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AN EXPANDED CHARACTERISTIC-MIXED FINITE ELEMENT METHOD FOR A CONVECTION-DOMINATED TRANSPORT PROBLEM
  • ISSN号:0254-9409
  • 期刊名称:《计算数学:英文版》
  • 时间:0
  • 分类:O357.5[理学—流体力学;理学—力学]
  • 作者机构:[1]Shanghai Jiao Tong Univ, Dept Math, Shanghai 200030, Peoples R China, [2]Shandong Normal Univ, Dept Math, Jinan 250014, Peoples R China
  • 相关基金:This work is supported by the Natural Science Foundation of China (Grant No.10271068), the Natural Science Foundation of Shandong Province (No.Y2002A01), China, and the Science Foundation For Young Scientist in Shandong Province (No.2004BS01009).
作者: Guo, L, Chen, HZ
中文摘要:

在这篇论文,我们为接近建议扩展混合特征的有限 ElementMethod 传送对流的答案统治了运输问题。方法是典型近似的联合及时处理传送对流部分并且一个扩展混合有限元素处理散开部分的空间近似。自从液体在分离水平上沿着近似特征被搬运,计划是稳定的。同时,它在三个变量明确地被对待的意义扩展标准混合有限元素方法:未知的数量,它的坡度,和它的流动。我们的分析证明方法接近未知的数量,它的坡度,和它的流动最佳地并且同时。我们 alsos 这个计划怎么标准方法比那些有小得多的时间截断错误。一个数字例子被举证明计划具有高效。

英文摘要:

In this paper, we propose an Expanded Characteristic-mixed Finite Element Method for approximating the solution to a convection dominated transport problem. The method is a combination of characteristic approximation to handle the convection part in time and an expanded mixed finite element spatial approximation to deal with the diffusion part. The scheme is stable since fluid is transported along the approximate characteristics on the discrete level. At the same time it expands the standard mixed finite element method in the sense that three variables are explicitly treated: the scalar unknown, its gradient, and its flux. Our analysis shows the method approximates the scalar unknown, its gradient, and its flux optimally and simultaneously. We also show this scheme has much smaller time-truncation errors than those of standard methods. A numerical example is presented to show that the scheme is of high performance.

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期刊信息
  • 《计算数学:英文版》
  • 主管单位:
  • 主办单位:中国科学院数学与系统科学研究院
  • 主编:
  • 地址:北京2719信箱
  • 邮编:100080
  • 邮箱:
  • 电话:
  • 国际标准刊号:ISSN:0254-9409
  • 国内统一刊号:ISSN:11-2126/O1
  • 邮发代号:
  • 获奖情况:
  • 中国期刊方阵“双效”期刊
  • 国内外数据库收录:
  • 美国数学评论(网络版),德国数学文摘,荷兰文摘与引文数据库,美国科学引文索引(扩展库),英国科学文摘数据库,日本日本科学技术振兴机构数据库
  • 被引量:193