85 results about "Mesh adaptation" patented technology

The invention discloses a multi-source data fusion-based travel safety monitoring method and system, and relates to the technical field of safety monitoring, and the method comprises the steps: obtaining multi-source heterogeneous data in real time, carrying out the preprocessing, generating a structured data stream, constructing an initial digital twinborn body, and triggering adaptive grid reconstruction based on the change of the structured data stream. The method comprises the steps of obtaining a dynamically updated digital twinborn model, constructing a microscopic, mesoscopic and macroscopic three-level coupling risk conduction network by adopting a graph neural network through the dynamically updated digital twinborn model, performing cross-spatio-temporal scale risk analysis, generating a risk conduction analysis result, and simulating N intervention schemes in a virtual intervention sandbox based on the risk conduction analysis result. Obtaining N simulation results, selecting an optimal intervention scheme through a reinforcement learning algorithm, and sending the optimal intervention scheme to physical equipment to implement the optimal intervention scheme; according to the method, high-fidelity mapping of physical and dynamic states of the scenic area is realized through a grid adaptive mechanism, real-time crowd distribution is supported, and computing resource allocation is optimized.

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.

Apparatus and method achieve topology optimization with bidirectional mesh adaptation. A mesh engine generates a mesh for a geometry of a computer aided design model of a design domain. A multi-physics simulator derives of physical field variables on the mesh based on material properties and boundary conditions of the design domain. An adjoint sensitivity is determined based on a given cost function and sensitivity formulation to drive a design variable lower or higher, the design variable defining a density of the design domain. An optimizer determines an optimization yielding a new set of design variables based on the adjoint sensitivity. A bidirectional mesh adaptation is performed on regions of the mesh by coarsening or refining the mesh element size. The multi-physics simulation, optimization and mesh adaptation are iteratively performed until optimized convergence criteria are met.

The invention discloses a 3D human avatar method and a 3D human avatar system which are generated based on 3d gaussian patterning and can be driven in real time. The 3D human avatar system comprises a data acquisition module, a Gaussian initialization module and a training rendering module, the data acquisition module acquires a small amount of human body data based on a single camera, predicts human body posture information based on an smplx model and expression information based on a Flame model from two-dimensional human body image data, and makes labels; a Gaussian initialization module carries out adaptive Gaussian initialization on a human body smplx model grid in any frame label to obtain a 3D Gaussian ellipsoid; and the training rendering module is used for training the 3D Gaussian ellipsoid initialized in the step 2 based on an improved 3d Gaussian sputtering model, and rendering a 3D human avatar capable of being driven in real time. According to the method, the topological consistency of the Gaussian point and the human body smplx model can be highly maintained, artifacts are reduced, and high fidelity 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 invention discloses a free grid layout conversion system and method based on a WEB end and a storage medium, and relates to the technical field of grid layout optimizing.The free grid layout conversion system comprises a user interface module, a layout analysis module, a grid self-adaption module, a response type design module, a grid optimization module and a data storage module, the modules are in electric signal connection; and the user interface module is used for providing an interactive interface and supporting real-time preview, so that a user can check the layout adjustment effect in real time. According to the method, the grid size and layout are dynamically adjusted, so that the flexibility and adaptability of the webpage layout are improved, the grid layout adaptive to different equipment and screen sizes can be automatically generated according to the input parameters and rules of the user, the webpage content can be ensured to keep good readability and layout effect in various environments, and the user experience is improved. The user experience is further improved, and the workload of customizing layouts for different devices is reduced.

The invention provides a deep learning-based T-shaped joint guidance grid self-adaption method, which comprises the following steps of S1, generating a T-shaped joint model of random geometric parameters, and defining a geometric shape through parametric design; s2, predicting the size distribution of grid units by using a deep learning model, and guiding the generation of a non-uniform grid; s3, integrating a finite element solver to carry out linear elastic mechanical calculation, and automatically setting material parameters and boundary conditions; and S4, outputting strain energy, stress distribution and an adaptive grid result through a visual tool. According to the method, the optimal non-uniform grid unit size distribution is obtained through the deep learning model, then the more accurate non-uniform grid is obtained, the deep learning model predicts the optimal grid distribution, the grid adjustment process based on posterior error estimation in a traditional method is avoided, and the accuracy and efficiency can be remarkably improved.

The invention provides a transformer temperature fluid field computational grid adaptive subdivision method, which comprises the following steps of: establishing a transformer three-dimensional entity model, carrying out initial grid subdivision, and calculating the distribution of numerical discrete errors in grid units according to an error calculation formula, the method comprises the following steps of: selecting a grid unit error size, rearranging unit numbers according to the grid unit error size, selecting to-be-encrypted units in a fluid domain according to a proportion, performing local encryption processing on the selected units, performing node distribution optimization, forming a new grid, replacing an old grid with the new grid, resolving each node field quantity, and the like. According to the method, error calculation, unit marking and grid refinement processes are repeatedly executed, and a self-adaption process is ended when a calculation result of an observation point meets requirements, so that self-adaption encryption of the grid is realized, and the transformer grid subdivision number which can ensure the solving precision and does not greatly reduce the solving efficiency is determined.

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.

The present invention relates to a posterior error estimation method for a finite element numerical solution, and specifically to a posterior error estimation method for a finite element numerical simulation of an electrostatic field Poisson equation based on an artificial neural network. The method is used to solve the shortcomings of existing posterior error estimation methods for finite element numerical solutions of the electrostatic field Poisson equation, which require different method designs for different finite element grid types, resulting in high complexity of algorithms and programs. The present invention uses a pytorch software package to construct a neural network model based on the electrostatic field Poisson equation. After the neural network training is completed by the neural network model, it can be used to estimate the posterior error of the finite element numerical solution under different grids without the need to retrain the neural network. In particular, when the posterior error is only used for a grid adaptive algorithm, compared with the classical posterior error estimation method, the present invention saves computational effort because the process of constructing the posterior error is omitted.

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 discloses a three-dimensional point cloud sampling method and device, electronic equipment and a storage medium. The method comprises the steps that a three-dimensional point cloud space is equally divided into a plurality of sub-blocks, the point cloud density of each sub-block is calculated, the sub-blocks with the point cloud density exceeding a threshold value are divided into two parts along a three-dimensional coordinate axis to generate eight grids, and a hierarchical incremental octree structure is formed through self-adaptive iteration; in the self-adaptive iteration division process, the point cloud density of the grids of each new level needs to be calculated again, whether subdivision continues or not is judged till the grids of each level meet the preset threshold condition, and finally pooling sampling is executed on the point cloud in the grids on the convergent level to obtain feature data. According to the method, the calculation complexity is reduced, the power consumption and delay of hardware implementation are reduced, the sampling precision is improved, and the targets of high precision, low power consumption and low delay of point cloud sampling are achieved.

The present invention discloses a GPU-accelerated adaptive sampling volume rendering method for non-uniform cuboid meshes. First, based on data bounding box rendering and GPU multi-threaded computing, a set of sampling rays for non-uniform cuboid meshes is generated. Subsequently, the intersection points of each ray with the mesh cell faces are calculated and the coordinate positions of the adaptive sampling points are determined. Then, the non-uniform cuboid mesh data is stored in the 3D texture memory of the GPU in a normalized manner, and texture hardware queries are performed using the weighted and corrected adaptive sampling point coordinates to obtain the trilinear interpolation result scalar values at the sampling points. Finally, the colors and transparencies corresponding to the sampling points are calculated according to the transfer function, and the Under operator in Alpha blending is used to achieve the correct color synthesis of all sampling points on the ray, and finally a visualization result image is formed. Experimental results show that the present invention can effectively improve the computational efficiency of Ray Casting volume rendering for non-uniform cuboid meshes and accelerate the visualization analysis and calculation process of non-uniform cuboid meshes.

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 present invention provides a finite element grid adaptive subdivision method for solving convection-based pollutant migration, which relates to the field of finite element numerical simulation technology, including: identifying convection-based finite element grids through a grid adaptive subdivision algorithm, and subdividing the convection-based finite element grids to obtain subdivided subunits; for each unsubdivided unit shared by an active edge, only the shared unit that needs to be subdivided into 4 subunits is subdivided to obtain subdivided subunits; for the units where all the remaining active edges are located, the remaining active edges are connected to the diagonal vertices of the remaining active edges to form 2 subdivided subunits. After the subdivided subunits are divided, the subdivided subunits have the same unit number as the parent unit, so that the subdivided subunits can reference the parameters of the parent unit. The present invention can effectively solve the problems of vibration of numerical solutions and large numerical dispersion in traditional numerical models when solving convection-based solute migration problems.

The present invention discloses a grid adaptive turbulence simulation method based on the Vreman dynamic coefficient coupled RSM model, and the main process of its implementation includes: step one, judging whether to apply the shielding function; step two, calculating the Vreman dynamic coefficient; step three, determining the local dynamic grid length scale; step four, constructing the scale-related adjustment function; step five, reconstructing the Reynolds stress tensor and turbulent viscosity of the RSM model; step six, using the reconstructed Reynolds stress tensor and turbulent viscosity to simulate turbulence. The present invention constructs the Vreman dynamic coefficient based on the local velocity gradient tensor, identifies the local grid size, and determines the local grid length scale Δ * , the Reynolds stress tensor and turbulent viscosity are reconstructed by constructing scale-related functions through turbulent energy spectrum integration, and grid adaptive simulation is realized, which effectively overcomes the problem that the existing turbulent mixing model is highly dependent on grid experience, broadens the grid adaptability, improves the calculation accuracy, reduces the calculation cost, and speeds up the turbulence simulation process.

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.