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首页> 外文期刊>SIAM Journal on Numerical Analysis >Variational mesh adaptation methods for axisymmetrical problems
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Variational mesh adaptation methods for axisymmetrical problems

机译:轴对称问题的变分网格自适应方法

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摘要

We study variational mesh adaptation for axially symmetric solutions to two-dimensional problems. The study is focused on the relationship between the mesh density distribution and the monitor function and is carried out for a traditional functional that includes several widely used variational methods as special cases and a recently proposed functional that allows for a weighting between mesh isotropy ( or regularity) and global equidistribution of the monitor function. The main results are stated in Theorems 4.1 and 4.2. For axially symmetric problems, it is natural to choose axially symmetric mesh adaptation. To this end, it is reasonable to use the monitor function in the form G = lambda(1)(r) e(r)e(r)(T) + lambda(2)(r) e(theta)e(theta)(T), where e(r) and e(theta) are the radial and angular unit vectors. It is shown that when higher mesh concentration at the origin is desired, a choice of lambda(1) and lambda(2) satisfying lambda(1)(0) < λ(2)(0) will make the mesh denser at r = 0 than in the surrounding area whether or not λ(1) has a maximum value at r = 0. The purpose can also be served by choosing λ(1) to have a local maximum at r = 0 when a Winslow-type monitor function with λ(1)( r) = λ(2)(r) is employed. On the other hand, it is shown that the traditional functional provides little control over mesh concentration around a ring r = r(λ) > 0 by choosing lambda(1) and lambda(2). In contrast, numerical results show that the new functional provides better control of the mesh concentration through the monitor function. Two-dimensional numerical results are presented to support the analysis. [References: 15]
机译:我们研究二维问题轴向对称解的变分网格自适应。该研究专注于网格密度分布与监控功能之间的关系,并且针对包括多种广泛使用的变分方法(作为特殊情况)的传统功能以及最近提出的允许网格各向同性(或规则性)加权的功能进行了研究。 )和监控器功能的全球平均分配。主要结果在定理4.1和4.2中说明。对于轴向对称问题,自然会选择轴向对称网格自适应。为此,以G = lambda(1)(r)e(r)e(r)(T)+ lambda(2)(r)e(theta)e(theta)的形式使用监视函数是合理的)(T),其中e(r)和e(theta)是径向和角单位矢量。结果表明,当希望在原点处获得更高的网格密度时,满足lambda(1)(0)<λ(2)(0)的lambda(1)和lambda(2)的选择将使网格在r = λ(1)是否在r = 0处具有最大值比周围区域大0。也可以通过选择Winslow型监视器功能时选择λ(1)在r = 0处具有局部最大值来达到目的。 λ(1)(r)=λ(2)(r)。另一方面,它表明,通过选择lambda(1)和lambda(2),传统函数几乎无法控制环r = r(λ)> 0周围的网格浓度。相反,数值结果表明,新功能通过监视功能可以更好地控制网格浓度。提出了二维数值结果以支持分析。 [参考:15]

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