CN119597461B - Neutron transport parallel calculation method and computing device for optimizing lateral leakage term processing - Google Patents
Neutron transport parallel calculation method and computing device for optimizing lateral leakage term processingInfo
- Publication number
- CN119597461B CN119597461B CN202411639704.3A CN202411639704A CN119597461B CN 119597461 B CN119597461 B CN 119597461B CN 202411639704 A CN202411639704 A CN 202411639704A CN 119597461 B CN119597461 B CN 119597461B
- Authority
- CN
- China
- Prior art keywords
- neutron
- boundary
- calculation
- segment
- stream
- 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.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5072—Grid computing
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5083—Techniques for rebalancing the load in a distributed system
-
- 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
- Y02E30/00—Energy generation of nuclear origin
- Y02E30/30—Nuclear fission reactors
Landscapes
- Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Monitoring And Testing Of Nuclear Reactors (AREA)
Abstract
一种优化横向泄漏项处理的中子输运并行计算方法及计算装置，属于核电领域。其中，优化横向泄漏项处理的中子输运并行计算方法在单个节块的计算过程中引入二阶勒让德多项式加权的边界流，并结合边界中子流对相邻节块进行更新，通过并行计算历遍所有节块得到更新后的节块中子通量、特征值keff和中子源项，将更新后的数据代回计算模型进行迭代，得到最终计算结果。该方法基于单个节块模型获得节块横向泄漏项的高阶展开系数，在保证计算精度的同时，提高计算稳定性。
A parallel neutron transport calculation method and device for optimizing lateral leakage term processing, belonging to the field of nuclear power. This method introduces boundary flows weighted by second-order Legendre polynomials during the calculation of a single node. Adjacent nodes are updated based on the boundary neutron flows. Parallel calculations are performed across all nodes to obtain updated neutron flux, eigenvalue keff , and neutron source terms. The updated data is then substituted back into the calculation model for iteration to obtain the final calculation result. This method obtains high-order expansion coefficients for the node lateral leakage term based on the single node model, improving computational stability while ensuring accuracy.
Description
Technical Field
The invention belongs to the field of nuclear power, and particularly relates to a neutron transport parallel computing method and a computing device for optimizing transverse leakage term processing.
Background
In the reactor reactivity and full-reactor fine power distribution calculation, accurate calculation of the proton transport behavior is the basis for obtaining accurate calculation results. The method of laterally integrating the segments is widely applied to neutron transport calculation, and the method needs to accurately consider the lateral leakage term of the segments so as to improve the calculation accuracy. In the nuclear reactor high-resolution neutron transport calculation based on cell homogenization, the radial grid is about 1cm in size, the resolution is higher, the calculation accuracy can be further improved through a discontinuous factor or a super equivalent homogenization factor, the axial grid is about 10cm in size, the grid size is larger, in a neutron transport calculation program system based on a transverse integral block method, transverse leakage terms are required to be accurately considered, the calculation accuracy of axial power distribution is improved, and further, key physical parameters such as accurate axial power offset (AO), hot spot factor (F Q) and the like are obtained.
The prior art scheme adopts a flat leakage approximation or a higher-order leakage approximation based on adjacent three section models. The flat leakage approximation method only considers the average value of leakage terms, and has low calculation accuracy. The higher-order leakage term processing method based on the adjacent three section models can obtain higher calculation accuracy, but when parallel calculation based on the region decomposition method is performed, the stability of the parallel calculation is reduced and even the calculation divergence is caused due to the delay of updating the section boundary flow information at the interface of each parallel region. In order to improve the stability of neutron transport parallel calculation based on a transverse integral block method, a high-order leakage term processing method based on a single-block model is needed.
Disclosure of Invention
The invention aims to provide a neutron transport parallel computing method for optimizing transverse leakage term processing, which simplifies the computing complexity of neutron transport behaviors and improves the computing efficiency and precision. The invention also provides a computing device.
According to an embodiment of one aspect of the present invention, there is provided a neutron transport parallel computing method for optimizing a lateral leakage term process, the method including the steps of:
providing a simulation model of a neutron transport calculation simulation object in a reactor, and dividing the simulation model into sections;
B), carrying out color marking on the segments, enabling adjacent segments to have different colors, taking the segments with the same color marking as a same-color segment group, and carrying out parallel region decomposition;
Step c), distributing the segments to a plurality of computation cores according to the parallel region decomposition result in the step b), executing segment response matrix computation, and providing neutron flux, neutron stream, neutron source item and initial values of characteristic value k eff;
Step d), calculating boundary sub-streams, average leakage terms of the segments and boundary streams weighted by second-order Legendre polynomials of the segments in one segment group respectively through each calculation core;
step e), updating the boundary stream calculated in the step d) to the adjacent section blocks;
Step f), taking the calculated section blocks of the boundary sub-stream, the section block average leakage term and the second order Legendre polynomial weighted boundary stream as calculated section blocks, and taking the rest section blocks as uncomputed section blocks;
Calculating the boundary sub-streams, the node average leakage items and the second order Legendre polynomial weighted boundary streams of each same-color node group one by one in the non-calculated node with updated boundary streams, and updating the calculated boundary sub-streams and the second order Legendre polynomial weighted boundary streams to adjacent node blocks;
step g), adopting a second order polynomial approximation of the transverse leakage term, and calculating a transverse leakage term expansion coefficient by taking the average leakage term of each section and the boundary flow weighted by the second order Legendre polynomial at the section boundary as constraint conditions;
step h), calculating and updating neutron flux of the section by taking neutron source items and neutron flux of the section boundary as input according to a neutron balance equation;
Step i), calculating a characteristic value k eff according to the neutron flux in the section block obtained by calculation in the step h), and updating the characteristic value k eff to all calculation cores;
Step j), updating the neutron source item according to the neutron stream item in the boundary of the calculated section, the second order Legendre polynomial weighted boundary stream, the transverse leakage item expansion coefficient calculated in the step g), and the neutron flux of the section calculated in the step h);
and k), repeating the steps d) to j) until the calculated result converges or reaches a given iteration number according to the updated boundary neutron stream, the boundary stream weighted by the second order Legendre polynomial, the node neutron flux and the characteristic value k eff, and outputting a final calculated result.
When neutron transport parallel calculation based on a transverse integral block method is performed, the method can obtain the high-order expansion coefficient of the transverse leakage term of the block based on a single block model, and improves the calculation stability while ensuring the calculation precision.
Further, in some embodiments, in the step a), the simulation model includes geometric information, material information, nuclear reaction cross-section information.
Further, in some embodiments, in the step b), the load variance of each of the parallel computing cores is minimized and the parallel computing area surface area to volume ratio is minimized during the area decomposition.
When the load variance of each parallel computing core is minimum, the load distribution of each parallel computing core can be balanced, and when the surface area and volume ratio of the parallel computing area are minimum, the message communication scale among the parallel computing cores can be reduced.
Further, in some embodiments, in the step d), the second order legendre polynomial weighted boundary streamThe calculation method of (1) is as follows:
Wherein phi (x 0, y, z) is the flux value at the coordinates (x 0, y, z), AndFor the second order Legendre polynomial, Δy k is the segment width of segment k in the y-direction, Δz k is the segment width of segment k in the z-direction, and x 0 is the x-direction coordinate value.
Further, in some embodiments, in the step g), the lateral leakage term expansion coefficientThe calculation method of (1) is as follows:
Wherein, the As the average leakage term for the segment k,A boundary stream weighted for the second order legendre polynomial at the left boundary of segment k,For a boundary stream weighted by a second order Legendre polynomial at the right boundary of segment k, deltax k is the width of segment k in the x-direction.
Further, in some embodiments, in the step i), the calculating method of the feature value k eff is:
Calculating, by each of the parallel computing cores, a total number of fission neutron production of all of the segments allocated Wherein g is the neutron energy group number,For the fission neutron production section of the g-th energy group of the segment k, phi k,g is the neutron flux of the g-th energy group of the segment k, V k is the volume of the segment k, the characteristic value
Further, in some embodiments, in the step k), the criterion of convergence is that the difference between the neutron flux, the neutron source term, the boundary neutron stream, the second order legendre polynomial weighted boundary stream, and the eigenvalue k eff in two rounds of calculation is smaller than a given threshold.
According to an embodiment of another aspect of the present invention, there is provided a computing device including a memory and a plurality of parallel computing cores, wherein the memory stores a neutron transport parallel computing program capable of implementing the neutron transport parallel computing method of optimizing the lateral leakage term processing provided in any of the foregoing embodiments when the neutron transport parallel computing program is executed by the parallel computing cores.
Further, in some embodiments, the computing program includes a modeling and initialization module, a segment response computing module, a single segment model-based higher order leakage term computing module, a source term and eigenvalue solving module, and a parallel scheduling module, wherein,
The modeling and initializing module is used for reading input information of a calculation object, and executing segment division, segment dyeing, parallel region decomposition and calculation result initialization;
The node response calculation module is used for defining a boundary stream weighted by a second order Legendre polynomial, and according to a node response matrix, taking neutron source items and neutron stream data in the previous iteration as inputs, and solving the node boundary neutron stream, a node average leakage item and the boundary stream weighted by the second order Legendre polynomial;
The high-order leakage term calculation module based on the single-section block model is used for solving the expansion coefficient of the transverse leakage term by taking the average leakage term of the single section block and the boundary flow weighted by the second order Legendre polynomial at the boundary of the section block as constraint conditions;
The source term and eigenvalue solving module is used for solving neutron flux, eigenvalue k eff and neutron source term according to neutron balance equation by taking the neutron flow in the section boundary, the average boundary flow weighted by the second order Legendre polynomial and the expansion coefficient of the transverse leakage term as input.
Drawings
FIG. 1 is a schematic diagram of a calculation object in one embodiment;
FIG. 2 is a schematic illustration of segment staining in one embodiment;
FIG. 3 is a block allocation diagram of one embodiment;
FIG. 4 is a schematic diagram of a parallel computing flow in an embodiment;
FIG. 5 is a block diagram of a parallel computing program according to an embodiment.
The above drawings are provided for the purpose of explaining the present invention in detail so that those skilled in the art can understand the technical concept of the present invention, and are not intended to limit the present invention. For simplicity of illustration, the above figures show only schematically the structures related to the technical features of the present invention, and not all the details and the complete structures are drawn strictly to the actual scale.
Detailed Description
The invention will now be described in further detail with reference to the accompanying drawings by means of specific examples.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment herein. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments limited to the same embodiment. Those skilled in the art will appreciate that embodiments herein may be combined with other embodiments without structural conflict.
In the description herein, the terms "first," "second," and the like are used merely to distinguish between different objects and should not be construed as indicating relative importance or defining the number, particular order, or primary and secondary relationships of the technical features described. In the description herein, the meaning of "plurality" is at least two.
In order to overcome the defects of low calculation accuracy and poor calculation stability of transverse leakage items in the conventional neutron transport calculation, the embodiment of the invention provides a neutron transport parallel calculation method for optimizing transverse leakage processing. The method adopts a high-order second-order parabolic approximation of the transverse leakage term, can improve the calculation precision of key nuclear characteristic parameters such as characteristic values, power distribution, power peak factors and the like, and simultaneously can obtain a leakage term high-order expansion coefficient based on calculation of a single section model by introducing a second-order Legendre polynomial weighted boundary flow, so that the stability of neutron transport parallel calculation of nuclear reactor sections based on a regional decomposition method is improved.
As shown in fig. 4, the method comprises the following steps:
Step 1, providing a calculation model of a nuclear reactor neutron transport calculation object, wherein the calculation model specifically comprises geometric information (namely geometric structure and dimensional characteristics), material information (material type and distribution), nuclear reaction section information and the like of the calculation object, simultaneously providing parallel calculation information, control parameters and the like of a system for parallel calculation, and dividing the calculation object into segments (grids) according to input information, as shown in figure 1.
And 2, as shown in fig. 2, marking the colors of the segments, wherein the color numbers are 1 to M, so that the colors of the adjacent segments are different, and carrying out parallel region decomposition according to parallel calculation information input data, so that the loads of the parallel calculation cores tend to be balanced, and particularly, the load variance of each calculation core is controlled to reach the minimum value. To reduce the size of the message traffic between the parallel computing cores, the principle of region decomposition is to minimize the surface area to volume ratio of the parallel regions as much as possible. The segments with the same color label are considered as one same color segment group.
And 3, as shown in fig. 3, according to the parallel region decomposition result in the step 2, each parallel computing core performs segment response matrix computation on the assigned segment to give initialized neutron flux, neutron stream, neutron source item and characteristic value k eff, and specifically, the initial value can be test data, historical simulation calculation data or other manually given initial values.
And 4, for the node blocks distributed by each parallel computing core, computing updated node block boundary neutron streams, node block average leakage terms and second order Legendre polynomial weighted boundary streams by taking data such as neutron source terms, neutron streams and the like of initial values (in a first iteration process) or last iterations (in a second and subsequent iteration processes) as input according to the node block response matrix in the step 3 according to the node blocks marked by the 1 st color.
Wherein the second order Legendre polynomial weighted boundary stream of segment kThe calculation method of (1) is as follows:
Wherein phi (x 0, y, z) is the flux value at the coordinates (x 0, y, z), AndFor the second order Legendre polynomial, Δy k is the segment width of segment k in the y-direction, Δz k is the segment width of segment k in the z-direction, and x 0 is the x-direction coordinate value.
And 5, carrying out message communication between the same-color segment group with the 1 st color and the adjacent segments at the interfaces of the parallel areas for the segments distributed by each parallel computing core, and updating the boundary stream information weighted by the sub-streams and the second order Legendre polynomials in the boundary of the latest segment to the adjacent segments.
And 6, each parallel computing core performs boundary flow computation weighted by the sub-flows, the average leakage term of the segments and the second order Legendre polynomial on the segments distributed to the parallel computing cores one by one aiming at the same-color segment groups from the color 2 to the color M which are not yet computed, and updates the boundary flow computation results weighted by the sub-flows and the second order Legendre polynomial to the adjacent segments. And calculating boundary streams weighted by sub-streams, average leakage terms of the segments and second order Legendre polynomials until the same-color segment groups of all colors are subjected to boundary stream calculation.
Step 7, each parallel computing core approximates the distributed node blocks by adopting a transverse leakage term second order polynomial, and solving the expansion coefficient of the transverse leakage term by taking the average leakage term of the single node block k and the boundary flow weighted by the second order Legendre polynomial at the node block boundary as constraint conditions
Wherein, the As the average leakage term for the segment k,A boundary stream weighted for the second order legendre polynomial at the left boundary of segment k,For a boundary stream weighted by a second order Legendre polynomial at the right boundary of segment k, deltax k is the width of segment k in the x-direction.
And 8, calculating and updating neutron flux of the section blocks by taking neutron source items and neutron flux of the section block boundaries as input according to neutron balance equations as constraint conditions for the section blocks allocated by the parallel calculation cores.
Step 9, each parallel computing core calculates the total fission neutron generation number for all the segments allocated to the parallel computing coreWherein g is the neutron energy group number,For the fission neutron production section of the g-th energy group of the segment k, phi k,g is the neutron flux of the g-th energy group of the segment k, V k is the volume of the segment k, the characteristic valueThe eigenvalue k eff is broadcast to all computing cores for updating through message communication.
And 10, updating neutron source items, including data of fission sources, scattering sources, total source items and the like, by each parallel computing core according to boundary neutron flows, second order Legendre polynomial weighted boundary flows, neutron fluxes and transverse leakage item expansion coefficients which are calculated in the steps 4 to 9 for the distributed section blocks.
And 11, taking the updated boundary neutron stream, the boundary stream weighted by the second order Legendre polynomial, the node neutron flux and the characteristic value k eff as inputs, and repeating the steps 4 to 10 for iterative calculation until the iterative calculation result converges or the iterative calculation reaches a given number of times.
The convergence judgment criterion comprises that the calculated deviation of neutron flux, neutron source item, neutron flow and characteristic value is smaller than a specified value. If the iterations have not converged to a specified number of times, it is stated that the calculated state itself may be divergent.
And outputting the final calculation result to finish neutron transport calculation.
The method provided by the above embodiment may be implemented by a parallel computing device. The parallel computing device includes a memory and a plurality of computing cores, the memory storing neutron transport computing programs, which when executed by the computing cores, are capable of implementing the neutron transport parallel computing method of optimizing the lateral leakage term processing provided in the foregoing embodiment.
Specifically, as shown in fig. 5, the neutron transport calculation program comprises a modeling and initializing module, a section response calculation module, a high-order leakage term calculation module based on a single section model, a source term and eigenvalue solving module and a parallel scheduling module.
The modeling and initializing module is used for reading input information of a calculation object, and executing section (grid) division, section dyeing, parallel area decomposition and calculation result initialization.
The node response calculation module defines a second order Legendre polynomial weighted boundary stream, and the module solves the node boundary neutron stream, the node average leakage term and the second order Legendre polynomial weighted boundary stream by taking neutron source, neutron stream and other data of the previous iteration as input according to the node response matrix.
And a high-order leakage term calculation module based on a single-section block model is used for solving the expansion coefficient of the transverse leakage term by taking the average leakage term of the single section block and the boundary flow weighted by the second order Legendre polynomial at the boundary of the section block as constraint conditions.
And the source term and eigenvalue solving module is used for solving neutron flux, eigenvalue and neutron source term by taking the neutron flow in the section boundary, the boundary flow weighted by the second order Legendre polynomial and the expansion coefficient of the transverse leakage term as input according to constraint conditions such as a neutron balance equation.
And the parallel scheduling module is used for carrying out parallel scheduling, message communication, result collection and broadcasting of neutron transport calculation in the nuclear reactor.
The above-described embodiments are intended to explain the present invention in further detail with reference to the figures so that those skilled in the art can understand the technical concept of the present invention. Within the scope of the present disclosure, the method steps involved are optimized or replaced equivalently, and the implementation manners of the different embodiments are combined on the premise that no structural and principle conflict occurs, which falls within the protection scope of the present disclosure.
Claims (9)
1. The neutron transport parallel computing method for optimizing the transverse leakage term processing is characterized by comprising the following steps of:
providing a simulation model of a neutron transport calculation simulation object in a reactor, and dividing the simulation model into sections;
B), carrying out color marking on the segments, enabling adjacent segments to have different colors, taking the segments with the same color marking as a same-color segment group, and carrying out parallel region decomposition;
Step c), distributing the segments to a plurality of computation cores according to the parallel region decomposition result in the step b), executing segment response matrix computation, and providing neutron flux, neutron stream, neutron source item and initial values of characteristic value k eff;
Step d), calculating boundary sub-streams, average leakage terms of the segments and boundary streams weighted by second-order Legendre polynomials of the segments in one segment group respectively through each calculation core;
step e), updating the boundary stream calculated in the step d) to the adjacent section blocks;
Step f), taking the calculated section blocks of the boundary sub-stream, the section block average leakage term and the second order Legendre polynomial weighted boundary stream as calculated section blocks, and taking the rest section blocks as uncomputed section blocks;
Calculating the boundary sub-streams, the node average leakage items and the second order Legendre polynomial weighted boundary streams of each same-color node group one by one in the non-calculated node with updated boundary streams, and updating the calculated boundary sub-streams and the second order Legendre polynomial weighted boundary streams to adjacent node blocks;
step g), adopting a second order polynomial approximation of the transverse leakage term, and calculating a transverse leakage term expansion coefficient by taking the average leakage term of each section and the boundary flow weighted by the second order Legendre polynomial at the section boundary as constraint conditions;
step h), calculating and updating neutron flux of the section by taking neutron source items and neutron flux of the section boundary as input according to a neutron balance equation;
Step i), calculating a characteristic value k eff according to the neutron flux in the section block obtained by calculation in the step h), and updating the characteristic value k eff to all calculation cores;
Step j), updating the neutron source item according to the neutron stream item in the boundary of the calculated section, the second order Legendre polynomial weighted boundary stream, the transverse leakage item expansion coefficient calculated in the step g), and the neutron flux of the section calculated in the step h);
and k), repeating the steps d) to j) until the calculated result converges or reaches a given iteration number according to the updated boundary neutron stream, the boundary stream weighted by the second order Legendre polynomial, the node neutron flux and the characteristic value k eff, and outputting a final calculated result.
2. The neutron transport parallel computing method for optimizing transverse leakage term processing according to claim 1, wherein,
In the step a), the simulation model comprises geometric information, material information and nuclear reaction section information.
3. The neutron transport parallel computing method for optimizing transverse leakage term processing according to claim 1, wherein,
In the step b), the load variance of each parallel computing core is minimized and the surface area to volume ratio of the parallel computing area is minimized in the process of area decomposition.
4. The neutron transport parallel computing method for optimizing transverse leakage term processing according to claim 1, wherein,
In the step d), the second order Legendre polynomial weighted boundary streamThe calculation method of (1) is as follows:
Wherein phi (x 0, y, z) is the flux value at the coordinates (x 0, y, z), AndFor the second order Legendre polynomial, Δy k is the segment width of segment k in the y-direction, Δz k is the segment width of segment k in the z-direction, and x 0 is the x-direction coordinate value.
5. The neutron transport parallel computing method for optimizing transverse leakage term processing according to claim 1, wherein,
In the step g), the lateral leakage term expansion coefficientThe calculation method of (1) is as follows:
Wherein, the As the average leakage term for the segment k,A boundary stream weighted for the second order legendre polynomial at the left boundary of segment k,For a boundary stream weighted by a second order Legendre polynomial at the right boundary of segment k, deltax k is the width of segment k in the x-direction.
6. The neutron transport parallel computing method for optimizing transverse leakage term processing according to claim 1, wherein,
In the step i), the calculation method of the characteristic value k eff is as follows:
Calculating, by each of the parallel computing cores, a total number of fission neutron production of all of the segments allocated Wherein g is the neutron energy group number,For the fission neutron production section of the g-th energy group of the segment k, phi k,g is the neutron flux of the g-th energy group of the segment k, V k is the volume of the segment k, the characteristic value
7. The neutron transport parallel computing method for optimizing transverse leakage term processing according to claim 1, wherein,
In the step k), the criterion of convergence is that the difference value between the neutron flux, the neutron source term, the boundary neutron stream, the second order legendre polynomial weighted boundary stream and the eigenvalue k eff in two rounds of calculation is smaller than a given threshold value.
8. A computing device comprising a memory, a plurality of parallel computing cores, wherein the memory stores a computing program that, when executed by the parallel computing cores, is capable of implementing the neutron transport parallel computing method of optimizing lateral leakage term processing of any one of claims 1 to 7.
9. The computing device of claim 8, wherein the computing program comprises a modeling and initialization module, a block response computing module, a single block model-based higher order leakage term computing module, a source term and eigenvalue solving module, and a parallel scheduling module, wherein,
The modeling and initializing module is used for reading input information of a calculation object, and executing segment division, segment dyeing, parallel region decomposition and calculation result initialization;
The node response calculation module is used for defining a boundary stream weighted by a second order Legendre polynomial, and according to a node response matrix, taking neutron source items and neutron stream data in the previous iteration as inputs, and solving the node boundary neutron stream, a node average leakage item and the boundary stream weighted by the second order Legendre polynomial;
The high-order leakage term calculation module based on the single-section block model is used for solving the expansion coefficient of the transverse leakage term by taking the average leakage term of the single section block and the boundary flow weighted by the second order Legendre polynomial at the boundary of the section block as constraint conditions;
The source term and eigenvalue solving module is used for solving neutron flux, eigenvalue k eff and neutron source term by taking the neutron flow at the section boundary, the average boundary flow weighted by the second order Legend polynomial and the expansion coefficient of the transverse leakage term as inputs according to a neutron balance equation;
the parallel scheduling module is used for parallel scheduling, message communication and result collection and broadcasting of neutron transport calculation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411639704.3A CN119597461B (en) | 2024-11-18 | 2024-11-18 | Neutron transport parallel calculation method and computing device for optimizing lateral leakage term processing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411639704.3A CN119597461B (en) | 2024-11-18 | 2024-11-18 | Neutron transport parallel calculation method and computing device for optimizing lateral leakage term processing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN119597461A CN119597461A (en) | 2025-03-11 |
| CN119597461B true CN119597461B (en) | 2025-09-30 |
Family
ID=94837944
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411639704.3A Active CN119597461B (en) | 2024-11-18 | 2024-11-18 | Neutron transport parallel calculation method and computing device for optimizing lateral leakage term processing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN119597461B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112632822A (en) * | 2020-12-21 | 2021-04-09 | 中国核动力研究设计院 | Nuclear reactor neutron flux obtaining method and device based on three-dimensional leakage item segmentation |
| CN113673116A (en) * | 2021-09-01 | 2021-11-19 | 上海交通大学 | Three-dimensional quasi-transportation acceleration method aiming at uniform geometric variable block method |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8117013B2 (en) * | 2006-12-11 | 2012-02-14 | The United States Of America As Represented By The Adminstrator Of The National Aeronautics And Space Administration | Apparatus, method and program storage device for determining high-energy neutron/ion transport to a target of interest |
| KR102261185B1 (en) * | 2019-11-15 | 2021-06-07 | 울산과학기술원 | A group constant generation method using stochastic theory of neutron transport and a group constant generation device |
| CN115048810A (en) * | 2022-07-12 | 2022-09-13 | 中国核动力研究设计院 | Three-dimensional neutron transport equation calculation method and system based on linear source acceleration |
| CN116340709A (en) * | 2023-03-29 | 2023-06-27 | 西安交通大学 | A Calculation Method for Steady State Neutron Diffusion in PWR Core with Hexagonal Modules |
| CN118332795A (en) * | 2024-04-12 | 2024-07-12 | 上海交通大学 | A fast variational block implementation method for the first-order hyperbolic neutron transport equation |
-
2024
- 2024-11-18 CN CN202411639704.3A patent/CN119597461B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112632822A (en) * | 2020-12-21 | 2021-04-09 | 中国核动力研究设计院 | Nuclear reactor neutron flux obtaining method and device based on three-dimensional leakage item segmentation |
| CN113673116A (en) * | 2021-09-01 | 2021-11-19 | 上海交通大学 | Three-dimensional quasi-transportation acceleration method aiming at uniform geometric variable block method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN119597461A (en) | 2025-03-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111914464B (en) | Method and system for optimizing multi-resonance nuclide resonance simulation subgroup of reactor assembly | |
| CN107092784A (en) | A kind of method that burnup coupling is calculated that transports suitable for nuclear reactor | |
| US20240419874A1 (en) | Graphics processing unit (gpu)-based numerical simulation system and method for helicopter flow field (ff) | |
| CN112766609A (en) | Power consumption prediction method based on cloud computing | |
| JP2011040077A (en) | Method for modelling nuclear reactor core and corresponding computer program product | |
| Waibel et al. | Physics meets machine learning: coupling FFD with regression models for wind pressure prediction on high-rise facades | |
| CN119597461B (en) | Neutron transport parallel calculation method and computing device for optimizing lateral leakage term processing | |
| CN114996658B (en) | Projection-based hypersonic aircraft aerodynamic heat prediction method | |
| CN108108883B (en) | Clustering algorithm-based vehicle scheduling network elastic simplification method | |
| CN115292770B (en) | Optimization method and system for fuel cell stack channel structure | |
| CN106096183B (en) | A Multiple Parallel Method Based on Feature Line Method | |
| CN114239437A (en) | Time step acceleration method for refining transient neutron transport calculation | |
| CN113239516A (en) | Water turbine rotor multidisciplinary reliability design optimization method considering uncertainty | |
| CN119004839A (en) | Mask collaborative optimization method, computer device, readable storage medium and program product | |
| CN107423542A (en) | A kind of non-homogeneous leakage modification method for being applied to calculate by rod | |
| CN111817298B (en) | Multi-scheduling interval distributed energy scheduling method and system containing random wind energy | |
| CN114117917B (en) | Multi-objective optimization ship magnetic dipole array modeling method | |
| CN112152267A (en) | Power grid random reactive power optimization scheduling method considering source load uncertainty | |
| CN114091271A (en) | A simplified method, device, electronic device and storage medium for a device model | |
| CN115081113A (en) | An optimization method for grid stiffener structure based on multilevel set function parameterization | |
| JPH10239480A (en) | Core performance calculation method and apparatus | |
| CN113792476A (en) | An Alternative Model Method Based on Optimization-Adaptive Sparse Grid | |
| CN114913301A (en) | Hexahedron mesh self-adaption method based on posterior error estimation | |
| Mittal et al. | Mixed-Order Meshes through Rp-Adaptivity for Surface Fitting to Implicit Geometries | |
| CN119227404B (en) | A fast fuel management model for liquid metal fast reactors and its construction method and application |
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 | ||
| GR01 | Patent grant |