发表机构
Hangzhou Institute of Technology, Xidian University（西安电子科技大学杭州研究院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
FSSDataBase提供5,000个程序化生成的FSS单元结构及HFSS仿真散射响应数据，支持条件建模、结构检索和深度学习逆向设计基准测试。
AI 中文摘要
数据驱动的频率选择表面（FSS）设计需要可复用的数据集，这些数据集在记录的仿真条件下将结构几何与电磁响应联系起来。本文介绍了FSSDataBase，这是一个公开可用的数据集，包含使用Ansys HFSS仿真的5,000个程序化生成的单层和多层FSS单元结构。该数据集覆盖10-20 GHz频段，提供横电和横磁反射与透射响应，包括幅度和相位，记录入射角为$0^{\circ}$和$30^{\circ}$。每条记录将二值结构掩模和基于JSON的重建元数据与原始响应样本及导出的幅度标签相关联。结构描述符、响应距离度量和面向任务代价函数表征了几何和电磁变化，并支持筛选极化稳定性、角度选择性带宽以及匹配幅度、180°相位分离的结构对。随附代码支持模型重建、数据处理和配置驱动的额外样本生成。除了条件正向建模和基于响应的结构检索外，FSSDataBase还有潜力作为基于深度学习的FSS逆向设计的参考数据集，在共享数据划分、输入条件和评估协议下支持跨网络架构的公平比较。
英文摘要
Data-driven design of frequency-selective surfaces (FSSs) requires reusable datasets that link structural geometry to electromagnetic response under documented simulation conditions. Here we present FSSDataBase, an openly available collection of 5,000 procedurally generated single- and multilayer FSS unit cells simulated using Ansys HFSS. The dataset covers 10-20 GHz with transverse-electric and transverse-magnetic relfection and transmission responses, including magnitude and phase, for recorded incidence angles of $0^{\circ}$ and $30^{\circ}$. Each record links binary structural masks and JSON-based reconstruction metadata to raw response samples and derived magnitude labels. Structural descriptors, response-distance measures and task-oriented cost functions characterize geometric and electromagnetic variation and support screening for polarization stability, angular-selective bandwidth and matched-amplitude, 180° phase-separated structure pairs. Accompanying code supports model reconstruction, data processing and configuration-driven generation of additional samples. Beyond conditional forward modelling and response-based structure retrieval, FSSDataBase has the potential to serve as a reference dataset for deep-learning-based FSS inverse design, supporting fair comparisons across network architectures under shared data splits,input conditions and evaluation protocols.
