Method for generating a cross-scale large-scale electromagnetic surface mesh with periodic fine features

By splitting and mapping the periodic features of the electromagnetic geometry model, a large-scale electromagnetic surface mesh across scales is generated, which solves the problems of memory bottleneck and wasted computing resources in traditional methods, and achieves efficient and stable mesh generation and simulation.

CN120951538BActive Publication Date: 2026-03-31ZHEJIANG UNIV
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Patent Information

Application Number
CN202511017010.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-07-23
Publication Date
2026-03-31
Estimated Expiration
2045-07-23

AI Technical Summary

Technical Problem

Traditional mesh generation methods suffer from problems such as memory bottlenecks, wasted computing resources, unstable mesh quality, and difficulty in reusing meshes when dealing with large-scale, multi-scale, periodic, and fine-featured electromagnetic simulation models, which affect simulation efficiency and reliability.

Method used

The electromagnetic geometric model is decomposed into a unit structure with periodic features. Through geometric mapping and boundary fusion strategies, a large-scale electromagnetic surface mesh across scales is generated. Periodic boundary conditions are used for batch copying and splicing to ensure the consistency and controllability of local mesh quality.

Benefits of technology

It significantly reduces the computational burden and memory usage of mesh generation, improves simulation efficiency and mesh quality, and has wide adaptability, especially suitable for simulation scenarios with periodic and cross-scale characteristics such as antenna arrays and metasurface devices.

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Abstract

The application discloses a cross-scale large-scale electromagnetic surface grid generation method with periodic fine features, comprising the following steps: reading a cross-scale electromagnetic geometric model with periodic fine features, setting a replication direction and a number; setting a periodic boundary condition of the electromagnetic geometric model, determining a source surface and a target surface of the replication direction, extracting a boundary line, and establishing a mapping relationship between the source surface, the target surface and the boundary line; discretizing the electromagnetic geometric model to generate a discrete background triangular grid; generating a size field of the overall geometry according to the periodic fine features and the cross-scale features of the electromagnetic geometric model; generating and merging surface grids of the source surface, the target surface and the remaining surfaces according to the discrete background triangular grid and the size field and the mapping relationship; and batch replicating and merging the surface grids according to the replication direction and the number to generate a cross-scale large-scale electromagnetic surface grid with periodic fine features.
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