source and the detector, and thus determines the response efficiency of the detector. By adjusting the geometric structure of the sample holder, the influence of different sample placement methods on the detection efficiency can be flexibly simulated, providing support for improving the calculation accuracy of the efficiency.

[0031] The sample container module is used to define and modify the geometric model and physical properties of the sample container. The sample container is usually used to hold the samples to be measured, and its geometric shape and material will affect the propagation path of the rays and the detector's response to the rays. This module allows users to adjust the structural parameters of the sample container according to the experimental requirements, such as the radius, thickness, material of the container, etc. By accurately setting the geometric model and physical properties of the sample container, the system can simulate the influence of the sample container on the radiation of the radiation source. The design of the sample container has an important impact on the interaction between the radiation source and the detector. An accurate container model can help the system better simulate the radiation interaction between the sample and the detector, thereby improving the accuracy of the detection efficiency calculation.

[0032] The radiation source module is used to define and modify the geometric model and physical properties of the radiation source. This module allows users to set different types of radiation sources according to different experimental conditions, such as point sources, cylindrical sources, or Marinelli beaker sources, etc. The parameters of the radiation source include the height of the source, material, detector distance, etc. By accurately setting the geometric model and physical properties of the radiation source, the system can accurately simulate the radiation characteristics of the rays, thereby providing reliable data support for the subsequent detection efficiency calculation. The accurate modeling of the radiation source is the key to the efficiency calculation because it directly determines the interaction situation between the rays and the detector. By defining different types of radiation source models, the system can flexibly simulate the radiation source situations under various experimental conditions, ensuring that the calculation results can truly reflect the influence of the radiation source on the detector.

[0033] The calculation module is the core module of the entire system, which is used to generate and calculate the efficiency curve of the high-purity germanium detector according to the parameters selected by the user for each module, and output the relevant calculation results. The calculation module combines all the parameters set by the detector module, sample holder module, sample container module, and radiation source module, and uses the Monte Carlo method to simulate the ray propagation and detection process, and calculates the efficiency curve of the detector. The efficiency curve is an important indicator for evaluating the performance of the detector, which can help researchers evaluate the efficiency of different design schemes and provide an important basis for subsequent experiments and data analysis.

[0034] It is not difficult to find that, compared with the related technologies, the solution provided in the embodiments of the present application adopts a modular design method, which allows users to flexibly set and combine different modules, greatly simplifies the writing process of Monte Carlo calculation files, and improves the accuracy and operability of efficiency calibration calculation. In this way, the system can not only improve the calculation efficiency, reduce human errors, but also meet different experimental requirements, and is widely applicable to the field of high-purity germanium detector performance evaluation.

[0035] Second Embodiment

[0036] The second embodiment of the present application relates to a modular calculation system for a high-purity germanium detector. The second implementation is an improvement based on the first embodiment. The specific improvement lies in:

[0037] As Figure 1 shown, the modular calculation system of the high-purity germanium (HPGe) detector realizes the flexible calculation and optimization of the efficiency of the high-purity germanium detector by dividing the Monte Carlo calculation file into different modules. Each module can be independently set according to specific requirements, and the codes can be freely combined, and finally a Monte Carlo calculation file is generated, thereby improving the calculation accuracy and efficiency. It mainly includes the following modules: detector module, sample rack module, sample container module, sample source module and calculation module. Each module has an independent function, and the parameters can be set through a graphical user interface or code configuration, and combined to generate a complete calculation file.

[0038] It is not difficult to find that in this embodiment, by optimizing the system interface and module configuration, more refined operation options are provided, enabling users to independently set the parameters of the detector, sample rack, sample container and sample source, and flexibly combine these modules to generate a Monte Carlo calculation file. In addition, the system supports operations such as creating, modifying, deleting and viewing each module, ensuring high customizability and precise control. Through the automated function of the calculation module, users can efficiently calculate the efficiency curve of the detector and optimize it by repeatedly adjusting the parameters. This technology not only improves the calculation accuracy and efficiency, but also greatly simplifies the user operation process, making the design and performance optimization of high-purity germanium detectors more intuitive and convenient.

[0039] It is worth mentioning that each module involved in this implementation is a logical module. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of the present application, units that are not closely related to solving the technical problems proposed in the present application are not introduced in this implementation, but this does not mean that there are no other units in this implementation.

[0040] Third Embodiment

[0041] The third embodiment of this application relates to a modular calculation method for a high-purity germanium detector. Applied to the system of the above embodiment, as Figure 2 shown, the method includes:

[0042] S101. According to the application requirements of the high-purity germanium detector, select and configure the detector module, sample rack module, sample container module, sample source module, and calculation module, and set corresponding parameters according to a predetermined geometric model and physical properties;

[0043] S102. Generate a Monte Carlo calculation file by freely combining the parameters of each module. Through the code writing of each module, combine the modular parameters to generate a complete calculation file;

[0044] S103. In the calculation module, according to the Monte Carlo calculation file and load the energy test file, run the calculation and output the efficiency curve and related calculation results of the high-purity germanium detector.

[0045] By freely combining the parameters of each module, generating a Monte Carlo calculation file and performing calculations, the efficiency curve and related calculation results of the high-purity germanium detector can be calculated efficiently. The following is the specific implementation process of this method:

[0046] For step S101 of selecting and configuring each module, according to the application requirements of the high-purity germanium detector, the user selects the required modules through the system interface, including: Detector module: The user selects the geometric model and physical properties of the detector according to specific requirements, such as the shape, size, material, etc. of the detector; Sample rack module: Select and configure the geometric shape, size, material, etc. of the sample rack; Sample container module: The user selects a suitable sample container according to the application requirements, such as a sample box, Marinelli beaker, etc., and sets the geometric and physical parameters of the container; Sample source module: Select different sample source models, such as point source, cylindrical source or Marinelli beaker source, and configure the specific parameters of the source, such as the size, position and material of the source, etc.; Calculation module: Configure the parameters for calculating the detector efficiency, select relevant test files and energy data sets to ensure the accuracy of the calculation process. In this step, the user can configure each module through a graphical interface or code, input the required physical parameters, and set different geometric and physical characteristics in each module to meet specific application scenarios.

[0047] For the step of freely combining module parameters to generate a calculation file in S102, the user adjusts the parameters of each module according to requirements and freely combines these parameters. The system will automatically integrate the settings of each module to generate a Monte Carlo calculation file that meets the requirements. The parameters of each module are automatically combined in the background. According to the set geometric shape, physical properties and other information, modular Monte Carlo code is generated. The code of each module generates a specific calculation file through a preset template. The content of the file includes the geometric models and physical parameter information of various parts such as detectors, sample racks, sample containers, and sample sources. Through the system interface, the user can modify, save or delete the parameter settings of each module at any time and regenerate the corresponding calculation file.

[0048] For the step of loading an energy file and running the calculation in S103, in the calculation module, the user starts the actual calculation by selecting the generated Monte Carlo calculation file and loading the energy test file. The energy test file contains the energy set of the radiation source, such as the energy points of gamma rays. The specific process includes: selecting the required energy file, which contains data at different energy points (such as 1332 keV, etc.) and loading it into the system. The system starts the simulation calculation of the high-purity germanium detector efficiency based on the loaded energy data and the generated Monte Carlo calculation file. The calculation module will automatically run the calculation according to the preset physical model, simulate the response of the detector and output the efficiency curve. The system displays the efficiency curve of the detector according to the calculation results and outputs relevant calculation results, such as relative error and simulated efficiency, etc.

[0049] For example, the user selects the detector module, sample rack module and sample source module according to a specific application scenario. During the configuration process, the user sets the geometric size and material of the detector, the height and material of the sample rack, and the radioactive characteristics and geometric position of the sample source. Through automated module combination, the system generates a complete Monte Carlo calculation file. Then, the user loads the corresponding energy test file and runs the calculation module. Finally, the efficiency curve of the high-purity germanium detector is obtained. By analyzing the results, the user can further optimize the parameter settings of the system to ensure that the detector can achieve the best performance.

[0050] It is not difficult to find that in this embodiment, the efficiency calculation process of the high-purity germanium detector can be greatly simplified, and the calculation accuracy and efficiency are improved. At the same time, the modular design enables each part to be flexibly configured to meet the requirements of different application scenarios. The user can adjust the parameters of each module according to specific needs, so as to achieve precise control and optimization of the detector performance.

[0051] The step division of the above various methods is only for clear description. When implemented, they can be combined into one step or some steps can be split into multiple steps. As long as the same logical relationship is included, it is within the protection scope of this application. Making insignificant modifications to the algorithm or process or introducing insignificant designs, but without changing the core design of the algorithm and process, are all within the protection scope of this application.

[0052] In addition, some embodiments of this application also provide an electronic device. The electronic device can be various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and so on. The electronic device can also be various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices, and other similar computing devices.

[0053] The electronic device includes: one or more processors; and a memory storing computer program instructions, which when executed cause the processors to execute the steps of the method provided in any one or more of the above embodiments. Figure 3 An exemplary structural diagram of the electronic device is disclosed. As Figure 3 shown, the electronic device includes: one or more processors 1101, a memory 1102, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. Each component is interconnected using different buses and can be installed on a common motherboard or in other ways as needed. The processor can process instructions executed within the electronic device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some other embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (such as an array of servers, a set of blade servers, or a multi-processor system). Among them, the components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of this application described and / or claimed herein.

[0054] The electronic device may further include: an input device 1103 and an output device 1104. The processor 1101, the memory 1102, the input device 1103, and the output device 1104 can be connected by a bus or other means, Figure 3 taking connection by bus as an example.

[0055] The input device 1103 can receive input digital or character information and generate key signal inputs related to the user settings and function controls of the electronic device, such as input devices like touchscreens, keypads, mice, trackpads, touchpads, pointing sticks, one or more mouse buttons, trackballs, joysticks, etc. The output device 1104 can include display devices, auxiliary lighting devices (e.g., LEDs), and tactile feedback devices (e.g., vibration motors), etc. The display device can include, but is not limited to, liquid crystal displays (LCDs), light-emitting diode (LED) displays, and plasma displays. In some embodiments, the display device can be a touchscreen.

[0056] To provide interaction with the user, the electronic device can be a computer. The computer has: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and the input from the user can be received in any form (including sound input, voice input, or tactile input).

[0057] In the embodiments of this application, a computer program / instructions is stored on a computer-readable medium. When the computer program / instructions are executed by a processor, the steps of the method provided in any one or more of the above embodiments are implemented. The computer-readable medium can be included in the electronic device described in the above embodiments; or it can exist separately without being assembled into the device. The above computer-readable medium carries one or more computer-readable instructions.

[0058] The memory 1102 can be used as a non-transitory computer-readable storage medium and can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules. The processor 1101 executes various functional applications and data processing of the server by running the non-transitory software programs, instructions, and modules stored in the memory 1102, so as to implement the program instructions / modules corresponding to the method provided in any one or more of the above embodiments of this application.

[0059] The memory 1102 may include a program storage area and a data storage area. The program storage area may store an operating system and application programs required for at least one function. The data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 1102 may include a high-speed random access memory and may also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory 1102 may optionally include a memory remotely disposed relative to the processor 1101, and these remote memories may be connected to the electronic device through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0060] It should be noted that the computer-readable medium described in this application may be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this application, the computer-readable medium may be any tangible medium that contains or stores a program, and the program may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0061] The computer-readable medium includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information may be computer-readable instructions, data structures, program modules, or other data. Examples of the computer's storage medium include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassette tapes, magnetic disk storage, or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0062] Computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0063] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. For example, an application-specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device can be used. In some embodiments, the software program of this application can be executed by a processor to implement the above steps or functions. Similarly, the software program of this application (including related data structures) can be stored in a computer-readable recording medium, for example, a RAM memory, a magnetic or optical drive, or a floppy disk and similar devices. In addition, some steps or functions of this application can be implemented by hardware, for example, as a circuit that cooperates with a processor to execute each step or function.

[0064] The computer program product provided by the embodiments of this application includes one or more computer programs / instructions. When the computer programs / instructions are executed by a processor, they entirely or partially generate the processes or functions described in the embodiments of this application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access, or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)), etc.

[0065] The flowcharts or block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of devices, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0066] The scope of the present application is defined by the appended claims rather than the above description. Therefore, all changes that fall within the meaning and scope of the equivalent elements of the claims are intended to be included in the present application. Any reference numerals in the claims should not be construed as limiting the claims involved. In addition, it is obvious that the term "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. The multiple elements or devices stated in the apparatus claims may also be implemented by one element or device through software or hardware. The terms "first", "second", etc. are only used for descriptive distinction and do not represent any specific order, nor can they be construed as indicating or implying relative importance.

[0067] As described above, the above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily mention changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims, and the above embodiments should be regarded as exemplary and non-limiting.

Claims

1. A modular computing system for a high purity germanium detector, characterized in that: The system comprises: According to the characteristics of the Monte Carlo input file, the input file is divided into a detector module, a sample rack module, a sample container module, a sample source module and a calculation module; the code of each module is written and freely combined to generate a Monte Carlo calculation file; Wherein, each module includes: Detector module, used to define and modify the geometric model and physical properties of high purity germanium detectors; Sample holder module, used to define and modify the geometric model and physical properties of the sample holder; Sample container module, used to define and modify the geometric model and physical properties of the sample container; Sample source module, used to define and modify the geometric model and physical properties of the radiation source; The calculation module is used to generate and calculate the efficiency curve of the high-purity germanium detector according to the selected module and output relevant calculation results.

2. The system according to claim 1, characterized in that The detector module comprises: The detector overall unit is used to set the detector overall parameters; Detector crystal unit, used to set detector crystal parameters; Crystal chamber unit, used to set crystal chamber parameters.

3. The system according to claim 1, characterized in that The sample rack module comprises: The basic parameters of the sample rack include name, bracket height, bracket top thickness, bracket outer radius, bracket wall thickness, bracket hole radius and bracket material.

4. The system according to claim 1, characterized in that The sample container module comprises: A sample box model, wherein basic parameters of the sample box model include name, sample box radius, sample box side thickness, sample box detector distance, sample box bottom thickness and sample box material; A Marin Cup model, wherein the basic parameters of the Marin Cup model include name, Marin Cup outer radius, Marin Cup inner radius, Marin Cup upper ground thickness, Marin Cup inner wall thickness, Marin Cup hole depth, Marin Cup lower bottom thickness and Marin Cup material.

5. The system according to claim 1, characterized in that The sample source module comprises: Point source, the basic parameters of the point source include name and point source detector distance; A cylindrical source, wherein basic parameters of the cylindrical source include name, source height, source material and precautions; Malin Cup source, the basic parameters of the Malin Cup source include name, source height, source material and precautions.

6. The system according to claim 1, characterized in that The calculation module comprises: The options of the corresponding modules and the energy test files are selected through the interface; the efficiency curve of the high-purity germanium detector is generated and calculated according to the parameters set by the detector module, the sample rack module, the sample container module, the sample source module and the selected energy test file, and the relevant calculation results are output; the calculation module is combined with the SIMMAX high-purity germanium software to generate the efficiency curve.

7. The system according to any one of claims 1 to 6, characterized in that: The system further comprises: Energy module, which is the energy set of the radiation source during simulation calculation; Material module, wherein the material module is the material used when constructing the model.

8. A modular calculation method for a high purity germanium detector, applied to the system according to any one of claims 1 to 7, characterized in that: The method comprises: According to the application requirements of high-purity germanium detectors, the detector module, sample rack module, sample container module, sample source module and calculation module are selected and configured, and the corresponding parameters are set according to the predetermined geometric model and physical properties; Generate Monte Carlo calculation files for the free combination of each module parameter, and generate complete calculation files by combining modular parameters through code writing of each module; In the calculation module, according to the Monte Carlo calculation file and the energy test file, the calculation is run and the efficiency curve and related calculation results of the high-purity germanium detector are output.

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