CN114997035A - Global variance reduction method based on volume and non-counting area correction - Google Patents
Global variance reduction method based on volume and non-counting area correction Download PDFInfo
- Publication number
- CN114997035A CN114997035A CN202210698739.9A CN202210698739A CN114997035A CN 114997035 A CN114997035 A CN 114997035A CN 202210698739 A CN202210698739 A CN 202210698739A CN 114997035 A CN114997035 A CN 114997035A
- Authority
- CN
- China
- Prior art keywords
- volume
- particle
- weight window
- grid
- counting
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 82
- 238000012937 correction Methods 0.000 title claims abstract description 80
- 239000002245 particle Substances 0.000 claims abstract description 100
- 238000004364 calculation method Methods 0.000 claims abstract description 82
- 230000005855 radiation Effects 0.000 claims abstract description 63
- 238000000342 Monte Carlo simulation Methods 0.000 claims abstract description 9
- 230000004907 flux Effects 0.000 claims description 34
- 238000010521 absorption reaction Methods 0.000 claims description 5
- 230000004048 modification Effects 0.000 claims 4
- 238000012986 modification Methods 0.000 claims 4
- 238000004088 simulation Methods 0.000 abstract description 28
- 238000011410 subtraction method Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 8
- 239000002689 soil Substances 0.000 description 6
- 230000005251 gamma ray Effects 0.000 description 5
- XLYOFNOQVPJJNP-ZSJDYOACSA-N Heavy water Chemical compound [2H]O[2H] XLYOFNOQVPJJNP-ZSJDYOACSA-N 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 241000282693 Cercopithecidae Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000004980 dosimetry Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 230000004992 fission Effects 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000011946 reduction process Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/25—Design optimisation, verification or simulation using particle-based methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/08—Probabilistic or stochastic CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a nuclear radiation environment numerical simulation calculation method, in particular to a global variance subtraction method based on volume and non-counting area correction, and solves the technical problems of low calculation precision and efficiency caused by grid cell/grid volume difference and non-counting area in the prior art. According to the global variance reduction method based on the volume and non-counting area correction, the volume and non-counting area correction are introduced on the basis of the Monte Carlo simulation global variance reduction method, the simulation particle transportation can be effectively guided, the grid cell/grid volume difference is large, the simulation particle distribution in the area containing the non-counting area is more reasonable, and the calculation accuracy and efficiency of a radiation field are improved.
Description
Technical Field
The invention relates to a nuclear radiation environment numerical simulation calculation method, in particular to a global variance reduction method based on volume and non-counting area correction.
Background
In the research of radiation environment of nuclear facilities and plants, nuclear radiation environment in early stage of nuclear explosion, nuclear electromagnetic pulse environment, personnel radiation dosimetry and the like, the overall distribution of a spatial radiation field is often required to be calculated. The global solution of the radiation field usually adopts a monte carlo method, and the distribution information of the radiation field is obtained by simulating statistics and calculation of a large number of simulated particle transport processes. When the calculation error of the radiation field obtained by direct simulation is large, a corresponding variance reduction method is often needed to improve the overall calculation accuracy and efficiency of the radiation field. Conventional local variance subtraction methods are generally only targeted at specific targets or detectors and it is difficult to give a reasonably reliable full spatial distribution of the radiation field. In contrast, the global variance reduction method is more suitable for full-space solution of the radiation field.
The global variance reduction method controls the distribution of global simulation particles through a global weight window, increases the number of simulation particles in a lower limit area of a low weight window, and enables the relative deviation of simulation results to be reduced as much as possible along with the distribution of space, thereby integrally improving the calculation efficiency in the global space. Davis and t.andrew, "composition of global variation reduction processes for Monte Carlo radiation transfer relationships of ITER", published in Fusion Engineering and Design journal 2011, volume 86, phase 9, adopt a global variance reduction method based on Monte Carlo forward calculation, obtain simulated particle distribution information such as simulated particle flux, quantity and weight through Monte Carlo simulation calculation, and are used for generating a grid/grid-based global weight window parameter, and carry out Monte Carlo simulation by using the global weight window parameter, and loop iteration is carried out until convergence. The method is widely applied to global radiation field calculation. Zheng et al published in journal of atomic energy science and technology, Vol 53, No 6, journal of 2018, "HBR-2 benchmark topic application of Global variance reduction method" applied it to a nuclear reactor device. Neixian et al, applied to Tokamak apparatus, in "Global variation reduction method for Global monkey particle transport relationships of CFETR", published in Nuclear Science and Techniques, journal, vol.115, No. 8, 2017, volume 8. Wang scholan et al published in journal of Nuclear Power engineering 2019, volume 40, phase 5, "simulation of radiation environment under severe accident of heavy Water reactor nuclear Power plant" and applied it to nuclear Power plants.
In some radiation field full-space solving problems with large space scale span and strong scattering outside a counting area, such as global calculation of a km-level early nuclear radiation environment, a series of problems are faced by directly adopting the existing global variance reduction method. One is that the existing global variance reduction method is applicable to equal-volume cells/grids, and guides the simulated particles to be transported to the global space of the model, so that the simulated particles are distributed uniformly in the full-space range, and the relative errors are relatively uniform in the full-space range. When the volume difference of the counting cells/grids in the radiation field is large, the number of analog particles in the large-volume cells/grids is large, the number of analog particles in the small-volume cells/grids is small, so that the analog relative errors are not uniformly distributed in the cells/grids, and the overall calculation precision and efficiency are reduced. The other is that the non-counting area near the calculation boundary occupies more calculation resources. A radiation field transport calculation model with strong scattering outside a counting area can be generally divided into the counting area and a non-counting area, and simulated particles in the non-counting area can be transported to the counting area to influence the flux calculation of the simulated particles in the counting area. The weight window parameters calculated by the global variance reduction method are uniformly applied to the counting area and the non-counting area, although the calculation accuracy of the counting area is ensured, the simulated particles in the non-counting area (especially in the absorption medium with a larger cross section) are excessively split, and more calculation resources are occupied, so that the calculation efficiency is reduced.
Disclosure of Invention
The invention aims to provide a global variance reduction method based on volume and non-counting area correction, aiming at the technical problems of low calculation accuracy and efficiency caused by grid cell/grid volume difference and non-counting area in the prior art, so as to reasonably guide the distribution of simulated particles and improve the calculation accuracy and efficiency of a radiation field.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a global variance reduction method based on volume and non-counting area correction is characterized by comprising the following steps:
s1, establishing a radiation field transport calculation model, and dividing the radiation field transport calculation model into a counting area and a non-counting area according to the requirement for solving the radiation field;
s2, tracking the transportation process of the simulated particles in the radiation field by adopting a Monte Carlo method, and counting and calculating the particle information in all grid cells/grids in the whole space of the transportation calculation model;
s3, calculating weight window parameters of a global variance reduction method of the transport calculation model according to the information of particles in all cells/grids in the transport calculation model overall space statistically calculated in S2;
s4, carrying out volume correction on the weight window parameter of the global variance reduction method to obtain a volume correction weight window parameter;
s5, carrying out non-counting area correction on the weight window parameter of the global variance reduction method to obtain a non-counting area correction weight window parameter;
s6, tracking the transportation process of the simulated particles under the guidance of the weight window according to the volume correction weight window parameter obtained in S4 and the weight window parameter obtained after correction of the middle non-counting area in S5, and statistically calculating the information of the particles in all cells/grids in the whole space of the transportation calculation model;
s7, judging whether the error convergence of the particle information results in all cells/grids in the whole space of the transport calculation model obtained in S6 meets the preset requirement or not;
if the preset requirement is met, acquiring particle information in all cells/grids in the whole space of the transport calculation model, namely the spatial distribution of a radiation field;
if the preset requirement is not met, executing S8;
and S8, returning to S3, and meanwhile substituting the particle information in all cells/grids in the whole space of the transport calculation model obtained in S6 into S3 for iterative calculation until the result error convergence meets the preset requirement.
Further, the particle information in S2 is particle flux information.
Further, S3 specifically includes:
according to the particle information in the grid cells/grids, calculating the lower limit w of a weight window of a global variance reduction method based on the particle flux in the particle information th
In the formula, phi i Modeling the particle flux, Max (phi), in the ith cell/grid i ) The maximum simulated particle average flux in all cells/grids, and beta is the ratio of the upper weight window limit to the lower weight window limit of all cells/grids.
Further, S4 specifically includes:
4.1) volume correction factor introducing lower limit of weight Window
In the formula, V i Is the volume of the ith cell/grid, V s The volume of the cell/grid in which the radiation source is located;
4.2) defining a lower limit w of a volume correction weight window th Is the lower limit w of the weight window in S3 th Volume correction factor f with it vol The product of which is the lower limit w of the obtained volume correction weight window th '
Further, S5 specifically includes:
correcting the lower limit of the weight window in the non-counting area, and setting the lower limit w of the weight window of the grid cell/grid in the non-counting area th,nonc
w th,nonc ＝w th,n e s/λ
In the formula, w th,n Is the lower limit w of the power window th,nonc The lower limit of the weight window of the counting area cell/grid nearest to the cell/grid, s is the distance between the center of the non-counting area cell/grid and the center of the counting area cell/grid nearest to the non-counting area cell/grid, and lambda is the average absorption free path of the simulated particles.
Further, in S7, the error converges to 5% or less.
Further, the value of the beta is 5.
Further, the particle information in S2 is particle error information, particle weight information, particle track information, particle number information, particle energy information, or particle collision information.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
1. the invention is based on the global variance reduction method of volume and non-counting area correction, introduces volume correction on the basis of Monte Carlo simulation global variance reduction method, and solves the technical problem of simulation particle excessive splitting in large-volume cells/grids caused by large cell/grid volume difference; and the correction of the non-counting area is introduced, so that the technical problem that more computing resources are occupied in the non-counting area is solved.
2. The global variance reduction method based on volume and non-counting area correction provided by the invention can effectively guide the transportation of simulation particles, so that the volume difference of grid cells/grids is larger, the distribution of the simulation particles in the area containing the non-counting area is more reasonable, the calculation precision and efficiency of the global solution of the radiation field are improved, and the applicability of the global variance reduction method in the global solution of the radiation field is enhanced.
Drawings
FIG. 1 is a flow chart of the global variance reduction method based on volume and non-count region correction according to the present invention.
FIG. 2 is a schematic diagram of a large-space gamma-ray radiation field transport calculation model established in the embodiment of the invention.
The reference numerals in fig. 2 are:
1-earth, 2-standard atmosphere, 3-gamma radiation source, 4-counting region grid cells and 5-non-counting region grid cells.
Fig. 3 is a schematic diagram of the distribution of gamma flux errors in the counting region obtained by direct simulation in the embodiment of the present invention.
FIG. 4 is a diagram illustrating a comparison of lower weight window limits calculated by the global variance reduction method for uncorrected, volume corrected and non-counting regions in the embodiment of the present invention.
Fig. 5 is a schematic diagram of a gamma flux error distribution in a counting area obtained by a global variance reduction method based on volume correction in the embodiment of the present invention.
Fig. 6 is a schematic two-dimensional distribution diagram of a lower limit of a weight window calculated by a global variance reduction method based on volume and non-counting area correction in the embodiment of the present invention.
Fig. 7 is a schematic view of the distribution of gamma flux errors in the counting area obtained after 3 iterations of a global variance reduction method based on volume and non-counting area correction in the embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments obtained by those skilled in the art without creative efforts based on the technical solutions of the present invention belong to the protection scope of the present invention.
As shown in fig. 1, a flow chart of a global variance reduction method based on volume and non-counting area correction provided by the present invention is provided, and a basic design idea of the method is to perform volume correction and non-counting area correction on a weight window parameter of the global variance reduction method, so as to solve a technical problem of low calculation efficiency caused by cell volume difference and non-counting area. The invention comprises the following steps:
s1, establishing a radiation field transport calculation model;
and establishing a radiation field transport calculation model, wherein the radiation field transport calculation model comprises radiation source parameters, a geometric model and counting parameters. Radiation source parameters include, but are not limited to, radiation source particle type, position, emission direction, energy, time, and weight information. The geometric model includes, but is not limited to, various media constituting the actual scene, the shape, size, position, density of each medium, and the elemental composition of each medium and the proportion of each elemental composition in the medium. The counting parameters include, but are not limited to, a counting area, a non-counting area, and a counting physical quantity. And dividing the radiation field transport calculation model into a counting area and a non-counting area according to the requirement of solving the radiation field.
S2, tracking the transportation process of the simulated particles in the radiation field by adopting a Monte Carlo method, and counting and calculating the particle information in all grid cells/grids in the whole space of the transportation calculation model; wherein the particle information is particle flux information;
s3, calculating weight window parameters of a global variance reduction method of the transport calculation model according to the particle information in all cells/grids in the overall space of the transport calculation model statistically calculated in S2;
according to the particle information in the grid cells/grids, calculating the lower limit w of a weight window of a global variance reduction method based on the particle flux in the particle information th
In the formula, phi i Modeling the particle flux, Max (phi), in the ith cell/grid i ) The maximum simulated particle average flux in all the cells/grids, and beta is the ratio of the upper weight window limit to the lower weight window limit of all the cells/grids.
S4, carrying out volume correction on the weight window parameter of the global variance reduction method to obtain a volume correction weight window parameter;
4.1) introducing a volume correction factor for the lower limit of the weight window
In the formula, V i Is the volume of the ith cell/grid, V s The volume of the cell/grid in which the radiation source is located;
4.2) defining a lower limit w of a volume correction weight window th Is the lower limit w of the weight window in S3 th Volume correction factor f therewith vol The product of which is the lower limit w of the volume correction weight window th '
S5, performing non-counting area correction on the weight window parameter of the global variance reduction method to obtain a non-counting area correction weight window parameter;
for right window in non-counting areaCorrecting the lower limit, and setting the lower limit w of the weight window of the cells/grids in the non-counting region th,nonc
w th,nonc ＝w th,n e s/λ
In the formula, w th,n Is the lower limit w of the power window th,nonc The lower limit of the weight window of the counting region cell/grid nearest to the cell/grid, s is the distance between the center of the non-counting region cell/grid and the center of the counting region cell/grid nearest to the non-counting region cell/grid, and lambda is the average absorption free path of the simulated particles.
S6, tracking the transportation process of the simulated particles under the guidance of the weight window according to the volume correction weight window parameters obtained in S4 and the weight window parameters obtained in S5 after the correction of the non-counting area, and statistically calculating the information of the particles in all cells/grids in the whole space of the transportation calculation model;
s7, judging whether the error convergence of the particle information results in all cells/grids in the overall space of the transport calculation model obtained in S6 meets the preset requirement or not;
if the preset requirement is met, acquiring particle information in all cells/grids in the whole space of the transport calculation model, namely the spatial distribution of a radiation field;
if the preset requirement is not met, executing S8;
and S8, returning to S3, and simultaneously substituting the particle information in all cells/grids in the whole space of the transport calculation model obtained in S6 into S3 for iterative calculation until the result error convergence meets the preset requirement. Wherein, the error convergence means that the calculation error is small enough to meet the actual calculation requirement.
The following is a specific embodiment of the present invention, which is a scenario of global transport calculation of gamma rays in a large spatial radiation field. The method comprises the following specific steps:
the method comprises the following steps: establishing a large-space gamma-ray radiation field transport calculation model
As shown in FIG. 2, the calculation model is a schematic diagram of global transport calculation in a large space gamma-ray radiation field. The transportation calculation model mainly comprises two media of standard atmosphere 2 (air) and earth 1 (namely soil), wherein the density of the standard atmosphere 2 is 1.205 multiplied by 10 - 3 g/cm 3 Soil of earthThe soil density is 2.35g/cm 3 . The mass ratios of C element, N element, O element and Ar element in the air medium are respectively as follows: 0.01%, 75.52%, 23.19% and 1.28%. The mass percentages of the H element, the O element, the Na element, the Mg element, the Al element, the Si element, the K element, the Ca element and the Fe element in the soil medium are respectively 0.6%, 49.9%, 1.7%, 0.3%, 4.6%, 31.5%, 1.9%, 8.3% and 1.2%. The height of a flux counting area of the gamma-ray transport calculation model is set to be 0-1 km, and the flux counting area is within a range of 5km from the center of a gamma radiation source 3 (a central area in figure 2). The required counting physical quantity is set to the gamma flux in the counting area. Since soil and air outside the counting area have strong scattering effect on gamma rays, a non-counting area should be established outside the counting area. Therefore, the maximum height of the transportation calculation model is 2km (namely the total height of the counting area and the non-counting area), the maximum distance from the horizontal direction of the source center is 6km, and the soil thickness is 1 m.
And (3) carrying out layering treatment on the air and the ground 1 in the transportation calculation model. For air, in the horizontal direction, the number of layers is 60 per 100 m; in the vertical direction, every 100m is divided into 20 layers. For the ground 1, the atmosphere is kept consistent in the horizontal direction, and 60 layers are divided every 100 m; in the vertical direction, every 0.125m is divided into 8 layers. The transportation calculation model is divided into 28 × 60 ═ 1680 cells, the counting area is divided into 10 × 50 ═ 500 counting cells 4, and the non-counting area is divided into 1680-. The gamma radiation source 3 is set to be a point source emitting isotropically, the weight of the gamma radiation source 3 is 1, the watt balance fission spectrum is taken as the energy spectrum of the gamma radiation source 3, the time of the gamma radiation source 3 is 0, the gamma radiation source 3 is positioned at the horizontal center of the model, and the height from the ground is 20 m.
Step two: tracking simulated particle transport process by adopting Monte Carlo method
And (4) counting, calculating and transporting the particle flux information in all cells in the overall space of the calculation model. As shown in fig. 3, the distribution of the gamma flux errors in the counting area obtained by direct simulation is given, and as can be seen from fig. 3, the gamma flux errors are large, especially the gamma flux errors of more than 4km horizontally are mostly greater than 37.5%, and the result is not reliable.
Step three: weight window parameter given by global variance reduction method calculated according to particle flux information
According to the distribution situation of particle flux information in the grid cells, the lower limit of a weight window of a global variance reduction method based on the particle flux in the particle information is calculated as follows:
wherein phi is i For the particle flux information in the ith cell, Max (phi) i ) And the maximum simulated particle average flux in all the cells, wherein beta is the ratio of the upper weight window limit to the lower weight window limit of all the cells, and the upper weight window limit is equal to the lower authority limit multiplied by beta. In this embodiment, β is 5. As shown in fig. 4, the near-ground (non-counting region) intra-cell weight window lower limit calculated by the global variance-reducing method based on volume correction, volume correction and non-counting region correction is given.
Step four: carrying out volume correction on the weight window parameter of the global variance reduction method to obtain the weight window parameter after volume correction
4.1) introduction of volume correction factor
Wherein V i Is the volume of the ith cell, V s Is the volume of the cell where the point source of the gamma radiation source 3 is located.
4.2) a large-space gamma radiation field transport calculation model is shown in figure 2; dividing the grid into 60 layers and 28 layers (including counting area and non-counting area) in horizontal (radial) and vertical directions respectively to generate corresponding circular grid cells with non-equal volumes; the cell volume is smallest at the center and largest at the edge in the radial direction. Calculating the volume correction factor f corresponding to the lower limit of the weight window of the cells from the 1 st cell at the center of the cell closest to the ground layer to the 60 th cell at the boundary vol I.e., 1, 3, 5 to 119. The lower limit of the weight window after the volume correction, which is calculated by the global variance reduction method after the volume correction, is the lower limit w of the weight window in the third step th And its volume correction factor f vol The product of the two. As shown in fig. 4, the lower weight window limit after volume correction (i.e., the lower volume correction weight window limit) is given. As shown in fig. 5, a schematic diagram of the distribution of gamma flux errors in the counting region simulated by the volume-corrected global variance reduction method is shown. The gamma flux error calculated after volume correction is much smaller than that directly simulated in fig. 3.
Step five: performing non-counting area correction on the weight window parameter of the global variance reduction method to obtain the corrected weight window parameter of the non-counting area
Correcting the lower limit of the right window in the non-counting area, and setting the lower limit of the right window of the grid cell in the non-counting area as follows:
w th,nonc ＝w th,n e s/λ (4)
wherein, w th,nonc Is the lower limit of the weight window, w, of the non-counting cell 5 th,n The lower limit of the weight window of the counting cell 4 closest to the non-counting area is s, the distance from the non-counting cell 5 to the counting cell 4 is s, and the average absorption free path of the simulated particles is lambda.
Lower limit of right window w th Decreases rapidly with increasing horizontal distance, without regard to correction of the non-counting area, the lower limit w of the weight window th All the while down to the calculation boundary of 6 km. After considering the correction of the non-counting area, the lower limit w of the right window th Reaches a minimum at 5km and then increases with increasing horizontal distance in the non-counting region, see fig. 4. As shown in FIG. 6, the lower limit w of the weight window obtained by volume correction and non-counting correction is shown th Schematic diagram of the two-dimensional distribution of (a).
Step six: and tracking the transportation process of the simulated particles under the guidance of the weight window according to the weight window parameters after volume correction obtained in the fourth step and the weight window parameters after non-counting area correction (namely the non-counting area correction weight window parameters) obtained in the fifth step, and counting and calculating the flux information of the simulated particles in the grid elements in the whole space of the transportation calculation model.
Step seven: judging whether the error convergence of the particle information results in all grid cells/grids in the overall space of the transport calculation model obtained in the step six meets the preset requirement or not;
if the preset requirement is met, acquiring particle information in all cells/grids in the whole space of the transport calculation model, namely the spatial distribution of a radiation field;
if the preset requirement is not met, executing a step eight;
step eight: and returning to the third step, and simultaneously substituting the particle information in all the cells/grids in the whole space of the transport calculation model obtained in the sixth step into the third step to carry out iterative calculation until the result error convergence meets the preset requirement.
In this embodiment, the simulation sets the CPU total running time to be truncated to 400 minutes, and the result converges after 3 iterations. As shown in fig. 7, the distribution of gamma flux errors in the counting area obtained after three iterations using the global variance reduction method based on volume correction and non-counting area correction is shown. As can be seen from fig. 7, the maximum error of the gamma flux does not exceed 5%, which is significantly smaller than the results of the direct simulation and the simulation based on volume correction given in fig. 3 and 5.
The main simulation parameters obtained with different global variance reduction methods are given in table 1. Wherein FOM G The global quality factor is used for evaluating the quality of the global variance reduction method. FOM G The larger the factor, the more computationally efficient the characterization. As can be seen from table 1, the calculation efficiency of the unmodified global variance reduction method in this embodiment is lower than that of the direct simulation calculation, which indicates that the applicability of the unmodified global variance reduction method in the calculation of the large-space gamma-ray radiation field is poor. FOM calculated by volume-corrected global variance-reducing method G The factor is improved by about 39 times over the direct simulation and the standard deviation based on error is reduced by about two orders of magnitude. After further introduction of non-counting zone correction, FOM G The factor is improved by about 54 times compared to the direct simulation. The average error obtained by simulation after 3 times of iteration convergence is 1.2%, the maximum error is 4.2%, and FOM G Factor 2.58, FOM G The factor is increased by about 561 times compared to the direct simulation. The global variance reduction method based on non-counting area correction can effectively guide the transportation of the simulation particles to ensure that the simulation particles in the cell are reasonably distributed, solve the problems of excessive splitting caused by large volume difference in the cell and excessive calculation resources occupied by the non-counting area, and improve the global calculation precision and efficiency of the radiation field.
TABLE 1 Main simulation parameters obtained by different global variance reduction methods
According to the main technical concept of the invention, the volume correction and non-counting area correction method can be applied to a global variance reduction method based on simulation particle information such as simulation particle errors, weights, tracks, numbers, energy and collisions; the method is suitable for the transport calculation of the neutron radiation field and is suitable for a grid-based global variance reduction method.
Claims (8)
1. A global variance reduction method based on volume and non-counting area correction is characterized by comprising the following steps:
s1, establishing a radiation field transport calculation model, and dividing the radiation field transport calculation model into a counting area and a non-counting area according to the requirement for solving the radiation field;
s2, tracking the transportation process of the simulated particles in the radiation field by adopting a Monte Carlo method, and counting and calculating the particle information in all grid cells/grids in the whole space of the transportation calculation model;
s3, calculating weight window parameters of a global variance reduction method of the transport calculation model according to the particle information in all cells/grids in the overall space of the transport calculation model statistically calculated in S2;
s4, carrying out volume correction on the weight window parameter of the global variance reduction method to obtain a volume correction weight window parameter;
s5, performing non-counting area correction on the weight window parameter of the global variance reduction method to obtain a non-counting area correction weight window parameter;
s6, tracking the transportation process of the simulated particles under the guidance of the weight window according to the volume correction weight window parameter obtained in S4 and the weight window parameter obtained after correction of the middle non-counting area in S5, and statistically calculating the information of the particles in all cells/grids in the whole space of the transportation calculation model;
s7, judging whether the error convergence of the particle information results in all cells/grids in the whole space of the transport calculation model obtained in S6 meets the preset requirement or not;
if the preset requirement is met, acquiring particle information in all cells/grids in the whole space of the transport calculation model, namely the spatial distribution of a radiation field;
if the preset requirement is not met, executing S8;
and S8, returning to S3, and simultaneously substituting the particle information in all cells/grids in the whole space of the transport calculation model obtained in S6 into S3 for iterative calculation until the result error convergence meets the preset requirement.
2. The method of claim 1, wherein the global variance reduction method is based on volume and non-count region modification, and comprises: the particle information in S2 is particle flux information.
3. The global variance reduction method based on volume and non-count region modification according to claim 2, wherein: s3 specifically includes:
according to the particle information in the grid cells/grids, calculating the lower limit w of a weight window of a global variance reduction method based on the particle flux in the particle information th
In the formula, phi i Modeling the particle flux, Max (phi), in the ith cell/grid i ) The maximum simulated particle average flux in all the cells/grids, and beta is the ratio of the upper weight window limit to the lower weight window limit of all the cells/grids.
4. The global variance reduction method based on volume and non-count area correction according to claim 3, wherein S4 specifically comprises:
4.1) introducing a volume correction factor for the lower limit of the weight window
In the formula, V i Is the volume of the ith cell/grid, V s The volume of the cell/grid in which the radiation source is located;
4.2) defining a lower limit w of a volume correction weight window th Is the lower limit w of the weight window in S3 th Volume correction factor f therewith vol The product of which is the lower limit w of the obtained volume correction weight window th '
5. The global variance reduction method based on volume and non-count area correction according to claim 4, wherein S5 specifically comprises:
correcting the lower limit of the weight window in the non-counting area, and setting the lower limit w of the weight window of the grid cell/grid in the non-counting area th,nonc
w th,nonc ＝w th,n e s/λ
In the formula, w th,n Is the lower limit w of the power window th,nonc The lower limit of the weight window of the counting region cell/grid nearest to the cell/grid, s is the distance between the center of the non-counting region cell/grid and the center of the counting region cell/grid nearest to the non-counting region cell/grid, and lambda is the average absorption free path of the simulated particles.
6. The method according to claim 5, wherein in S7, the error converges to 5% or less.
7. The global variance reduction method based on volume and non-count region modification according to claim 6, wherein: the value of beta is 5.
8. The method of claim 1, wherein the global variance reduction method is based on volume and non-count region modification, and comprises: the particle information in S2 is particle error information, particle weight information, particle track information, particle number information, particle energy information, or particle collision information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210698739.9A CN114997035A (en) | 2022-06-20 | 2022-06-20 | Global variance reduction method based on volume and non-counting area correction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210698739.9A CN114997035A (en) | 2022-06-20 | 2022-06-20 | Global variance reduction method based on volume and non-counting area correction |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114997035A true CN114997035A (en) | 2022-09-02 |
Family
ID=83035542
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210698739.9A Pending CN114997035A (en) | 2022-06-20 | 2022-06-20 | Global variance reduction method based on volume and non-counting area correction |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114997035A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116933553A (en) * | 2023-08-02 | 2023-10-24 | 上海交通大学 | Unstructured grid volume correction method for numerical reactor neutron |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5870697A (en) * | 1996-03-05 | 1999-02-09 | The Regents Of The University Of California | Calculation of radiation therapy dose using all particle Monte Carlo transport |
| US20050192764A1 (en) * | 2004-03-01 | 2005-09-01 | Holland Richard A. | Computation of radiating particle and wave distributions using a generalized discrete field constructed from representative ray sets |
| CN106295213A (en) * | 2016-08-18 | 2017-01-04 | 中国科学院合肥物质科学研究院 | A kind of iteration based on particle density inhomogeneities is covered card overall situation power window parameter and is generated method |
| US20180060463A1 (en) * | 2016-08-30 | 2018-03-01 | Hefei Institutes of Physical Science, CAS | Hybrid Monte Carlo and Deterministic Particle Transport Method Based on Transition Area |
| CN111539151A (en) * | 2020-04-27 | 2020-08-14 | 西北核技术研究院 | Particle angle distribution condition acquisition method based on Monte Carlo point flux recording |
| CN114004133A (en) * | 2022-01-04 | 2022-02-01 | 电子科技大学 | Unequal weight macro particle correction method of electron impact ionization Monte Carlo model |
-
2022
- 2022-06-20 CN CN202210698739.9A patent/CN114997035A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5870697A (en) * | 1996-03-05 | 1999-02-09 | The Regents Of The University Of California | Calculation of radiation therapy dose using all particle Monte Carlo transport |
| US20050192764A1 (en) * | 2004-03-01 | 2005-09-01 | Holland Richard A. | Computation of radiating particle and wave distributions using a generalized discrete field constructed from representative ray sets |
| CN106295213A (en) * | 2016-08-18 | 2017-01-04 | 中国科学院合肥物质科学研究院 | A kind of iteration based on particle density inhomogeneities is covered card overall situation power window parameter and is generated method |
| US20180060463A1 (en) * | 2016-08-30 | 2018-03-01 | Hefei Institutes of Physical Science, CAS | Hybrid Monte Carlo and Deterministic Particle Transport Method Based on Transition Area |
| CN111539151A (en) * | 2020-04-27 | 2020-08-14 | 西北核技术研究院 | Particle angle distribution condition acquisition method based on Monte Carlo point flux recording |
| CN114004133A (en) * | 2022-01-04 | 2022-02-01 | 电子科技大学 | Unequal weight macro particle correction method of electron impact ionization Monte Carlo model |
Non-Patent Citations (1)
| Title |
|---|
| 刘聪: "SN共轭函数用于蒙特卡罗粒子输运自动减方差的研究", 计算物理, vol. 35, no. 5, 30 September 2018 (2018-09-30), pages 535 - 544 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116933553A (en) * | 2023-08-02 | 2023-10-24 | 上海交通大学 | Unstructured grid volume correction method for numerical reactor neutron |
| CN116933553B (en) * | 2023-08-02 | 2024-02-13 | 上海交通大学 | Unstructured grid volume correction method for numerical reactor neutron |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108549753B (en) | Radiation shielding calculation method for coupling point kernel integration method and Monte Carlo method | |
| CN107038294A (en) | For the Resonance self-shielding computational methods based on equivalent one-dimensional rod model of light water reactor | |
| Cai et al. | Optimization of radiation shielding material aiming at compactness, lightweight, and low activation for a vehicle-mounted accelerator-driven DT neutron source | |
| CN114997035A (en) | Global variance reduction method based on volume and non-counting area correction | |
| CN109670239B (en) | Pressurized water reactor production isotope simulation method and system based on pin-by-pin model | |
| CN111584019B (en) | Method for obtaining response of detector outside reactor based on first collision source-Monte Carlo coupling | |
| CN107038293A (en) | For the Resonance self-shielding computational methods based on equivalent one-dimensional Slab of plate type fuel element | |
| CN113609099B (en) | Method for manufacturing fusion reactor multi-group shielding database based on Monte Carlo method | |
| Peplow et al. | Simultaneous optimization of tallies in difficult shielding problems | |
| Sato et al. | Evaluation of shutdown gamma-ray dose rates around the duct penetration by three-dimensional Monte Carlo decay gamma-ray transport calculation with variance reduction method | |
| Colangeli et al. | Neutronics study for DTT tokamak building | |
| Matijević et al. | Dose rates modeling of pressurized water reactor primary loop components with SCALE6. 0 | |
| CN115270423A (en) | MC (monomer casting) accompanying transport-based efficient nuclear explosion neutron dose field acquisition method | |
| CN114694863A (en) | Method for calculating multi-group slow-release photon yield by using fission yield and decay data | |
| Laky et al. | Neutron fluence at the pressure vessel of a pressurized water reactor determined by the MCNP code | |
| Castellanos et al. | Thick-target yields of secondary ions and neutrons for validation of radiation transport codes | |
| Ishida et al. | Finding the best fuel assemblies shuffling scheme of ADS for MA transmutation using Dynamic Programming | |
| CN108595796A (en) | The computational methods and medium of large space deep penetration radiation field Dose Rate | |
| He et al. | Performance study of global weight window generator based on particle density uniformity | |
| CN114117870B (en) | Feedback type radiation shielding analysis method, system, terminal and medium | |
| Dučkić et al. | Estimation of Dose Rates Around Dry Storage Building During Campaign One Loading in Nuclear Power Plant Krsko | |
| Rose | Comparison of Attila SN Particle Transport Code with MCNP in the Analysis of Small Modular Reactor Shielding | |
| Royston et al. | Secondary-Source Core Reload Modeling with VERA | |
| Takeda et al. | Pin-by-pin minor actinides transmutation analysis for heterogeneous minor actinides target loaded core by reconstruction of neutron spectrum | |
| Chang et al. | A Deterministic Dose Calculation Algorithm for Boron Neutron Capture Therapy |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |