Dimension reduction-dynamic coupling simulation method and device for tritium migration in plant

Abstract

The application discloses a kind of plant-oriented tritium migration dimension reduction-dynamic coupling simulation method and equipment, it is related to fusion technology field.The method includes: obtaining the geometric model of plant, ventilation system parameter, tritium leakage source term parameter and building material parameter, and establishes three-dimensional air flow field model, identifies thin layer building material domain, and matches corresponding low-dimensional building material retention model;Establish the corresponding relationship between each thin layer building material domain and the wall surface in three-dimensional air flow field model;In each time step, execute the two-way data exchange between low-dimensional building material retention model and three-dimensional air flow field model, and carry out conservation error accounting;Iterative execution until reaching the preset simulation termination time, output includes gas phase tritium concentration space-time distribution and wall surface tritium retention amount cumulative value.Therefore, through thin layer building material dimension reduction and two-way dynamic coupling, the calculation overhead can be reduced while ensuring the accuracy of three-dimensional flow field, and the safety evaluation efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of fusion technology, and in particular to a dimensionality-reduced dynamic coupling simulation method and device for tritium migration in a fusion plant. Background Technology

[0002] Tritium is the core radionuclide in the deuterium-tritium fuel cycle system of a fusion reactor. It possesses strong diffusivity, readily undergoes isotope exchange, and can migrate simultaneously in multiple chemical forms, including HT, HTO, T2, and DT. During the operation of the fusion device, tritium fuel cycle, blanket tritium extraction, process waste gas purification, and equipment maintenance, even a small leak can lead to tritium diffusion and transport across a large space via the plant's ventilation system. Simultaneously, it is easily adsorbed and retained for extended periods by non-metallic building materials such as wall coatings, concrete substrates, ceiling panels, insulation layers, and sealants, and subsequently undergoes secondary release. Therefore, quantitative analysis of tritium safety in the plant requires a comprehensive and simultaneous characterization of six major physical processes: the evolution of the three-dimensional ventilation system throughout the plant, gaseous tritium convection and diffusion transport, tritium adsorption and exchange on solid wall surfaces, solid-phase diffusion of tritium within building materials, retention at material trap sites, and desorption and re-release of tritium after the accident is terminated.

[0003] Currently, the mainstream technology for simulating the migration of radioactive contaminants in industrial plants is CFD (Computational Fluid Dynamics): This involves building a three-dimensional geometric model of the plant's air domain and solving the control equations for ventilation turbulence and convection diffusion of contaminants, effectively characterizing the concentration distribution and diffusion evolution of gaseous tritium in space. However, this approach only sets static boundary conditions such as fixed flux, constant concentration, no mass exchange, or empirical deposition on solid walls, failing to fully characterize the dynamic adsorption, internal retention, and subsequent secondary release of tritium by building materials such as coatings and concrete.

[0004] In the specific research field of tritium transport in solid materials, professional simulation tools such as FESTIM, TMAP8, and OpenFOAM multi-domain solvers can simulate the diffusion, trapping, interfacial surface reactions, and mass transfer processes of hydrogen isotopes within solid materials. However, the application scenarios of these tools are concentrated on structural components, material samples, fuel cycle equipment, and plasma-irradiated materials, and a standardized dimension-reduction coupled simulation process adapted to the ventilation flow fields of large spaces in factory buildings and the interfaces of batches of thin-layer buildings has not yet been formed.

[0005] At the numerical algorithm level, publicly available research results exist for numerical methods such as 3D-1D coupling, volume-surface reaction-diffusion, flux conservation at mismatched mesh interfaces, and POD (Proper Orthogonal Decomposition) reduced-order surrogate models. Domestic and international patents have also disclosed technical solutions based on 3D CFD combined with reduced-order models for predicting gas leaks in integrated utility tunnels, assessing urban air pollutant diffusion, and calibrating real-time parameters using digital twins.

[0006] However, the simulation of tritium migration in a factory building faces an inherent contradiction due to the significant differences in the characteristic scales of two types of physical processes: the characteristic scale of the air domain can reach meters to hundreds of meters, while the thickness of thin building materials such as anti-corrosion coatings, decorative paint layers, and ceiling coverings is only millimeters, and the effective layer thickness of the concrete surface participating in tritium exchange is also much smaller than the characteristic dimensions of the factory space. If a full 3D solid model is uniformly adopted for the air domain and all building material solid areas, extreme mesh refinement must be implemented in the thin-layer areas to ensure the continuity of the fluid-solid interface and the quality of mesh calculation. This directly results in a significant increase in the overall mesh size, memory usage, and numerical calculation time, which cannot meet the actual needs of rapid evaluation and batch comparative analysis of multiple engineering conditions. Summary of the Invention

[0007] The purpose of this invention is to propose a dimension-reduction-dynamic coupling simulation method and device for tritium migration in factory buildings. This addresses the technical problem in existing technologies where the significant difference in geometric scale between the factory air domain and the thin-layer building material results in a surge in the mesh size of the full-domain 3D solid model, leading to excessive computational overhead and making it difficult to meet the needs of rapid evaluation under multiple engineering conditions. Simultaneously, it solves the technical problem in existing CFD simulations that use static boundary conditions, failing to reproduce the tritium adsorption saturation effect, solid-phase diffusion hysteresis characteristics, and long-term secondary release process after an accident.

[0008] In a first aspect, embodiments of the present invention propose a dimensionality-reduction and dynamic coupling simulation method for tritium migration in a factory building, comprising: acquiring the geometric model of the factory building, ventilation system parameters, tritium leakage source parameters, and building material parameters; establishing a three-dimensional airflow field model of the factory building based on the geometric model, the ventilation system parameters, and the tritium leakage source parameters; identifying thin-layer building material domains in the factory building based on the building material parameters and matching them with corresponding low-dimensional building material retention models; establishing the correspondence between each thin-layer building material domain and the wall surface in the three-dimensional airflow field model; and performing simulations in each... Within each time step, bidirectional data exchange and conservation error calculation are performed. The bidirectional data exchange includes: the three-dimensional airflow model transmitting interface gas phase parameters to the low-dimensional tritium retention model according to the correspondence; the low-dimensional tritium retention model solving for the cross-gas-solid interface exchange flux based on the interface gas phase parameters and transmitting it back to the corresponding wall. The conservation error calculation includes: calculating the mass conservation error across the gas-solid interface. Each simulation time step is iteratively executed until the preset simulation termination time is reached, and simulation results including the spatiotemporal distribution of gas phase tritium concentration and the cumulative value of tritium retention on the wall are output.

[0009] In some embodiments, establishing a three-dimensional airflow field model of the plant based on the geometric model, the ventilation system parameters, and the tritium leakage source term parameters includes: generating a three-dimensional computational grid of the air domain inside the plant based on the geometric model; setting the air supply velocity and direction, return air pressure and flow rate at the air supply outlet, using the ventilation system parameters as boundary conditions on the three-dimensional computational grid, and setting the leakage point location and release rate using the tritium leakage source term parameters as mass source terms; and solving the airflow field distribution, including the velocity field, pressure field, and tritium concentration field, using a three-dimensional computational fluid dynamics model according to the boundary conditions and the mass source terms.

[0010] In some embodiments, the building material parameters include the thickness of all walls in the factory building; identifying thin-layer building material domains in the factory building based on the building material parameters includes: comparing the thickness of each wall with a preset thickness threshold; and marking the wall with a thickness less than or equal to the preset thickness threshold as the thin-layer building material domain.

[0011] In some embodiments, the matching of the corresponding low-dimensional building material retention model includes: for each thin-layer building material domain, obtaining the gas-solid interface exchange intensity, building material tritium retention contribution, and tritium solid-phase diffusion coefficient corresponding to the thin-layer building material domain in the building material parameters, and calculating the solid-phase diffusion characteristic time of tritium in the thin-layer building material domain based on the tritium solid-phase diffusion coefficient; and matching the thin-layer building material domain into one of a two-dimensional surface model, a one-dimensional normal diffusion model, or a zero-dimensional stock model based on the thickness, solid-phase diffusion characteristic time, gas-solid interface exchange intensity, and building material tritium retention contribution of the thin-layer building material domain.

[0012] In some embodiments, establishing the correspondence between each of the thin-layer building material domains and the walls in the three-dimensional airflow field model includes: assigning a unique interface number to each wall in the three-dimensional airflow field model; associating each of the thin-layer building material domains with the corresponding interface number to establish a one-to-one correspondence between each of the thin-layer building material domains and the corresponding wall.

[0013] In some embodiments, the three-dimensional airflow field model transfers interface gas phase parameters to the low-dimensional tritium retention model according to the correspondence, including: the three-dimensional airflow field model determining the target wall corresponding to each low-dimensional tritium retention model according to the correspondence; extracting the gas phase tritium concentration, wall temperature, relative humidity and convection mass transfer coefficient at each target wall as the interface gas phase parameters; and transferring the interface gas phase parameters to the low-dimensional tritium retention model of the corresponding wall.

[0014] In some embodiments, the low-dimensional tritium retention model solves for the cross-gas-solid interface exchange flux based on the interface gas phase parameters, including: the low-dimensional tritium retention model updates its own internal tritium state parameters of the building material based on the interface gas phase parameters, the internal tritium state parameters of the building material including the tritium concentration on the building material surface, the concentration distribution in the thickness direction, the total adsorption stock, the occupancy of trap sites, and the desorption secondary release rate; and calculates the cross-gas-solid interface exchange flux based on the updated internal tritium state parameters of the building material.

[0015] In some embodiments, the backfeeding to the corresponding wall includes: when the cross-gas-solid interface exchange flux is the net adsorption flux from the gas phase to the solid phase, the cross-gas-solid interface exchange flux is used as the gas phase tritium mass loss boundary and backfeeded to the corresponding wall; when the cross-gas-solid interface exchange flux is the net desorption flux released from the interior of the building material to the gas phase, the cross-gas-solid interface exchange flux is used as the gas phase tritium mass internal source boundary and backfeeded to the corresponding wall.

[0016] In some embodiments, the simulation results include a spatial cloud map of the global gas phase tritium concentration of the plant, time history curves of tritium concentration at key monitoring points, total tritium retention in building materials on each wall, secondary release flux of building materials in the later stages of an accident, tritium emissions from ventilation exhaust gas, and global mass conservation residuals.

[0017] Secondly, embodiments of the present invention propose an electronic device, including: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the dimensionality reduction-dynamic coupling simulation method for tritium migration in a factory as described in the first aspect embodiment.

[0018] The dimensionality-reduced dynamic coupling simulation method and device for tritium migration in a factory building, as described in this invention, first acquires the geometric model of the factory building, ventilation system parameters, tritium leakage source parameters, and building material parameters. Then, based on the geometric model, ventilation system parameters, and tritium leakage source parameters, a three-dimensional airflow field model of the factory building is established. Thin-layer building material domains in the factory building are identified based on the building material parameters, and corresponding low-dimensional building material retention models are matched. Subsequently, the correspondence between each thin-layer building material domain and the wall surfaces in the three-dimensional airflow field model is established. Within each simulation time step, bidirectional simulation is performed. The data exchange and conservation error calculation include: the two-way data exchange comprising: the three-dimensional airflow field model transmitting interface gas phase parameters to the low-dimensional tritium retention model according to the correspondence; the low-dimensional tritium retention model solving for the cross-gas-solid interface exchange flux according to the interface gas phase parameters and transmitting it back to the corresponding wall; the conservation error calculation comprising: calculating the mass conservation error across the gas-solid interface; iteratively executing each simulation time step until the preset simulation termination time is reached, and outputting simulation results including the spatiotemporal distribution of gas phase tritium concentration and the cumulative value of tritium retention on the wall. Therefore, by identifying and matching corresponding low-dimensional building material retention models in the thin-layer building material domains on the factory walls that meet the dimensionality reduction conditions, the problem of increased computational scale caused by extreme mesh refinement in thin-layer regions in full-domain 3D solid modeling is avoided, significantly reducing computational overhead. By establishing the correspondence between the low-dimensional building material retention model and the wall surface in the 3D airflow field model, and performing bidirectional data exchange at each time step, the cross-gas-solid interface exchange flux calculated in real time by the low-dimensional model is used as the dynamic boundary condition of the wall surface in the 3D flow field model, replacing the static boundary conditions of fixed flux or constant concentration in traditional CFD simulation. This enables the dynamic reproduction of the tritium adsorption saturation effect of building materials, the solid-phase diffusion hysteresis characteristics, and the long-term secondary release process after an accident, effectively improving the computational accuracy and efficiency of tritium migration simulation in long-term safety assessment and multi-condition engineering analysis.

[0019] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0020] Figure 1 This is a flowchart of a dimension reduction-dynamic coupling simulation method for tritium migration in a factory, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the air-solid interface coupling logic of a three-dimensional airflow field and a low-dimensional building material retention model according to an embodiment of the present invention. Figure 3 This is a structural block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0021] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0022] The simulation of tritium migration in existing factory buildings faces the following technical challenges: Firstly, the simulation needs to simultaneously consider two physical processes: the evolution of large-scale ventilation flow field and the tritium retention of small-scale thin-layer building materials. If a unified modeling of the entire domain and three-dimensional solid is adopted, the mesh size will expand rapidly, the overall computational cost will be too high, and it will be difficult to meet the timeliness requirements of the project.

[0023] Secondly, building materials such as wall coatings, ceilings, and concrete generally exhibit adsorption, solid-phase diffusion, long-term retention, and secondary release behaviors of HTO and various tritium forms. However, traditional static fixed boundary conditions cannot characterize the dynamic tritium memory effect of building materials, resulting in serious distortion of long-tail concentration predictions after accidents.

[0024] Third, in the full-domain simulation model of the factory building, the building material types, thicknesses, porosity, diffusion coefficients and adsorption / desorption kinetic parameters of different walls vary significantly. There is an urgent need for a standardized and unified coupling expression system that can adapt to multiple types of building materials and cover multiple physical degrees of freedom in order to achieve universal modeling of complex building envelopes.

[0025] Fourth, when the three-dimensional gas flow field model and the low-dimensional building material retention model are solved independently step by step, it is necessary to strictly ensure the continuity of gas-solid interface flux, global mass conservation, and stability of time-stepped solution to avoid numerical oscillations and cumulative error amplification caused by explicit data exchange mode.

[0026] Fifth, during the engineering evaluation phase, it is necessary to compare the impact patterns of various working conditions, such as ventilation layout, leak source location, wall material properties, and accident duration. Therefore, it is necessary to build a simulation framework with adaptively adjustable calculation accuracy and efficiency to support large-scale working condition scanning and scheme optimization.

[0027] To address this, this invention provides a dynamic simulation technology for tritium migration in fusion reactor tritium processing facilities and the containment spaces of various nuclear facilities. This technology boasts low computational overhead, high scalability, and verifiable results. While fully preserving the accuracy of the calculations for the three-dimensional ventilation flow field and gaseous tritium concentration distribution within the facility, this method equivalently transforms the computational domain of the thin-layer building material entity into a low-dimensional tritium retention model attached to the wall boundary, fundamentally avoiding the problem of excessive global mesh refinement caused by the extremely small thickness of the thin layer.

[0028] Meanwhile, this invention can completely reproduce the entire physical process of tritium adsorption and desorption on building material surfaces, solid-phase diffusion along the thickness direction, lattice trap retention, and long-term secondary release after an accident. The three-dimensional flow field wall boundary no longer relies on fixed empirical adsorption parameters, but instead constructs dynamic boundary conditions that change in real time with simulation duration, interface gas phase concentration, ambient temperature and humidity, and the amount of tritium inside the building material. A dual constraint mechanism of interface residuals and global mass conservation residuals is used to quantitatively evaluate the coupling error, effectively improving the credibility of the dimensionality reduction simulation model and providing reliable numerical calculation support for optimizing plant ventilation strategies, inverting leakage accident source terms, designing plant decontamination schemes, and quantitatively evaluating tritium safety.

[0029] The following describes, with reference to the accompanying drawings, a dimension-reduction-dynamic coupling simulation method and apparatus for tritium migration in a factory building according to embodiments of the present invention.

[0030] Figure 1 This is a flowchart of a dimension reduction-dynamic coupling simulation method for tritium migration in a factory, according to an embodiment of the present invention. The method can be executed by an electronic device, including but not limited to servers, workstations, desktop computers, or high-performance computing clusters.

[0031] like Figure 1 As shown, the dimension reduction-dynamic coupling simulation method for tritium migration in factory buildings includes: S1, obtain the geometric model of the plant, ventilation system parameters, tritium leakage source parameters, and building material parameters.

[0032] Specifically, the geometric model should include at least the building's structural outline, internal equipment layout, pipeline routing, and the spatial coordinates and normal vector information of each enclosing wall surface (including walls, floors, and ceilings). Scale-level analysis can be performed on the geometric model, and based on the ratio of the building's characteristic length to the thickness of each building material, a preliminary division can be made into the main air computational domain and the thin-layer building material domain.

[0033] The ventilation system parameters include the location and size of the air supply outlet, the location and size of the exhaust outlet, the air supply temperature, the air supply velocity, the relative humidity of the air supply, the exhaust back pressure, the ventilation system operation mode (normally open / intermittent / emergency switching), and the time history curves of the air supply and exhaust flow rates. The tritium leakage source parameters include the spatial coordinates of each leakage point, the leakage start and end times, the leakage release rate time history curve, the released tritium forms (including one or more of HTO, HT, T2, DT, tritium-containing water vapor, and organically bound tritium) and their proportions, the release temperature, and the direction of release momentum; the leakage source parameters cover equipment leaks, pipeline micro-leaks, glove box exhaust emissions, instantaneous releases during accidents, and secondary re-release sources from building materials.

[0034] The building material parameters are configured independently for different building envelope sections, specifically including: the thickness, density, porosity, tortuosity, solid tritium diffusion coefficient, surface adsorption site density, adsorption / desorption rate constant (including temperature correction coefficient and humidity correction coefficient), lattice trap trapping site density, trap trapping rate constant, trap release rate constant, maximum tritium solid solubility in the material, and material-air partition coefficient for each building material layer; for multi-layer composite building envelope structures, the above physical property parameters can be configured independently for each layer and interlayer interface mass transfer conditions can be established.

[0035] Optionally, ambient temperature and humidity parameters can also be obtained. These parameters include the initial distribution of ambient temperature, the initial distribution of ambient relative humidity, and the dynamic boundary conditions of temperature and humidity changes as the ventilation system operates.

[0036] After obtaining the above input parameters, all the input parameters can be stored in the parameter database in a unified data format, and a unique interface number can be assigned to each enclosure wall unit. An initial data mapping index table between the three-dimensional air domain mesh unit and each low-dimensional building material model can be established for dynamic data exchange and calling during the subsequent simulation time step process.

[0037] S2, based on the geometric model, ventilation system parameters and tritium leakage source parameters, establishes a three-dimensional airflow field model of the plant.

[0038] In some embodiments of the present invention, a three-dimensional airflow field model of the plant is established based on a geometric model, ventilation system parameters, and tritium leakage source term parameters. This includes: generating a three-dimensional computational grid of the internal air domain of the plant based on the geometric model; setting the air supply velocity and direction, return air pressure and flow rate at the air supply outlet, and using the ventilation system parameters as boundary conditions on the three-dimensional computational grid, and setting the leakage point location and release rate using the tritium leakage source term parameters as mass source terms; and solving the problem using a three-dimensional computational fluid dynamics model based on the boundary conditions and mass source terms to obtain an airflow field distribution including a velocity field, a pressure field, and a tritium concentration field.

[0039] Specifically, a three-dimensional computational mesh for the internal air domain of the plant is generated based on the geometric model. This includes: retaining all air domain space in the plant's geometric model; geometrically identifying and marking all enclosure wall boundaries, such as equipment exterior walls, pipeline exterior surfaces, walls, floors, and ceilings; generating a three-dimensional computational mesh for the air domain using a polyhedral mesh, hexahedral core mesh, or tetrahedral / prism layer hybrid mesh generation strategy, with local densification near air inlets, outlets, leak points, and areas with personnel activity; generating boundary layer prism meshes for all wall boundaries to resolve near-wall velocity and concentration gradients; assigning a unique interface number to each wall boundary mesh unit, establishing a spatial mapping relationship between the wall unit and the plant's physical walls, and ensuring that the normal direction of the wall unit points into the air domain.

[0040] The system uses ventilation system parameters as boundary conditions to set the air supply outlet velocity and direction, and the return air outlet pressure and flow rate. It also uses tritium leakage source parameters as mass source parameters to set the leakage point location and release rate. This includes: setting the air supply outlet boundary as a velocity inlet boundary condition, and assigning the velocity vector value, temperature value, and turbulence intensity value at the inlet based on the air supply temperature, air supply velocity, and air supply relative humidity in the ventilation system parameters; setting the exhaust outlet boundary as a pressure outlet or mass flow rate outlet boundary condition, and assigning the static pressure value or flow rate value at the outlet based on the exhaust back pressure or exhaust flow rate time history curve in the ventilation system parameters; setting each tritium leakage source point as a mass source term or mass flow rate inlet boundary condition, and injecting tritium mass source terms at the corresponding spatial coordinates by time interpolation based on the release rate time history curve, the released tritium form, and the form proportion in the tritium leakage source term parameters; and for multi-form mixed release scenarios, setting corresponding component mass source terms according to the proportion of each form.

[0041] A three-dimensional computational fluid dynamics model is used to solve the airflow field distribution, which includes the velocity field, pressure field, and tritium concentration field. This includes establishing a set of convection-diffusion-source term governing equations describing the transport of gaseous tritium in the air domain of the plant. The set of governing equations includes the continuity equation, the Reynolds-averaged Navier-Stokes equation or the large eddy simulation governing equation, the turbulence model transport equation, the energy conservation equation, the humidity transport equation, and the convection-diffusion transport equations for each tritium speciation component.

[0042] During the solution process, the flow field is initially initialized using zero-flux Neumann boundaries or preliminary estimated boundaries based on empirical adsorption coefficients for all wall boundaries in the air domain. After the subsequent low-dimensional building material model completes its initialization, the flow field is switched to dynamic boundary fluxes fed back in real time by the low-dimensional model. After the three-dimensional flow field solution is completed, the gaseous tritium concentration Cg,Γ (including individual values ​​and summation values ​​of each morphology), wall temperature T, wall relative humidity RH, and local convection mass transfer coefficient hm at all wall boundary grid cells are extracted. These parameters are stored in the data cache according to the interface number for the low-dimensional building material retention model to call in subsequent coupling steps.

[0043] Thus, the three-dimensional computational fluid dynamics model fully preserves the real impact of the plant's spatial structure, equipment shielding, and ventilation arrangement on the tritium transport path. At the same time, a unique number and data cache channel are established for each wall unit to ensure the physical consistency and data closure of the subsequent gas-solid interface flux transfer, laying the foundation for the accurate calculation of the global mass conservation error.

[0044] S3 identifies thin-layer building material domains in the factory based on building material parameters and matches them with corresponding low-dimensional building material retention models.

[0045] In some embodiments of the present invention, the building material parameters include the thickness of all walls in the factory building; identifying thin-layer building material domains in the factory building based on the building material parameters includes: comparing the thickness of each wall with a preset thickness threshold; and marking the wall with a thickness less than or equal to the preset thickness threshold as a thin-layer building material domain.

[0046] Matching the corresponding low-dimensional building material retention model includes: for each thin-layer building material domain, obtaining the gas-solid interface exchange intensity, building material tritium retention contribution, and tritium solid-phase diffusion coefficient corresponding to the thin-layer building material domain in the building material parameters, and calculating the solid-phase diffusion characteristic time of tritium in the thin-layer building material domain based on the tritium solid-phase diffusion coefficient; matching the thin-layer building material domain into one of the following types based on the thickness, solid-phase diffusion characteristic time, gas-solid interface exchange intensity, and building material tritium retention contribution: a two-dimensional surface model, a one-dimensional normal diffusion model, or a zero-dimensional stock model.

[0047] Specifically, before comparing the thickness of each wall surface with a preset thickness threshold, the process includes: traversing and identifying all enclosing walls in the factory's geometric model. These enclosing walls include wall coatings, plaster layers, ceiling panels, floor leveling layers, insulation layers, sealant layers, and concrete structural layers. Each independent wall surface is uniquely identified based on its type, spatial orientation, and material composition, and its geometric thickness δ, area A, spatial location, and normal vector information are extracted. The preset thickness threshold can be determined based on the factory's airspace characteristic size and mesh resolution, and its range can be 0.5% to 5% of the factory's characteristic length. For example, when the factory's airspace characteristic size is 10m, the preset thickness threshold is 0.1m to 0.5m. Furthermore, when adaptive mesh refinement is used, the preset thickness threshold is associated with the height of the first mesh layer near the wall surface; when the building material thickness is less than or equal to three times the near-wall mesh height, the wall surface is marked as a thin-layer building material domain. For walls with a thickness greater than a preset thickness threshold, retain the option to model the three-dimensional solid, or use a layered serial dimensionality reduction model to reduce the dimensionality of thin layers that only participate in tritium exchange near the wall, while keeping the deep layers one-dimensional.

[0048] The gas-solid interface exchange intensity is determined as follows: based on the adsorption / desorption kinetic parameters of the building material surface and the near-wall convective mass transfer coefficient hm, the characteristic exchange rate k_int = f(hm,ka,kd,T,RH) is calculated, where ka is the adsorption rate constant and kd is the desorption rate constant. A higher interface exchange intensity indicates that the tritium concentrations on both the gas and solid sides tend to reach equilibrium more quickly; in this case, a simplified form with lower dimensions can be used for the building material model.

[0049] The characteristic time of tritium solid-phase diffusion, τ_diff, is calculated as follows: τ_diff = δ² / D_s, where δ is the thickness of the building material and D_s is the solid-phase diffusion coefficient of tritium in the building material.

[0050] The contribution of building materials to tritium retention is determined as follows: based on the proportion of the total surface area of ​​the building materials, the adsorption capacity of the building materials for tritium, and the proportion of the total cumulative tritium release during the accident to the total release from the plant, the total contribution weight of each wall surface to tritium retention is calculated. When the contribution of a certain type of building material to tritium retention is less than a set lower threshold (e.g., 1%~5%), the impact of that building material on the overall tritium behavior of the plant is negligible, and a zero-dimensional stock balance model is directly matched to minimize computational overhead; when the contribution is higher than the upper threshold, a one-dimensional normal diffusion model is preferentially matched to ensure accurate characterization of critical retention paths.

[0051] Based on the thickness of the thin-layer building material domain, the solid-phase diffusion characteristic time, the gas-solid interface exchange intensity, and the tritium retention contribution of the building material, the thin-layer building material domain is matched into one of the following types: a two-dimensional surface model, a one-dimensional normal diffusion model, or a zero-dimensional stock model. The specific matching logic is as follows: The conditions for matching to a two-dimensional surface model are: when the thickness of the thin building material domain is less than or equal to the preset thickness threshold, and the tritium solid-phase diffusion characteristic time is much less than the gas-solid interface exchange characteristic time, and the tritium retention contribution of the building material is at a medium level (between the lower threshold and the upper threshold), it indicates that tritium rapidly achieves a uniform concentration distribution inside the solid phase, and the interface exchange is the rate-limiting step. At this time, a two-dimensional surface model can be used (considering only the adsorption / desorption and surface diffusion at the gas-solid interface, ignoring the normal concentration gradient).

[0052] The conditions for matching to a one-dimensional normal diffusion model are: when the thickness of the thin building material domain is less than or equal to the preset thickness threshold, and the characteristic time of tritium solid-phase diffusion is comparable to or greater than the characteristic time of gas-solid interface exchange, and the contribution of tritium retention in the building material is higher than the upper limit threshold, it indicates that the normal concentration gradient inside the solid phase cannot be ignored, and the interface exchange and solid-phase diffusion jointly control the retention process. At this time, a one-dimensional normal diffusion model must be matched (the diffusion equation is solved only along the wall normal direction, ignoring in-plane transverse diffusion).

[0053] The conditions for matching to the zero-dimensional stock model are as follows: when the thickness of the thin-layer building material domain is less than or equal to the preset thickness threshold, and the tritium solid-phase diffusion characteristic time is much less than the gas-solid interface exchange characteristic time, and the tritium retention contribution of the building material is lower than the lower limit threshold, it indicates that the building material has a negligible impact on the overall tritium behavior of the plant, and the solid phase interior and interface can be regarded as instantaneous equilibrium. At this time, the zero-dimensional stock model can be directly matched (only considering the total tritium stock balance under lumped parameters, ignoring spatial distribution and diffusion dynamics).

[0054] Write the low-dimensional model type, model parameters, and wall interface number of each matched thin-layer building material domain into the model configuration file, and establish a one-to-one correspondence index table between the three-dimensional air domain wall elements and the solution nodes of the low-dimensional building material model for quick indexing and calling during subsequent coupled calculations.

[0055] Therefore, by using four indicators—thickness threshold, diffusion characteristic time, interface exchange intensity, and retention contribution—the appropriate dimensionality reduction model type for each wall surface is automatically determined. This avoids the high aspect ratio deformed cells and huge computational overhead caused by uniformly using a full 3D mesh to partition thin-layer building materials. At the same time, it ensures that high-fidelity one-dimensional diffusion models are preferentially used for key walls with high tritium retention contribution, balancing simulation accuracy and computational efficiency, and achieving adaptive matching of multi-level models for different walls according to local conditions.

[0056] S4. Establish the correspondence between each thin-layer building material domain and the wall surface in the three-dimensional airflow field model.

[0057] In some embodiments of the present invention, establishing the correspondence between each thin-layer building material domain and the wall surface in the three-dimensional airflow field model includes: assigning a unique interface number to each wall surface in the three-dimensional airflow field model; associating each thin-layer building material domain with the corresponding interface number to establish a one-to-one correspondence between each thin-layer building material domain and the corresponding wall surface.

[0058] Specifically, a unique interface number is assigned to each wall in the 3D airflow field model. This includes: traversing all wall boundary mesh cells in the 3D airflow field model and grouping the mesh cells according to their respective physical wall partitions (including walls, floors, ceilings, equipment exteriors, pipeline exteriors, etc.); assigning a unified wall partition number to all wall mesh cells within each group; and further assigning an independent mesh cell sub-number to each wall mesh cell within that group. The wall partition number and the mesh cell sub-number together constitute the unique interface number of that wall mesh cell globally. The unique interface number can adopt a hierarchical coding format, with coding fields including: plant area code, wall type code, physical partition number, and mesh cell local number, to ensure that each wall cell can be quickly located and indexed in large-scale parallel computing or complex multi-partition plant geometry.

[0059] For physical wall partitions where wall parameters (including wall temperature, surface roughness, coating type, etc.) are uniformly distributed, all grid cell sub-numbers under the same wall partition number share the same low-dimensional building material retention model instance's state variables. For physical wall partitions where wall parameters are not uniformly distributed, the same physical wall partition is further divided into multiple parameter-consistent sub-regions based on differences in wall temperature field distribution, coating damage level, or spatial orientation. Each sub-region is independently assigned a wall partition number and matched with an independent low-dimensional building material retention model instance.

[0060] Each thin-layer building material domain is associated with its corresponding interface number to establish a one-to-one correspondence between each thin-layer building material domain and its corresponding wall surface. This includes: using each thin-layer building material domain marked in step S3 as a basic association unit, obtaining the spatial location information of the physical wall surface corresponding to that thin-layer building material domain; retrieving wall mesh units located in the same spatial location and with the same normal direction in the wall mesh of the three-dimensional airflow field model, and binding the unique interface number of the wall mesh unit with the low-dimensional model instance number of the thin-layer building material domain; when a thin-layer building material domain corresponds to multiple wall mesh units, a one-to-many association method is adopted, that is, one low-dimensional model instance is associated with multiple wall interface numbers at the same time, and these wall mesh units share the same set of low-dimensional model state variables; when a single wall mesh unit corresponds to multiple superimposed thin-layer building material domains (e.g., coating superimposed on concrete surface), a many-to-one association method is adopted, and multiple low-dimensional model instances are associated with the same wall interface number according to the interlayer coupling relationship to form a serial calculation chain.

[0061] After all associations are completed, a two-dimensional association mapping table is generated. The association mapping table contains at least the following fields: unique interface number of the three-dimensional wall mesh element, corresponding low-dimensional model instance number, low-dimensional model type identifier, pointer to the storage address of model state variables, and pointer to the storage address of model parameters. The association mapping table is indexed according to the size order of the unique interface number, so that the three-dimensional flow field solver and the low-dimensional model solver can quickly query and exchange data through the interface number during the simulation time step, avoiding the computational delay caused by traversal search.

[0062] Establishing the correspondence between each thin-layer building material domain and the wall in the three-dimensional airflow field model also includes: before each simulation time step, the three-dimensional flow field solver locates the corresponding low-dimensional model instance number and state variable storage address within a constant time using the hash index of the association mapping table based on the wall mesh element number of the current time step, and writes the wall interface gas phase tritium concentration Cg,Γ, wall temperature T, wall relative humidity RH, and local convection mass transfer coefficient hm calculated in the current step into the corresponding state variable storage area; after the low-dimensional model solver completes the state update of the current step, it backfeeds the calculated cross-interface exchange flux JΓ to the wall boundary condition buffer of the three-dimensional flow field solver through the same index path for flow field solution in the next time step or the current step sub-iteration step.

[0063] By assigning a hierarchical and unique interface number to each wall mesh unit and establishing a hash-indexed association mapping table, constant-level time indexing and high-speed data exchange between large-scale wall meshes and low-dimensional building material model instances in the 3D air domain are realized within each simulation time step. This significantly reduces the computational latency and communication overhead of traditional traversal matching methods under large-scale meshes in complex factory buildings. The strategy of multiple mesh units sharing a single model instance within the same physical partition effectively controls the total number of low-dimensional model instances while ensuring computational accuracy, avoiding memory overflow and solver overload problems caused by model instance explosion. The interlayer serial association mechanism of the multi-layer composite structure ensures that the 3D flow field solver only needs to perform a single interface data exchange with the outermost low-dimensional model to drive the complete cascade update of the multi-layer building material model, greatly simplifying the coupling interface logic and improving the stability and maintainability of multi-physics synchronous solution.

[0064] S5 performs bidirectional data exchange and conservation error calculation within each simulation time step.

[0065] The bidirectional data exchange includes: the three-dimensional airflow field model transmitting interface gas phase parameters to the low-dimensional tritium retention model according to the correspondence; the low-dimensional tritium retention model solving the cross-gas-solid interface exchange flux according to the interface gas phase parameters and transmitting it back to the corresponding wall; the conservation error calculation includes: calculating the mass conservation error across the gas-solid interface.

[0066] In some embodiments of the present invention, the three-dimensional airflow field model transmits interface gas phase parameters to the low-dimensional tritium retention model according to the correspondence, including: the three-dimensional airflow field model determines the target wall corresponding to each low-dimensional tritium retention model according to the correspondence; extracts the gas phase tritium concentration, wall temperature, relative humidity and convection mass transfer coefficient at each target wall as interface gas phase parameters; and transmits the interface gas phase parameters to the low-dimensional tritium retention model of the corresponding wall.

[0067] The low-dimensional tritium retention model solves for the cross-gas-solid interface exchange flux based on the interface gas phase parameters, including: updating the tritium state parameters inside the building material based on the interface gas phase parameters, which include the tritium concentration on the building material surface, the concentration distribution along the thickness direction, the total adsorption stock, the occupancy of trap sites, and the desorption secondary release rate; and calculating the cross-gas-solid interface exchange flux based on the updated tritium state parameters inside the building material.

[0068] The process of transferring the flux back to the corresponding wall includes: when the cross-gas-solid interface exchange flux is the net adsorption flux from the gas phase to the solid phase, transferring the cross-gas-solid interface exchange flux back to the corresponding wall as the gas phase tritium mass loss boundary; and when the cross-gas-solid interface exchange flux is the net desorption flux released from the interior of the building material to the gas phase, transferring the cross-gas-solid interface exchange flux back to the corresponding wall as the gas phase tritium mass internal source boundary.

[0069] The calculation of mass conservation error across the gas-solid interface includes: balancing the change in gas phase tritium mass, the change in tritium mass in the low-dimensional building material model, and external mass source terms within the current time step. External mass source terms include tritium leakage and release and the amount discharged from the ventilation system.

[0070] Specifically, within the current time step, the change in gas phase tritium mass in the three-dimensional airflow field model is equal to the total amount of tritium source terms entering the air domain minus the sum of the total tritium flux adsorbed by building materials across the gas-solid interface, the total amount of tritium mass discharged by the ventilation system, and the amount of tritium decay consumption; in the low-dimensional building material model, the change in building material tritium mass is equal to the total adsorption flux across the gas-solid interface minus the sum of the total desorption flux released from the building material interior to the gas phase and the amount of tritium decay consumption within the building material; by subtracting the cumulative amount of external mass source terms from the sum of the change in gas phase tritium mass and the change in building material tritium mass within the current time step, the mass conservation residual is obtained.

[0071] When the mass conservation residual exceeds a preset threshold, the current time step's coupled calculation is deemed to have failed to converge, and a sub-iteration loop is initiated. This involves repeatedly performing bidirectional data exchange and conservation error calculation until the mass conservation residual is less than or equal to the preset threshold, at which point the simulation proceeds to the next time step. The preset threshold for the mass conservation residual can be a mass tolerance set according to simulation accuracy requirements, or a preset percentage of the total accumulated leakage release within the current time step.

[0072] like Figure 2 As shown, the gas-solid interface coupling logic between the three-dimensional airflow field 1 and the low-dimensional building material retention model 6 is as follows: the three-dimensional airflow field 1 transmits the gas phase tritium concentration Cg,Γ, wall temperature T, relative humidity RH, and local convection mass transfer coefficient hm of the wall interface to the low-dimensional building material retention model 6 through the input channel 7 via the plant wall or material interface 2; the low-dimensional building material retention model 6 solves for the cross-interface exchange flux JΓ based on the surface tritium concentration Cs,0 of the current surface coating or paint layer 3, porous ceiling or insulation layer 4, and concrete matrix 5, the tritium concentration distribution Cs(ξ,t) inside the building material, the total tritium storage Ms(t) of the building material, and the adsorption / desorption kinetic parameters; this flux is returned to the three-dimensional airflow field 1 through the output channel 8 as the Neumann boundary, Robin boundary, or mixed boundary condition of the three-dimensional gas phase model. The material layer and the low-dimensional building material retention model are synchronized in real time through the material inventory and re-release status update channel 9. The mass conservation error and interface residual control module 10 respectively feeds back the correction amount to the three-dimensional airflow field 1 and the low-dimensional building material retention model 6.

[0073] The cross-interface exchange flux JΓ is a composite function of gas-phase adsorption flux, building material desorption flux, and solid-phase internal diffusion flux, expressed as JΓ = Φ(Cg,Γ, Cs,0, Ms, T, RH, hm). When tritium inside the building material is not saturated with adsorption, JΓ represents the net adsorption flux from the gas phase to the solid phase. After ventilation and purification of the plant, the concentration of the interfacial gas phase decreases, and the tritium retained inside the building material is released outward through desorption and solid-phase diffusion, thus reversing the direction of flux JΓ.

[0074] During the simulation time-step solution phase, the execution logic within a single time step is as follows: First, solve the three-dimensional airflow field tritium concentration field in the gas phase, extracting Cg,Γ, T, RH, and h_m of all interface mesh elements; then, synchronously update the surface concentration Cs, total tritium stock Ms, and desorption release rate Rdes of the corresponding wall material low-dimensional model; finally, read the low-dimensional model output flux JΓ and refresh the three-dimensional flow field wall boundary conditions. If the obtained interface flux residual or global mass conservation residual exceeds the preset convergence threshold, then start the interface sub-iteration loop in the current time step until the residual meets the convergence criterion.

[0075] The multi-degree-of-freedom coupled system of this invention includes geometric degrees of freedom, building material property degrees of freedom, physical process degrees of freedom, and time scale degrees of freedom. Geometric degrees of freedom are manifested in the simultaneous coexistence of four types of dimensionality-reduced geometric models: a three-dimensional air domain, a two-dimensional interface layer, a one-dimensional building material thickness direction, and a zero-dimensional existing unit. Building material property degrees of freedom are manifested in the independent configuration of specific diffusion, adsorption, desorption, and trapping parameters for different building envelope surfaces. Physical process degrees of freedom include the synchronous coupling solution of multiple physical processes such as air revelation, turbulent diffusion, surface adsorption, solid-phase desorption, lattice retention, secondary release, and ventilation exhaust. Time scale degrees of freedom are manifested in the step-by-step solution or sub-cycle acceleration of the fast transient process of airflow and the slow, long-term process of tritium retention in building materials.

[0076] By using bidirectional dynamic coupling between the three-dimensional flow field and the low-dimensional building material model, the wall boundary conditions are adaptively adjusted in real time according to the tritium retention state of the building material, thus fully depicting the physical reversal process of net adsorption of building materials in the early stage of the accident and net release of building materials in the later stage of the accident. Through a multi-degree-of-freedom coupling system, different wall types, different physical processes, and different time scales are uniformly expressed and solved synchronously within the same simulation framework, taking into account both the simulation accuracy and computational efficiency of the entire process of large-scale flow field transport and small-scale building material retention.

[0077] S6 iterates through each simulation time step until the preset simulation termination time is reached, and outputs simulation results including the spatiotemporal distribution of gas phase tritium concentration and the cumulative value of tritium retention on the wall.

[0078] In some embodiments of the present invention, the simulation results include a spatial cloud map of the global gas phase tritium concentration in the plant, time history curves of tritium concentration at key monitoring points, total tritium retention in building materials on each wall, secondary release flux of building materials in the later stage of an accident, tritium emissions from ventilation exhaust gas, and global mass conservation residuals.

[0079] Specifically, the iterative execution continues until the preset simulation termination time is reached. This includes: after completing the bidirectional data exchange and conservation error calculation for the current time step, determining whether the current cumulative time t_current has reached the termination time t_end; if not, setting t_current = t_current + Δt, proceeding to the next time step, and repeating the execution; if it has reached the termination time, terminating the time step and transitioning to the result post-processing and output stage. The simulation time step Δt supports two modes: fixed step size and adaptive variable step size. The adaptive variable step size automatically adjusts the step size based on the convergence rate of the current step's interface flux residual and the global mass conservation residual.

[0080] The simulation results are output as follows: after each simulation time step, the solution results of the three-dimensional air flow field are written into the gas phase field history database, and the solution results of the low-dimensional building material model are written into the building material state history database; after the simulation is terminated, all time series data are read from the two historical databases, visualization and quantitative statistics are performed, and simulation result output files are generated.

[0081] The global gaseous tritium concentration spatial cloud map is generated using spatial interpolation based on the concentration values ​​at the 3D computational grid nodes at each time step. This generates a 3D volumetric rendering cloud map or a cross-sectional slice cloud map to visually represent the tritium transport and diffusion paths and the evolution of local high-concentration areas. The tritium concentration time-history curves at key monitoring points are extracted from the historical gaseous field database based on user-preset monitoring point coordinates, and plotted to assess the radiation safety risk at each monitoring location. The total tritium retention on each wall surface is retrieved from the historical building material status database, showing the total tritium retention of each low-dimensional model instance at each time step. This is categorized by wall type, summarized, and output as a cumulative curve and a bar chart comparing the simulation termination time. For the one-dimensional normal diffusion model, the tritium concentration distribution curve along the thickness direction of the selected wall surface is also output. The secondary release flux from building materials in the later stages of an accident is extracted from the desorption release flux and its cumulative total release within the tail period after the source term stops. The tritium emission rate in the ventilation exhaust gas is obtained by integrating the product of the mass flow rate and tritium concentration at each exhaust vent over time, and then compared with the total leakage release to evaluate the ventilation purification efficiency. The global mass conservation residual is calculated and output after each time step according to Residual = M_release - (M_air + M_wall + M_exhaust). The percentage of the residual to the total cumulative release is used as a quantitative evaluation index of the simulation quality reliability. Wherein, Residual represents the mass conservation residual within the current simulation time step, used to quantitatively evaluate the global numerical conservation of the cross-gas-solid interface coupling calculation between the three-dimensional airflow field model and the low-dimensional building material retention model; M_release represents the total cumulative mass of tritium released into the plant air domain via the leakage source term from the start of the accident to the end of the current time step; M_air represents the change in the total mass of tritium in the three-dimensional airflow field within the current time step Δt; M_wall represents the change in the total mass of tritium in all low-dimensional building material retention models (including two-dimensional surface models, one-dimensional normal diffusion models, and zero-dimensional stock models) within the same time step Δt; and M_exhaust represents the total cumulative mass of tritium discharged outside the plant via the ventilation system exhaust vents from the start of the accident to the end of the current time step.

[0082] Before output, data format standardization processing is performed to generate result files that conform to VTK, CGNS, or HDF5 standard formats, supporting import into general scientific computing visualization software such as ParaView, Tecplot, or Ensight. At the same time, a summary report document is generated, which organizes key quantitative indicators, including the initial adsorption rate, saturated adsorption amount and time to reach saturation of each wall building material, the half-life of wall desorption and release after an accident, the peak concentration of gaseous tritium and the ventilation time required for the concentration to drop to the safe limit.

[0083] By synchronously accumulating and storing full-time history data, the entire dynamic evolution information of the coupled simulation was fully recorded, providing a traceable data foundation for the entire accident process. The three-dimensional transport path and risk time sequence characteristics of tritium at key locations were intuitively revealed through multi-dimensional visualization output. The output of total building material retention and secondary release flux filled the technical gap that conventional methods could not quantify the contribution of building materials to long-term release. The full-time history output of global mass conservation residuals provided verifiable quantitative indicators for the credibility of the dimensionality reduction coupled simulation, significantly improving the credibility and engineering applicability of the simulation results.

[0084] The method described in this invention is applied and verified using a simulation scenario of a trace HTO leak occurring in a fusion reactor tritium processing plant.

[0085] The air domain of the factory building is discretized using a complete three-dimensional CFD mesh. The wall coatings, ceiling panels, and concrete substrates are adaptively reduced to a one-dimensional normal diffusion model or a zero-dimensional stock model based on their thickness and diffusion characteristic time, respectively. During the simulation time step, the three-dimensional flow field solver and each low-dimensional building material model perform data exchange and flux feedback at each step according to the bidirectional coupling logic described in step S5.

[0086] In the initial stage of the accident, HTO was released from the leak point and transported and diffused within the plant space primarily by the ventilation flow field. The concentration of HTO in the interfacial gas phase was higher than the equilibrium concentration on the building material surface, and the cross-gas-solid interface exchange flux JΓ > 0. Each building material model exhibited a net adsorption state, and HTO gradually seeped into and accumulated on the surface and inside of the building materials. In the middle stage of the accident, after ventilation and purification were activated, the concentration of HTO in the gas phase within the plant rapidly decreased, and the concentration of the interfacial gas phase fell below the equilibrium concentration on the building material surface. The flux direction automatically reversed, and JΓ < 0. HTO retained inside the building materials was released back into the air through desorption and solid-phase diffusion, forming a long-term secondary release process in the later stage of the accident.

[0087] In the simulation results output stage, this invention simultaneously outputs the instantaneous peak tritium concentration during the accident and the long-tail concentration decay law over time after the accident. Comparative verification shows that if only pure gas-phase CFD simulation is used and the effects of building material retention and secondary release are ignored, the tritium concentration in the plant during the later stages of the accident will be significantly underestimated, leading to a misjudgment of the long-term radiation risk of the plant.

[0088] This scenario verifies the complete applicability of the method of the present invention in the HTO leakage accident scenario of a fusion reactor tritium processing plant, and can provide reliable numerical simulation support for the formulation of emergency ventilation strategies and subsequent safety assessment of the plant.

[0089] Figure 3 This is a structural block diagram of an electronic device according to an embodiment of the present invention.

[0090] like Figure 3As shown, the electronic device 500 includes a processor 501 and a memory 503. The processor 501 and the memory 503 are connected, for example, via a bus 502. Optionally, the electronic device 500 may also include a transceiver 504. It should be noted that in practical applications, the transceiver 504 is not limited to one type, and the structure of this electronic device 500 does not constitute a limitation on the embodiments of the present invention.

[0091] Processor 501 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. Processor 501 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0092] Bus 502 may include a pathway for transmitting information between the aforementioned components. Bus 502 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 502 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0093] The memory 503 is used to store a computer program corresponding to the dimensionality reduction-dynamic coupling simulation method for tritium migration in a factory according to the above embodiments of the present invention. This computer program is controlled and executed by the processor 501. The processor 501 is used to execute the computer program stored in the memory 503 to implement the content shown in the aforementioned method embodiments.

[0094] Among them, electronic devices 500 include, but are not limited to: terminals such as laptops and desktop computers. Figure 3 The electronic device 500 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0095] In summary, the dimension reduction-dynamic coupling simulation method and equipment for tritium migration in factory buildings according to embodiments of the present invention can achieve the following technical effects: 1) By transforming the computational domain of the thin-layer building material entity into a low-dimensional tritium retention state model attached to the wall boundary, the problem of high aspect ratio distorted mesh generation caused by the extremely small thickness of the thin layer in the full-size factory 3D modeling is fundamentally avoided. This significantly reduces the overall mesh size, reduces hardware memory usage and computing power consumption, and enables large-scale factory tritium migration simulation to be completed efficiently within an acceptable engineering time.

[0096] 2) The low-dimensional building material retention model stores in real time the tritium concentration on the building material surface, the concentration distribution along the thickness direction, the total adsorbed amount, and the occupancy of trap sites, fully restoring the time memory effect of tritium accumulation on the building envelope. The three-dimensional flow field wall boundary no longer relies on fixed empirical adsorption parameters, but instead constructs dynamic boundary conditions that change in real time with the simulation duration, the interfacial gas phase concentration, the ambient temperature and humidity, and the tritium content inside the building material, eliminating the overestimation or underestimation of the risk of secondary tritium release caused by traditional fixed adsorption boundaries.

[0097] 3) By dynamically coupling the gas-solid interface in both directions, the entire process of long-term secondary release of tritium is simultaneously and completely characterized, including net adsorption of building materials in the early stage of an accident, saturation retention in the middle stage, and gradual desorption of tritium inside the building materials after the accident and release of tritium through solid-phase diffusion. This significantly improves the long-term prediction accuracy of tritium long-tail concentration in the plant after the accident and makes up for the technical deficiency that pure gas phase CFD simulation cannot quantify the contribution of secondary release of building materials.

[0098] 4) By adopting the dual constraint method of global mass conservation residual and interface flux residual, the coupling calculation error between the three-dimensional gas phase domain and the low-dimensional building material model is quantitatively calculated, which significantly improves the verifiability and credibility of the dimensionality reduction simulation results and overcomes the technical bottleneck of untraceable error and unverifiable results in dimensionality reduction coupling simulation.

[0099] 5) A single plant simulation model can be adapted to multiple types of enclosure walls such as coatings, concrete, ceilings, insulation layers, and sealants. Each wall is independently configured with exclusive diffusion, adsorption, desorption, and trap capture parameters. The three-dimensional air domain and low-dimensional building material model adopt a step-by-step independent solution architecture, which supports data interoperability across software platforms and solvers. It can be easily connected to commercial CFD software, dedicated tritium material transport programs, nuclear facility digital twin platforms, and tritium safety quantitative evaluation programs to achieve integrated application.

[0100] 6) Significantly reduced computational overhead for a single simulation, supporting batch scanning calculations of multiple operating conditions such as ventilation layout schemes, leak source locations, building material parameters, and accident duration, providing reliable numerical support for the design of tritium safety structures in fusion reactor buildings, the formulation of emergency response plans for leak accidents, the assessment of radiation doses for on-site personnel, and the design of post-contamination treatment plans for the buildings.

[0101] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0102] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A dimension-reduction-dynamic coupling simulation method for tritium migration in factory buildings, characterized in that, include: Obtain the geometric model of the plant, ventilation system parameters, tritium leak source parameters, and building material parameters; Based on the geometric model, the ventilation system parameters, and the tritium leakage source parameters, a three-dimensional airflow field model of the plant is established. Based on the building material parameters, identify the thin-layer building material domain in the factory building and match the corresponding low-dimensional building material retention model; Establish the correspondence between each of the thin-layer building material domains and the wall surface in the three-dimensional airflow field model; Within each simulation time step, bidirectional data exchange and conservation error calculation are performed. The bidirectional data exchange includes: the three-dimensional airflow model transmitting interface gas phase parameters to the low-dimensional tritium retention model according to the correspondence; the low-dimensional tritium retention model solving for the cross-gas-solid interface exchange flux according to the interface gas phase parameters and transmitting it back to the corresponding wall. The conservation error calculation includes: calculating the mass conservation error across the gas-solid interface. The simulation is iteratively executed at each time step until the preset simulation termination time is reached, and the simulation results, including the spatiotemporal distribution of gas phase tritium concentration and the cumulative value of tritium retention on the wall, are output.

2. The method according to claim 1, characterized in that, The establishment of a three-dimensional airflow field model for the plant based on the geometric model, the ventilation system parameters, and the tritium leakage source parameters includes: A three-dimensional computational mesh for the air domain inside the factory building is generated based on the geometric model. On the three-dimensional computational grid, the ventilation system parameters are used as boundary conditions to set the air supply velocity and direction, return air pressure and flow rate, and the tritium leakage source parameters are used as mass source terms to set the leakage point location and release rate. Based on the boundary conditions and the mass source term, a three-dimensional computational fluid dynamics model is used to solve the problem and obtain the airflow field distribution, which includes the velocity field, pressure field, and tritium concentration field.

3. The method according to claim 1, characterized in that, The building material parameters include the thickness of all walls in the factory building; the identification of thin-layer building material domains in the factory building based on the building material parameters includes: The thickness of each wall surface is compared with a preset thickness threshold. Wall surfaces with a thickness less than or equal to the preset thickness threshold are marked as the thin-layer building material domain.

4. The method according to claim 1, characterized in that, The matching low-dimensional building material retention model includes: For each thin-layer building material domain, the gas-solid interface exchange intensity, tritium retention contribution, and tritium solid-phase diffusion coefficient of the thin-layer building material domain are obtained from the building material parameters, and the solid-phase diffusion characteristic time of tritium in the thin-layer building material domain is calculated based on the tritium solid-phase diffusion coefficient. Based on the thickness of the thin-layer building material domain, the solid-phase diffusion characteristic time, the gas-solid interface exchange intensity, and the tritium retention contribution of the building material, the thin-layer building material domain is matched to one of the following: a two-dimensional surface model, a one-dimensional normal diffusion model, or a zero-dimensional stock model.

5. The method according to claim 1, characterized in that, The establishment of the correspondence between each of the thin-layer building material domains and the wall surface in the three-dimensional airflow field model includes: Each wall in the three-dimensional airflow field model is assigned a unique interface number; Each of the thin-layer building material domains is associated with its corresponding interface number to establish a one-to-one correspondence between each of the thin-layer building material domains and its corresponding wall surface.

6. The method according to claim 1, characterized in that, The three-dimensional airflow field model transmits interface gas phase parameters to the low-dimensional tritium retention model according to the correspondence, including: The three-dimensional airflow field model determines the target wall corresponding to each low-dimensional tritium retention model based on the correspondence. The gaseous tritium concentration, wall temperature, relative humidity, and convective mass transfer coefficient at each target wall surface are extracted as the interfacial gaseous parameters. The interface gas phase parameters are transferred to the low-dimensional tritium retention model of the corresponding wall surface.

7. The method according to claim 1, characterized in that, The low-dimensional tritium retention model solves for the cross-gas-solid interface exchange flux based on the interface gas phase parameters, including: The low-dimensional tritium retention model updates its internal tritium state parameters based on the interface gas phase parameters. The internal tritium state parameters include the tritium concentration on the building material surface, the concentration distribution along the thickness direction, the total adsorption stock, the occupancy of trap sites, and the desorption secondary release rate. The gas-solid interface exchange flux is calculated based on the updated tritium state parameters inside the building material.

8. The method according to claim 1, characterized in that, The feedback to the corresponding wall surface includes: When the cross-gas-solid interface exchange flux is the net adsorption flux from the gas phase to the solid phase, the cross-gas-solid interface exchange flux is used as the gas phase tritium mass loss boundary and fed back to the corresponding wall. When the cross-gas-solid interface exchange flux is the net desorption flux released from the interior of the building material to the gas phase, the cross-gas-solid interface exchange flux is used as the internal source boundary of the gas phase tritium mass and fed back to the corresponding wall surface.

9. The method according to claim 1, characterized in that, The simulation results include the spatial cloud map of the global gas phase tritium concentration in the plant, the time history curve of tritium concentration at key monitoring points, the total amount of tritium retained in the building materials on each wall, the secondary release flux of building materials in the later stage of the accident, the tritium emission of ventilation exhaust gas, and the global mass conservation residual.

10. An electronic device, characterized in that, include: A memory and a processor, wherein the memory stores a computer program, which, when executed by the processor, implements the dimensionality reduction-dynamic coupling simulation method for tritium migration in a factory, as described in any one of claims 1 to 9.

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