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Smoothness-increasing accuracy-conserving filters (SIAC) for discontinuous Galerkin solutions.

机译:用于不连续Galerkin解决方案的提高平滑度的精度保持过滤器(SIAC)。

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摘要

Smoothness-increasing accuracy-conserving (SIAC) filters were introduced as a class of postprocessing techniques to ameliorate the quality of numerical solutions of discontinuous Galerkin (DG) simulations. SIAC filtering works to eliminate the oscillations in the error by introducing smoothness back to the DG field and raises the accuracy in the L2 –norm up to its natural superconvergent accuracy in the negative-order norm. The increased smoothness in the filtered DG solutions can then be exploited by simulation postprocessing tools such as streamline integrators where the absence of continuity in the data can lead to erroneous visualizations. However, lack of extension of this filtering technique, both theoretically and computationally, to nontrivial mesh structures along with the expensive core operators have been a hindrance towards the application of the SIAC filters to more realistic simulations.;In this dissertation, we focus on the numerical solutions of linear hyperbolic equations solved with the discontinuous Galerkin scheme and provide a thorough analysis of SIAC filtering applied to such solution data. In particular, we investigate how the use of different quadrature techniques could mitigate the extensive processing required when filtering over the whole computational field. Moreover, we provide detailed and efficient algorithms that a numerical practitioner requires to know in order to implement this filtering technique effectively. In our first attempt to expand the application scope of this filtering technique, we demonstrate both mathematically and through numerical examples that it is indeed possible to observe SIAC filtering characteristics when applied to numerical solutions obtained over structured triangular meshes. We further provide a thorough investigation of the interplay between mesh geometry and filtering. Building upon these promising results, we present how SIAC filtering could be applied to gain higher accuracy and smoothness when dealing with totally unstructured triangular meshes. Lastly, we provide the extension of our filtering scheme to structured tetrahedral meshes. Guidelines and future work regarding the application of the SIAC filter in the visualization domain are also presented. We further note that throughout this document, the terms postprocessing and filtering will be used interchangeably.
机译:引入增加平滑度的精度保持(SIAC)滤波器作为一类后处理技术,以改善不连续Galerkin(DG)仿真的数值解的质量。 SIAC滤波通过将平滑度引入DG场来消除误差中的振荡,并提高了L2-范数的精度,使其达到了负阶范数的自然超收敛精度。然后,可以通过模拟后处理工具(例如流线积分器)来利用已过滤的DG解决方案中增加的平滑度,在这种工具中,数据中缺乏连续性会导致错误的可视化。然而,这种滤波技术在理论上和计算上都缺乏对非平凡网格结构的扩展以及昂贵的岩心算子,这一直阻碍了SIAC滤波器在更现实的仿真中的应用。用不连续Galerkin方案求解的线性双曲方程的数值解,并提供了对应用于此类解数据的SIAC滤波的全面分析。尤其是,我们研究了在整个计算字段上进行过滤时,如何使用不同的正交技术来减轻所需的大量处理。此外,我们提供了数字从业人员需要了解的详细有效的算法,以便有效地实施此过滤技术。在我们首次尝试扩展这种滤波技术的应用范围时,我们通过数学和数值例子论证了,当将SIAC滤波特性应用于在结构化三角形网格上获得的数值解时,确实有可能观察到。我们进一步提供了对网格几何形状和过滤之间相互作用的彻底研究。基于这些有希望的结果,我们介绍在处理完全非结构化的三角形网格时,如何应用SIAC滤波来获得更高的精度和平滑度。最后,我们将过滤方案扩展到结构化的四面体网格。还介绍了有关SIAC过滤器在可视化领域中的应用的指南和未来的工作。我们进一步注意到,在本文档中,术语后处理和过滤将互换使用。

著录项

  • 作者

    Mirzaee, Hanieh.;

  • 作者单位

    The University of Utah.;

  • 授予单位 The University of Utah.;
  • 学科 Applied Mathematics.;Computer Science.;Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 199 p.
  • 总页数 199
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:42:02

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