9 results about "Mesh adaptation" patented technology

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 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 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.

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.

This invention provides a method, apparatus, and device for generating anti-counterfeiting graphic mosaic backgrounds, relating to the field of image processing technology. The method includes: acquiring an original image and at least one graphic unit object; generating a set of directional guiding curves based on the original image; arranging the at least one graphic unit object to generate a graphic object group; aligning the original image, the directional guiding curve group, and the graphic object group to obtain an overlapping image; determining the corresponding point of each graphic unit object in the graphic object group on the vector curve in the directional guiding curve group within the overlapping image; rotating each graphic unit object according to the tangent direction vector of the corresponding point relative to the vector curve to obtain a rotated graphic unit object; and filling the rotated graphic unit object with color to obtain a target graphic mosaic background object. This invention combines directional curve guidance with adaptive grid rotation to generate a novel anti-counterfeiting mosaic background, improving both anti-counterfeiting performance and visual effect.

A high-quality tetrahedral mesh adaptive generation method based on symbolic distance field is disclosed, relating to the fields of computer-aided engineering (CAE) and numerical computation preprocessing. This method calculates the adaptive mesh size based on the gradient of the symbolic distance field, densely samples constraint points near the implicit interface, and generates an initial Delaunay tetrahedral mesh. For this initial mesh, the geometric boundary is restored through edge swapping and point insertion, and the tetrahedral mass ratio is ensured to meet specified values ​​through topology optimization methods of edge swapping and geometric optimization methods of point smoothing. Finally, material properties are assigned based on the symbolic distance field value of the tetrahedral mass center. The method of this invention can improve the geometric accuracy of the tetrahedral mesh, ensure the quality of tetrahedral elements, automatically identify areas near the interface that require refinement, minimize redundant elements while maintaining accuracy, and ensure computational stability.

This invention provides a method for aerodynamic optimization design of wind tunnel profiles, belonging to the field of wind tunnel profile technology. This invention identifies high-gradient feature points by extracting the curvature distribution of profile features, generates a hybrid mesh using a graph-driven adaptive topology reconstruction algorithm, performs flow field calculations based on the hybrid RANS-LES turbulence simulation method, solves the control equations using a high-precision shock capture format coupled with a WENO limiter, and performs adaptive mesh refinement. It adjusts the coordinates of profile control points using a topological potential-based asymptotic optimization algorithm, and determines whether to output the optimization results or return to iterate again by judging whether the aerodynamic performance evaluation parameters meet the convergence criteria. This solves the technical problem of low optimization efficiency and difficulty in converging to the optimal solution caused by the disconnect between mesh generation, flow field calculation, and profile adjustment in the aerodynamic optimization process of wind tunnel profiles.