19 results about "Computational electromagnetics" patented technology

The invention belongs to the technical field of computational electromagnetics, and discloses a numerical calculation method for simulating electromagnetic wave propagation characteristics in time-varying plasma, which is a three-dimensional Newton-HIE-FDTD method for efficiently simulating propagation of electromagnetic waves in time-varying plasma based on a hybrid explicit-implicit finite difference time domain method and Newton's second law of motion. The method inherits the advantages of the Newton-ADE-FDTD method, the time-varying electron density is accurately represented through the time derivative, and the abundant dynamic characteristics of the time-varying plasma can be accurately captured. On the basis, the method also fuses the advantages of an HIE-FDTD method, so that the time step length of the algorithm is only restricted by the sizes of grids in two directions, and compared with other simulation methods based on time-varying plasma, the method provided by the invention is more excellent in calculation efficiency and is more suitable for large-scale popularization and application. The method is especially suitable for analysis and simulation of electromagnetic wave propagation characteristics in time-varying plasma.

The invention discloses a triangular mesh-based high-order electromagnetic field simulation method, and belongs to the field of computational electromagnetism. In order to solve the problems of significant numerical dispersion and phase error accumulation when an existing triangular mesh time domain finite difference method is used for processing a complex geometric structure, the method comprises the following steps: firstly, introducing a first additional loop on a basic triangular mesh, and combining with a first optimization coefficient to construct a high-order model; and a second additional loop is further introduced, and an optimization model is constructed in combination with a second optimization coefficient, so that the phase error is effectively inhibited under the coarse mesh, and high-precision electromagnetic simulation of a large-scale polygon structure is realized.

The embodiment of the invention provides an electromagnetic scattering calculation method based on a heterogeneous GPU cluster. The method is applied to the field of computational electromagnetism, and comprises the following steps: constructing a hierarchical bounding volume geometric acceleration structure of a target object and adding an edge index, and meanwhile, completely copying and distributing data of the acceleration structure to a video memory of each computational node in a heterogeneous GPU cluster; generating a random ray path starting from an emission source, modeling an electromagnetic scattering process as a ray path set in a probability space, and generating a ray direction through an importance sampling strategy; determining a static scheduling strategy for the ray batch based on the calculation cost of pre-sampling and geometric enhancement, and carrying out non-uniform distribution on task tiles according to the heterogeneous GPU calculation power; and monitoring the execution state of the heterogeneous GPU cluster in real time, and dynamically adjusting the distribution strategy of the residual ray tasks based on execution feedback. According to the method, the calculation overhead can be remarkably reduced while the calculation precision is ensured, and the efficiency and expandability of complex target electromagnetic scattering calculation are improved.

This invention belongs to the field of computational electromagnetics numerical simulation and provides a simulation method for electromagnetic scattering of thin-coated targets based on Schur complement preconditions. First, for the IBC scattering target to be solved, equivalent surface current and equivalent surface magnetic current are introduced as independent unknowns. The electromagnetic scattering solution equation is established using SDIE and then discretized. Next, the impedance matrix is ​​decomposed into near-field and far-field matrices using an octree structure. For the near-field matrix, key operator sub-blocks are explicitly assembled and extracted. Then, approximate operators in block diagonal form and Schur complement operators are constructed and approximately inverted. Simultaneously, the diagonal product of intermediate blocks is pre-calculated and stored based on the approximate operators. Finally, the constructed preconditions are applied to the GMRES iterative solver. When the iteration error reaches the preset convergence criterion, the current and magnetic current distributions on the target surface are output. Further calculations of radiation characteristic parameters such as the target's radar cross section are then performed, achieving low-cost, high-efficiency, and easily parallelizable electromagnetic simulation solutions.

The invention belongs to the field of computational electromagnetism numerical simulation, and particularly relates to a non-uniform conformal FDTD method based on a sub-grid technology. According to the method, non-uniform conformal geometric correction is introduced into the sub-grids, so that high-precision fitting of a curved surface boundary is realized, step approximation errors are reduced, and the calculation precision of field quantities near the boundary is improved; according to the method, bidirectional coupling transfer which simultaneously meets line integral conservation and flux conservation is established on a main-sub grid interface, and a conservation relation required by a non-uniform conformal FDTD method is prevented from being damaged, so that interface numerical value reflection is effectively inhibited, energy non-physical errors are reduced, and long-term stability is improved; and fine grids are only adopted in the local fine structure neighborhood and are matched with time sub-cycle propulsion, so that global grid encryption and limitation of global time step length to a minimum unit are avoided, and the storage and calculation time overhead is remarkably reduced while the precision is ensured. According to the method, geometric modeling precision, interface stability and calculation efficiency are considered, and the method has high engineering application value.

The invention discloses a coated target electromagnetic scattering modeling method based on multi-core heterogeneous parallel computing, and belongs to the field of computational electromagnetism and high-performance computing. The method comprises the steps that an MPI + OpenMP + DSP three-level heterogeneous parallel framework is constructed, and optimal configuration of computing resources is achieved through one-to-one binding of an MPI process and a DSP acceleration card and one-to-one mapping of an OpenMP thread and a CPU core; dispersing a to-be-solved coating target by adopting a triangular grid, and defining an RWG primary function to expand surface current; substituting the surface current approximate expansion into an electric field integral equation based on impedance boundary conditions; carrying out impedance matrix calculation by adopting a process-based parallel filling strategy, and carrying out parallel solution on a matrix equation based on a ScaLAPACK library; and finally, calculating a far-region scattering field and a radar scattering sectional area according to the solved current coefficient. According to the method, through an innovative heterogeneous parallel architecture and a calculation task scheduling strategy, the problems of insufficient memory and low calculation efficiency during processing of an electrically large coated target in a traditional method are effectively solved, and an efficient and reliable technical means is provided for electromagnetic stealth design of a complex target.

The application belongs to the technical field of computational electromagnetics, and discloses a numerical calculation method for simulating electromagnetic wave propagation characteristics in time-varying plasma, which is a three-dimensional Newton-HIE-FDTD method for efficiently simulating electromagnetic wave propagation in time-varying plasma based on a mixed explicit-implicit finite-difference time-domain method and Newton's second law of motion. The method inherits the advantages of the Newton-ADE-FDTD method, accurately represents the time-varying electron density through the time derivative, and can accurately capture the rich dynamic characteristics of the time-varying plasma. On this basis, the method also integrates the advantages of the HIE-FDTD method, so that the time step of the algorithm is only restricted by the grid size in two directions. Compared with other simulation methods based on time-varying plasma, the method is more efficient in calculation, and is particularly suitable for the analysis and simulation of electromagnetic wave propagation characteristics in time-varying plasma.

This invention belongs to the field of numerical simulation in computational electromagnetics, specifically a non-uniform conformal FDTD method based on submesh technology. This invention introduces non-uniform conformal geometric corrections within the submesh to achieve high-precision fitting of curved surface boundaries, reducing step approximation errors and improving the accuracy of field calculations near the boundaries. At the master-submesh interface, a bidirectional coupling transfer is established that simultaneously satisfies line integral conservation and flux conservation, avoiding disruption of the conservation relationships required by the non-uniform conformal FDTD method. This effectively suppresses numerical reflections at the interface, reduces energy non-physical errors, and improves long-term stability. Furthermore, by using fine meshes only in the neighborhood of local microstructures and coordinating with time sub-cycle progression, global mesh refinement and the global time step being limited by the smallest unit are avoided, significantly reducing storage and computation time overhead while maintaining accuracy. This invention balances geometric modeling accuracy, interface stability, and computational efficiency, and has high engineering application value.

The invention relates to an unmanned aerial vehicle electromagnetic scattering characteristic solving method and device based on a graph neural network, and belongs to the technical field of computational electromagnetism and radar target recognition, and the method specifically comprises the steps: carrying out the initialization of a system and the discretization of an unmanned aerial vehicle grid; constructing graph structure data based on an RWG primary function, and establishing a mapping relation between an unstructured grid of a physical space and graph data which can be processed by a graph neural network; a GraphSolver model of a graph neural network solver is constructed, and an end-to-end deep neural network model is formed; training and optimizing the model; according to the method, the problems of too long calculation time and huge memory consumption when an existing full-wave numerical calculation method is used for analyzing complex targets such as an unmanned aerial vehicle are solved; and the existing deep learning method is difficult to accurately process the non-uniform triangular mesh of the unmanned aerial vehicle and is easy to lose key geometric details such as wing edges.

This invention belongs to the field of computational electromagnetics, specifically a method for transforming a one-dimensional axial magnetic field into a three-dimensional axisymmetric magnetic field. This invention uses two variable-step-size, four-point numerical differential calculations followed by averaging to approximate the first derivative at the point to be calculated. This avoids the problem that calculating four points once might not improve accuracy, and also avoids the overly complex formula of directly using five points. Furthermore, by using the approximate value of the first derivative at known coordinates combined with Spline curve fitting to estimate the approximate value of the first derivative at the point z to be calculated, the problem of error superposition is effectively avoided, resulting in a higher accuracy for the radial component B of the calculated three-dimensional axisymmetric magnetic field. r The results are closer to the theoretical values. This invention effectively solves the problems of low accuracy and error accumulation in the transformation from one-dimensional axial magnetic field to three-dimensional magnetic field, and provides strong support for magnetic field loading in the design of devices such as vacuum electronic devices, ion sources, and particle accelerators.

The present application belongs to the field of computational electromagnetics, and provides an electromagnetic simulation isosurface extraction method based on space rearrangement and deep learning prediction, which is used to solve the problems of waste of computing resources, memory bottleneck of unstructured grid data and insufficient real-time performance in the prior art. First, the unstructured grid data output by electromagnetic simulation is rearranged in memory by using Morden code, the field points that are adjacent in geometry are forced to be continuous in physical memory, random memory access is converted into streaming memory access, and the bandwidth utilization is greatly improved. Then, a lightweight fully connected neural network is constructed, the field scalar values of the grid cell vertices and the target isosurface are input, and the probability of the grid cell crossing the isosurface is output. The trained network model is used for fast batch reasoning on the rearranged grid data, most of the background space is removed at a very low computing cost, and an active cell candidate table is generated. Finally, accurate geometric interpolation is performed on the active cells to generate high-quality isosurface grids.

The application discloses a target echo classification method and system based on multi-modal data fusion, relates to the technical field of computational electromagnetics, and solves the technical problems of classification accuracy reduction of a model in a noise environment, limited generalization ability, and large performance fluctuation when the distribution of modal data changes; the weight of each feature is analyzed when modeling the time sequence dependence of BiLSTM, global information is reserved through cross-modal fusion after the features are removed, cross fusion focuses on key discriminant features after the features are removed, and both can take into account information integrity and calculation efficiency. The contribution of different modal features to the classification result is dynamically adjusted through the hidden state of GRU. If some modal data is missing, the original fusion path can still use other modal information, and the screening fusion path can depend on the key features of the remaining modal. The balance between redundant feature reservation and key feature screening can reduce the sensitivity of the model to specific noise patterns.

The application discloses a PIN diode modeling and simulation method based on LP-CDI-FDTD, belongs to the field of computational electromagnetics, microwave technology and circuit simulation, and comprises the following steps: firstly, an equivalent lumped parameter model of a semiconductor device is established, and a voltage-current relationship thereof is obtained; then, the relationship is converted into an equivalent current density, and is embedded into a Maxwell curl equation according to the relationship between an electric field and a voltage, so as to construct an electromagnetic-circuit coupling equation set; further, a leapfrog compliant divergence unconditional stable time domain finite difference method is adopted to discretize the coupling equation set, and a discrete updating equation is obtained; finally, iterative calculation is carried out according to the equation, and electromagnetic fields and device states are synchronously updated. The method realizes the inherent strong coupling between full-wave electromagnetic fields and semiconductor physical processes, and breaks through the time step restriction caused by a CFL condition in traditional methods by using the unconditional stability of the algorithm, so that the calculation efficiency can be significantly improved when simulating a device containing a fine structure.

This invention discloses a method and system for integrated load-bearing and wave-transmission optimization design of array antenna windows, relating to the field of computational electromagnetics structural strength cross-section and optimization technology. The invention includes: S1: Constructing a load-bearing and wave-transmission optimization model for the array antenna window, and obtaining initial sample points using the Latin hypercube sampling method; S2: Obtaining the actual response values ​​of the initial sample points using an integrated load-bearing and wave-transmission simulation analysis method for the array antenna window, and constructing a load-bearing and wave-transmission surrogate optimization model for the array antenna window using a Kriging surrogate model. This invention can solve the problems of high time cost and the inability to simultaneously optimize load-bearing / wave-transmission performance during the optimization design of array antenna windows, obtaining an array antenna window structure with optimal wave-transmission performance under load constraints with less time cost, thus reducing the optimization design cycle and cost of array antenna windows.

This invention discloses a knowledge graph-based method for predicting the heat dissipation performance of transformers, relating to the field of internal heat conduction technology in transformers. The method includes the following steps: S1, outputting a static topological adjacency matrix; S2, by improving the MTGNN model, using a field-based inverse tracing mechanism based on computational electromagnetics and physical priors, physically aligning discrete time-series data into entity center features, performing cross-level spatiotemporal aggregation, and outputting the predicted entity temperature; S3, instantiating over-limit entities as abnormal hotspot entities; S4, generating a weighted knowledge graph; S5, generating the maximum thermal resistance bottleneck link; S6, marking edges with abnormal resistance values; S7, outputting a visualized tracing graph of transformer heat dissipation anomalies. This invention overcomes the limitations of traditional methods that ignore the dynamic evolution of heat transfer characteristics and the fragmented processing of anomaly tracing, providing an efficient solution for accurate prediction and visualized tracing of transformer heat dissipation anomalies.

The application relates to a SAR waveform design method combined with electromagnetic characteristics and K-means clustering, comprising the following steps: obtaining target scattering characteristic data based on a computational electromagnetic technique; constructing a signal model of a SAR one-dimensional range image based on the target scattering characteristic data; constructing a target function representing SAR waveform design by taking a signal-to-clutter ratio as an optimization criterion based on the signal model; constructing an original mathematical model of a SAR waveform design optimization problem by applying a constant modulus constraint and a similarity constraint to the target function; and converting the original mathematical model into a convex optimization problem and finally iteratively solving the convex optimization problem to obtain a SAR waveform. The application improves the dark weak target detection capability through azimuth angle domain scattering feature grouping and robust optimization.

The invention relates to a field line coupling simulation method under a complex terrain, belongs to the technical field of computational electromagnetism and electromagnetic compatibility, and solves the technical problem that the calculation precision is affected due to an edge effect existing in field line coupling calculation by a finite difference time domain method. The field line coupling simulation method comprises the following steps: establishing a layered irregular complex terrain and a closed TF / SF boundary; calculating an excitation field of a total field scattering field TF / SF boundary by adopting a fine line time domain finite difference method; and performing iterative calculation on field line coupling at the position of the cable by adopting a fine line time domain finite difference method to obtain a current I and a unit length charge Q at a cable sampling point. The method is used for field line coupling high-precision solution under the complex terrain.

The invention belongs to the field of computational electromagnetics and numerical simulation, and discloses an electromagnetic field numerical calculation method based on physical field priori knowledge and a related device, and the method comprises the steps: carrying out the mesh generation of a geometric calculation model of a to-be-calculated electromagnetic structure, carrying out the type division of a plurality of mesh units, and determining the unit type of each mesh unit; generating a discontinuous bit function interpolation function based on the enhanced enrichment function fused with the prior knowledge of the physical field; based on the unit type of each grid unit, a non-continuity bit function interpolation function is combined, and a unit stiffness matrix of each grid unit is obtained through calculation; combining the element stiffness matrix of each grid element, and constructing a multi-scale finite element discrete equation; solving the multi-scale finite element discrete equation to obtain an electromagnetic field numerical calculation result of the electromagnetic structure to be calculated; according to the method, the calculation precision of bit function distribution and field distribution near the medium interface is remarkably improved, and the physical fidelity of interface calculation is fundamentally improved.

The present application belongs to the cross field of computational electromagnetics and artificial intelligence, and specifically provides a three-dimensional metal target electromagnetic simulation method based on neural network and equivalent principle, to solve the technical problems of high computational complexity, large memory consumption and low efficiency of traditional numerical integration method existing in the operator matrix construction and scattering characteristic solving stage of equivalent principle algorithm in three-dimensional metal target electromagnetic scattering characteristic analysis. The present application combines deep neural network with multi-frequency triangular feature, spatial coupling perception activation mechanism, constructs a prediction model of equivalent principle operator matrix, significantly reduces the required computing resources and time of operator matrix construction and scattering characteristic solving while maintaining high prediction accuracy, and provides an efficient, stable and scalable fast solving scheme for complex three-dimensional metal target electromagnetic scattering problem.