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Barrier Function Local and Global Analysis of an L1 Finite Element Method for a Multiterm Time-Fractional Initial-Boundary Value Problem
Journal of Scientific Computing ( IF 2.8 ) Pub Date : 2020-06-20 , DOI: 10.1007/s10915-020-01250-9
Xiangyun Meng , Martin Stynes

An initial-boundary value problem of the form \(\sum _{i=1}^{l}q_i D _t ^{\alpha _i} u(x,t)- \Delta u =f\) is considered, where each \(D _t ^{\alpha _i}\) is a Caputo fractional derivative of order \(\alpha _i\in (0,1)\) and the spatial domain \(\Omega \) lies in \(\mathbb {R}^d\) for \(d\in \{1,2,3\}\). To solve the problem numerically, we apply the L1 discretisation to each fractional derivative on a graded temporal mesh, together with a standard finite element method for the spatial derivatives on a quasiuniform spatial mesh. A new proof of the stability of this method, which is more complicated than the \(l=1\) case of a single fractional derivative, is given using barrier functions; this powerful new technique leads to sharp error estimates in \(L^2(\Omega )\) and \(H^1(\Omega )\) at each time level \(t_m\) that show precisely the improvement in accuracy of the method as one moves away from the initial time \(t=0\). Consequently, while for global optimal accuracy one needs a mesh that is strongly graded when all the \(\alpha _i\) are near zero, for local optimal accuracy away from \(t=0\) one needs a much less severe mesh grading. Numerical experiments show the sharpness of our theoretical results.



中文翻译:

多项式时间分数阶初边值问题的L1有限元方法的障碍函数局部和全局分析

考虑形式为\(\ sum _ {i = 1} ^ {l} q_i D _t ^ {\ alpha _i} u(x,t)-\ Delta u = f \)的初边值问题,其中每个\(D _t ^ {\ alpha _i} \)是阶\(\ alpha _i \ in(0,1)\)的Caputo分数导数,而空间域\(\ Omega \)位于\(\ mathbb {R} ^ d \)代表\(d \ in \ {1,2,3 \} \)。为了从数值上解决问题,我们将L1离散化应用于渐变时空网格上的每个分数导数,以及用于准均匀空间网格上空间导数的标准有限元方法。此方法稳定性的新证明,它比\(l = 1 \)更复杂使用分数函数给出单个分数导数的情况;这项功能强大的新技术可在每个时间水平 \(t_m \)上对\(L ^ 2(\ Omega)\)\(H ^ 1(\ Omega)\)进行清晰的误差估计,从而精确地显示出精度的提高。该方法远离初始时间\(t = 0 \)。因此,虽然对于全局最佳精度,当所有\(\ alpha _i \)都接近零时,需要一个网格进行强分级 ,但对于远离\(t = 0 \)的局部最优精度,则需要的网格分级要低得多。数值实验表明了我们理论结果的敏锐性。

更新日期:2020-06-23
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