CN112966428A - Cross-section treatment system for reactor core - Google Patents
Cross-section treatment system for reactor core Download PDFInfo
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Abstract
The present application provides a cross-section handling system for a reactor core, comprising: the group constant generation module is used for counting cross section related parameters of the reactor core; the storage output module is used for constructing a data storage and output format and storing and outputting the cross section related parameters based on the constructed data storage and output format; the equivalent homogenization factor calculation module is used for calculating a super homogenization factor and a discontinuity factor by utilizing a Monte Carlo method; the flow control module is used for automatically generating Monte Carlo component program input cards under a series of different state points by reading a Python input file given by a user, calculating all state points by using an automatically generated sh file, and giving physical state parameters in an output H5 file according to a material corresponding to a physical state specified by the user to construct a section parameter library; and the section library processing module is used for analyzing and fitting the section parameters in the section parameter library by a least square method through a polynomial fitting method.
Description
Technical Field
The present application relates to the field of technology, and more particularly, to a reactor core cross-section handling system.
Background
The traditional determinism program coupling framework adopts a determinism component program calculation-determinism core calculation coupling mode to carry out core design calculation. The determinism method is to solve the neutron transport equation, but due to the complexity of the equation, a series of simplifications and assumptions need to be introduced in the solving process. These simplifications and assumptions differ for different heap types and energy spectrum applicability, so it is difficult to determine the universality of the procedure. Meanwhile, the deterministic method cannot use continuous energy points, so it first processes multi-population constants using nuclide population cross-section processing software and an evaluation nuclear database with a specific approximate energy spectrum, as shown in fig. 1. It can be seen that the determinism method depends on the accuracy of the energy spectrum and the reliability of the evaluation nuclear data, and meanwhile, the space self-screening and the energy self-screening are considered, and the traditional mainstream program resonance processing is not satisfactory in terms of complex problems.
In conclusion, for a complex core structure containing dispersed fuel, no good geometric modeling mode and transportation solving model exist in the current determinacy program. The traditional solving method has very large calculation deviation, and reasonable reactor core parameters cannot be obtained.
Disclosure of Invention
The object of the present application is to solve at least to some extent one of the above mentioned technical problems.
To this end, an object of the present application is to provide a reactor core cross-section processing system that can overcome the difficulty of modeling analysis of complex core structures by a deterministic method by using a monte carlo method.
To achieve the above object, the present invention provides a section processing system of a reactor core, including:
a group constant generation module for counting cross-section related parameters of the reactor core; wherein the cross-section related parameters comprise group constant macroscopic cross-section, nuclide microscopic cross-section, nuclide density, burnup distribution, power distribution and component grid element flux;
the storage output module is used for constructing a data storage and output format and storing and outputting the cross section related parameters based on the constructed data storage and output format;
the equivalent homogenization factor calculation module is used for calculating a super homogenization factor and a discontinuity factor by utilizing a Monte Carlo method;
the flow control module is used for automatically generating Monte Carlo component program input cards under a series of different state points by reading a Python input file given by a user, calculating all the state points by an automatically generated sh script file, and giving physical state parameters in an output H5 file according to materials corresponding to the physical state specified by the user to construct a section parameter library;
and the section library processing module is used for carrying out least square analysis fitting on the section parameters in the section parameter library by a polynomial fitting method.
In some embodiments of the present application, the group constant generation module is specifically configured to:
obtaining a group reactivity and a group flux of the reactor core by a volumetric flux weighting method;
calculating the group constant macroscopic cross section according to the group reaction rate and the group flux;
calculating the microscopic section of the nuclide by adopting a one-step homogenization mode;
calculating the nuclide density based on a corresponding average density of the j nuclides over the homogenization area of the reactor core;
obtaining the component cell flux based on a cell counter of a Monte Carlo component program;
obtaining, by a burn-up module of the Monte Carlo component program, the burn-up profile and the power profile.
In some embodiments of the present application, the population constant generation module calculates the population response rate and the population flux by the following equations:
where R denotes the reaction rate, Φ denotes the neutron flux, Σ denotes the macroscopic cross section, V denotes the homogenization region volume, E denotes the neutron energy, t denotes the time, R denotes the neutron spatial position, subscript j denotes the number of different regions included in the calculation target, and g denotes the energy group.
In some embodiments of the present application, the group constant generation module calculates the nuclide microscopic sections by:
wherein σj,x,gG-group microscopic cross-section representing the j-th nuclide, x-type cross-section, WTL representing the trace length of the particle multiplied by the particle weight, ViRepresenting the volume of the region, and N is the number of neutrons within the region.
In some embodiments of the present application, the physical state comprises: burnup, boron concentration, xenon concentration, moderator density, fuel temperature.
In some embodiments of the present application, the equivalent equalization factor calculation module is specifically configured to:
carrying out non-uniform calculation on a calculation object to obtain a few-group constant and a few-group flux, initializing a super homogenization factor, and adjusting the non-uniform few-group constant;
calling a reactor core transportation or diffusion program to perform homogenization calculation;
obtaining an effective value-added factor keffAcquiring the homogenized flux and normalizing;
calculating the super-homogenization factor by using non-homogenization flux and uniform flux;
and judging whether the super homogenization factor is iteratively converged, if not, adjusting a non-uniform few-group constant according to the super homogenization factor, and returning to the step of executing the calling reactor core transportation or diffusion program to perform homogenization calculation.
According to the cross-section processing system of the reactor core, the cross-section related parameters of the reactor core are counted through the group constant generation module, the storage output module constructs a data storage and output format, the cross-section related parameters are stored and output based on the constructed data storage and output format, the equivalent homogenization factor calculation module calculates the super homogenization factor and the discontinuity factor by using a Monte Carlo method, the process control module automatically generates a series of Monte Carlo component program input cards under different state points by reading a Python input file given by a user, calculates all the state points through an automatically generated sh file, and gives the physical state parameters in an output H5 file according to the material corresponding to the physical state specified by the user to construct a cross-section parameter library; and (3) performing least square analysis fitting on the section parameters in the section parameter library through a polynomial fitting method by using a section library processing module. Therefore, the core calculation coupling mode of the Monte Carlo method component calculation-deterministic theory is adopted, and an accurate section parameter library can be provided for a downstream core program, so that the fine and efficient modeling analysis of reactor types containing dispersed fuel (such as a high-temperature gas cooled reactor) and the like is realized, the calculation precision of the traditional deterministic theory two-step method can be obviously improved, and the problem that the traditional two-step method of a complex geometric core structure cannot be analyzed and calculated is solved.
Additional aspects and advantages of the present 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 present application.
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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 of which:
FIG. 1 is an exemplary illustration of a continuous energy absorption cross section and a group 70 absorption cross section of U-238;
FIG. 2 is a block diagram of a cross-sectional reactor core handling system according to an embodiment of the present disclosure;
fig. 3 is an exemplary diagram of an H5 file format of section data of an embodiment of the present application;
FIG. 4 is a flowchart of the calculation of the super-homogenization method of the embodiment of the present application in a program;
FIG. 5 is a Python calculation flow chart according to the embodiment of the present application;
FIG. 6 is an exemplary graph comparing 550K burnup point data for embodiments of the present application;
FIG. 7 is an exemplary graph of the relative deviation of the power distribution of 0.05MWD/KgHM in an embodiment of the present application;
FIG. 8 is an exemplary graph of the relative deviation of the power distribution of 2.5MWD/KgHM in an embodiment of the present application;
FIG. 9 is an exemplary graph of the relative deviation of the power distribution of 11.5MWD/KgHM in an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
A cross-sectional reactor core handling system of an embodiment of the present application is described below with reference to the drawings.
It should be noted that the present application is performed by using a Monte Carlo method component calculation and determinism core calculation coupling mode. The upstream component calculation of the present application employs the Monte Carlo program RMC (Reactor Monte Carlo code, Reactor Monte analysis program). The Monte Carlo method can overcome the problem that the modeling analysis of the determinacy method on the complex core structure is difficult.
The core of the coupling calculation is to introduce a section parameterization method by utilizing the group constant statistical function of a Monte Carlo component program and provide a set of section parameter library for a downstream reactor core program. The cross section parameterization method is an important content of reactor physical analysis. In order to meet the requirements of nuclear power development, improve the effectiveness of transient and accident condition simulation, and determine the safety margin of a nuclear power plant under the accident condition, the method has important research value. The assembly homogenized section is used as an important feedback part of the neutron-thermal interaction of the reactor core, and the accuracy and the effectiveness of the assembly homogenized section can have important influence on the performance of the whole coupling procedure. Therefore, the method has important significance for analyzing the influence factors of the homogenization section of the component and providing an effective expression mode. Meanwhile, the component calculation is usually performed under a given state, and the actual core state parameters are unknown, so that the component homogenization small group section parameters under various working conditions during the operation of the reactor need to be obtained by using a section processing program. The process of processing the cross section is cross section parameterization.
Fig. 2 is a block diagram of a cross-sectional processing system of a reactor core according to an embodiment of the present disclosure. As shown in fig. 2, the cross-sectional reactor core handling system 200 may include: the system comprises a group constant generation module 10, a storage output module 20, an equivalent homogenization factor calculation module 30, a flow control module 40 and a section library processing module 50.
Specifically, the group constant generation module 10 is used for counting cross-section related parameters of the reactor core; the cross section related parameters comprise group constant macroscopic cross section, nuclide microscopic cross section, nuclide density, burnup distribution, power distribution and component grid element flux.
In some embodiments of the present application, the group constant generation module 10 may obtain the group reactivity and the group flux of the reactor core by a volume flux weighted method and calculate the group constant macroscopic cross-section from the group reactivity and the group flux. As an example, the group constant generation module 10 may calculate the group flux by the following equation (1):
wherein phi is neutron flux, V is homogenization area volume, E represents neutron energy, t is time, r represents neutron space position, subscript j is the number of different areas contained in the calculation object, and g is an energy group;
in this example, the group constant generation module 10 may calculate the group reaction rate by the following equation (2):
where R denotes the reaction rate, Φ denotes the neutron flux, Σ denotes the macroscopic cross section, V denotes the homogenization region volume, E denotes the neutron energy, t denotes the time, R denotes the neutron spatial position, subscript j denotes the number of different regions included in the calculation target, and g denotes the energy group.
In this embodiment, monte statistical equations (3) and (4) of the group flux and group reaction rate of a single region j can be obtained by derivation and modification of the above equations (1) and (2), i being the simulated particle number while normalizing the group flux and group reaction rate to the contribution of a single particle.
Wherein, W0Representing the weight of the neutron. After the group reactivity and the group flux are obtained, the group constant macroscopic cross section can be obtained by dividing the group reactivity by the group flux.
In the present embodiments, nuclide microscopic sections may include, but are not limited to, microscopic absorption sections, microscopic fission sections, microscopic neutron production sections, microscopic neutron energy production sections, microscopic N2N, N3N sections, and the like. The group constant generating module 10 may calculate the nuclide microscopic cross-sections in a one-step homogenization manner. Wherein, the formula of the one-step homogenization mode is expressed as the following formula (5):
wherein σj,x,gRepresents the g-population microscopic cross-section of the j-th nuclear species, the x-type cross-section. The right side of equation (5) represents the accumulation of all statistical regions.
In an embodiment of the present application, the group constant generation module 10 may calculate the nuclide densities based on the corresponding average density of the j nuclides over the homogenization area of the reactor core. For example, the nuclear density of the microscopic nuclide can be calculated by the following equation (6):
where ρ is the micronuclide nuclear density, V is the region volume, subscript i denotes the region number, and j denotes the nuclide number. In equation (6), the right side is the average density of the corresponding j nuclides under the whole homogenization region, and the right side ρi,jThe density of the j species representing the i-region is given by the material information of the input card.
In the embodiment of the present application, the group constant generation module 10 may obtain the component cell flux based on the cell counter of the monte carlo component program, and obtain the burn-up distribution and the power distribution through the burn-up module of the monte carlo component program.
The storage output module 20 is used for constructing a data storage and output format, and storing and outputting the section related parameters based on the constructed data storage and output format. It should be noted that, the section parameter library of the embodiment of the present application may be stored and output in a tree structure. For example, as shown in fig. 3, each state point contains a series of data sets, each of which contains specific data. As one example, the storage output module 20 may utilize integrated storage output in H5 format.
The equivalent homogenization Factor calculation module 30 is used for calculating a super homogenization Factor (SPH) and a Discontinuity Factor (DF) by using a montecard method. It should be noted that, the monte carlo component program implements a simpler solution of the edge discontinuity factor and the angle discontinuity factor by using a flux statistical process of the monte carlo method, as shown in the following formula (7):
where F denotes a discontinuity factor, A denotes an area, V denotes a volume, r denotes a neutron space position, E denotes neutron energy, S denotes a plane, subscript i denotes a plane number, and g denotes an energy group. The numerator in equation (7) represents the non-homogenized average flux and the denominator represents the homogenized average flux. The theoretical model is based on the assumption that the volume average flux within a single component can be approximated as representing the homogenized area average flux. Whether this assumption applies to core boundary calculations requires further validation. For the calculation of the angular discontinuity factor, the numerator of the above formula is simply converted to the flux at the corner point.
Compared with the generalized equivalent theory, the super homogenization theory does not need additional equivalent homogenization parameters, the group constant is directly adjusted in the equivalent homogenization process, the reactor core procedure does not need additional modification, and the applicability of the super homogenization method is greatly improved.
FIG. 4 is a flow chart of the calculation of the super-homogenization method in the program. As shown in fig. 4, the process of calculating the super-uniformization factor SPH by the equivalent uniformization factor calculating module 30 is as follows:
and S41, performing non-uniform calculation on the calculation object to obtain a small group constant and a small group flux, initializing a super homogenization factor, and adjusting the non-uniform small group constant.
And S42, calling a core transportation or diffusion program to perform homogenization calculation.
S43, obtaining the effective value-added factor keffAnd obtaining and normalizing the homogenized flux.
And S44, calculating a super-homogenization factor by using the non-homogenization flux and the uniform flux.
And S45, judging whether the super homogenization factor is iteratively converged.
S46, if the super homogenization factor iteration does not converge, adjusting the non-uniform small group constant according to the super homogenization factor, and returning to execute the step S42, namely returning to execute the step of calling the core transportation or diffusion program to perform homogenization calculation.
In the embodiment of the present application, if the super-homogenization factor iteratively converges, it is determined that the super-homogenization factor SPH iterative solution ends.
The flow control module 40 is configured to automatically generate a series of monte carlo component program input cards at different state points by reading a Python input file given by a user, calculate all the state points by using an automatically generated sh script file, and give physical state parameters in an output H5 file according to a material corresponding to a physical state specified by the user to construct a section parameter library.
That is, an important function of the cross-section parameterization is flow control, so that corresponding restart and secondary line calculation are realized. The flow is implemented by using a Python program. For example, as shown in FIG. 5, the flow control of the flow control module 40 may be as follows: by reading a Python input file given by a user, a series of Monte Carlo component program input cards at different state points are automatically generated. Wherein all restart Monte Carlo component program input cards are placed under the restart folder, and all auxiliary line input cards are placed under the auxiliary line folder. And calculating all state points through automatically generated sh, and finally giving out physical state parameters in an output H5 file according to the materials corresponding to the physical state specified by the user.
It should be noted that for restart calculations, the process utilizes a sequential calculation function. The subsequent calculation may output an input file of RMC (Reactor Monte Carlo code, Reactor Monte Carlo program) corresponding to each burnup step, where each file includes the material and nuclide under the burnup point. In the embodiment of the present application, the physical state may include 5, that is: burnup, boron concentration, xenon concentration, moderator density, fuel temperature, and the like. The parameters such as boron concentration, moderator density and the like in the physical state have input convenience.
The section library processing module 50 is configured to perform least squares analysis fitting on the section parameters in the section parameter library by a polynomial fitting method.
It should be noted that, the parameterization method of the component section generally includes a polynomial fitting method and a multidimensional table interpolation method. In the embodiment of the present application, a polynomial fitting method is performed in a regression analysis-based manner. The method is characterized in that the method comprises the steps of analyzing various influence factors by using a stepwise regression model by using the thought that the importance of various factors influencing the section is different, selecting significant factors, forming a reasonable polynomial and directly fitting the section. The various macroscopic cross-sections are also represented as the sum of a series of sub-sections, in the form:
each section is a polynomial function of physical state quantity, generally 2-3 physical quantities are linearly combined, and the times are between 0-3. For example:
and (3) fitting by adopting a bivariate polynomial form according to the influence of the density of the moderator and the boron concentration on the section parameters of the uniform small group of the component:
in the formula, aiIs the coefficient of each polynomial. The polynomial fitting method of the embodiment of the present application is also implemented externally by using a Python program. The initial polynomial considered contains three major terms:
Σi＝Σ(burnup,BC,XE)+Σ(burnup,BC,MD)+Σ(burnup,TFuel,MD) (10)
in the formula, burnup represents Fuel consumption, BC represents Boron Concentration (Boron Concentration), MD represents Moderator Density (Moderator Density), XE represents Xenon Concentration (Xenon Concentration), and TFuel represents Fuel Temperature (Fuel Temperature).
It can be seen that the group constant generation module is the basis of the whole technical scheme, and data required by the calculation of the downstream reactor core can be generated only by realizing the group constant generation module. The storage output module can format the data, so that the data can be conveniently read and processed. The equivalent homogenization factor calculation module can improve the section precision and improve the calculation accuracy. The process control module is used for realizing section calculation under different states, the function is also very important in the technical scheme, and only when the function is realized, a set of complete section database can be constructed for a downstream reactor core. The section library processing module, which is also the last functional module in the computational flow, functions to further process the section library into parameters that can be used directly by the downstream core.
Meanwhile, the correctness of the coupling process and the section parameterization method of the application are fully verified. When the inventor verifies, a 10 × 10 pressurized water reactor model is constructed and is subjected to example verification. A section library of three temperature points of 400K, 500K and 600K is generated in advance. Of the three points, 600K is the dominant line calculation. And (5) performing secondary line calculation by using Python flow control at 400K and 500K to generate a secondary line calculation section library. And comparing the 550K multi-group calculation result obtained by the interpolation of the section parameter library with the 550K continuous energy RMC accurate calculation result for verification. As shown in FIG. 6, the results of the comparison calculations for the multiple clusters performed for the 550K library are shown in Table 1 for the 550K burnup point data comparisons.
TABLE 1550K burnup point data contrast
| Step | RMC continuous energy | Multiple group computing | Relative deviation (pcm) |
| 0 | 1.179881 | 1.178647 | 123.4 |
| 1 | 1.149456 | 1.149575 | 11.9 |
| 2 | 1.166661 | 1.16565 | 101.1 |
| 3 | 1.165531 | 1.164513 | 101.8 |
| 4 | 1.164228 | 1.163652 | 57.6 |
| 5 | 1.162347 | 1.161281 | 106.6 |
| 6 | 1.16069 | 1.160169 | 52.1 |
| 7 | 1.159095 | 1.157965 | 113 |
| 8 | 1.156514 | 1.154763 | 175.1 |
| 9 | 1.14495 | 1.144422 | 52.8 |
| 10 | 1.13964 | 1.138056 | 158.4 |
| 11 | 1.135396 | 1.134719 | 67.7 |
| 12 | 1.130832 | 1.130409 | 42.3 |
| 13 | 1.126472 | 1.12633 | 14.2 |
| 14 | 1.122124 | 1.121316 | 80.8 |
| 15 | 1.117846 | 1.117473 | 37.3 |
| 16 | 1.113375 | 1.112881 | 49.4 |
| 17 | 1.108662 | 1.109897 | 123.5 |
| 18 | 1.104564 | 1.104411 | 15.3 |
As can be seen from fig. 6 and table 1, the maximum deviation is 175pcm, which completely meets the engineering accuracy requirements. It is thus possible to prove that the cross-sectional parameterization function of the program is correct. Meanwhile, the power distribution conditions at different burnup points of 550K are further verified, and the results are shown in fig. 7 to 9. As can be seen from fig. 7 to 9, the power distribution of the interpolated temperature 550K corresponds well to the continuous energy calculation result. The maximum deviation of the radial distribution power is less than 2%. The accuracy meets engineering requirements.
According to the cross-section processing system of the reactor core, the cross-section related parameters of the reactor core are counted through the group constant generation module, the storage output module constructs a data storage and output format, the cross-section related parameters are stored and output based on the constructed data storage and output format, the equivalent homogenization factor calculation module calculates the super homogenization factor and the discontinuity factor by using a Monte Carlo method, the process control module automatically generates a series of Monte Carlo component program input cards under different state points by reading a Python input file given by a user, calculates all the state points through an automatically generated sh file, and gives the physical state parameters in an output H5 file according to the material corresponding to the physical state specified by the user to construct a cross-section parameter library; and (3) performing least square analysis fitting on the section parameters in the section parameter library through a polynomial fitting method by using a section library processing module. Therefore, the core calculation coupling mode of the Monte Carlo method component calculation-deterministic theory is adopted, and an accurate section parameter library can be provided for a downstream core program, so that the fine and efficient modeling analysis of reactor types containing dispersed fuel (such as a high-temperature gas cooled reactor) and the like is realized, the calculation precision of the traditional deterministic theory two-step method can be obviously improved, and the problem that the traditional two-step method of a complex geometric core structure cannot be analyzed and calculated is solved.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," 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 application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer 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, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (6)
1. A cross-sectional handling system for a reactor core, comprising:
a group constant generation module for counting cross-section related parameters of the reactor core; wherein the cross-section related parameters comprise group constant macroscopic cross-section, nuclide microscopic cross-section, nuclide density, burnup distribution, power distribution and component grid element flux;
the storage output module is used for constructing a data storage and output format and storing and outputting the cross section related parameters based on the constructed data storage and output format;
the equivalent homogenization factor calculation module is used for calculating a super homogenization factor and a discontinuity factor by utilizing a Monte Carlo method;
the flow control module is used for automatically generating Monte Carlo component program input cards under a series of different state points by reading a Python input file given by a user, calculating all the state points by an automatically generated sh script file, and giving physical state parameters in an output H5 file according to materials corresponding to the physical state specified by the user to construct a section parameter library;
and the section library processing module is used for carrying out least square analysis fitting on the section parameters in the section parameter library by a polynomial fitting method.
2. The system of claim 1, wherein the group constant generation module is specifically configured to:
obtaining a group reactivity and a group flux of the reactor core by a volumetric flux weighting method;
calculating the group constant macroscopic cross section according to the group reaction rate and the group flux;
calculating the microscopic section of the nuclide by adopting a one-step homogenization mode;
calculating the nuclide density based on a corresponding average density of the j nuclides over the homogenization area of the reactor core;
obtaining the component cell flux based on a cell counter of a Monte Carlo component program;
obtaining, by a burn-up module of the Monte Carlo component program, the burn-up profile and the power profile.
3. The system of claim 2, wherein the group constant generation module calculates the group reaction rate and group flux by:
where R denotes the reactivity, R denotes the neutron spatial position, Φ denotes the neutron flux, Σ denotes the macroscopic cross section, V denotes the homogenization region volume, E denotes the neutron energy, t denotes the time, subscript j denotes the number of the different regions included in the calculation target, and g denotes the energy group.
4. The system of claim 2, wherein the group constant generation module calculates the nuclide microscopic sections by:
wherein σj,x,gG-group microscopic cross-section representing the j-th nuclide, x-type cross-section, WTL representing the trace length of the particle multiplied by the particle weight, ViRepresenting the volume of the region, and N is the number of neutrons within the region.
5. The system of claim 1, wherein the physical state comprises: burnup, boron concentration, xenon concentration, moderator density, fuel temperature.
6. The system of claim 1, wherein the equivalent homogenization factor calculation module is specifically configured to:
carrying out non-uniform calculation on a calculation object to obtain a few-group constant and a few-group flux, initializing a super homogenization factor, and adjusting the non-uniform few-group constant;
calling a reactor core transportation or diffusion program to perform homogenization calculation;
obtaining an effective value-added factor keffAcquiring the homogenized flux and normalizing;
calculating the super-homogenization factor by using non-homogenization flux and uniform flux;
and judging whether the super homogenization factor is iteratively converged, if not, adjusting a non-uniform few-group constant according to the super homogenization factor, and returning to the step of executing the calling reactor core transportation or diffusion program to perform homogenization calculation.
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| CN113326648A (en) * | 2021-06-17 | 2021-08-31 | 中国核动力研究设计院 | Cell homogenization constant calculation method and system considering environmental effect and terminal |
| CN113806941A (en) * | 2021-09-22 | 2021-12-17 | 上海核星核电科技有限公司 | Pressurized water reactor burnup tracking calculation method with xenon transient simulation capability |
| CN113868591A (en) * | 2021-09-28 | 2021-12-31 | 西安交通大学 | Method for obtaining high-precision total reaction section of indistinguishable resonance region |
| CN114169164A (en) * | 2021-12-03 | 2022-03-11 | 中国原子能科学研究院 | Method and device for determining the core power of a critical device |
| CN114692062A (en) * | 2022-03-31 | 2022-07-01 | 西安交通大学 | Method for efficiently obtaining nuclear reactor fuel rod surface partial neutron flux discontinuous factors |
| WO2023142595A1 (en) * | 2022-01-29 | 2023-08-03 | 刘畅源 | Method for calculating particle transport nuclear reaction cross section and path integral, apparatus and device |
| CN114169164B (en) * | 2021-12-03 | 2024-05-31 | 中国原子能科学研究院 | Method and device for determining core power of critical device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107145721A (en) * | 2017-04-20 | 2017-09-08 | 西安交通大学 | A kind of mixing computational methods for obtaining the few group cross-section parameter of fast neutron reactor |
| CN109741793A (en) * | 2018-12-06 | 2019-05-10 | 华南理工大学 | A kind of calculation method of coat of silicon carbide molten salt reactor thermal neutron scattering effect |
-
2021
- 2021-03-31 CN CN202110347763.3A patent/CN112966428B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107145721A (en) * | 2017-04-20 | 2017-09-08 | 西安交通大学 | A kind of mixing computational methods for obtaining the few group cross-section parameter of fast neutron reactor |
| CN109741793A (en) * | 2018-12-06 | 2019-05-10 | 华南理工大学 | A kind of calculation method of coat of silicon carbide molten salt reactor thermal neutron scattering effect |
Non-Patent Citations (4)
| Title |
|---|
| LIN-SEN LI 等: "Coupling of RMC and CFX for analysis of Pebble Bed-Advanced High Temperature Reactor core", 《NUCLEAR ENGINEERING AND DESIGN》 * |
| YUAN YUAN 等: "Research on the on-the-fly homogenization method based on RMC code for criticality calculations", 《ANNALS OF NUCLEAR ENERGY》 * |
| 李松阳 等: "MCNP温度相关中子截面库制作方法", 《核动力工程》 * |
| 李满仓 等: "BN理论在连续能量蒙卡方法产生均匀化群常数上的应用", 《中国核科学技术进展报告(第二卷)》 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113312792A (en) * | 2021-06-17 | 2021-08-27 | 中国核动力研究设计院 | Method and system for calculating equivalent homogenization constant of grid cell in reactor core rod-by-rod calculation |
| CN113326648A (en) * | 2021-06-17 | 2021-08-31 | 中国核动力研究设计院 | Cell homogenization constant calculation method and system considering environmental effect and terminal |
| CN113806941A (en) * | 2021-09-22 | 2021-12-17 | 上海核星核电科技有限公司 | Pressurized water reactor burnup tracking calculation method with xenon transient simulation capability |
| CN113806941B (en) * | 2021-09-22 | 2024-01-05 | 上海核星核电科技有限公司 | Pressurized water reactor fuel consumption tracking calculation method with xenon transient simulation capability |
| CN113868591A (en) * | 2021-09-28 | 2021-12-31 | 西安交通大学 | Method for obtaining high-precision total reaction section of indistinguishable resonance region |
| CN113868591B (en) * | 2021-09-28 | 2022-12-09 | 西安交通大学 | Method for obtaining high-precision total reaction cross section of unresolved resonance region |
| CN114169164A (en) * | 2021-12-03 | 2022-03-11 | 中国原子能科学研究院 | Method and device for determining the core power of a critical device |
| CN114169164B (en) * | 2021-12-03 | 2024-05-31 | 中国原子能科学研究院 | Method and device for determining core power of critical device |
| WO2023142595A1 (en) * | 2022-01-29 | 2023-08-03 | 刘畅源 | Method for calculating particle transport nuclear reaction cross section and path integral, apparatus and device |
| CN114692062A (en) * | 2022-03-31 | 2022-07-01 | 西安交通大学 | Method for efficiently obtaining nuclear reactor fuel rod surface partial neutron flux discontinuous factors |
| CN114692062B (en) * | 2022-03-31 | 2024-04-09 | 西安交通大学 | Method for efficiently obtaining partial neutron flow discontinuity factors on surface of nuclear reactor fuel rod |
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