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Geometric algorithms for electromagnetic modeling of large scale structures.

机译:用于大型结构电磁建模的几何算法。

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摘要

With the rapid increase in the speed and complexity of integrated circuit designs, 3D full wave and time domain simulation of chip, package, and board systems becomes more and more important for the engineering of modern designs. Much effort has been applied to the problem of electromagnetic (EM) simulation of such systems in recent years. Major advances in boundary element EM simulations have led to O(n log n) simulations using iterative methods and advanced Fast. Fourier Transform (FFT), Multi-Level Fast Multi-pole Methods (MLFMM), and low-rank matrix compression techniques. These advances have been augmented with an explosion of multi-core and distributed computing technologies, however, realization of the full scale of these capabilities has been hindered by cumbersome and inefficient geometric processing. Anecdotal evidence from industry suggests that users may spend around 80% of turn-around time manipulating the geometric model and mesh.;This dissertation addresses this problem by developing fast and efficient data structures and algorithms for 3D modeling of chips, packages, and boards. The methods proposed here harness the regular, layered 2D nature of the models (often referred to as "2.5D") to optimize these systems for large geometries. First, an architecture is developed for efficient storage and manipulation of 2.5D models. The architecture gives special attention to native representation of structures across various input models and special issues particular to 3D modeling.;The 2.5D structure is then used to optimize the mesh systems First, circuit/EM co-simulation techniques are extended to provide electrical connectivity between objects. This concept is used to connect independently meshed layers, allowing simple and efficient 2D mesh algorithms to be used in creating a 3D mesh. Here, adaptive meshing is used to ensure that the mesh accurately models the physical unknowns (current and charge).;Utilizing the regularized nature of 2.5D objects and the known characteristics of stripline, microstrip, and coplanar waveguide propagation, rules are developed to predictively mesh 2.5D models. Creating the meshes based on this a priori knowledge eliminates the expensive solver adaptation loop commonly used to model EM structures. In addition, this method allows for the use of long, thin triangles following the predominate current paths at high frequencies, greatly reducing the number of mesh elements required to model the interactions accurately.
机译:随着集成电路设计速度和复杂性的迅速提高,芯片,封装和电路板系统的3D全波和时域仿真对于现代设计的工程越来越重要。近年来,已经对此类系统的电磁(EM)仿真问题进行了大量努力。边界元EM模拟的重大进展已导致使用迭代方法和高级Fast进行O(n log n)模拟。傅立叶变换(FFT),多级快速多极方法(MLFMM)和低秩矩阵压缩技术。随着多核和分布式计算技术的爆炸式增长,这些进步得到了增强,但是,繁琐和低效的几何处理阻碍了这些功能的全面实现。行业中的轶事证据表明,用户可能花费大约80%的周转时间来操纵几何模型和网格。本论文通过开发快速,高效的数据结构和芯片,封装以及电路板的3D建模算法来解决此问题。这里提出的方法利用了模型的规则,分层的2D性质(通常称为“ 2.5D”)来针对大型几何优化这些系统。首先,开发了一种体系结构,用于有效存储和操纵2.5D模型。该体系结构特别关注跨各种输入模型的结构的本机表示形式以及3D建模所特有的特殊问题;然后将2.5D结构用于优化网格系统首先,扩展了电路/ EM协同仿真技术以提供电连接性在对象之间。此概念用于连接独立的网格层,从而允许在创建3D网格时使用简单有效的2D网格算法。在此,自适应网格化可确保网格准确地建模物理未知数(电流和电荷).;利用2.5D对象的正则化性质以及带状线,微带和共面波导的传播的已知特征,制定规则以进行预测网格2.5D模型。基于此先验知识创建网格消除了通常用于建模EM结构的昂贵的求解器自适应循环。另外,该方法允许在高频下沿主要电流路径使用长而细的三角形,从而大大减少了精确建模相互作用所需的网格元素数量。

著录项

  • 作者

    Pingenot, James.;

  • 作者单位

    University of Washington.;

  • 授予单位 University of Washington.;
  • 学科 Engineering Electronics and Electrical.;Physics Electricity and Magnetism.;Computer Science.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 142 p.
  • 总页数 142
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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