CN117236081B

CN117236081B - Meng Ka transport simulation method and device based on CAD and CSG mixed geometry

Info

Publication number: CN117236081B
Application number: CN202311518720.2A
Authority: CN
Inventors: 王侃; 申鹏飞; 刘冠洋
Original assignee: Tsinghua University
Current assignee: Tsinghua University
Priority date: 2023-11-15
Filing date: 2023-11-15
Publication date: 2024-01-30
Anticipated expiration: 2043-11-15
Also published as: CN117236081A

Abstract

The application provides a Meng Ka transportation simulation method and device based on CAD and CSG mixed geometry, and relates to the technical field of reactor physical calculation, wherein the method comprises the following steps: establishing a mixed geometric input model, and analyzing and converting the mixed geometric input model into a Meng Ka algorithm built-in mixed geometric model based on the selected particle transport mode; establishing a mixed transportation frame, wherein the mixed transportation frame comprises a first transportation mode and a second transportation mode, the first transportation mode is CAD and CSG geometric nesting transportation, and the second transportation mode is CAD geometric filling-in CSG geometric transportation; performing particle transport simulation based on the established mixed transport frame and the converted mixed geometric model; and acquiring simulation data in the transportation simulation process, carrying out statistics based on the simulation data, and reducing statistical errors in the statistics in a variance reduction mode to obtain a final simulation result. The application adopting the scheme realizes Monte Carlo transport calculation under the CAD and CSG mixed geometric model.

Description

Meng Ka transport simulation method and device based on CAD and CSG mixed geometry

Technical Field

The application relates to the technical field of reactor physical computing, in particular to a Meng Ka transportation simulation method and device based on CAD and CSG mixed geometry.

Background

The monte carlo delivery procedure is one of the common tools in the field of reactor physics calculations. Physical modeling of the reactor core and particle transport calculations can be performed using a monte carlo transport program. In the physical modeling of a reactor, current monte carlo delivery procedures widely use either a build entity geometry (Constructive Solid Geometry, CSG for short) or CAD (Computer Aided Design) for geometric modeling. Wherein, the CSG-based geometric modeling mode cannot effectively construct a complex geometric structure comprising spline lines and spline faces; the CAD-based modeling transport is inefficient and limited in the number of geometries. There is therefore a need for a Meng Ka transport method for CSG and CAD hybrid geometries that effectively addresses the problem of incompatibility of the two.

Disclosure of Invention

The present application aims to solve, at least to some extent, one of the technical problems in the related art.

Therefore, a first object of the present application is to provide a Meng Ka transportation simulation method based on CAD and CSG hybrid geometry, which solves the technical problem of mutual incompatibility of CAD and CSG in the existing method, realizes Meng Ka transportation simulation based on CSG and CAD hybrid geometry, and effectively improves Meng Ka transportation efficiency under complex geometric model.

A second object of the present application is to propose a Meng Ka transportation simulator based on CAD and CSG hybrid geometry.

To achieve the above object, an embodiment of the first aspect of the present application provides a Meng Ka transportation simulation method based on CAD and CSG hybrid geometry, including: establishing a mixed geometric input model, and analyzing and converting the mixed geometric input model into a Meng Ka algorithm built-in mixed geometric model based on the selected particle transport mode; establishing a mixed transportation frame, wherein the mixed transportation frame comprises a first transportation mode and a second transportation mode, the first transportation mode is CAD and CSG geometric nesting transportation, and the second transportation mode is CAD geometric filling-in CSG geometric transportation; performing particle transport simulation based on the established mixed transport frame and the converted mixed geometric model; and acquiring simulation data in the transportation simulation process, carrying out statistics based on the simulation data, and reducing statistical errors in the statistics in a variance reduction mode to obtain a final simulation result.

According to the Meng Ka transportation simulation method based on the CAD and CSG mixed geometry, after a CAD and CSG mixed geometry frame is established and particle tracking and transportation flow is regulated, a mixed geometry input model can be converted into a Meng Ka algorithm built-in mixed geometry model in a critical mode and/or fixed source mode calculation, during particle transportation simulation, a ray tracing method-based flow is adopted, a related function in the mixed transportation frame is called, and steps of particle-to-surface distance, particle movement track length, search of adjacent grid cells after particle surface penetration and the like are circularly calculated, so that transportation simulation under the mixed geometry is realized; in addition to transport simulation, various physical reactions between particles and other particles such as target targets are simulated; and the statistics is carried out under the mixed geometric structure, the statistical error in the statistics is reduced, and the confidence of the calculation result is improved. According to the processing scheme, the Monte Carlo transport calculation is carried out under the CAD and CSG mixed geometric model, and the capability of efficiently processing the mixed geometric model is achieved; the source description of various forms is supported, and various neutron physical information can be counted; the variance reduction function is supported, and the high-efficiency parallel computation is supported.

Optionally, in one embodiment of the present application, the hybrid geometry input model includes a CAD and a CSG-described geometry model, the CAD-described geometry model including material, boundary conditions, temperature, and cell importance, and the CSG-described geometry model including material, boundary conditions, temperature, cell importance.

Optionally, in one embodiment of the present application, when the hybrid transportation frame is the first transportation mode, the hybrid transportation frame is expressed as:

respectively constructing a full space by using CAD and CSG, wherein the CAD geometric filling area has visual characteristics;

marking a CAD geometric nesting transportation space through a CSG geometric description file;

performing a transportation simulation of the Monte Care through the hybrid transportation frame, comprising:

and positioning the CAD geometric part by using the global coordinates in transportation, and updating the global and local coordinates simultaneously when the CSG geometric transportation is performed.

Optionally, in one embodiment of the present application, when the hybrid transportation frame is the second transportation mode, the hybrid transportation frame is expressed as:

based on a hierarchical filling structure of the CSG geometry, using a single CAD description file, and filling CAD Universe calibrated by the CSG geometry;

and positioning the CAD geometric part by using the local coordinates in the transportation, and updating the global and local coordinates simultaneously when the CSG geometric transportation is performed.

Optionally, in one embodiment of the present application, performing particle transport simulation based on the established mixed transport frame and the converted mixed geometric model includes:

in a particle tracking process of CSG level filling, carrying out transport simulation by using different CAD transport positioning schemes according to labeling of CAD space;

a flow based on a ray tracing method is adopted, a related function in a mixed transport frame is called, and a particle simulation step is circulated to realize transport simulation under mixed geometry, wherein the mode particle simulation step comprises the steps of calculating a particle-to-surface distance, calculating a particle motion track length and searching adjacent cells after the particles pass through the surface;

the method further comprises the steps of:

in addition to transport simulation, various types of physical reactions of the particles with other particles are simulated.

To achieve the above object, an embodiment of the second aspect of the present application provides a Meng Ka transportation simulation device based on CAD and CSG hybrid geometry, which includes a model building module, a frame building module, a simulation module, and a data statistics module, wherein,

the model building module is used for building a mixed geometric input model and analyzing and converting the mode mixed geometric input model into a Meng Ka algorithm built-in mixed geometric model based on the selected particle transport mode;

the frame building module is used for building a mixed transportation frame, wherein the mixed transportation frame is in a first transportation mode or a second transportation mode, the first transportation mode is the nested transportation of CAD and CSG geometry, and the second transportation mode is the transportation of CAD geometry filling in the CSG geometry;

the simulation module is used for carrying out particle transport simulation based on the established mixed transport frame and the converted mixed geometric model;

the data statistics module is used for collecting simulation data in the transportation simulation process, carrying out statistics based on the simulation data, and reducing statistical errors in the statistics in a variance reduction mode to obtain a final simulation result.

the method further comprises the steps of:

Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.

Drawings

The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

fig. 1 is a schematic flow chart of a Meng Ka transportation simulation method based on CAD and CSG hybrid geometry according to an embodiment of the present disclosure;

FIG. 2 is a diagram of an example CAD and CSG geometric nesting transport according to an embodiment of the present application;

FIG. 3 is a diagram of a CAD and CSG geometry nesting transport framework of an embodiment of the present application;

FIG. 4 is a CAD-filled CAD transport frame diagram of embodiments of the present application;

FIG. 5 is a diagram illustrating an example of a hybrid geometry input model construction in accordance with an embodiment of the present application;

FIG. 6 is a statistical chart of fuel pellet mixing geometry model parameters according to an embodiment of the present application;

FIG. 7 is a graph of flux statistics for a fuel pellet hybrid geometry model in accordance with an embodiment of the present application;

FIG. 8 is an exemplary diagram of a hybrid geometry input model in accordance with an embodiment of the present application;

fig. 9 is a schematic structural diagram of a Meng Ka transportation simulator based on CAD and CSG hybrid geometry according to an embodiment of the present application.

Detailed Description

Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application.

A Meng Ka transport simulation method and apparatus based on CAD and CSG hybrid geometry according to embodiments of the present application are described below with reference to the accompanying drawings.

Fig. 1 is a schematic flow chart of a Meng Ka transportation simulation method based on CAD and CSG hybrid geometry according to an embodiment of the present application.

As shown in fig. 1, the Meng Ka transport simulation method based on CAD and CSG hybrid geometry includes the steps of:

step 101, establishing a mixed geometric input model, and analyzing and converting the mode mixed geometric input model into a mixed geometric model built in Meng Ka algorithm based on a selected particle transport mode;

102, establishing a mixed transportation frame, wherein the mixed transportation frame comprises a first transportation mode and a second transportation mode, the first transportation mode is CAD and CSG geometric nested transportation, and the second transportation mode is CAD geometric filling-in CSG geometric transportation;

step 103, carrying out particle transport simulation based on the established mixed transport frame and the converted mixed geometric model;

and 104, collecting simulation data in the transportation simulation process, carrying out statistics based on the simulation data, and reducing statistical errors in the statistics in a variance reduction mode to obtain a final simulation result.

In this embodiment, statistics under a mixed geometry structure is supported, and variance reduction is used to reduce statistical errors during statistics and improve confidence of calculation results.

Further, in the embodiment of the present application, the hybrid geometry input model includes a geometry model of CAD and CSG descriptions, the geometry model of CAD descriptions includes materials, boundary conditions, temperatures, and cell importance, and the geometry model of CSG descriptions includes materials, boundary conditions, temperatures, and cell importance.

Further, in the embodiment of the application, when the hybrid transportation frame is in the first transportation mode, considering the characteristics of the hybrid transportation frame and the hybrid transportation frame, the CAD and CSG geometry nested transportation frame is formed by using CAD and CSG geometry to respectively construct a full space. The CAD geometric filling area reserves the characteristic of 'what you see is what you get', and is stored in the same file; CSG geometry description files should specify the space for CAD geometry nested transport. In the practical implementation level, the global coordinates in transportation are used for positioning the CAD geometric part, and the global and local coordinates are updated simultaneously during the transportation of the CSG geometric part, so that the constructed hybrid transportation frame and framework are shown in fig. 2 and 3.

Further, in the embodiment of the application, when the hybrid transportation frame is in the second transportation mode, the functions of CSG repeated geometry filling and the like are utilized, so that CAD geometry filling into CSG geometry can be realized for transportation. The basic transport frame is as follows: hierarchical fill structures based on CSG geometry, use a separate CAD description file and fill in CAD universes for CSG geometry calibration. In the practical implementation level, the local coordinates in transportation are used for positioning the CAD geometric part, global and local coordinates are updated simultaneously during the transportation of the CSG geometric part, and the constructed mixed transportation frame and framework are shown in figure 4.

Further, in an embodiment of the present application, particle transport simulation is performed based on the established mixed transport frame and the converted mixed geometric model, including:

and adjusting a particle transport simulation flow according to the determined mixed transport frame. In a particle tracking process of CSG level filling, carrying out transport simulation by using different CAD transport positioning schemes according to labeling of CAD space;

the method further comprises the steps of:

The Meng Ka transport simulation method based on CAD and CSG hybrid geometry of the present application is described below by taking a fuel pellet model as an example.

First, a hybrid geometry input model is built in CAD software or CAE software, as shown in fig. 5. In this embodiment, a CAD geometry is used to create a fuel sphere and a fuel pellet that are radially divided into four layers. The fuel sphere layers are filled with fuel, air gap, cladding, and moderator materials, respectively. The fuel pellets are filled with nuclear fuel, air gaps, moderator material. The CSG geometry is used to create a lead shield outside the fuel sphere and an inert gas material filling the whole space. As previously mentioned, the parameters of material, temperature, boundary conditions, importance, etc. need to be set up when building the respective geometry.

Then selecting a particle transport mode, including a critical mode and a fixed source mode. The present embodiment selects the critical calculation mode. After the calculation mode is selected, the mixed geometric input model can be converted into a mixed geometric model built in Meng Ka algorithm in a parsing way.

Then, in the particle transport simulation process, a first mixed transport frame is adopted, and transport simulation is completed based on a ray tracing method. In the transportation simulation, a related function in a mixed transportation frame is called, and the steps of particle-to-surface distance, particle motion track length, searching of adjacent cells after particle surface penetration and the like are circularly calculated, so that the transportation simulation under the mixed geometry is realized;

in addition to transport simulation, various physical reactions between the simulated particles and other particles such as target targets are required;

and acquiring simulation data in the transportation simulation process, carrying out statistics based on the simulation data, and reducing statistical errors in the statistics in a variance reduction mode to obtain a final simulation result. In this embodiment, parameters such as critical multiplication coefficient of the model and neutron flux of each layer of the fuel pellet are counted, as shown in fig. 6 and 7, fig. 6 is a parameter statistical chart of the fuel pellet mixed geometric model, and fig. 7 is a flux statistical result chart of the fuel pellet mixed geometric model. In addition, in the present embodiment, the entire model is also plotted as shown in fig. 8.

The simulation result shows that the simulation calculation result of the fuel pellet mixed geometric model is well matched with the result of the same CAD model. The results of the cell counter, the grid counter and the face counter are all within 3 times sigma of expected, and the maximum deviation is only 1.92 times sigma. CAD and CSG hybrid transport schemes can be accelerated by about 52.5% from a time consuming point of view.

To implement the above embodiment, the present application also proposes a Meng Ka transportation simulator based on CAD and CSG hybrid geometry.

As shown in fig. 9, the Meng Ka transportation simulation device based on CAD and CSG hybrid geometry includes a model building module, a frame building module, a simulation module, a data statistics module, wherein,

the method further comprises the steps of:

It should be noted that the foregoing explanation of the embodiment of the Meng Ka transportation simulation method based on CAD and CSG hybrid geometry is also applicable to the Meng Ka transportation simulation device based on CAD and CSG hybrid geometry of this embodiment, and will not be repeated here.

In the description of the present specification, a description referring to the terms "one embodiment," "some embodiments," "examples," "particular examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.

Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" is at least two, such as two, three, etc., unless explicitly defined otherwise.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.

Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.

It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.

Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.

The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. Although embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.

Claims

1. A Meng Ka transport simulation method based on CAD and CSG hybrid geometry, comprising the steps of:

establishing a mixed geometric input model, and analyzing and converting the mixed geometric input model into a Meng Ka algorithm built-in mixed geometric model based on a selected particle transport mode;

establishing a mixed transportation frame, wherein the mixed transportation frame is in a first transportation mode or a second transportation mode, the first transportation mode is CAD and CSG geometric nesting transportation, and the second transportation mode is CAD geometric filling-in CSG geometric transportation;

performing particle transport simulation based on the established mixed transport frame and the converted mixed geometric model;

collecting simulation data in the transportation simulation process, carrying out statistics based on the simulation data, and reducing statistical errors in the statistics in a variance reduction mode to obtain a final simulation result;

wherein, when the mixed transport frame is in the first transport mode, the mixed transport frame is expressed as:

performing a card transport simulation by the hybrid transport frame, comprising:

positioning a CAD geometric part by using the global coordinates in transportation, and updating the global and local coordinates simultaneously when the CSG geometric transportation is performed;

when the mixed transport frame is in the second transport mode, the mixed transport frame is expressed as:

2. The method of Meng Ka transport simulation based on CAD and CSG hybrid geometry of claim 1, wherein the hybrid geometry input model comprises a CAD and CSG described geometry model comprising material, boundary conditions, temperature and cell importance, the CSG described geometry model comprising material, boundary conditions, temperature, cell importance, the particle transport mode being either a critical mode or a fixed source mode.

3. The method for Meng Ka transport simulation based on CAD and CSG hybrid geometry according to claim 1, wherein the performing particle transport simulation based on the established hybrid transport framework and the converted hybrid geometry model comprises:

a flow based on a ray tracing method is adopted, a related function in a mixed transportation frame is called, and a particle simulation step is circulated to realize transportation simulation under mixed geometry, wherein the particle simulation step comprises the steps of calculating a particle-to-surface distance, calculating a particle motion track length and searching adjacent cells after particle passing through a surface;

the method further comprises the steps of:

4. The Meng Ka transport simulation device based on CAD and CSG mixed geometry is characterized by comprising a model building module, a frame building module, a simulation module and a data statistics module, wherein,

the model building module is used for building a mixed geometric input model and analyzing and converting the mixed geometric input model into a Meng Ka algorithm built-in mixed geometric model based on a selected particle transport mode;

the frame building module is used for building a mixed transportation frame, wherein the mixed transportation frame is in a first transportation mode or a second transportation mode, the first transportation mode is CAD and CSG geometric nested transportation, and the second transportation mode is CAD geometric filling-in CSG geometric transportation;

the data statistics module is used for collecting simulation data in the transportation simulation process, carrying out statistics based on the simulation data, and reducing statistical errors in the statistics in a variance reduction mode to obtain a final simulation result;

5. The Meng Ka conveyor simulator based on CAD and CSG hybrid geometry of claim 4, wherein the hybrid geometry input model comprises a CAD and CSG descriptive geometry model comprising material, boundary conditions, temperature and cell importance, and the CSG descriptive geometry model comprising material, boundary conditions, temperature and cell importance.

6. The CAD and CSG hybrid geometry based Meng Ka transportation simulation device of claim 4, wherein the performing particle transport simulation based on the established hybrid transportation framework and the converted hybrid geometry model comprises:

the apparatus further comprises: