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arXiv 1502.02629math.NAcs.NA
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求解粗网格上拟线性对流扩散问题的改进方法

An improved method for solving quasilinear convection diffusion problems on a coarse mesh

Texas A&M University(德克萨斯农工大学)

Sara Pollock

AI总结:

本文提出一种改进方法,用于在粗网格上求解拟线性对流扩散问题,通过正则化伪瞬态延续框架设计新的时间积分器,引入可控的数值耗散以减少迭代波动,并通过自适应网格划分策略提高稳定性。

摘要:

本文开发了一种用于求解拟线性对流扩散问题的方法,该方法在粗网格上进行,其中数据和解依赖的系数未解析,问题不稳定且近似性质不成立。求解器的牛顿类迭代基于正则化伪瞬态延续框架,所提出的时序积分器是新马克策略的变种,旨在引入可控的数值耗散并减少粗网格区域中迭代之间的波动,其中数据粗糙且线性化问题可能病态且不定。本文提出了一种算法和更新的标记策略,以生成稳定的迭代序列,通过自适应网格划分捕捉边界和内部层。该方法适用于利用局部误差指示器确定网格细化和目标正则化的自适应框架。方法的推导和q线性局部收敛性得到建立,数值示例验证了理论,包括预测的迭代收敛率。

英文摘要:

A method is developed for solving quasilinear convection diffusion problems starting on a coarse mesh where the data and solution-dependent coefficients are unresolved, the problem is unstable and approximation properties do not hold. The Newton-like iterations of the solver are based on the framework of regularized pseudo-transient continuation where the proposed time integrator is a variation on the Newmark strategy, designed to introduce controllable numerical dissipation and to reduce the fluctuation between the iterates in the coarse mesh regime where the data is rough and the linearized problems are badly conditioned and possibly indefinite. An algorithm and updated marking strategy is presented to produce a stable sequence of iterates as boundary and internal layers in the data are captured by adaptive mesh partitioning. The method is suitable for use in an adaptive framework making use of local error indicators to determine mesh refinement and targeted regularization. Derivation and q-linear local convergence of the method is established, and numerical examples demonstrate the theory including the predicted rate of convergence of the iterations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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