Ball bed reactor cross section parameter homogenization method and device, electronic equipment and storage medium

Abstract

This disclosure provides a method, apparatus, electronic device, and storage medium for homogenizing the cross-sectional parameters of a pebble bed reactor, relating to the field of nuclear reactor technology. It obtains the individual cross-sectional parameters of various fuel spheres in the reactor core to reflect the individual neutron reaction characteristics of different fuel spheres. Then, based on the actual mixing state of the fuel spheres within the core region, it calculates the neutron collision probability between different fuel sphere groups to match the actual neutron transport scenario in the reactor core. Subsequently, based on this collision probability, it establishes and solves the neutron flux density distribution equation to obtain the accurate neutron flux density of each fuel sphere group under different energy groups. Finally, based on the principle of reaction rate conservation, it combines the volume fraction of each fuel sphere group with the corresponding neutron flux density for weighted fusion to generate regional homogenized cross-sectional parameters. Therefore, it can solve the problems of inaccurate regional homogenized cross-sectional parameters and large calculation errors in the core neutron flux and power distribution in existing technologies.

Description

Technical Field

[0001] This disclosure relates to the field of nuclear reactor technology, and in particular to a method and apparatus for homogenizing cross-sectional parameters of a pebble bed reactor, electronic equipment, and storage medium. Background Technology

[0002] As the core reactor type of the fourth-generation nuclear energy system, the pebble bed high-temperature gas-cooled reactor is widely used in the field of advanced nuclear power generation. It constructs a core physical model of dynamic fuel mixing through the collaboration of spherical fuel elements and online refueling mechanism. The technical implementation covers the entire process of fuel sphere geometry configuration and neutron transport calculation, including key links such as component calculation, flux distribution modeling, and cross-sectional parameter homogenization.

[0003] Existing technologies often employ the volume averaging method in VSOP software to perform component calculations by establishing a hypothetical single fuel sphere model. However, this method cannot effectively correlate the energy group transport cross section with the geometric parameters of the fuel sphere, and can only reflect the transport characteristics of a single fuel sphere. It is difficult to adapt to the quantification requirements of flux density differences in mixed scenarios of multiple batches of fuel spheres.

[0004] In calculating the cross-sectional parameters for regional homogenization, existing schemes directly use simple weighting based on volume fractions, without considering the neutron transport interactions between different batches of fuel pellets (e.g., differences in enrichment and burnup levels). This leads to distortion in the neutron flux density distribution, and in regions with drastic changes in mixing ratios, such as the refueling zone, power calculation errors can reach 5-10%, easily causing core design deviations. Furthermore, existing technologies have not established a set of collision probability equations for energy group-batch coupling, making it impossible to accurately solve for the flux distribution of multiple energy groups. This, in turn, affects the accuracy of cross-sectional parameter superposition under the constraint of reaction rate conservation, ultimately resulting in insufficient reliability of core physics calculations. Summary of the Invention

[0005] This disclosure provides a method, apparatus, electronic device, and storage medium for homogenizing the cross-sectional parameters of a pebble bed. Its main objective is to at least partially address one of the technical problems in the related art.

[0006] According to a first aspect of this disclosure, a method for homogenizing the cross-sectional parameters of a pebble bed is provided, comprising: Obtain the single-sphere cross-sectional parameters of various fuel spheres in the reactor core; Calculate the neutron collision probability between different fuel sphere groups based on the actual mixing state of the fuel spheres within the reactor core region; Based on the neutron collision probability, the neutron flux density distribution equation is established and solved to obtain the neutron flux density of each fuel sphere under different energy groups. Based on the principle of reaction rate conservation, the volume fraction of each fuel pellet and the corresponding neutron flux density are weighted and fused to generate regional homogenization cross-sectional parameters.

[0007] Optionally, obtaining the single-sphere cross-sectional parameters of various fuel spheres in the reactor core includes: The microscopic cross-sectional parameters of each fuel sphere are calculated using a neutronics component calculation program. These parameters include the scattering cross-section, absorption cross-section, and fission neutron production cross-section.

[0008] Optionally, calculating the neutron collision probability between different fuel sphere groups includes: Based on the geometric characteristics and material composition of each fuel sphere, the escape probability and penetration probability of neutrons within the fuel sphere, as well as the proportion of the surface area of ​​each fuel sphere in the total surface area of ​​the region, are calculated respectively. Based on the escape probability, penetration probability, and surface area share, the neutron collision probability between different fuel spheres is determined comprehensively.

[0009] Optionally, establishing and solving the neutron flux density distribution equation based on the neutron collision probability includes: A set of collision probability equations was constructed with the neutron flux density of each fuel sphere group under the multi-energy group as the variable; The equations were solved by numerical iteration to obtain the neutron flux density distribution of each fuel pellet in each energy group.

[0010] Optionally, the step of weighted fusion of the volume fraction of each fuel sphere and the corresponding neutron flux density to generate regional homogenization cross-sectional parameters includes: The volume fraction of each fuel pellet is multiplied by the neutron flux density of its corresponding energy group, and this is used as a weighting factor. The cross-sectional parameters of each fuel pellet group are weighted and averaged according to the weighting factor to obtain the regional homogenized cross-sectional parameters.

[0011] Optional, also includes: Based on the requirements of core physics calculations, the fuel balls in the core area are divided into multiple groups according to burnup depth or composition characteristics; Based on the number and distribution of fuel balls in each group, the volume share and surface area share of each group are determined.

[0012] According to a second aspect of this disclosure, a device for homogenizing the cross-sectional parameters of a pebble bed is provided, comprising: The acquisition unit is used to acquire the single-sphere cross-sectional parameters of various fuel spheres in the reactor core; The calculation unit is used to calculate the neutron collision probability between different fuel sphere groups based on the actual mixing state of the fuel spheres in the core area. The solution unit is used to establish and solve the neutron flux density distribution equation based on the neutron collision probability, and obtain the neutron flux density of each fuel sphere under different energy groups; The generation unit is used to generate regional homogenization cross-sectional parameters by weighted fusion of the volume fraction of each fuel pellet and the corresponding neutron flux density based on the principle of reaction rate conservation.

[0013] Optionally, the acquisition unit is also used for: The microscopic cross-sectional parameters of each fuel sphere are calculated using a neutronics component calculation program. These parameters include the scattering cross-section, absorption cross-section, and fission neutron production cross-section.

[0014] Optionally, the computing unit is also used for: Based on the geometric characteristics and material composition of each fuel sphere, the escape probability and penetration probability of neutrons within the fuel sphere, as well as the proportion of the surface area of ​​each fuel sphere in the total surface area of ​​the region, are calculated respectively. Based on the escape probability, penetration probability, and surface area share, the neutron collision probability between different fuel spheres is determined comprehensively.

[0015] Optionally, the solver element is also used for: A set of collision probability equations was constructed with the neutron flux density of each fuel sphere group under the multi-energy group as the variable; The equations were solved by numerical iteration to obtain the neutron flux density distribution of each fuel pellet in each energy group.

[0016] Optionally, the generating unit is also used for: The volume fraction of each fuel pellet is multiplied by the neutron flux density of its corresponding energy group, and this is used as a weighting factor. The cross-sectional parameters of each fuel pellet group are weighted and averaged according to the weighting factor to obtain the regional homogenized cross-sectional parameters.

[0017] Optional, also includes: The determination unit is used to divide the fuel balls in the core area into multiple groups according to the burnup depth or composition characteristics based on the core physics calculation requirements; and to determine the volume share and surface area share of each group based on the number and distribution of fuel balls in each group.

[0018] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0019] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0020] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0021] The pebble bed reactor cross-section parameter homogenization method, apparatus, electronic equipment, and storage medium disclosed herein acquire the individual sphere cross-section parameters of various fuel spheres in the reactor core to reflect the individual neutron reaction characteristics of different fuel spheres. Then, based on the actual mixing state of the fuel spheres in the core region, the neutron collision probability between different fuel sphere groups is calculated to match the real neutron transport scenario in the reactor core. Subsequently, based on this collision probability, a neutron flux density distribution equation is established and solved to obtain the accurate neutron flux density of each fuel sphere group under different energy groups. Finally, based on the principle of reaction rate conservation, combined with the volume fraction of each fuel sphere group and... By weighting and fusing neutron flux densities to generate regional homogenization cross-section parameters, this approach can solve the problems in existing technologies where the use of a hypothetical single-fuel sphere model, neglecting neutron transport interactions between different fuel sphere groups, failing to accurately solve for multi-energy group neutron flux densities, and relying solely on simple weighting based on volume fractions leads to inaccurate regional homogenization cross-section parameters and large calculation errors in core neutron flux and power distribution. This improves the accuracy of regional homogenization cross-section parameter calculations, thereby enhancing the reliability of core neutron flux density and power distribution calculations and preventing core design deviations caused by parameter errors.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0023] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 A schematic flowchart illustrating a method for homogenizing cross-sectional parameters of a ball bed assembly, provided in an embodiment of this disclosure; Figure 2 This is a schematic diagram of the structure of a ball bed stack cross-sectional parameter homogenization device provided in an embodiment of the present disclosure; Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0024] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0025] The following description, with reference to the accompanying drawings, outlines a method and apparatus for homogenizing the cross-sectional parameters of a ball bed stack, an electronic device, and a storage medium according to embodiments of the present disclosure.

[0026] Figure 1 This is a schematic flowchart illustrating a method for homogenizing the cross-sectional parameters of a ball bed according to an embodiment of this disclosure.

[0027] like Figure 1 As shown, the method includes the following steps: Step 101: Obtain the single-sphere cross-sectional parameters of various fuel spheres in the reactor core.

[0028] In the embodiments of this disclosure, in order to accurately calculate the homogenization cross-sectional parameters of the reactor core region, it is necessary to first obtain the individual cross-sectional parameters of each type of fuel ball in the reactor core. The individual cross-sectional parameters are key parameters reflecting the nuclear reaction characteristics of each fuel ball during neutron transport, such as scattering, absorption, and fission. Their core function is to clarify the individual neutron reaction differences of different types of fuel balls, providing basic data support for subsequent calculations based on the actual fuel mixing state in the reactor core, and ensuring that subsequent calculations can adapt to the actual scenario of diverse fuel ball types in the reactor core. As one implementation method, a component calculation program with neutron transport simulation function can be used to model and calculate each type of fuel ball separately to obtain the above-mentioned individual cross-sectional parameters. The obtained parameters may specifically include scattering cross-section, absorption cross-section, and fission neutron production cross-section, etc.

[0029] By obtaining the single-sphere cross-sectional parameters of various fuel spheres, the differences in neutron reaction characteristics of different fuel spheres are fully reflected, avoiding the problem of ignoring individual differences when using a single hypothetical fuel sphere model in the existing technology. This lays a reliable data foundation for the subsequent construction of a calculation model that fits the actual reactor core, thereby improving the calculation accuracy of the regional homogenization cross-sectional parameters.

[0030] Step 102: Calculate the neutron collision probability between different fuel sphere groups based on the actual mixing state of the fuel spheres within the reactor core area.

[0031] In the embodiments of this disclosure, after obtaining the single-sphere cross-sectional parameters of various fuel spheres, it is necessary to calculate the neutron collision probability between different fuel sphere groups based on the actual mixing state of the fuel spheres in the core area (i.e., the distribution and quantity ratio of different types of fuel spheres in the area, reflecting information such as the actual fuel configuration of the core). The neutron collision probability is used to quantify the probability of the first collision after a neutron is transported from one group of fuel spheres to another group of fuel spheres. Its core is to establish the correlation between neutron transport between different fuel sphere groups by closely matching the actual fuel mixing information of the core, avoiding calculation deviations caused by deviating from the actual state of the core, and providing key transport characteristics for subsequent accurate solution of neutron flux density distribution. As one implementation method, the surface area share of each fuel sphere group, the escape probability of neutrons in the fuel spheres, and the penetration probability can be combined when calculating the neutron collision probability, but it is not limited to the specific calculation factors mentioned above.

[0032] By combining the actual mixing state of fuel spheres in the core region to calculate the neutron collision probability, the shortcomings of existing technologies that ignore the interaction of neutron transport between different fuel sphere groups are effectively avoided. This makes the calculation of neutron transport characteristics more consistent with the actual situation of the core, providing reliable support for obtaining accurate neutron flux density distribution in the future, and thus improving the rationality of the calculation of regional homogenization cross-section parameters.

[0033] Step 103: Based on the neutron collision probability, establish and solve the neutron flux density distribution equation to obtain the neutron flux density of each fuel sphere under different energy groups.

[0034] In the embodiments of this disclosure, after obtaining the neutron collision probabilities between different fuel spheres, a neutron flux density distribution equation is constructed based on these neutron collision probabilities. This equation is used to quantify the correlation between the neutron flux density and the neutron collision probability of each fuel sphere under different neutron energy groups. The different energy groups correspond to different ranges of neutron energy, which can fully reflect the influence of neutron energy differences on flux distribution. By solving this equation, the neutron flux density of each fuel sphere under each energy group can be obtained. The core is to establish a mathematical model that conforms to the neutron transport law by using the neutron collision probabilities that fit the actual reactor core, ensuring that the results reflect the differences in neutron distribution among different fuel spheres and different energy groups. As one implementation method, the neutron flux density distribution equation can take the form of a multi-group collision probability equation system, but is not limited to this specific type.

[0035] This solves the problem that existing technologies cannot accurately obtain the neutron flux density of each fuel sphere under multi-energy groups, providing accurate flux data for subsequent volume fraction weighted fusion, further ensuring the accuracy of regional homogenization cross-sectional parameter calculation, and avoiding subsequent calculation errors caused by flux data deviation.

[0036] Step 104: Based on the principle of reaction rate conservation, the volume fraction of each fuel pellet and the corresponding neutron flux density are weighted and fused to generate regional homogenization cross-sectional parameters.

[0037] In the embodiments of this disclosure, after obtaining the neutron flux density of each fuel pellet under different energy groups, based on the principle of reaction rate conservation (i.e., the principle that the total neutron reaction rate in the region is consistent with the sum of the neutron reaction rates of each fuel pellet), the volume fraction of each fuel pellet (reflecting the volume proportion of each fuel pellet in the core region, reflecting its spatial distribution weight) and the neutron flux density of the corresponding energy group (reflecting the neutron activity of each fuel pellet, reflecting its reaction contribution weight) are weighted and fused to finally generate a region homogenization section parameter. This parameter is used to represent the overall neutron reaction characteristics of the core region, providing a unified and realistic basic parameter for subsequent core physics calculations. As one implementation method, the weighted fusion process can be implemented by a weighted average formula based on volume fraction and neutron flux density, but is not limited to this specific calculation form.

[0038] This technology solves the problem of inaccurate regional homogenization cross-sectional parameters caused by simply weighting based on volume fraction and ignoring differences in neutron flux density in existing technologies. It enables the generated parameters to more accurately reflect the neutron reaction characteristics within the region, thereby improving the reliability of core neutron flux density and power distribution calculations and avoiding core design errors caused by parameter deviations.

[0039] The pebble bed reactor cross-section parameter homogenization method disclosed herein obtains the individual cross-section parameters of various fuel spheres in the reactor core to reflect the individual neutron reaction characteristics of different fuel spheres. Then, based on the actual mixing state of the fuel spheres within the reactor core region, it calculates the neutron collision probability between different fuel sphere groups to match the real neutron transport scenario in the reactor core. Subsequently, based on this collision probability, it establishes and solves the neutron flux density distribution equation to obtain the accurate neutron flux density of each fuel sphere group under different energy groups. Finally, based on the principle of reaction rate conservation, it combines the volume fraction of each fuel sphere group with the corresponding neutron flux density for weighted fusion to generate the regional homogenization cross-section parameters. Therefore, it can solve the problems in existing technologies where the use of a hypothetical single fuel sphere model, neglecting the neutron transport interaction between different fuel sphere groups, failing to accurately solve for the neutron flux density of multiple energy groups, and relying solely on simple weighting based on volume fraction leads to inaccurate regional homogenization cross-section parameters and large calculation errors in the neutron flux and power distribution of the reactor core. This method improves the calculation accuracy of the regional homogenization cross-section parameters, thereby enhancing the reliability of the calculation of the neutron flux density and power distribution of the reactor core, and avoiding core design deviations caused by parameter errors.

[0040] As a specific embodiment of this disclosure, based on the basic scheme, the method of obtaining the single-sphere cross-sectional parameters of various fuel spheres in the reactor core is further defined as follows: calculating the micro-section parameters of each fuel sphere by means of a neutronics component calculation program, wherein the micro-section parameters include the scattering cross-section, the absorption cross-section, and the fission neutron production cross-section.

[0041] Specifically, when obtaining the single-sphere cross-sectional parameters of various fuel spheres in the reactor core, a neutronics assembly calculation program is used to perform specific calculation operations. This neutronics assembly calculation program is preferably a Monte Carlo-type calculation program with high-precision neutron transport simulation capabilities, such as NECP-MCX or Serpent. Before the calculation, the three-dimensional structure of each fuel sphere needs to be constructed based on its actual structural parameters (such as fuel sphere radius, fuel particle distribution, coating thickness, and graphite matrix size) and material composition (such as fuel nuclide enrichment, coating material composition, and graphite matrix density). The program generates a geometric model and imports it into a nuclear database that conforms to nuclear data standards (such as the ENDF / B series or JENDL series nuclear databases). During the calculation, the program tracks the transport path of neutrons in each fuel sphere model, and counts the event probabilities of scattering, absorption, and fission reactions between neutrons and various nuclides in the fuel sphere. Finally, it outputs the microscopic cross-sectional parameters corresponding to each type of fuel sphere. The microscopic cross-sectional parameters explicitly include the scattering cross-section reflecting the probability of neutron scattering reaction, the absorption cross-section reflecting the probability of neutron absorption reaction, and the fission neutron production cross-section reflecting the number of neutrons produced by the fission reaction.

[0042] By combining a professional neutronics component calculation program with actual fuel sphere parameters for modeling, the calculation accuracy of microscopic cross-sectional parameters was ensured. At the same time, the cross-sectional parameters covering three key reactions were clearly defined, providing comprehensive and reliable basic data for subsequent neutron collision probability calculation and neutron flux density solution, effectively avoiding subsequent calculation deviations caused by missing or insufficient accuracy of basic cross-sectional parameters.

[0043] As a specific embodiment of this disclosure, based on the basic scheme, the calculation of the neutron collision probability between different fuel spheres is further defined as follows: according to the geometric characteristics and material composition of each fuel sphere, the escape probability, penetration probability and the proportion of the surface area of ​​each fuel sphere in the total surface area of ​​the region are calculated respectively; based on the escape probability, penetration probability and surface area proportion, the neutron collision probability between different fuel spheres is comprehensively determined.

[0044] Specifically, when calculating the neutron collision probability between different fuel spheres, key parameters are first calculated based on the geometric characteristics (such as fuel sphere radius and spherical structure dimensions) and material composition (such as fuel nuclide type and matrix material composition, which determine the neutron transport characteristics within the sphere). The escape probability of a neutron within a fuel sphere is quantified by combining the transport cross-section (reflecting the material's ability to impede neutrons) and radius of the sphere, determining the probability that a neutron escapes the sphere without any collision. The penetration probability, based on the same transport cross-section and radius parameters, is calculated to determine the probability that a neutron penetrates the sphere wall without collision after entering the sphere. The calculation of the surface area share of each fuel sphere group requires first obtaining the total surface area of ​​the group based on the surface area of ​​a single sphere (derived from the sphere radius) and the number of fuel spheres in the group, then dividing this total surface area by the total surface area of ​​all fuel sphere groups within the core region to determine the surface area share of that group. Subsequently, based on the escape probability (reflecting the possibility of neutrons leaving the source sphere), penetration probability (reflecting the possibility of neutrons entering the target sphere), and surface area share (reflecting the spatial proportion of the target sphere) obtained from the above calculations, coupled calculations were performed according to the physical correlation of neutron transport to comprehensively determine the neutron collision probability between different fuel spheres.

[0045] By disassembling and accurately calculating the key sub-parameters affecting the neutron collision probability, and fully incorporating the geometric and material properties of the fuel spheres, the calculation of the collision probability is made more consistent with the actual neutron transport process. This effectively avoids the collision probability deviation caused by simplifying the parameters and provides a reliable premise for the accurate solution of the subsequent neutron flux density distribution.

[0046] As a specific embodiment of this disclosure, based on the basic scheme, the establishment and solution of the neutron flux density distribution equation based on the neutron collision probability is further defined, including: constructing a set of collision probability equations with the neutron flux density of each fuel sphere under multiple energy groups as variables; and solving the set of equations by numerical iteration method to obtain the neutron flux density distribution of each fuel sphere under each energy group.

[0047] Specifically, when establishing and solving the neutron flux density distribution equation based on neutron collision probability, a set of collision probability equations is first constructed. This set of equations uses the neutron flux density of each fuel sphere in multiple energy groups (i.e., multiple energy groups divided according to neutron energy ranges) as the core variable. Each equation in the set corresponds to a certain energy group of a fuel sphere. The equations are coupled with the neutron transport relationship between different fuel spheres and different energy groups through neutron collision probability. The left side of the equation reflects the total amount of neutron absorption and leakage in the energy group of the fuel sphere, while the right side includes the amount of neutrons generated by the fission of the fuel sphere and the amount of neutrons transferred to the energy group of the fuel sphere by scattering from other energy groups of the fuel sphere. This ensures that the set of equations fully reflects the generation, transport and consumption process of neutrons in the reactor core. The equations were then solved using a numerical iterative method, with the source iteration method being preferred. An initial neutron source distribution (e.g., the initial flux density of each energy group in each fuel sphere) was assumed and substituted into the equations to calculate the flux density for the first iteration. The neutron source distribution was then updated based on this flux density, and the calculation was repeated until the relative deviation of the flux densities of each energy group in each fuel sphere obtained from two adjacent iterations was less than a preset convergence threshold (e.g., 10). -5 The output at this point is the neutron flux density distribution of each fuel sphere in each energy group.

[0048] By constructing a set of collision probability equations coupled with multi-energy groups and multi-fuel spheres, the complex correlation of neutron transport is accurately characterized. The numerical iteration method is combined to ensure the convergence and accuracy of the solution, effectively avoiding flux density deviation caused by simplified solution, and providing key data support for the accurate generation of subsequent regional homogenization cross-sectional parameters.

[0049] As a specific embodiment of this disclosure, based on the basic scheme, the method of weighted fusion of the volume fraction of each fuel sphere and the corresponding neutron flux density to generate regional homogenization cross-sectional parameters is further defined as follows: multiplying the volume fraction of each fuel sphere by the neutron flux density of its corresponding energy group as a weighting factor; and weighting the cross-sectional parameters of each fuel sphere according to the weighting factor to obtain the regional homogenization cross-sectional parameters.

[0050] Specifically, when performing weighted fusion by combining the volume share of each fuel sphere with its corresponding neutron flux density, the volume share of each fuel sphere is first determined. This share is the ratio of the total volume of a fuel sphere to the total volume of all fuel spheres within the target calculation area of ​​the reactor core. It can be calculated by obtaining the number of spheres and the volume of a single sphere (derived from the fuel sphere radius) through core geometry modeling. Then, for each energy group, the volume share of each fuel sphere in that energy group is directly multiplied by its corresponding neutron flux density (i.e., the neutron flux density of each sphere in that energy group obtained previously) to obtain the weighting factor of that sphere in that energy group. This factor simultaneously covers the spatial proportion of the sphere and the neutron activity level. Subsequently, based on the single-sphere cross-sectional parameters of each fuel sphere (consistent with the previously obtained microscopic cross-sectional parameters such as scattering and absorption cross-sections), for each type of cross-sectional parameter in each energy group, the sum of "weighting factor × corresponding cross-sectional parameter" of all fuel spheres is calculated. This sum is then divided by the sum of the weighting factors of all fuel spheres in that energy group to obtain the regional homogenization result of that type of cross-sectional parameter in that energy group. All types of homogenized cross-sectional parameters of all energy groups together constitute the final regional homogenized cross-sectional parameters.

[0051] By using a weighting factor that couples volume fraction with neutron flux density, the drawback of relying solely on volume fraction weighting and ignoring differences in neutron activity is avoided. The weighted averaging process accurately matches energy groups and cross-section types, enabling the regional homogenization cross-section parameters to truly reflect the actual contribution of each sphere group to the regional neutron reaction, further improving the accuracy of core power distribution and neutron flux distribution calculations.

[0052] As a specific embodiment of this disclosure, based on the basic scheme, the embodiments of this disclosure further include: dividing the fuel balls in the core area into multiple groups according to the burnup depth or composition characteristics based on the core physics calculation requirements; and determining the volume share and surface area share of each group based on the number and distribution of fuel balls in each group.

[0053] Specifically, before performing the relevant calculations for the basic scheme, the grouping and share determination of fuel spheres must be completed according to the core physics calculation requirements. When grouping, if the grouping is based on burnup depth, fuel spheres with the same or similar burnup depth (e.g., 0-4 GWd / tU, 4-8 GWd / tU) should be grouped together based on the residence time of the fuel spheres in the core and the degree of fission nuclide consumption. If the grouping is based on compositional characteristics, fuel spheres with consistent or similar compositional properties should be grouped together based on the enrichment degree of fuel nuclides within the fuel sphere (e.g., 3%, 5%), whether combustible poisons (e.g., boron, gadolinium) have been added, and the purity of the graphite matrix. After grouping, the number of fuel balls in each group within the target calculation area of ​​the reactor core is counted. Combined with the volume of a single ball, the total volume of fuel balls in each group is obtained (number of groups × volume of a single ball). The total volume of each group is then divided by the total volume of fuel balls in all groups in the area to obtain the volume share of each group. At the same time, based on the surface area of ​​a single ball, the total surface area of ​​fuel balls in each group is calculated (number of groups × surface area of ​​a single ball). The total surface area of ​​each group is then divided by the total surface area of ​​fuel balls in all groups in the area to determine the surface area share of each group.

[0054] By precisely grouping fuel spheres according to their burnup or composition characteristics, the grouping is made to fit the actual physicochemical properties of the fuel spheres. The volume and surface area shares calculated by combining the quantity and geometric parameters provide accurate weight data for subsequent neutron collision probability calculations and weighted fusion, avoiding subsequent calculation deviations caused by grouping ambiguity or share errors, and further ensuring the overall calculation accuracy.

[0055] It should be noted that the embodiments of this disclosure may include multiple steps. For ease of description, these steps are numbered, but these numbers are not a limitation on the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of this disclosure do not limit this.

[0056] Corresponding to the above-described method for homogenizing the cross-sectional parameters of a pebble bed, this disclosure also proposes a device for homogenizing the cross-sectional parameters of a pebble bed. Since the device embodiments of this disclosure correspond to the method embodiments described above, details not disclosed in the device embodiments can be referred to the method embodiments described above, and will not be repeated here.

[0057] Figure 2 This is a schematic diagram of a device for homogenizing the cross-sectional parameters of a ball bed according to an embodiment of this disclosure, as shown below. Figure 2 As shown, it includes: Acquisition unit 21 is used to acquire the single-sphere cross-sectional parameters of various fuel spheres in the reactor core; Calculation unit 22 is used to calculate the neutron collision probability between different fuel ball groups based on the actual mixing state of the fuel balls in the core area; Solver 23 is used to establish and solve the neutron flux density distribution equation based on the neutron collision probability, and obtain the neutron flux density of each fuel sphere under different energy groups; The generation unit 24 is used to generate regional homogenization cross-sectional parameters by weighted fusion of the volume fraction of each fuel pellet and the corresponding neutron flux density based on the principle of reaction rate conservation.

[0058] The pebble bed reactor cross-section parameter homogenization device disclosed herein obtains the single-sphere cross-section parameters of various fuel spheres in the reactor core to reflect the individual neutron reaction characteristics of different fuel spheres. Then, based on the actual mixing state of the fuel spheres within the reactor core region, it calculates the neutron collision probability between different fuel sphere groups to match the real neutron transport scenario in the reactor core. Subsequently, based on this collision probability, it establishes and solves the neutron flux density distribution equation to obtain the accurate neutron flux density of each fuel sphere group under different energy groups. Finally, based on the principle of reaction rate conservation, it combines the volume fraction of each fuel sphere group with the corresponding neutron flux density for weighted fusion to generate the regional homogenization cross-section parameters. Therefore, it can solve the problems in existing technologies where the use of a hypothetical single-fuel sphere model, neglecting the neutron transport interaction between different fuel sphere groups, failing to accurately solve for the neutron flux density of multiple energy groups, and relying solely on simple weighting based on volume fraction leads to inaccurate regional homogenization cross-section parameters and large calculation errors in the neutron flux and power distribution of the reactor core. This achieves the technical effect of improving the calculation accuracy of the regional homogenization cross-section parameters, thereby improving the reliability of the calculation of the neutron flux density and power distribution of the reactor core, and avoiding core design deviations caused by parameter errors.

[0059] Furthermore, in one possible implementation of this embodiment, the acquisition unit 21 is also used for: The microscopic cross-sectional parameters of each fuel sphere are calculated using a neutronics component calculation program. These parameters include the scattering cross-section, absorption cross-section, and fission neutron production cross-section.

[0060] Furthermore, in one possible implementation of this embodiment, the computing unit 22 is also used for: Based on the geometric characteristics and material composition of each fuel sphere, the escape probability and penetration probability of neutrons within the fuel sphere, as well as the proportion of the surface area of ​​each fuel sphere in the total surface area of ​​the region, are calculated respectively. Based on the escape probability, penetration probability, and surface area share, the neutron collision probability between different fuel spheres is determined comprehensively.

[0061] Furthermore, in one possible implementation of this embodiment, the solving unit 23 is also used for: A set of collision probability equations was constructed with the neutron flux density of each fuel sphere group under the multi-energy group as the variable; The equations were solved by numerical iteration to obtain the neutron flux density distribution of each fuel pellet in each energy group.

[0062] Furthermore, in one possible implementation of this embodiment, the generation unit 24 is also used for: The volume fraction of each fuel pellet is multiplied by the neutron flux density of its corresponding energy group, and this is used as a weighting factor. The cross-sectional parameters of each fuel pellet group are weighted and averaged according to the weighting factor to obtain the regional homogenized cross-sectional parameters.

[0063] Furthermore, in one possible implementation of this embodiment, such as Figure 2 As shown, it also includes: The determination unit 25 is used to divide the fuel balls in the core area into multiple groups according to the burnup depth or composition characteristics based on the core physics calculation requirements; and to determine the volume share and surface area share of each group based on the number and distribution of fuel balls in each group.

[0064] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and the principle is the same, so it is not limited in this embodiment.

[0065] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0066] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0067] like Figure 3 As shown, the electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 302 or a computer program loaded from storage unit 308 into RAM (Random Access Memory) 303. The RAM 303 may also store various programs and data required for the operation of the electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O (Input / Output) interface 305 is also connected to the bus 304.

[0068] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0069] The computing unit 301 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the ball bed revetment cross-section parameter homogenization method. For example, in some embodiments, the ball bed revetment cross-section parameter homogenization method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the aforementioned ball bed cross-section parameter homogenization method by any other suitable means (e.g., by means of firmware).

[0070] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0071] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0072] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0073] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0074] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0075] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0076] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0077] The various numerical designations such as "first," "second," etc., used in this disclosure are merely for ease of description and are not intended to limit the scope of the embodiments of this disclosure, nor do they indicate a sequential order.

[0078] At least one of the features described in this disclosure can also be described as one or more, and multiple features can be two, three, four or more, and this disclosure does not impose any limitations. In the embodiments of this disclosure, for a technical feature, the technical features in that technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", etc., and there is no sequential order or size order among the technical features described by "first", "second", "third", "A", "B", "C" and "D".

[0079] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0080] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for homogenizing the cross-sectional parameters of a ball bed stack, characterized in that, include: Obtain the single-sphere cross-sectional parameters of various fuel spheres in the reactor core; Calculate the neutron collision probability between different fuel sphere groups based on the actual mixing state of the fuel spheres within the reactor core region; Based on the neutron collision probability, the neutron flux density distribution equation is established and solved to obtain the neutron flux density of each fuel sphere under different energy groups. Based on the principle of reaction rate conservation, the volume fraction of each fuel pellet and the corresponding neutron flux density are weighted and fused to generate regional homogenization cross-sectional parameters.

2. The method according to claim 1, characterized in that, The acquisition of single-sphere cross-sectional parameters of various fuel spheres in the reactor core includes: The microscopic cross-sectional parameters of each fuel sphere are calculated using a neutronics component calculation program. These parameters include the scattering cross-section, absorption cross-section, and fission neutron production cross-section.

3. The method according to claim 1, characterized in that, The calculation of the neutron collision probability between different fuel spheres includes: Based on the geometric characteristics and material composition of each fuel sphere, the escape probability and penetration probability of neutrons within the fuel sphere, as well as the proportion of the surface area of ​​each fuel sphere in the total surface area of ​​the region, are calculated respectively. Based on the escape probability, penetration probability, and surface area share, the neutron collision probability between different fuel spheres is determined comprehensively.

4. The method according to claim 1, characterized in that, The process of establishing and solving the neutron flux density distribution equation based on the neutron collision probability includes: A set of collision probability equations was constructed with the neutron flux density of each fuel sphere group under the multi-energy group as the variable; The equations were solved by numerical iteration to obtain the neutron flux density distribution of each fuel pellet in each energy group.

5. The method according to claim 1, characterized in that, The process of weighted fusion of the volume fraction of each fuel pellet and the corresponding neutron flux density to generate regional homogenization cross-sectional parameters includes: The volume fraction of each fuel pellet is multiplied by the neutron flux density of its corresponding energy group, and this is used as a weighting factor. The cross-sectional parameters of each fuel pellet group are weighted and averaged according to the weighting factor to obtain the regional homogenized cross-sectional parameters.

6. The method according to claim 1, characterized in that, Also includes: Based on the requirements of core physics calculations, the fuel balls in the core area are divided into multiple groups according to burnup depth or composition characteristics; Based on the number and distribution of fuel balls in each group, the volume share and surface area share of each group are determined.

7. A device for homogenizing the cross-sectional parameters of a ball bed stack, characterized in that, include: The acquisition unit is used to acquire the single-sphere cross-sectional parameters of various fuel spheres in the reactor core; The calculation unit is used to calculate the neutron collision probability between different fuel sphere groups based on the actual mixing state of the fuel spheres in the core area. The solution unit is used to establish and solve the neutron flux density distribution equation based on the neutron collision probability, and obtain the neutron flux density of each fuel sphere under different energy groups; The generation unit is used to generate regional homogenization cross-sectional parameters by weighted fusion of the volume fraction of each fuel pellet and the corresponding neutron flux density based on the principle of reaction rate conservation.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

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