CN113887097A - Nuclear thermal strong coupling method based on inverse distance weighted interpolation - Google Patents
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Abstract
The invention discloses a nuclear thermal strong coupling method based on inverse distance weighted interpolation, which comprises the following steps: 1. constructing a grid model according to the geometric structure of the nuclear fuel assembly; 2. setting corresponding boundary conditions; 3. performing computational fluid mechanics steady state calculation, completing data transmission among grid models by using inverse distance weighted interpolation after the current residual convergence standard is reached, and starting neutron physical calculation; 4. updating a temperature database of nuclides through a corresponding temperature root mean square interpolation algorithm; 5. inAfter the sub-physical calculation is finished, extracting effective multiplication factor k in the calculation resulteffUpdating an energy source item in the computational fluid mechanics program by using inverse distance weighted interpolation according to the power density of the grid cells; 6. comparing the effective multiplication factor k calculated by adjacent iterationseffWhether the convergence is achieved or not, if yes, the calculation is finished; otherwise, returning to the step 1 for recalculation. The invention can realize high-precision steady-state nuclear thermal coupling analysis and obtain the distribution result of the reactor assembly in actual thermal hydraulic parameters and neutron physical parameters.
Description
Technical Field
The invention relates to the field of nuclear reactor core design and safety analysis, in particular to a nuclear thermal strong coupling method based on inverse distance weighted interpolation.
Background
The reactor multi-physics field coupling is a key technology for comprehensively analyzing the reactor, neutron physics calculation and thermal fluid calculation are divided in a traditional mode, and the obtained result is usually conservative and cannot accurately reflect the real physics condition and phenomenon of the reactor or components in the reactor. Therefore, the steady state analysis of nuclear thermal coupling by coupling a neutronics calculation program with a thermal fluid calculation program will provide finer physical parameters and related design criteria for reactor design.
The mainstream Monte Carlo method transportation calculation program mainly comprises MCNP, OpenMC, Serpent and SCALE; the mainstream Computational Fluid Dynamics (CFD) software mainly includes: ANSYS Fluent, ANSYS CFX, and STAR-CCM +. At present, most of core thermal coupling programs adopt MCNP and Fluent, MCNP and STAR-CCM +, MCNP and OpenFOAM for coupling, wherein grid mapping of the MCNP and the starccm is a big difficulty, and a commonly used method is grid one-to-one mapping: the MCNP and Fluent use the same set of grids, and the grid number of the MCNP and Fluent, the central coordinates of grid cells and the coordinates of each surface are completely the same; however, the method has the disadvantages that when the target structure is very complex, the MCNP is difficult to generate meshes, and the MCNP has limitations on the maximum number of cells and the maximum number of curved surfaces on the input card, so when a large number of meshes are needed for fluid mechanics calculation, in order to ensure the successful operation of the MCNP, the number of meshes for fluid mechanics calculation has to be reduced by using a mesh-to-mesh mapping method, which may cause the situation that the quality of the fluid mechanics calculation meshes is poor and the error is large.
A more common method is a volume weighting method, which is greatly improved compared with the above method, wherein a same set of grids are not used for neutron science calculation and fluid mechanics calculation, but a coarse grid is used for MCNP, and a fine grid is adopted for fluid mechanics calculation, so that the factor limited by the maximum number of MCNP grids can be overcome to a certain extent, but the method causes large calculation amount and difficult solution when solving volume and weighting factors; the method is easily influenced by a geometric model and a grid division mode, if the geometric model is complex or any one of MCNP and a fluid mechanics calculation grid adopts an unstructured grid, a large amount of calculation can be carried out on a solution volume during fine coupling solution, and therefore certain calculation difficulty is caused.
The inverse distance weighted interpolation algorithm may also be referred to as an inverse distance multiplication algorithm. The calculation result does not depend on relevant mathematical conditions. The value of the target node is calculated after weighted average of the distance between the target node and the interpolation node and the value of the interpolation node. When the distance between the interpolation node and the target node is far, the influence of the interpolation node on the target node is proved to be small, so that the weight is small; on the contrary, when the distance between the interpolation node and the target node is relatively close, the influence of the interpolation node on the target node is proved to be relatively large, so that the weight is relatively large.
When the three-dimensional nuclear thermal coupling method of the inverse distance weighted interpolation is used, the key point is the coordinates of the central point of the grid, so the inverse distance weighted interpolation can be calculated by using two grids of thickness. Wherein, the ANSYS Fluent calculation adopts a fine grid, and the MCNP adopts a rough grid for calculation. Therefore, the running speed of the MCNP can be effectively improved, the accuracy of an ANSYS Fluent calculation result is improved, and the limitation of the maximum cell number of the MCNP is broken through. In the process of nuclear thermal coupling by an inverse distance weighted interpolation algorithm, the relative shape of a geometric body is secondary, and only the original point and the relative position of a thick-thin grid are required to be ensured to be the same, so that the method is very effective when the method is used for processing complicated time.
In summary, the nuclear thermal coupling of the inverse distance weighted interpolation algorithm has the following advantages:
1. breaking through the limitation of the maximum number of MCNP (micro computer network processor) grid cells and the maximum number of curved surfaces;
2. a more refined ANSYS Fluent grid model can be divided to perform more accurate fluid mechanics calculation;
3. the MCNP operation speed is increased;
4. the inverse distance weighted interpolation algorithm is irrelevant to the shape of a geometric body, and complex geometry is processed more efficiently;
the flow channel of the plate type fuel assembly of the Chinese advanced experimental fast reactor is a closed flow channel, the exchange of the mass and momentum of the coolant hardly exists among the coolant flow channels in the assembly, the water gap among the assemblies is small, the flow velocity of the coolant in the plate type fuel assembly is high, and the heat transfer performance is also large; compared with a rod-bundle fuel assembly with the same volume, the neutron flux density is higher, the working temperature is lower, the fuel consumption is deeper, and in order to solve the neutron physics and thermal hydraulic conditions in the plate-type fuel element and the assembly more finely, a fine three-dimensional nuclear thermal strong coupling method based on inverse distance weighted interpolation is developed.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention aims to provide a nuclear thermal strong coupling method based on inverse distance weighted interpolation, and data obtained by applying the method of the invention can provide reference for relevant design and research works of fuel elements, components, a reactor core and the like in a reactor.
In order to achieve the purpose, the invention adopts the following technical scheme:
a nuclear thermal strong coupling method based on inverse distance weighted interpolation comprises the following steps:
the method comprises the following steps: carrying out model construction and grid division on a calculation object by using preprocessing modeling software, computational fluid mechanics software and a Monte Carlo method transport calculation program; constructing a geometric model of the nuclear fuel assembly by using pre-processing modeling software, introducing the geometric model into computational fluid dynamics software, dividing a fine structured grid of the nuclear fuel assembly by using the computational fluid dynamics software, and performing fluid mechanics calculation; modeling a nuclear fuel assembly by using a Monte Carlo method to transport a calculation program, wherein the model comprises a fuel element, a coolant and a cladding; the method comprises the steps that a nuclear fuel assembly model applied to a Monte Carlo method transportation calculation program is correspondingly achieved through a user-defined function in computational fluid dynamics software, and automatic coarse grid division is achieved; the method comprises the following specific steps of correspondingly applying a user-defined function in computational fluid dynamics software to a nuclear fuel assembly model in a Monte Carlo method transport calculation program to finish automatic rough grid division:
step 1: specifying dimensions and materials of a geometric model of a nuclear fuel assembly into a user-defined function of computational fluid dynamics software;
step 2: specifying a coordinate origin position when a user-defined function of computational fluid dynamics software is used to mesh a geometric model of a nuclear fuel assembly;
and step 3: appointing the grid division number in the X direction, the Y direction and the Z direction, and obtaining the grid center point coordinate and the curved surface position coordinate of the nuclear fuel assembly through a user-defined function of computational fluid dynamics software;
and 4, step 4: generating a curved surface input card of a Monte Carlo transportation calculation program for neutron physical calculation according to the grid central point coordinates and the curved surface position coordinates obtained in the step 3;
and 5: according to the curved surface input card generated in the step 4, a corresponding Boolean operation rule is appointed, and a grid cell input card for a Monte Carlo method transport calculation program for neutron physical calculation is generated;
step 6: generating a material input card for a Monte Carlo method transport calculation program for neutron physical calculation by designating different area material labels according to the grid cell input card generated in the step 5;
and 7: assigning the number of simulated particles, the number of iterations and the distribution of fission source items in the eigenvalue calculation to generate an eigenvalue calculation input card;
and 8: designating fission energy statistical counting and generating a fission energy counting input card;
and step 9: merging the curved surface input card generated in the step 4, the grid cell input card generated in the step 5, the material input card generated in the step 6, the eigenvalue calculation input card generated in the step 7 and the fission energy counting input card generated in the step 8 to obtain a final input card for transporting the calculation program by the Monte Carlo method;
step two: respectively setting boundary conditions for nuclear fuel assemblies in computational fluid dynamics software and a Monte Carlo method transport calculation program; the computational fluid dynamics software sets components as a speed inlet boundary condition and an outlet boundary condition with zero pressure, and symmetric boundary conditions are arranged around the components; the Monte Carlo method transports the boundary condition of total reflection around the computer program setting assembly, upper and lower ends are the vacuum boundary condition;
step three: performing fluid mechanics calculation by using computational fluid mechanics software, considering that the fluid mechanics calculation is converged when the continuity residual error is reduced to 1E-3, extracting the temperature and density of each grid of a target geometric body in a fluid mechanics calculation result by using a user-defined function, performing calculation by using an inverse distance weighted interpolation algorithm, and mapping data on a fine grid in a fluid mechanics calculation model into a rough grid of a Monte Carlo method transport calculation program;
inverse distance weighted interpolation algorithm:
if d (x, x)i) If the temperature is more than or equal to err, then:
otherwise:
u(x)＝ui
wherein:
in the formula:
i is an index of an interpolation node;
d(x,xi) The distance between the target node and the interpolation node is taken as the distance;
err is a minimum positive number and is used for floating point judgment in a computer;
wi(x) The weight of the node at the position x and the index of the node is i;
n is the number of interpolation nodes;
uian interpolation node value with index i;
u (x) is the target node value;
p is a power value;
step four: calculating the section data of nuclides in the selected temperature interval through a temperature root mean square interpolation function according to the temperature data and the density data obtained in the third step;
the temperature root mean square interpolation formula is:
Σ(T)＝fLΣ(TL)+(1-fL)Σ(TH)
in the formula:
t is the nuclear fuel assembly grid temperature;
THthe highest temperature/K of the selected temperature interval;
TLis the lowest temperature/K of the selected temperature interval;
Σ(TH) Cross-sectional data for the highest temperature of the selected temperature interval;
Σ(TL) Cross-sectional data for the lowest temperature of the selected temperature interval;
sigma (T) is macroscopic section/m-1；
fLThe share of the lowest temperature in the temperature interval and the share in the database;
selecting and generating section data of the Monte Carlo method transportation calculation program through a temperature root mean square interpolation formula, further generating an input card of the Monte Carlo method transportation calculation program, and calling the Monte Carlo method transportation calculation program for calculation;
step five: after the Monte Carlo method transport calculation program is calculated, reading the effective multiplication factor k in the output fileeffThe calculation of the real power of the nuclear fuel assembly is performed with a normalized power distribution followed by a power distribution by a power density distribution function:
the power density distribution function is:
in the formula:
gicalculating a normalization result for each grid cell in the output file of the Monte Carlo method transport calculation program;
∑gisumming all the normalized results;
p is the total power density of the component or assembly;
piweighting the calculated true power density for each cell;
carrying out inverse distance weighted interpolation on the real power density of each grid cell after the calculation by the formula is finished, namely realizing grid mapping and data transmission from a coarse grid of a Monte Carlo method transport calculation program to a fine grid of a fluid mechanics calculation model; in the interpolation process, a memory structure in a user-defined function is used for data storage, and then an energy source item is given to a specified area in the fluid mechanics calculation model through the user-defined function so as to carry out the next fluid mechanics calculation work;
step six: extracting effective multiplication factor k after Monte Carlo method transport calculation program calculation in several coupling calculationseffK for several iterationseffAnd if the fluctuation range is less than 1E-3, the coupling calculation is considered to be converged, and if the calculation is finished, the step is returned to the first step to start the next iterative calculation.
Compared with the prior art, the invention has the following advantages:
1. the limitation of the maximum grid element number and the maximum curved surface number in a Monte Carlo method transport calculation program is broken through;
2. a more refined computational fluid dynamics software grid model can be divided to perform more accurate fluid dynamics calculation;
3. the running speed of the Monte Carlo method for transporting the calculation program is increased;
4. the inverse distance weighted interpolation algorithm is independent of the shape of a geometric body, and can efficiently process complex geometry;
drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a geometric model of a plate type fuel assembly of a Chinese advanced experiment fast reactor;
FIG. 3 is a grid model of a Chinese advanced experimental fast reactor plate type fuel assembly;
Detailed Description
The invention is further described in detail with reference to the accompanying drawings and the specific embodiment of the fast reactor plate type fuel assembly for the Chinese advanced experiment, wherein the three-dimensional modeling software used in the embodiment is ANSYS Design Moder, the computational fluid dynamics software is ANSYS Fluent, and the Monte Carlo method transport calculation program is MCNP.
As shown in fig. 1, the fine three-dimensional nuclear thermal strong coupling method based on inverse distance weighted interpolation in this embodiment includes the following steps:
the method comprises the following steps: using ANSYS Design Modelr, ANSYS Fluent and MCNP to construct a model of the plate type fuel assembly and divide a grid; ANSYS Design Modler constructs a plate type fuel assembly geometric model for hydromechanical calculations, as shown in FIG. 2; ANSYS Fluent constructs a plate-type fuel assembly grid model for hydrodynamics calculations, as shown in FIG. 3; the MCNP constructs a geometric model and a grid model for neutron physics calculation, wherein the grid model for neutron physics calculation is constructed by using a user-defined function in ANSYS Fluent, and the construction of the grid model comprises the following specific steps:
step 1: specifying the geometric model dimensions and materials of the plate-type fuel assembly to a user-defined function;
step 2: appointing the coordinate origin position of the plate type fuel assembly when using a user-defined function in an ANSYS Fluent to perform grid division;
and step 3: appointing the grid division number in the X direction, the Y direction and the Z direction, and acquiring the grid center point coordinate and the curved surface position coordinate of the plate type fuel assembly through a user-defined function in ANSYS fluent;
and 4, step 4: generating a curved surface input card of the MCNP according to the grid central point coordinates and the curved surface position coordinates obtained in the step 3;
and 5: according to the curved surface input card generated in the step 4, a corresponding Boolean operation rule is appointed, and a cell input card of the MCNP is generated;
step 6: generating a material input card of the MCNP by appointing material labels of different areas according to the cell input card generated in the step 5;
and 7: assigning the number of simulated particles, the number of iterations and the distribution of fission source items in the eigenvalue calculation to generate an eigenvalue calculation input card;
and 8: designating fission energy statistical counting to generate a fission energy counting card;
and step 9: merging the curved surface input card generated in the step 4, the grid cell input card generated in the step 5, the material input card generated in the step 6, the eigenvalue calculation input card generated in the step 7 and the fission energy counting card generated in the step 8 to obtain an integral input card of the MCNP;
step two: setting physical boundary conditions corresponding to the ANSYS Fluent and the MCNP for the plate type fuel assembly; wherein, the ANSYS Fluent sets the plate type fuel assembly as a speed inlet boundary condition, an outlet boundary condition with zero pressure and a symmetrical boundary condition at the periphery; the MCNP sets a total reflection boundary condition around the component, and a vacuum boundary condition is arranged at the upper end and the lower end of the component;
step three: firstly, performing fluid mechanics calculation by using an ANSYS Fluent, judging whether a continuity residual error in the fluid mechanics calculation is smaller than 1E-3 by using a user-defined function of the ANSYS Fluent, and if the continuity residual error is smaller than 1E-3, considering that the fluid mechanics calculation is converged at the moment, and finishing the fluid mechanics calculation of the ANSYS Fluent; after the ANSYS Fluent is calculated, extracting the temperature and the density of each grid of a target geometric body in the ANSYS Fluent through a user-defined function, and mapping data on the fine grid of the ANSYS Fluent middle plate type fuel assembly into the rough grid of the MCNP middle plate type fuel assembly by using a reverse distance weighted interpolation algorithm;
inverse distance weighted interpolation algorithm:
if d (x, x)i) If the temperature is more than or equal to err, then:
otherwise:
u(x)＝ui
wherein:
in the formula:
i is an index of an interpolation node;
d(x,xi) The distance between the target node and the interpolation node is taken as the distance;
err is a minimum positive number and is used for floating point judgment in a computer;
wi(x) The weight of the node at the position x and the index of the node is i;
n is the number of interpolation nodes;
uian interpolation node value with index i;
u (x) is the target node value;
p is a power value;
step four: calculating nuclide section data in the selected temperature interval through a temperature root mean square interpolation function according to the temperature data and the density data obtained in the third step;
the temperature root mean square interpolation formula is:
Σ(T)＝fLΣ(TL)+(1-fL)Σ(TH)
in the formula:
t is the nuclear fuel assembly grid temperature;
THthe highest temperature/K of the selected temperature interval;
TLis the lowest temperature/K of the selected temperature interval;
Σ(TH) Cross-sectional data for the highest temperature of the selected temperature interval;
Σ(TL) Cross-sectional data for the lowest temperature of the selected temperature interval;
sigma (T) is macroscopic section/m-1；
fLThe share of the lowest temperature in the temperature interval and the share in the database;
selecting and generating nuclide section data through a temperature root mean square interpolation formula, further generating an MCNP input card, and calling the MCNP to perform neutron physical calculation;
step five: after MCNP calculation is completed, reading effective multiplication factor k in an output fileeffWith power distribution, the MCNP output is normalized power density, and calculation of real power is required, so power is distributed by a power density distribution function:
the power density distribution function is:
in the formula:
gicalculating a normalization result for each cell in the MCNP output file;
∑gisumming all the normalized results;
p is the total power density of the component or assembly;
piweighting the calculated true power density for each cell;
and performing inverse distance weighted interpolation on the real power density of each grid cell after the calculation by the formula is completed, namely performing grid mapping and data transmission on the coarse grid of the plate type fuel assembly of the MCNP to the fine grid of the plate type fuel assembly of the ANSYS flow and endowing an energy source item for the next calculation work of the ANSYS flow.
Step six: extracting k after MCNP calculation in several coupling calculationseffSeveral times keffAnd if the fluctuation range is less than 1E-3, the coupling calculation is considered to be converged, and if the calculation is finished, the step is returned to the first step to start the next iterative calculation.
Claims (2)
1. A nuclear thermal strong coupling method based on inverse distance weighted interpolation is characterized in that:
solving a three-dimensional fluid mechanics equation by using a finite volume method and solving a three-dimensional neutron transport equation by using a Monte Carlo method; the method comprises the steps of constructing a fluid mechanics fine grid model and a Monte Carlo method transportation calculation coarse grid model, considering feedback effects of coolant temperature and fuel temperature on neutron physics, using an inverse distance weighted interpolation algorithm to complete data mapping between the coarse grid model and the fine grid model, and realizing fine nuclear thermal coupling calculation after coupling iteration; the method can provide high-precision nuclear thermal coupling calculation results for nuclear reactor design, safety analysis and operation;
the method comprises the following steps:
the method comprises the following steps: carrying out model construction and grid division on a calculation object by using preprocessing modeling software, computational fluid mechanics software and a Monte Carlo method transport calculation program; constructing a geometric model of the nuclear fuel assembly by using pre-processing modeling software, introducing the geometric model into computational fluid dynamics software, dividing a fine structured grid of the nuclear fuel assembly by using the computational fluid dynamics software, and performing fluid mechanics calculation; modeling a nuclear fuel assembly by using a Monte Carlo method to transport a calculation program, wherein the model comprises a fuel element, a coolant and a cladding; the method comprises the steps that a nuclear fuel assembly model applied to a Monte Carlo method transportation calculation program is correspondingly achieved through a user-defined function in computational fluid dynamics software, and automatic coarse grid division is achieved; the method comprises the following specific steps of completing automatic division of a coarse grid by corresponding a user-defined function in computational fluid dynamics software to a nuclear fuel assembly model applied to a Monte Carlo method transport calculation program:
step 1: specifying dimensions and materials of a geometric model of a nuclear fuel assembly into a user-defined function of computational fluid dynamics software;
step 2: specifying a coordinate origin position when a user-defined function of computational fluid dynamics software is used to mesh a geometric model of a nuclear fuel assembly;
and step 3: appointing the grid division number in the X direction, the Y direction and the Z direction, and obtaining the grid center point coordinate and the curved surface position coordinate of the nuclear fuel assembly through a user-defined function of computational fluid dynamics software;
and 4, step 4: generating a curved surface input card of a Monte Carlo transportation calculation program for neutron physical calculation according to the grid central point coordinates and the curved surface position coordinates obtained in the step 3;
and 5: according to the curved surface input card generated in the step 4, a corresponding Boolean operation rule is appointed, and a grid cell input card for a Monte Carlo method transport calculation program for neutron physical calculation is generated;
step 6: generating a material input card for a Monte Carlo method transport calculation program for neutron physical calculation by designating different area material labels according to the grid cell input card generated in the step 5;
and 7: assigning the number of simulated particles, the number of iterations and the distribution of fission source items in the eigenvalue calculation to generate an eigenvalue calculation input card;
and 8: designating fission energy statistical counting and generating a fission energy counting input card;
and step 9: merging the curved surface input card generated in the step 4, the grid cell input card generated in the step 5, the material input card generated in the step 6, the eigenvalue calculation input card generated in the step 7 and the fission energy counting input card generated in the step 8 to obtain a final input card for transporting the calculation program by the Monte Carlo method;
step two: respectively setting boundary conditions for nuclear fuel assemblies in computational fluid dynamics software and a Monte Carlo method transport calculation program;
step three: performing fluid mechanics calculation by using computational fluid mechanics software, considering that the fluid mechanics calculation is converged when the continuity residual error is reduced to 1E-3, extracting the temperature and density of each grid of a target geometric body in a fluid mechanics calculation result by using a user-defined function, performing calculation by using an inverse distance weighted interpolation algorithm, and mapping data on a fine grid in a fluid mechanics calculation model into a rough grid of a Monte Carlo method transport calculation program;
inverse distance weighted interpolation algorithm:
if d (x, x)i) If the temperature is more than or equal to err, then:
otherwise:
u(x)＝ui
wherein:
in the formula:
i is an index of an interpolation node;
d(x,xi) The distance between the target node and the interpolation node is taken as the distance;
err is a minimum positive number and is used for floating point judgment in a computer;
wi(x) The weight of the node at the position x and the index of the node is i;
n is the number of interpolation nodes;
uian interpolation node value with index i;
u (x) is the target node value;
p is a power value;
step four: calculating the section data of nuclides in the selected temperature interval through a temperature root mean square interpolation function according to the temperature data and the density data obtained in the third step;
the temperature root mean square interpolation formula is:
Σ(T)＝fLΣ(TL)+(1-fL)Σ(TH)
in the formula:
t is the nuclear fuel assembly grid temperature;
THthe highest temperature/K of the selected temperature interval;
TLis the lowest temperature/K of the selected temperature interval;
Σ(TH) Cross-sectional data for the highest temperature of the selected temperature interval;
Σ(TL) Cross-sectional data for the lowest temperature of the selected temperature interval;
sigma (T) is macroscopic section/m-1；
fLThe share of the lowest temperature in the temperature interval and the share in the database;
selecting and generating section data of the Monte Carlo method transportation calculation program through a temperature root mean square interpolation formula, further generating an input card of the Monte Carlo method transportation calculation program, and calling the Monte Carlo method transportation calculation program for calculation;
step five: after the Monte Carlo method transport calculation program is calculated, reading the effective multiplication factor k in the output fileeffThe calculation of the real power of the nuclear fuel assembly is performed with a normalized power distribution followed by a power distribution by a power density distribution function:
the power density distribution function is:
in the formula:
gitransport calculation program output for Monte Carlo methodCalculating a normalization result for each cell in the file;
∑gisumming all the normalized results;
p is the total power density of the component or assembly;
piweighting the calculated true power density for each cell;
carrying out inverse distance weighted interpolation on the real power density of each grid cell after the calculation by the formula is finished, namely realizing grid mapping and data transmission from a coarse grid of a Monte Carlo method transport calculation program to a fine grid of a fluid mechanics calculation model; in the interpolation process, a memory structure in a user-defined function is used for data storage, and then an energy source item is given to a specified area in the fluid mechanics calculation model through the user-defined function so as to carry out the next fluid mechanics calculation work;
step six: extracting effective multiplication factor k after Monte Carlo method transport calculation program calculation in several coupling calculationseffK for several iterationseffAnd if the fluctuation range is less than 1E-3, the coupling calculation is considered to be converged, and if the calculation is finished, the step is returned to the first step to start the next iterative calculation.
2. The nuclear thermal strong coupling method based on inverse distance weighted interpolation of claim 1, wherein: setting boundary conditions for the nuclear fuel assembly in computational fluid dynamics software and a Monte Carlo method transportation computation program respectively in the step two; the computational fluid dynamics software sets boundary conditions of the assembly as a speed inlet boundary condition and an outlet boundary condition with zero pressure, and symmetric boundary conditions are arranged around the assembly; the Monte Carlo method transports the boundary condition of total reflection around the computer program setting assembly, the upper and lower ends are vacuum boundary conditions.
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