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高性能计算在目标电磁散射特性分析中的应用
引用本文:刘阳,周海京,郑宇腾,陈晓洁,王卫杰,鲍献丰,李瀚宇.高性能计算在目标电磁散射特性分析中的应用[J].电波科学学报,2019,34(1):3-11.
作者姓名:刘阳  周海京  郑宇腾  陈晓洁  王卫杰  鲍献丰  李瀚宇
作者单位:北京应用物理与计算数学研究所,北京,100094;中物院高性能数值模拟软件中心,北京,100088
基金项目:科学挑战专题TZ2018002中物院复杂电磁环境重点实验室基金FZ2018国家自然科学基金11571196
摘    要:基于高性能计算的电磁数值模拟在目标电磁散射特性分析中发挥着越来越重要的作用.由于任一种数值方法都有一定的适用范围,不能高效处理所有问题,因此,有必要发展和集成多种数值方法,形成能够为不同类型问题的雷达散射截面(radar cross section,RCS)计算提供高效解决途径的软件系统.文中在并行自适应结构/非结构网格应用支撑软件框架之上,充分考虑数值方法的可扩展性以及物理个性的可分离性,通过基于机理、数据的混合可计算建模和接口设计,以及算法的模块化开发,发展了多种用于RCS计算的数值方法,并将其集成到高性能电磁数值模拟软件系统JEMS中.数值算例表明了JEMS具有高效分析多种目标电磁散射特性的能力,并在大规模并行计算方面具有显著优势.

关 键 词:电磁散射  雷达散射截面  高性能计算  数值方法  并行支撑框架
收稿时间:2018-08-30

Applications of the high performance computing in analyzing the electromagnetic scattering characteristics of targets
Affiliation:1.Institute of Applied Physics and Computational Mathematics, Beijing 100094, China2.Software Center for High Performance Numerical Simulation of CAEP, Beijing 100088, China
Abstract:Abstract The electromagnetic numerical simulation based on high performance computing gains more and more attention in analyzing the electromagnetic scattering characteristics of targets to meet the engineering increasing requirements. Since each method has its own advantages and disadvantages, and there is no one method which can deal with all problems, it is necessary to develop multi approach for integrating the software system, which can provide efficient means to analyze the electromagnetic scattering characteristics of different targets. Considering scalability of algorithms and separability of physical characteristics, based on parallel adaptive structured/unstructured mesh applications infrastructure, several numerical methods are developed and integrated into the electromagnetic numerical simulation software system, JEMS, with studying computable modeling, interface design and modularized realization of algorithms. Some numerical examples illustrate JEMS has the capability in efficient solving the radar cross sections of different targets, and has advantages in large-scale parallel computing.
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