A method for multi-dimensional heterogeneous void fraction neutronics modeling of a helical petal fuel assembly

Abstract

This invention proposes a neutronics computational modeling method for multidimensional non-uniform void fraction in helical petal-shaped fuel assemblies. The method first constructs a geometric model of the fuel rods and the gas-liquid two-phase flow coolant region. Then, it performs axial-radial adaptive unrestricted partitioning of the coolant region and adjusts the scale according to the void fraction distribution characteristics. Next, it sets the axial baseline void fraction and radial correction coefficient for each sub-region and establishes a unified partitioning numbering rule. Subsequently, it constructs a void fraction exponential decay coupling model by combining gas-liquid two-phase flow theory and the secondary flow effect of the helical structure. The mixed density is obtained by coupling coolant density and boron concentration. Geometric and physical property information is stored in HDF5 format, and geometric consistency verification is completed. Finally, the partitioned modeling results and coupling analysis report are output through gas-liquid two-phase flow numerical simulation verification. This method provides a scientific, efficient, and accurate modeling solution for multiphysics coupling analysis of pressurized water reactor cores using helical petal-shaped fuel assemblies.

Description

Technical Field

[0001] This invention relates to the field of nuclear reactor neutron physics and thermo-hydraulic coupling analysis technology, and to a two-phase flow modeling method applicable to fuel assemblies with irregular geometric features, particularly to a neutronics calculation modeling method for multidimensional non-uniform void fraction of spiral petal-shaped fuel assemblies. Background Technology

[0002] Existing experimental studies have shown that under undersaturated boiling and subsequent flow boiling conditions, the coolant cavitation fraction within the runner exhibits a significantly non-uniform radial distribution. When the overall cavitation fraction is low, cavitation is mainly concentrated in the near-wall region of the cladding. As the cavitation fraction increases and flow boiling develops, cavitation gradually drifts towards the center of the runner. Under the influence of vortices, cavitation drift, and turbulent mixing, the cavitation distribution across the entire cross-section exhibits complex non-uniform characteristics. Data from existing pressurized water reactor runner and assembly test benchmarks (such as the international benchmark PSBT for pressurized water reactor runners and assemblies) indicate that assuming a simple uniform or linear distribution is insufficient to accurately reproduce this characteristic.

[0003] To address the aforementioned phenomena, existing literature has proposed exponential decay cavitation distribution models. These models assume that the cavitation fraction decreases exponentially from the outer surface of the cladding towards the center of the channel. By adjusting the peak value and decay coefficient, the volume-average cavitation fraction can be made consistent with experimental or benchmark calculations. These models essentially assume that the diffusion and condensation process of bubbles generated on the wall towards the liquid volume can be approximated as diffusion-drift behavior, making them simple and easy to apply in engineering analysis. However, traditional models are mostly designed for cylindrical fuel rod channels, failing to fully consider the influence of the fuel rod cross-sectional shape and channel geometry on cavitation distribution. Furthermore, they typically only model in the radial dimension, neglecting the non-uniformity in the axial and circumferential directions.

[0004] On the other hand, existing pressurized water reactor coolant cavitation modeling methods often employ a fixed number of regularly sized partitions in spatial discretization, failing to adaptively adjust the partition scale based on the actual cavitation fraction gradient. This makes it difficult to refine the description of regions with large cavitation gradients while maintaining controllable computational load. Furthermore, existing methods do not adequately consider the quantitative coupling between cavitation fraction and coolant density and boron concentration, lacking a systematic modeling process that can directly generate standardized data files and easily couple with gas-liquid two-phase flow numerical simulations and neutronics programs. For these reasons, it is essential to propose a multidimensional non-uniform cavitation fraction neutronics computational modeling method for helical petal-shaped fuel assemblies. This method adaptively partitions the coolant region axially and radially, introduces an exponentially decaying cavitation model considering the helical structure's influence, and couples it with coolant density and boron concentration to form a standardized data interface that can be directly used in numerical simulations. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies in describing the two-phase flow of coolant in petal-shaped helical fuel assemblies, including insufficient dimensionality, limited spatial resolution, incomplete coupling between void fraction and coolant density and boron concentration, and a lack of standardized data interfaces. This invention proposes a neutronics computational modeling method for the multidimensional non-uniform void fraction of helical petal-shaped fuel assemblies. Based on the geometry of helical petal-shaped fuel rods (such as FPF and TPF), this invention performs unrestricted axial and radial multidimensional partitioning of the coolant region. An exponential decay coupling model is used to describe the non-uniform distribution of void fraction, and the coolant density of each partition is calculated. Finally, a standard data file (such as HDF5) is generated, and the modeling results are comprehensively verified from neutronics and thermohydraulic perspectives through gas-liquid two-phase flow numerical simulation.

[0006] This invention is achieved through the following technical solution: This invention proposes a neutronics computational modeling method for the multidimensional non-uniform void fraction of a spiral petal-shaped fuel assembly, the method comprising: Discretization partitioning of spiral geometry: The coolant region is spatially discretized in the axial and radial directions to construct computational partitions suitable for spiral petal-shaped geometric configurations; Establishment of partitioned parameterized index and correction rules: Establish a coolant partition index mechanism, define the baseline cavitation share distribution trend of the axial level and the lateral correction rules of the radial sub-region; Constructing a coupled modified cavitation-density model: Based on the secondary flow effect induced by the spiral structure and the phase distribution characteristics, combined with the preset constitutive relation of gas-liquid two-phase flow, the local cavitation fraction and the corresponding mixing density parameters of each discrete partition are calculated. Adaptation solution: The mixing density parameters are mapped to the target neutronics calculation code to perform physical calculations for the multi-lobed spiral fuel assembly.

[0007] Furthermore, the spiral petal-shaped fuel assembly includes a fuel rod with a spiral feature, the cross-section of which is composed of multiple alternating convex and concave arcs; the cross-sectional geometry of the spiral petal-shaped fuel assembly includes any one or a combination of 2 to 8 petals.

[0008] Furthermore, in the process of constructing the discretized partitions of the spiral geometry, in the radial dimension, based on the radial gradient distribution characteristics of the cavitation fraction, the coolant region is adaptively divided into N annular or irregular geometric sub-regions, where N≥2; the radial width ratio of adjacent sub-regions is dynamically adjusted according to the intensity of the flow field gradient. In the axial dimension, the coolant region is divided into M hierarchical sub-regions, where M≥2; the height of the hierarchy is set in relation to the helical pitch of the fuel rods to capture the axial periodic fluctuations or overall transport trends of the cavitation fraction.

[0009] Furthermore, a parameterized partitioning system is established during the process of creating parameterized indexes and correction rules for partitions, specifically as follows: Axial reference distribution: The region is divided into multiple levels along the axial dimension, and the reference cavitation share of each level is defined. The reference cavitation fraction increases monotonically or is distributed according to a specific function along the flow direction. Radial Correction Distribution: The region is divided into multiple feature groups along the radial dimension, and a correction coefficient for each group relative to the baseline cavitation fraction is defined. .

[0010] Furthermore, the coolant partition indexing mechanism adopts a hierarchical coding format, assigning a unique material identifier to each discrete sub-volume unit. The identifier contains a combination of axial hierarchical code and radial grouping code to achieve automated mapping of material properties and geometric space.

[0011] Furthermore, the constructed coupled modified cavitation-density model is based on the following relationship to calculate the local cavitation fraction. : ;in, Represents the radial coordinates from the center of the component. The outer radius of the fuel rod cladding. This represents the peak value of the cavitation fraction, which is dynamically adjusted according to the gas-liquid two-phase flow conditions. The attenuation coefficient is obtained by fitting experimental data of gas-liquid two-phase flow or benchmark calculation results. Helix angle The correction function is used to reflect the influence of the axial helical structure on the cavitation distribution.

[0012] Furthermore, the calculation of the mixing density parameter for each discrete partition... Follow these steps: Based on the local cavitation fraction Combined with liquid phase density With gas phase density Calculate using the following formula: Simultaneously, a boron concentration correction term is introduced into the calculation to adjust the mixed density parameter. A boron concentration correction is performed, wherein the correction term adjusts the liquid density based on the product of a preset boron dilution coefficient and the boron concentration.

[0013] Furthermore, during the adaptation and solution process, geometric and physical property information is stored in HDF5 format and geometric consistency verification is completed. Finally, the partitioned modeling results and coupling analysis report are output through the gas-liquid two-phase flow numerical simulation verification method. Specifically, according to the encoding format and the cavitation-density model, the geometric boundaries, cavitation fraction, mixing density parameters, and operating parameters of each coolant sub-region are written into the HDF5 file in the form of a dataset. The consistency between the partitioned topology and the geometric model is verified by summing the volumes of all partitions and comparing them with the total coolant volume given by the geometric model. Subsequently, the HDF5 file is read using the gas-liquid two-phase flow numerical simulation program, and steady-state or transient calculations are performed on representative spiral petal components or sub-channels. The accuracy of the modeling method is verified by comparing the cavitation fraction and pressure drop distribution with the experimental benchmark or the upper-level fine calculation results.

[0014] The present invention also proposes an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the neutronics computational modeling method for multidimensional non-uniform void fraction of a spiral petal-shaped fuel assembly.

[0015] The present invention also proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the method for neutronics computational modeling of multidimensional non-uniform void fraction in a spiral petal-shaped fuel assembly.

[0016] The beneficial effects of this invention are: 1. This invention performs multi-dimensional unrestricted partitioning of the coolant region of the spiral petal-shaped component in both axial and radial dimensions. The number of partitions can be adaptively adjusted according to the cavitation gradient. The partitioning is made more dense in the near-wall and high gradient regions, which can more accurately describe the strong non-uniform distribution of coolant cavitation under undersaturated boiling and flow boiling conditions.

[0017] 2. The partitioning system established by this invention (such as axial layering, radial grouping and unified numbering rules) gives the initial value of the cavitation fraction of each partition a clear physical meaning and hierarchical structure, which facilitates parameter management and rapid retrieval in numerical simulation.

[0018] 3. The cavitation fraction calculation method proposed in this invention achieves simultaneous and accurate simulation of radial decay and circumferential undulations of cavitation distribution by coupling an exponential decay model from the outer surface of the cladding to the center of the channel with a correction function reflecting the influence of secondary flow in the helical structure. The advantages of this method are: the cavitation fraction prediction error is preferably no greater than 5%, providing high-precision density input; simultaneously, the framework of this invention has good versatility, is compatible with other empirical or mechanistic cavitation models, and greatly expands its application range in multi-lobed helical fuel assemblies.

[0019] 4. This invention explicitly couples the void fraction with the coolant density and boron concentration, uses a mixed density formula and provides a range of boron concentration correction coefficients, so that the obtained coolant density can be directly used for multiphysics field coupling calculations of neutronics and thermal-hydraulic systems, thereby improving the reliability of core safety analysis.

[0020] 5. This invention encapsulates the geometric and physical property information of multidimensional non-uniform partitions into a standard data file (such as HDF5) and provides geometric and volume consistency verification steps, which facilitates the interface with existing gas-liquid two-phase flow numerical simulation programs and system analysis programs, and has good standardization and scalability.

[0021] 6. The method of the present invention is optimized for the special geometry of helical petal-shaped fuel assemblies (including FPF, TPF, etc.), and can be directly applied under typical pressurized water reactor conditions. It helps to give full play to the advantages of high heat transfer and high self-supporting capacity of petal-shaped helical fuels, and provides accurate thermal-hydraulic boundary conditions for subsequent multi-physics field coupling analysis with neutronics and structural mechanics. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0023] Figure 1 This is a flowchart of a neutronics computational modeling method for a multidimensional non-uniform void fraction of a spiral petal-shaped fuel assembly, as implemented in this invention. Figure 2 This is a three-dimensional structural schematic diagram of a single four-petaled spiral fuel rod and its surrounding coolant channels, as implemented in this invention. Figure 3 This is a schematic diagram of the coolant region division in the xy plane at the z=60 section of the four-petaled spiral fuel assembly of the present invention. Figure 4 This is a schematic diagram of the coolant region division in the xy plane at the z=30 section of the four-petaled spiral fuel assembly of the present invention. Figure 5 This is a schematic diagram of the coolant region division in the xy plane at the z=0 section of the four-petaled spiral fuel assembly according to the present invention. Figure 6 This is a schematic diagram of the coolant region division in the xy plane at the z=-30 section of the four-petaled spiral fuel assembly of the present invention. Figure 7The image shows a planar neutron flux distribution cloud at a typical axial position for the four-petaled petal spiral fuel assembly (FHF assembly) of this invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] Example 1 The present invention discloses a neutronics computational modeling method for multidimensional non-uniform void fraction of a spiral petal-shaped fuel assembly. First, a geometric model of the fuel rod and the gas-liquid two-phase flow coolant region is constructed. Then, the coolant region is subjected to axial-radial adaptive unrestricted partitioning, and the scale is adjusted according to the void fraction distribution characteristics. Next, an axial reference void fraction and radial correction coefficient are set for each sub-region, and a unified partitioning numbering rule is established. Subsequently, a void fraction exponential decay coupling model is constructed by combining gas-liquid two-phase flow theory and the secondary flow effect of the spiral structure. The mixing density is obtained by coupling the coolant density and boron concentration. Then, the geometric and physical property information is stored in HDF5 format, and geometric consistency verification is completed. Finally, the partitioning modeling results and coupling analysis report are output through a gas-liquid two-phase flow numerical simulation verification method.

[0026] Furthermore, the cross-sectional shape of the spiral petal-shaped fuel rod includes, but is not limited to, any combination of 2 to 8 petals, such as a spiral three-petal (TPF) or four-petal (FPF) fuel assembly. A preferred embodiment of the method described in this invention uses a "four-petal fuel rod (FPF)" for verification calculations. The geometric parameters of this FPF fuel rod are configured as follows: concave arc radius R is 0.1876 cm, convex arc radius r is 0.0938 cm, the length l at the connection between the convex and concave arcs is 0.1076 cm, the fuel rod cladding thickness is 0.03 cm, the fuel is a 50% U-50% Zr alloy by mass, the fuel rod cladding material is 42CrNiMo, and the core active length is 120 cm. The above parameters are only the configuration for a specific verification example; the method of this invention is also applicable to spiral petal-shaped fuel assemblies with other size ratios and material combinations.

[0027] Furthermore, the multi-dimensional unrestricted partitioning of the coolant includes: dividing the coolant region into N concentric geometric sub-regions in the radial direction (where N≥2), the boundaries of the geometric sub-regions being adaptively set according to the radial gradient of the cavitation fraction, preferably such that the radial width ratio of adjacent regions is 1:(0.5~2); dividing the coolant region into M segmented sub-regions in the axial direction (where M≥2), the segment height of each segmented sub-region can be related to the helical pitch of the fuel rod, for example, the ratio is 1:(2~20), to adapt to the periodic fluctuation of the cavitation fraction along the axial direction, and to appropriately densify the high gradient region.

[0028] Furthermore, the axial reference cavitation rate of the coolant partition is set as follows: the coolant region is divided into multiple layers in the axial direction (e.g., four layers from 1 to 4). As an example configuration: the first layer corresponds to the top of the component or the outlet position, and the reference cavitation rate is a first preset value (e.g., 60%); the second layer corresponds to the upper-middle position, and the reference cavitation rate is a second preset value (e.g., 40%); the third layer corresponds to the lower-middle position, and the reference cavitation rate is a third preset value (e.g., 15%); the fourth layer corresponds to the bottom of the component or the inlet position, and the reference cavitation rate is a fourth preset value (e.g., 0%).

[0029] Furthermore, the radial correction factor for the coolant partition is set as follows: the coolant region is divided into multiple characteristic groups (e.g., four groups, 1 to 4) in the radial direction. As an example configuration: Group 1 is the central hot channel, whose cavitation share is increased by a positive correction value (e.g., 5%) based on the axial reference cavitation rate; Group 2 is increased by a small correction value (e.g., 2%); Group 3 remains unchanged; Group 4 is the edge cold channel, whose cavitation share is decreased by a negative correction value (e.g., 5%).

[0030] Furthermore, the numbering rule for the coolant sub-regions is as follows: a hierarchical index code containing axial hierarchy information and radial grouping information is established. As a specific implementation, for the sub-regions of radial groups 1 to 3, the numbering format is "two-digit axial layer number_radial group number + suffix 1 to 4"; for the sub-region of radial group 4, the numbering format is "two-digit axial layer number_4". This coding rule ensures a unique mapping between physical field data and geometric space.

[0031] Furthermore, the calculation of the cavitation fraction in the partitioned flow can employ an exponential decay coupled model. This model is based on the theory of cavitation distribution in gas-liquid two-phase flow and assumes that the cavitation fraction reaches its peak radially from the outer radius of the fuel rod cladding, subsequently decaying exponentially towards the center of the channel. To accurately reflect the influence of the helical petal-shaped fuel rod structure on the flow field, a helix angle correction function is introduced into the model. To characterize the secondary flow effect induced by the helical structure and its impact on phase distribution characteristics. The local cavitation fraction of each coolant region. Calculate using the following formula: In the formula, Represents the radial coordinates from the center of the component. The outer radius of the fuel rod cladding. This represents the peak value of the cavitation fraction, which is dynamically adjusted according to the gas-liquid two-phase flow conditions. The attenuation coefficient is obtained by fitting experimental data of gas-liquid two-phase flow or benchmark calculation results. Helix angle The correction function is used to reflect the influence of the axial helical structure on the cavitation distribution; when using this model for fitting calculation, the fitting error of the cavitation share model is preferably no greater than 5%. The method described in this invention is also compatible with other empirical or mechanistic models to calculate the local cavitation share; the above-mentioned exponential decay coupling model is only a preferred example configuration.

[0032] Furthermore, the coupling relationship between the coolant density, cavitation fraction, and boron concentration is as follows: Using a gas-liquid two-phase flow property database, the liquid phase density and gas phase density are determined separately, and the mixing density of each coolant sub-region is calculated using the following formula: Based on this, considering the effect of dissolved boron on the coolant density, the density is... Boron concentration correction is performed, and the ratio of the boron concentration correction term to the boron concentration is preferably 0.00001 to 0.00003 g·cm³. -3 / ppm, to obtain the corrected effective density It is used for multiphysics field coupling analysis of neutronics and thermal-hydraulic systems.

[0033] Furthermore, the process of generating the HDF5 file and performing geometric verification is as follows: according to the numbering rules and the cavitation-density model, the geometric boundaries, cavitation fraction, density, and operating parameters of each coolant sub-region are written into the HDF5 file in the form of a dataset; the consistency between the partition topology and the geometric model is verified by summing the volumes of all partitions and comparing them with the total coolant volume given by the geometric model; subsequently, the HDF5 file is read using a gas-liquid two-phase flow numerical simulation program, and steady-state or transient calculations are performed on representative spiral petal components or sub-channels. The accuracy of the method of the present invention is verified by comparing the cavitation fraction and pressure drop distribution of the numerical results with those of the experimental benchmark or the upper-level fine calculation results.

[0034] Example 2 like Figure 1As shown, this invention implements a neutronics computational modeling method for multidimensional non-uniform void fraction of a spiral petal-shaped fuel assembly. The overall process follows a logical progression of "geometric construction - spatial partitioning - parameter setting - model establishment - data encapsulation - verification and validation," specifically including: constructing a refined geometric model of the spiral petal-shaped fuel rod (this embodiment uses a four-petal FPF as an example, but the method is also applicable to three-petal TPFs or other multi-petal structures) and the gas-liquid two-phase flow coolant region → performing unrestricted adaptive partitioning of the coolant region in axial and radial dimensions → setting the axial baseline void fraction and radial correction coefficient, and establishing a unified partitioning numbering rule → constructing a void fraction exponential decay coupling model (also applicable to other models), achieving quantitative coupling with coolant density and boron concentration → generating a standardized HDF5 data file and completing geometric consistency verification → performing steady-state and transient verification through gas-liquid two-phase flow numerical simulation, and outputting the partitioning modeling results and a multiphysics coupling analysis report. The entire process is interconnected, ensuring the scientific validity, operability, and reliability of the modeling method.

[0035] As a specific verification example of the present invention, such as Figure 2 As shown, the fuel element used in this embodiment is a four-petaled petal-shaped spiral fuel rod (FPF). Its geometric and material parameters strictly refer to the adaptation standards of mature application scenarios. The specific configuration is as follows: the radius R of the concave arc is 0.1876 cm, the radius r of the convex arc is 0.0938 cm, the length l at the connection between the convex arc and the concave arc is 0.1076 cm, the cladding thickness is 0.03 cm, the fuel core is U-Zr alloy or dispersed fuel, and the cladding material is selected from 42CrNiMo alloy or other alloy materials with excellent mechanical properties and neutron characteristics. The height of the active region of the core is 120 cm, which has good compatibility with the active length of the small modular pressurized water reactor core. Based on the above precise parameters, a three-dimensional geometric model of a single FPF and its surrounding coolant channels is first established using professional geometric modeling software (such as SolidWorks and ANSYS DesignModeler). In the model, the fuel rods are spirally extended along the axial direction at a preset helical angle, and the external coolant channels are designed as cylinders. The coolant (H2O) flows from bottom to top in the channels, and the flow direction forms a specific angle with the spiral direction of the fuel rods to restore the flow field characteristics in the actual reactor.

[0036] Based on the geometric model of a single fuel rod, and following the standard layout specifications for pressurized water reactor (PWR) core assemblies, 72 FPFs were assembled in a compact hexagonal arrangement to form an FHF assembly. Simultaneously, six combustible poison rods with an inner radius of 0.2515 cm, six combustible poison rods with an inner radius of 0.483 cm, and one control rod with a radius of 0.89 cm were placed at specific locations within the assembly. These were then encased in two layers of hexagonal boxes (inner layer thickness 0.07 cm, outer layer side length 1.776 cm; outer layer thickness 0.165 cm, outer layer side length 5.89 cm, material E-110 alloy), ultimately forming a complete helical petal-shaped fuel assembly geometric model. This model fully reproduces the spatial relationships and dimensional matching of the various structures within the assembly, providing a precise geometric foundation for subsequent coolant zoning and cavitation distribution modeling.

[0037] In the spatial discretization stage, this invention breaks through the limitations of traditional fixed partitioning and implements multi-dimensional unrestricted adaptive partitioning of the coolant region in both the axial and radial directions. The core objective is to achieve a refined description in regions with large cavitation gradients while controlling the overall computational load. Specifically, in the radial direction, with the center of the assembly as the origin and the radius of the outer tangent circle of the fuel rod cladding (0.483 cm) as the reference benchmark, the coolant region surrounding the multiple fuel rods within the assembly is divided into N concentric annular sub-regions (in this embodiment, N=8 is taken based on the cavitation distribution gradient characteristics; in actual applications, N≥2 can be adjusted according to operating conditions). The boundaries of each concentric ring sub-region are not uniformly divided, but are adaptively set according to the radial gradient of the cavitation fraction. By fitting the experimental data and numerical simulation results, the radial width ratio of adjacent rings is determined to be preferably 1:(0.5~2). For example, a narrower radial width (0.05~0.1 cm) is set in the near-wall region of the shell (where the cavitation gradient is large), and a wider radial width (0.15~0.3 cm) is set in the center region of the sub-channel (where the cavitation gradient is gentle). This significantly improves the accuracy of describing the cavitation distribution while ensuring computational efficiency.

[0038] In the axial direction, considering the characteristics of the fuel rod helical pitch (in this embodiment, the helical pitch is adapted to the active length), the coolant region is divided into M segmented sub-regions along the flow direction (in this embodiment, M=12, but M≥2 can be flexibly adjusted). The segment height of each segmented sub-region is not equal, but is correlated with the helical pitch of the fuel rod, with the ratio of segment height to helical pitch set to 1:(2~20). For example, in the upper-middle region where the void fraction fluctuates drastically along the axial direction, the segment height is set to 5~8cm to achieve denser segmentation; in the region near the inlet where the void fraction is low and changes gradually, the segment height is set to 10~15cm to balance computational efficiency. This axial partitioning method can accurately adapt to the periodic fluctuation characteristics of the void fraction along the axial direction, avoiding the distortion problem in the description of high-gradient regions caused by uniform segmentation.

[0039] like Figures 3-6 The figures illustrate the coolant region partitioning effect in the xy plane at four typical axial cross-sections (z = 60 cm, z = 30 cm, z = 0 cm, and z = -30 cm) of the four-petal spiral fuel assembly in this embodiment of the invention. It is clearly shown that the concentric ring partitions in the radial direction fit well with the petal-shaped cross-section of the fuel rod. The partition boundaries are denser in the near-wall region corresponding to the outward convex arc of the fuel rod, while they are relatively sparse in the gap region formed by the subchannel center and the inward concave arc of the fuel rod, fully demonstrating the core advantage of adaptive partitioning. The consistency between the number of partitions and their boundary positions in different axial cross-sections ensures that the cross-combination of axial and radial partitions can form a continuous and complete coolant sub-region network in three-dimensional space, laying a spatial foundation for the subsequent accurate assignment of cavitation fraction and density.

[0040] After completing the spatial partitioning, it is necessary to set initial parameters with clear physical meaning for the cavitation fraction of each coolant sub-region. In this embodiment, the parameter setting is achieved through a combination of "axial reference cavitation rate + radial correction coefficient". Specifically, in the axial direction, according to the boiling development law of the coolant during pressurized water reactor operation, the coolant region is divided into 4 levels from bottom to top (inlet to outlet), each corresponding to a different reference cavitation rate: Level 4 (bottom / inlet, z = -60 to -30 cm), the coolant is in a non-boiling state, and the reference cavitation rate is set to 0%; Level 3 (lower middle, z = -30 to 0 cm), the coolant begins to enter the undersaturated boiling stage, and the reference cavitation rate is set to 15%; Level 2 (upper middle, z = 0 to 30 cm), the flow boiling is fully developed, and the reference cavitation rate is set to 40%; Level 1 (top / outlet, z = 30 to 60 cm), the boiling degree is the highest, and the reference cavitation rate is set to 60%. The baseline cavitation rate configuration references typical data from the PSBT test baseline, ensuring the rationality of the initial parameters.

[0041] In the radial direction, considering the differences in the thermal characteristics of the coolant channels, the coolant region is divided into four characteristic groups: Group 1 is the central hot channel region, which has the highest heat transfer intensity and the largest amount of cavitation generated, and is given a 5% positive correction value based on the corresponding axial reference cavitation rate; Group 2 is the medium-high cavitation region, located between the central hot channel and the middle region, with moderate heat transfer intensity, and is given a 2% minor correction value; Group 3 is the medium cavitation region, located in the middle of the coolant channel, with relatively stable thermal conditions, and the cavitation share remains unchanged at the axial reference value; Group 4 is the edge cold channel region, close to the component shell, with the lowest heat transfer intensity and the least amount of cavitation generated, and is given a 5% negative correction value based on the axial reference cavitation rate. Through the cross-combination of axial layers and radial groups, each coolant sub-region obtains a unique initial target cavitation rate. For example, the sub-region combining the second axial layer (reference 40%) and the first radial group (+5%) has an initial target cavitation rate of 45%, which conforms to the thermal-hydraulic laws and provides a reasonable initial value for the subsequent fitting of the exponential decay model.

[0042] To achieve a unique mapping between physical field data and geometric space, and to facilitate the calling of numerical simulation programs and data management, this invention establishes a unified partitioning and numbering rule. This rule employs a hierarchical indexing coding method, integrating axial hierarchy information and radial grouping information. The specific format is as follows: For sub-regions in the 1st to 3rd radial groups, the numbering is in the form of "two-digit axial layer number_radial group number + suffix 1 to 4". For example, the four adjacent sub-regions in the 1st radial group of the 1st axial layer (code 01) are numbered 01_11, 01_12, 01_13, and 01_14 respectively. For sub-regions in the 4th radial group (edge ​​cold channels, relatively continuous spatial distribution), the numbering is in the form of "two-digit axial layer number_4". For example, the sub-region in the 4th radial group of the 3rd axial layer is numbered 03_4. This coding rule is concise and clear, enabling rapid location of the spatial position of sub-regions (axial layer + radial group) and facilitating the differentiation of different sub-regions within the same radial group, providing an efficient indexing method for subsequent data storage and retrieval in HDF5 files.

[0043] In the core step of cavitation modeling, this invention, based on the gas-liquid two-phase flow cavitation distribution theory and combined with the structural characteristics of the helical petal-shaped fuel assembly, constructs a coupled model for the exponential decay of cavitation fraction in different zones. The core assumption of this model is that the cavitation fraction reaches its peak in the radial direction from the outer radius of the fuel rod cladding and decays exponentially towards the center of the sub-channel. Simultaneously, a helical angle correction function is introduced to characterize the influence of the secondary flow induced by the helical structure of the petal-shaped fuel rod on the cavitation distribution. The cavitation fraction of each coolant sub-region is calculated as follows: .

[0044] In the formula, This represents the average radial coordinate (in cm) of the sub-region from the center of the component. The outer radius of the fuel rod cladding (in this embodiment, it is 0.483 cm + 0.03 cm = 0.513 cm). The peak value of the void fraction (unit: %) is dynamically adjusted according to the gas-liquid two-phase flow conditions (such as inlet temperature, pressure, and mass flow rate). In this embodiment, the peak value range is determined to be 65% to 85% based on the PSBT baseline data fitting. Attenuation coefficient (unit: cm) -1 The values ​​were obtained by fitting experimental data of gas-liquid two-phase flow or by fine calculations at the higher level. In this embodiment, the fitted values ​​are 0.8–1.2 cm. -1 This ensures that the radial decay trend of the cavitation fraction is consistent with the experimental pattern; Helix angle A correction function is used to reflect the perturbation effect of the secondary flow induced by the axial helical structure on the radial distribution of cavitation, enabling the model to simultaneously capture the radial attenuation characteristics and circumferential undulation features of the cavitation fraction. Through fitting and validation with PSBT experimental baseline data, the deviation of the volume-average cavitation fraction predicted by the model from the reference value is no greater than 5%.

[0045] In terms of coolant density calculation, this invention achieves explicit coupling between the cavitation fraction and the coolant density and boron concentration. First, using a gas-liquid two-phase flow property database (such as IAPWS-IF97), the liquid phase density is determined based on the current operating conditions (temperature 313℃, pressure 15.7MPa). It is 0.72 g / cm³ 3 gas phase density It is 0.03 g / cm³ 3 Subsequently, the mixing density of each coolant sub-region was calculated using the mixing density formula. The formula is as follows: .

[0046] After assigning values ​​to the cavitation fraction and effective density of each coolant sub-region, the relevant geometric and physical property information needs to be uniformly packaged into a standardized HDF5 data file for interfacing with existing gas-liquid two-phase flow numerical simulation programs (such as Fluent) and neutronics programs (such as OpenMC). The specific process is as follows: Following the aforementioned partitioning numbering rules, the geometric boundary parameters (radial inner boundary, radial outer boundary, axial start position, axial end position), calculated cavitation fraction values, calculated effective density values, and operating condition parameters (inlet temperature 277℃, outlet temperature 313℃, design pressure 15.7 MPa, boron concentration, etc.) of each sub-region are categorized and written into the HDF5 file in dataset form. The file structure adopts a hierarchical structure of "operating condition group - partition group - parameter dataset," for example, "Condition_1 / Zone_01_11 / void_fraction" corresponds to the cavitation fraction dataset of sub-region number 01_11 under operating condition 1.

[0047] To ensure the geometric accuracy of the partition modeling, geometric consistency verification is required: First, calculate the volume of each coolant sub-region (obtained by integrating the radial area and axial length of the sub-region), then sum the volumes of all partitions to obtain the total calculated volume of the coolant; compare this calculated volume with the total designed volume of the coolant region in the geometric model (in this embodiment, the total volume of the component minus the sum of the volumes of the fuel rods, combustible poison rods, control rods, and hexagonal boxes), requiring that the relative deviation between the two is no greater than 1%. If the deviation exceeds the range, return to the spatial partitioning stage to adjust the sub-region boundaries until the geometric consistency requirements are met.

[0048] Finally, the accuracy of the method of the present invention was verified using a gas-liquid two-phase flow numerical simulation program. The specific steps are as follows: read the geometric boundary, initial value of void fraction, effective density, and other data from the HDF5 file as input conditions for numerical simulation; select a representative spiral petal component or sub-channel and set boundary conditions (inlet mass flow rate, outlet pressure, wall heat flux density) consistent with the experimental benchmark; perform steady-state and transient numerical calculations respectively. The steady-state calculation is used to verify the spatial distribution accuracy of void fraction and density, and the transient calculation is used to verify the model's response characteristics to changes in operating conditions; compare the void fraction distribution, pressure drop distribution, and neutron flux distribution with the PSBT experimental benchmark or higher-level fine calculation results, where the local deviation of void fraction is no greater than 8%, the pressure drop deviation is no greater than 10%, and the neutron flux distribution trend is consistent.

[0049] like Figure 7As shown, a planar neutron flux distribution cloud map of the four-petaled petal spiral fuel assembly (FHF assembly) of this invention at a typical axial position (z = 30 cm) is presented. The figure shows a clear correlation between the neutron flux distribution and the coolant cavitation fraction distribution: the neutron flux is higher in the edge cold channel region (4th radial group) with a lower cavitation fraction, and relatively lower in the central hot channel region (1st radial group) with a higher cavitation fraction. This pattern is consistent with the basic principles of neutron physics, indicating that the cavitation fraction model established in this invention has good coupling compatibility with the neutron flux distribution, and can provide accurate thermo-hydraulic boundary conditions for neutron physics calculations.

[0050] As can be seen from the detailed implementation process described above, the neutronics computational modeling method for multidimensional non-uniform void fraction of helical petal-shaped fuel assemblies proposed in this invention not only achieves a refined description of the coolant region in the geometric construction and spatial partitioning stages, but also fully considers the influence of the helical structure and multi-parameter coupling relationships in the model building stage. Furthermore, through standardized data encapsulation and multi-dimensional verification, it ensures the engineering practicality and reliability of the method. This method effectively solves the problems of insufficient descriptive dimensions, limited spatial resolution, incomplete coupling, and lack of standardized interfaces in existing technologies, providing a scientific, efficient, and accurate modeling solution for multiphysics coupling analysis of pressurized water reactor cores using helical petal-shaped fuel assemblies.

[0051] The present invention also proposes an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the neutronics computational modeling method for multidimensional non-uniform void fraction of a spiral petal-shaped fuel assembly.

[0052] The present invention also proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the method for neutronics computational modeling of multidimensional non-uniform void fraction in a spiral petal-shaped fuel assembly.

[0053] The memory in this application embodiment can be volatile memory or non-volatile memory, or it can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory used in the methods described in this invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0054] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., high-density digital video discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0055] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0056] It should be noted that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuitry in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied as execution by a hardware decoding processor, or as a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0057] The foregoing has provided a detailed description of the neutronics computational modeling method for multidimensional non-uniform void fraction of a spiral petal-shaped fuel assembly proposed in this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for neutronics computational modeling of multidimensional non-uniform void fraction in a spiral petal-shaped fuel assembly, characterized in that, The method includes: Discretization partitioning of spiral geometry: The coolant region is spatially discretized in the axial and radial directions to construct computational partitions suitable for spiral petal-shaped geometric configurations; Establishment of partitioned parameterized index and correction rules: Establish a coolant partition index mechanism, define the baseline cavitation share distribution trend of the axial level and the lateral correction rules of the radial sub-region; Constructing a coupled modified cavitation-density model: Based on the secondary flow effect induced by the spiral structure and the phase distribution characteristics, combined with the preset constitutive relation of gas-liquid two-phase flow, the local cavitation fraction and the corresponding mixing density parameters of each discrete partition are calculated. Adaptation solution: The mixing density parameters are mapped to the target neutronics calculation code to perform physical calculations for the multi-lobed helical fuel assembly; In the process of constructing the discretized partitions of the spiral geometry, in the radial dimension, based on the radial gradient distribution characteristics of the cavitation fraction, the coolant region is adaptively divided into N annular or irregular geometric sub-regions, where N≥2; the radial width ratio of adjacent sub-regions is dynamically adjusted according to the intensity of the flow field gradient. In the axial dimension, the coolant region is divided into M hierarchical sub-regions, where M≥2; the height of the hierarchy is set in relation to the helical pitch of the fuel rods to capture the axial periodic fluctuations or overall transport trends of the cavitation fraction.

2. The method according to claim 1, characterized in that, The spiral petal-shaped fuel assembly comprises a fuel rod with a spiral feature, the cross-section of which is composed of multiple alternating convex and concave arcs; the cross-sectional geometry of the spiral petal-shaped fuel assembly includes any one or a combination of 2 to 8 petals.

3. The method according to claim 1, characterized in that, A parameterized partitioning system is established during the process of creating parameterized indexes and correction rules for partitions. Specifically: Axial reference distribution: The region is divided into multiple levels along the axial dimension, and the reference cavitation share of each level is defined. The reference cavitation fraction increases monotonically or is distributed according to a specific function along the flow direction. Radial Correction Distribution: The region is divided into multiple feature groups along the radial dimension, and a correction coefficient for each group relative to the baseline cavitation fraction is defined. .

4. The method according to claim 3, characterized in that, The coolant partition indexing mechanism adopts a hierarchical coding format, assigning a unique material identifier to each discrete sub-volume unit. The identifier contains a combination of axial hierarchical code and radial grouping code to achieve automated mapping of material properties to geometric space.

5. The method according to claim 4, characterized in that, The constructed coupled modified cavitation-density model is based on the following relationship to calculate the local cavitation fraction. : ;in, Represents the radial coordinates from the center of the component. The outer radius of the fuel rod cladding. This represents the peak value of the cavitation fraction, which is dynamically adjusted according to the gas-liquid two-phase flow conditions. The attenuation coefficient is obtained by fitting experimental data of gas-liquid two-phase flow or benchmark calculation results. Helix angle The correction function is used to reflect the influence of the axial helical structure on the cavitation distribution.

6. The method according to claim 5, characterized in that, The mixing density parameters of each discrete partition are calculated. Follow these steps: Based on the local cavitation fraction Combined with liquid phase density With gas phase density Calculate using the following formula: Simultaneously, a boron concentration correction term is introduced into the calculation to adjust the mixed density parameter. A boron concentration correction is performed, wherein the correction term adjusts the liquid density based on the product of a preset boron dilution coefficient and the boron concentration.

7. The method according to claim 6, characterized in that, During the adaptation and solution process, geometric and physical property information is stored in HDF5 format and geometric consistency verification is completed. Finally, the partitioned modeling results and coupling analysis report are output through the gas-liquid two-phase flow numerical simulation verification method. Specifically, according to the encoding format and the cavitation-density model, the geometric boundaries, cavitation fraction, mixing density parameters, and operating parameters of each coolant sub-region are written into the HDF5 file in the form of a dataset. The consistency between the partitioned topology and the geometric model is verified by summing the volumes of all partitions and comparing them with the total coolant volume given by the geometric model. Subsequently, the HDF5 file is read using the gas-liquid two-phase flow numerical simulation program, and steady-state or transient calculations are performed on representative spiral petal components or sub-channels. The accuracy of the modeling method is verified by comparing the cavitation fraction and pressure drop distribution with the experimental benchmark or the upper-level fine calculation results.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-7.

9. A computer-readable storage medium for storing computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the method according to any one of claims 1-7.

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