56 results about "Mesh adaptation" patented technology

The invention relates to the technical field of equipment intelligent diagnosis, in particular to a generator digital twinning diagnosis method based on temperature field online simulation, which comprises the following steps: respectively constructing a three-dimensional virtual model, a temperature field simulation model and an intelligent agent diagnosis model; the digital twin is in data connection with the physical entity; data alignment is achieved through a unified space-time coordinate system, a mapping relation is established between a vertex of the three-dimensional virtual model and a grid node in the temperature field simulation model, and a fault probability matrix output by the intelligent agent diagnosis model is matched to a three-dimensional grid of the three-dimensional virtual model through spatial interpolation; according to a fault probability output by the intelligent agent diagnosis model, correcting a boundary condition of the temperature field simulation model, triggering local grid adaptive encryption of the temperature field simulation model, and marking a fault position in real time through a three-dimensional virtual model; and the simulation result of the temperature field simulation model verifies the fault probability output by the intelligent agent diagnosis model. Through the method, the fault identification accuracy can be effectively improved.

The invention discloses a three-dimensional unstructured grid adaptive refinement method and system based on machine learning, and belongs to the field of machine learning, partial differential equation solving and computational fluid mechanics simulation. Residual errors of a fluid control equation are used as a novel error indicator and a refinement criterion, imprecise flow field data and the fluid control equation are obtained by fusing coarse grids of simulation flow through a physical information neural network, and the total residual errors of the equations are conveniently calculated by using automatic differentiation after training is completed. Therefore, the coarse grid units with relatively high residual errors can be adaptively marked and refined. By matching an h-refinement scheme, Delaunay tetrahedron subdivision is executed after vertexes are strategically inserted to maintain the quality of the refined grid. According to the method, any numerical solver can be flexibly matched to carry out grid adaptive refinement, so that various typical flow problems can be solved with high precision. The method achieves better balance between calculation precision and the number of grids, and has the advantages of being simple, convenient, high in compatibility and universality and the like.

The invention discloses an electromagnetic field simulation grid adaptive generation method based on a neural network. The method comprises the following steps: performing mesh generation on a semiconductor device simulation model to obtain original generation data, and constructing node features; an undirected graph is constructed, graph nodes of the undirected graph adopt node features of grid points, and connecting edges adopt Euclidean distances between the grid points and adjacent grid points; inputting the undirected graph into a double-branch neural network, and outputting a predicted node position; and correcting each node of the original subdivision data by using the predicted node position obtained by the double-branch neural network to form new subdivision data for electromagnetic field simulation. According to the method, physical field information can be fused to efficiently adjust the node density, and the geometric boundary and topological structure characteristics of the device can be strictly kept.

The invention discloses a micro-scale turbine blade boundary layer heat-flow double-field synchronous test method and system. The test method comprises the steps that temperature field initial data and velocity field initial data are acquired; based on the initial data of the temperature field and the initial data of the velocity field, the distribution state of the microparticles in the boundary layer is diagnosed, and according to the diagnosis result, the optimal distribution of the microparticles in the boundary layer is obtained by feeding back and controlling the operation parameters of the reverse cyclone separation system; based on the optimal distribution, an improved PIV algorithm is adopted to calculate a boundary layer velocity field, and the improved PIV algorithm is obtained by introducing multistage grid adaptive encryption, physical constraint conditions and a transition area recognition mechanism into the PIV algorithm; a boundary layer temperature field reconstruction model is established, depth phase coupling is carried out on a temperature field reconstruction result and a boundary layer velocity field, synchronous analysis of heat-flow coupling behaviors in a turbine blade boundary layer is achieved, and finally a boundary layer coupling cloud picture reflecting heat-flow interaction characteristics is obtained.

The invention belongs to the field of electromagnetic field numerical solution, and particularly provides a finite element mesh adaptive method for network parameter analysis of a multi-port microwave device, which comprises the following steps: firstly, establishing a geometric structure of the multi-port microwave device, setting simulation frequency, excitation and boundary conditions, and establishing an electromagnetic simulation model; secondly, performing preliminary division and finite element electromagnetic simulation calculation on a computational domain by adopting a tetrahedral mesh to obtain a numerical solution corresponding to each group of excitation, and synthesizing results based on a posterior error estimation method for posterior error estimation; and finally, according to a posterior error indication grid encryption parameter, carrying out simulation calculation again after encryption, and repeating the process until the solution meets the precision requirement. In conclusion, by combining the characteristics of a finite element algorithm and the characteristics of an error estimation algorithm, in the microwave device network parameter analysis process, multiple sets of excited numerical solutions are comprehensively used for posterior error estimation and grid adaptive encryption indication, so that the analysis precision of network parameters is improved.

The invention discloses a three-dimensional geologic modeling level exploration system, belongs to the technical field of three-dimensional modeling, and aims to solve the problem that accurate evaluation of mineral resource reserves is affected due to the fact that fine morphological changes of an ore body are difficult to accurately present by a traditional method. Mesh subdivision adopts an improved algorithm, grid adaptive adjustment is realized according to physical properties of a geologic body, the expression ability of a model to a complex geologic structure is greatly improved, an attribute assignment unit accurately connects and fuses data and a grid unit and endows the data and the grid unit with real physical attributes, so that the model is more practical, and a dynamic updating unit analyzes by means of a time sequence, so that the dynamic updating efficiency is improved. Time dimension is fused, a model is updated in real time, geological dynamic changes are reflected, the problem of traditional updating lag is solved, the geological analysis unit utilizes multiple methods, volume, trend, inclination angle and resource distribution prediction quantitative data are output for geological research, deep analysis of geological conditions is assisted, and the dilemma that a traditional analysis function is single is overcome.

The embodiment of the invention discloses a space grid adaptive division method and device, equipment and a medium. According to the embodiment of the invention, the method comprises the steps: obtaining the multi-source heterogeneous three-dimensional data of a target region, carrying out the preprocessing of the multi-source heterogeneous three-dimensional data, and obtaining the vertex density of each vertex in the target region; according to the vertex coordinates of the vertexes, performing prediction based on a pre-trained environment factor continuous expression model to obtain multivariate environment factors corresponding to the vertexes; for any grid in the target area, determining whether the grid is a to-be-divided grid based on the vertex density of each vertex in the grid and the multivariate environment factor; and continuously dividing the grid to be divided based on the longest axis bisection strategy. Therefore, the vertex density and the environmental factors are integrated into the judgment mechanism of the grid to be divided, recursive division is performed through the judgment mechanism, so that a finer grid is obtained in a complex area or a high-risk environment, a thicker grid is maintained in a simple area or a low-risk environment, and non-uniform and differentiated adaptive division is realized.

This application discloses a spatial grid adaptive partitioning method, apparatus, device, and medium. The embodiment acquires multi-source heterogeneous 3D data of a target region and preprocesses the data to obtain the vertex density of each vertex within the target region. Based on the vertex coordinates, a pre-trained continuous environmental factor expression model predicts the multivariate environmental factors corresponding to each vertex. For any grid within the target region, based on the vertex density and multivariate environmental factors, it is determined whether the grid is to be partitioned. The grid to be partitioned is further partitioned based on the longest axis bisection strategy. Thus, by incorporating vertex density and environmental factors into the determination mechanism of the grid to be partitioned, and recursively partitioning through this mechanism, complex regions or high-risk environments obtain finer grids, while simple regions or low-risk environments maintain coarser grids, achieving non-uniform and differentiated adaptive partitioning.

The application discloses an intelligent dynamic grid self-adapting method and equipment for droplet pool simulation of additive manufacturing, and the method comprises the following steps: establishing a simulation model of additive manufacturing by using a pool simulation tool; extracting the simulation real-time gas phase fraction gradient, solid phase fraction gradient, solute concentration gradient and pool temperature gradient of each grid at each time step of simulation as the perceived physical parameters; adaptively calculating the encryption urgency index of each grid according to the perceived physical parameters; obtaining the historical encryption urgency index of each grid, calculating the second-order difference value, and predicting the change trend of the encryption urgency index of each grid at the future time; determining the encryption threshold and the coarsening threshold according to the encryption urgency index of all grids at the current time step, and combining the change trend of the encryption urgency index, the size relationship between the encryption urgency index and the threshold to determine whether the grid needs to be encrypted or coarsened; and iterating until the simulation is completed. The application has high precision, low cost and high automation degree.

This invention belongs to the field of numerical electromagnetic field solution, specifically a mesh adaptive method based on reconstructive posterior error estimation. The invention first performs finite element modeling of the target microwave component, introducing boundary conditions and excitations to establish a corresponding electromagnetic simulation model. Then, a tetrahedral mesh is used to divide the solution domain, and finite element electromagnetic simulation analysis is performed on the model to calculate the electric field at the centroid of the four faces of the tetrahedral mesh. The least squares principle is then used to refit the electric field on the tetrahedral mesh to reconstruct a first-order linear fitting expression. Next, the reconstructed solution at the nodes is calculated using the reconstructed fitting expression, and posterior error estimation is performed based on the electric field at the nodes. Finally, the mesh is refined according to the error on the tetrahedral mesh, and finite element electromagnetic simulation analysis is performed again until the finite element solution meets the accuracy requirements. This invention has the advantages of simple engineering implementation, low computational cost, and high universality.

The invention provides a numerical simulation method for fluid-structure interaction vibration of wind tunnel airflow and a tunnel wall structure, and belongs to the technical field of wind tunnels. Geometric parameters of a wind tunnel section are obtained, a multi-layer grid sequence is established, an implicit Runge-Kutta format and an explicit Newmak method are adopted to solve a flow field and a structure field respectively, and the wind tunnel airflow and tunnel wall structure fluid-structure interaction vibration is obtained. Mesh deformation is realized by using tightly-supported radial basis function interpolation, a volume conservation constraint is introduced, an interface projection matrix is constructed based on a virtual work equivalence principle to transmit interface data, a force balance and displacement coordination constraint is introduced, and coupling iteration convergence is accelerated through an inverse Broyden formula. A density gradient shock wave sensor is adopted to drive grid adaptive encryption and a mixed indicator function to control turbulence model switching, and the technical problems that wind tunnel section airflow and wall surface structure fluid-structure interaction vibration numerical simulation calculation is low in efficiency and insufficient in precision are solved.

The present invention discloses a method for simulating the filtration of a fan rotating airflow filter cartridge, comprising the following steps: S1, drawing a three-dimensional model; S2, importing the three-dimensional model into simulation software and performing rotation domain division; S3, naming and setting the fluid domain, and exporting it; S4, importing the three-dimensional model file into a grid generation tool and performing grid division; S5, establishing a rotation region model and setting the air permeability and filtration performance of the filter material; S6, setting the rotation domain of the impeller rotation region inside the fan in the three-dimensional model; S7, setting the simulation time according to the size and length of the three-dimensional model; S8, selecting a solution method and performing calculations; S9, using grid adaptation for the entire process of the airflow entering the filter cartridge from the fan inlet to the filter area under the action of the impeller rotation; S10, exporting the basic framework and result database of the simulation and importing them into CFD POST for viewing. The method can simulate the real state of the airflow forming a rotating airflow under negative pressure injection, and can also set the air permeability of the filter material.

The invention belongs to the field of electromagnetic field numerical solution, relates to antenna electromagnetic simulation, and particularly provides an error field energy-based grid adaptive encryption method, which comprises the following steps of: modeling a target antenna, introducing corresponding excitation and boundary conditions, determining an adaptive frequency point and a solution frequency band, and establishing an electromagnetic simulation model; secondly, carrying out primary division and finite element electromagnetic simulation calculation on a computational domain by adopting a tetrahedral mesh to obtain an electric field at each element node of the tetrahedral mesh, calculating energy corresponding to an error field on an interface of each element, and carrying out posterior error estimation; and finally, calculating a grid encryption strategy according to a posterior error, including an encryption unit and an encryption size, performing simulation calculation again after encryption, and repeating the process until a solution meets a precision requirement. In conclusion, according to the method, the part, not meeting the constraint condition, of the electromagnetic field solution serves as an error source, corresponding energy serves as posterior error estimation, and grid self-adaptive encryption is achieved.

The invention relates to the technical field of pipeline engineering, in particular to a pipeline real-time adjusting and optimizing system and method based on edge calculation and a dynamic evolution algorithm, five modules of distributed edge perception, position space prediction, real-time finite element analysis, multi-target optimization and layout adjustment are fused, firstly, an edge perception network collects multi-source data, and a unified tensor is generated; then, a position space prediction module predicts multi-time scale position space change based on tensor data by using a Shenchang differential equation; the real-time finite element analysis module receives prediction data, pipeline stress is calculated through a grid self-adaptive refinement technology, and hot spots are identified; the multi-objective optimization module adopts a dynamic variation differential evolution algorithm to generate a plurality of pipeline layout candidate schemes based on the hotspot data; the layout adjustment module performs multi-constraint conflict detection, adaptively adjusts candidate schemes and outputs a final pipeline layout; the system realizes intelligentization, precision and high efficiency of pipeline layout.

The application provides an improved sparse learning out-of-grid direction-of-arrival estimation method based on variational Bayesian. The method is characterized in that: the original data received by a hydrophone array is preprocessed, a real value transformation is used to convert a vectorized covariance matrix signal in a complex number field to a real number field, and the idea of variational sparse Bayesian learning and grid evolution is combined to make the grid evolve from an initial uniform grid to a non-uniform grid adaptively in an iteration process. The evolution process includes grid updating and grid fission. The evolved grid points are gradually close to the real source position through the alternately iterative grid updating process and grid fission process. Compared with the traditional compressed sensing method, the method has higher DOA estimation accuracy, reduces the operation complexity, optimizes the operation efficiency, improves the resolution capacity of the source, and has higher application value in actual engineering, especially in the case of few snapshots and low signal-to-noise ratio.

The invention discloses a physical property encryption and calculation method based on triangular mesh adaptive encryption, which comprises the following steps: marking a to-be-encrypted mesh according to the intersection condition of an initial mesh and a saturation line; generating a first layer of encryption points on the edge according to the intersection condition of the edge of the marked grid and the saturation line; determining the position of a central encryption point according to the distribution of the first layer of encryption points; judging whether the grids which are not intersected with the saturation line need to be encrypted or not according to interpolation deviation; constructing an association array of the encrypted grid to record a topological relation of points, edges and triangles; performing iterative encryption on the triangle according to a precision requirement; marking the overall phase state of the triangle according to the triangle vertex phase state; and selecting an interpolation strategy to calculate a physical property value according to the encryption state of the grid where the query point is located. According to the method, on one hand, two-phase encryption can be carried out on the saturation line, on the other hand, regional encryption can be carried out on the part with severe physical property change, and relatively high calculation precision can be realized by utilizing relatively few physical property points.

The invention relates to the technical field of computer aided design and real-time graphic calculation, in particular to a CAD modeling-oriented grid adaptive subdivision method and real-time preview method, which comprises the following steps of: sorting vertex coordinates of a model according to spatial positions, and constructing an adjacency relation by adopting a half-side structure for a grid data structure of the model; and calculating projection areas of different grid subdivision areas in the view cone as importance weights omega, and allocating computing resources and arranging a subdivision sequence according to the importance weights omega. According to the method, the importance weight omega of the grid subdivision area is rapidly calculated, the subdivision area with the high preview priority is preferentially provided with the calculation resources for subdivision, the dynamic adaptability of grid subdivision is improved, the calculation resources are reasonably distributed, and the calculation efficiency is improved.

The invention discloses a sealing performance evaluation method and device of a sealing structure, relates to the technical field of liquid rocket engine research, and aims to solve the problem of poor accuracy of sealing performance evaluation of the sealing structure in the prior art. The method comprises the steps of obtaining static stress load data of a target sealing flange structure in a target liquid rocket engine; based on the static stress load data, determining wear parameters between a soft coating and a flange contact surface in the target sealing flange structure by using a soft coating friction wear analysis model; the soft coating frictional wear analysis model is an analysis model obtained by at least performing grid ALE self-adaption on a grid corresponding to a soft coating of a target sealing flange structure in the two-dimensional axisymmetric finite element model and setting a grid node motion control mode; based on the wear parameters, evaluating the sealing performance of the target sealing flange structure; therefore, the accuracy of evaluating the sealing performance of the sealing structure is improved.

The present application relates to the technical field of computer aided design and real-time graphics computing, in particular to a grid adaptive subdivision method and real-time preview method for CAD modeling, comprising the following steps: sorting vertex coordinates of a model according to spatial positions, and constructing an adjacency relationship by using a half-edge structure for a grid data structure of the model; calculating a projection area of different grid subdivision regions in a view frustum as an importance weight ω, and distributing computing resources and arranging a subdivision order according to the importance weight ω. The present application quickly calculates the importance weight ω of the grid subdivision region, arranges computing resources for the subdivision of the subdivision region with a higher preview priority first, improves the dynamic adaptability of the grid subdivision, reasonably distributes the computing resources, and improves the computing efficiency.

The invention discloses a broadband scattering simulation method based on grid adaptive encryption, and belongs to the technical field of electromagnetic simulation. According to the method, independent self-adaptive grid encryption is carried out only at the lowest frequency point of the frequency band. For other frequency points in a frequency band, optimization grids are not independently generated any more, and optimization is guided by using error information at adjacent frequencies. And then, by adopting a Cauchy method, on the basis of frequency sampling points obtained by solving on the optimization grid, reconstructing response data between adjacent sampling points, thereby efficiently and accurately obtaining broadband electromagnetic response. According to the method disclosed by the invention, the grid at each frequency point can be efficiently optimized without carrying out independent adaptive optimization at each selected frequency point like a traditional adaptive encryption method, and meanwhile, the advantage that the adaptive encryption realizes higher precision with less unknown quantity is kept; the complex frequency band response can be efficiently and accurately reconstructed by using the Cauchy method.

This invention discloses a method, apparatus, and storage medium for establishing ACM weld point models. It automatically detects and deletes target weld points through scripts or program instructions, determines the size of the weld nugget refinement mesh based on the set weld nugget diameter, obtains modeling information and corresponding finite element models of non-coincident weld points, and automatically locates and adaptively updates the refinement area of ​​the connector based on the weld nugget refinement mesh and the modeling information of non-coincident weld points. It traverses all target weld points to be updated, completing the refinement of the weld point connector mesh and the batch automatic generation of new ACM weld points. This method ensures the accuracy of the ACM weld point model and improves modeling efficiency.

The present application discloses a method for predicting underwater explosion bubble motion based on grid adaptive discontinuous galvanometer, which relates to the field of underwater explosion technology. In the framework of underwater explosion bubble motion prediction based on discontinuous galvanometer, the method determines the solution resolution of each grid unit according to the underwater explosion bubble motion prediction result at each grid adaptive adjustment moment, and adjusts the grid division result based on the adjustment target of improving the solution resolution to enter the solution at the next forecast moment. The grid adaptive adjustment method can effectively improve the prediction accuracy, thereby achieving higher-precision result capture in the process of underwater explosion shock wave propagation and bubble motion, providing important support for interface capture of underwater near-field explosion process.

The application discloses a neural network-based electromagnetic field simulation grid self-adaptive generation method. The application performs grid partitioning on a semiconductor device simulation model, obtains original partitioning data, and constructs node features; a non-directed graph is constructed, the graph nodes of which adopt the node features of the grid points, and the connecting edges adopt the Euclidean distances between the grid points and adjacent grid points; the non-directed graph is input into a double-branch neural network, and a predicted node position is output; each node of the original partitioning data is corrected by using the predicted node position obtained by the double-branch neural network, and new partitioning data is formed to perform electromagnetic field simulation. The method can not only efficiently adjust the node density by fusing physical field information, but also strictly maintain the geometric boundary and topological structure characteristics of the device.

The application belongs to the technical field of three-dimensional electromagnetic radiation numerical solution, and relates to an electromagnetic radiation simulation analysis method based on local grid self-adaptive division. Firstly, the application carries out finite element modeling on a target antenna, introduces PML boundary and wave port excitation to establish a corresponding finite element calculation domain model, and adopts tetrahedral grid division to classify the calculation domain model; then finite element electromagnetic radiation simulation analysis is carried out to obtain finite element solution, and error estimation and encryption strategy are used to give the encryption size of the grid nodes in the non-PML region; finally, the grid is encrypted, finite element electromagnetic radiation simulation analysis is carried out again, and the process is repeated until the overall solution error is less than the set error limit, the final calculation grid is obtained, and finite element electromagnetic radiation simulation analysis is carried out. The application only encrypts the tetrahedral grid in the non-PML calculation domain, ensures the original characteristics of the tetrahedral grid in the PML calculation domain, and realizes the rapid simulation design of the antenna radiation characteristics while ensuring the calculation accuracy.

The invention relates to the field of aviation electromagnetic inversion, and discloses a three-dimensional frequency domain aviation electromagnetic adaptive norm underground anomalous body inversion method comprising the following steps: obtaining observed frequency domain aviation electromagnetic data; performing preliminary inversion on the frequency domain aviation electromagnetic data by adopting a coarse scale grid and norm constraint to obtain underground anomalous body features, calculating indication factors based on the underground anomalous body features, setting judgment values, and determining the frequency domain aviation electromagnetic data according to the comparison conditions of the judgment values and the indication factors. And carrying out inversion by adopting fine-scale grid adaptive norm constraint to obtain final divergent smooth and blocky underground anomalous body features. According to the method, adaptive Ekblom norm constraint is adopted for model constraint terms in the inversion process, final divergent smooth and blocky underground anomalous body features are obtained, the multi-scale technology is introduced, and the calculation efficiency is improved.

The application discloses a kind of multi-source data fusion's travel safety monitoring method and system, it is related to safety monitoring technical field, including, real-time acquisition multi-source heterogeneous data, and pre-processing is carried out, structured data stream is generated, constructs initial digital twin, based on the change of structured data stream, trigger adaptive grid reconstruction, obtain dynamic updated digital twin model, through dynamic updated digital twin model, using graph neural network constructs microcosmic, medium and macro three-level coupling risk transmission network, carries out cross spatio-temporal scale risk analysis, generates risk transmission analysis result, simulates N kinds of intervention schemes in virtual intervention sandbox based on risk transmission analysis result, obtains N kinds of simulation results, selects optimal intervention scheme by reinforcement learning algorithm, and sends to physical equipment and implements optimal intervention scheme;The application realizes the high-fidelity mapping of scenic spot physics and dynamic state by grid adaptive mechanism, supports real-time crowd distribution, optimizes computing resource allocation.

The invention relates to the technical field of motor electromagnetic field simulation, and discloses a permanent magnet synchronous motor electromagnetic field finite element rapid simulation calculation method. The method comprises the steps that a three-dimensional model is constructed, material attributes are loaded, and an initial grid is generated; after the electromagnetic field equation is solved, space gradient information of field distribution is extracted so as to accurately identify a magnetic field violent change area and a smooth area; dynamically adjusting the grid density according to the identification result, encrypting the key area, and keeping the non-key area sparse; and recalculating and evaluating the error based on the optimized grid, and performing loop iteration until the result meets the preset tolerance. According to the method, the gradient information is used for directly driving grid self-adaption, accurate distribution of computing resources is achieved, the problem that the efficiency is low due to the fact that a traditional method depends on experience or mathematical residual errors is solved, and the simulation speed is increased while the computing precision is guaranteed.

This invention discloses a finite element method, storage medium, and computer program product for the microstructural evolution of rock masses based on material heterogeneity mapping. The method includes data acquisition; parameter inversion; mesh construction; coordinate registration; weighted statistics; assigning equivalent parameters to elements; adaptive mesh refinement in high-gradient regions; model initialization and solution: initial field loading and boundary condition definition are completed, and elastoplastic or multi-field coupled calculations are performed. The advantage of this invention is that it improves the predictive ability of the finite element model for the non-uniform deformation and microstructural evolution of rock masses.

The invention relates to a metal casting process optimization method, and relates to the technical field of metal casting process optimization, 3D design software is used for constructing a casting three-dimensional model and a mold model, MAGMASOFT software is used for setting process parameters, the process parameters comprise temperature parameters, time parameters and cooling conditions, corresponding thermophysical parameters of a built-in material library of the MAGMASOFT software are called, and the temperature parameters, the time parameters and the cooling conditions of the casting three-dimensional model and the mold model of the casting three-dimensional model are calculated. MAGMASOFT software is operated to carry out multi-physics field coupling simulation, TAG grid adaptive subdivision is adopted, potential defect types and areas are identified, a temperature field cloud picture and solidification animation are generated, the defect types comprise shrinkage cavities, shrinkage porosity, air holes and hot cracks, technological parameters are adjusted, simulation is carried out again, a DOE experimental design method and genetic algorithm iteration are adopted to carry out technological parameter adjustment, and the temperature field cloud picture and solidification animation are obtained. And finally, the required process conditions are met. According to the technical scheme, the casting simulation precision is improved, defects in actual production are reduced, and the production efficiency is improved by optimizing process parameters, reducing the production cost and shortening the process development period.

The invention discloses a strong shear turbulence dynamic grid adaptive simulation method coupled with an SA series model. The method mainly comprises the following steps of: 1, judging whether a shielding function is applied or not; step 2, calculating a Vman dynamic coefficient; step 3, identifying the self-adaptive length scale of the shear layer; step 4, constructing a scale-related adjustment function based on the turbulence energy spectrum integral; 5, reconstructing the turbulence viscosity of the SA series model by using an adjustment function; and 6, performing turbulence simulation by using the reconstructed turbulence viscosity. According to the method, the size of a local grid is identified by constructing a Vman dynamic coefficient, the length scale of the local grid is jointly determined in combination with the length scale of the shear layer adaptive sub-grid, and then the scale correlation function is constructed through the turbulence energy spectrum integral to reconstruct the turbulence viscosity, so that grid adaptive simulation is realized; an effective numerical simulation method is provided for solving low-consumption and high-precision simulation of strong shear turbulence in a complex engineering flow problem.