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Approaches to the Numerical Estimates of Grid Convergence of NSE in the Presence of Singularities

机译:在奇点存在下NSE网格收敛的数值估计的方法

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Evaluating the order of accuracy (order) is an integral part of the development and application of numerical algorithms. Apart from theoretical functional analysis to place bounds on error estimates, numerical experiments are often essential for nonlinear problems to validate the estimates in a reliable answer. The common workflow is to apply the algorithm using successively finer temporal/spatial grid resolutions delta(i), measure the error epsilon(i) in each solution against the exact solution, the order is then obtained as the slope of the line that fits (log epsilon(i), log delta(i)). We show that if the problem has singularities like divergence to infinity or discontinuous jump, this common workflow underestimates the order if solution at regions around the singularity is used. Several numerical examples with different levels of complexity are explored. A simple one-dimensional theoretical model shows it is impossible to numerically evaluate the order close to singularity on uniform grids.
机译:评估准确度(订单)的顺序是数值算法的开发和应用的组成部分。除了理论功能分析到误差估计上的界限外,数值实验通常是必不可少的非线性问题,以在可靠的答案中验证估计。常见的工作流程是使用连续更精细的时间/空间网格分辨率Δ(i)应用算法,测量每个解决方案中的epsilon(i)对准确切的解决方案,然后获得订单作为适合的线的斜率(日志epsilon(i),log delta(i))。我们展示如果问题有不同于无限或不连续的跳转等奇点,则这种常见的工作流程低估了命令如果使用周围的奇点周围的区域。探讨了具有不同复杂程度的几个数值例子。一个简单的一维理论模型表明,不可能在数值上评估靠近均匀网格上的奇异性的顺序。

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