A two-parameter Tikhonov regularization for a fractional sideways problem with two interior temperature measurements

IF 5.4 3区 材料科学 Q2 CHEMISTRY, PHYSICAL
Dang Duc Trong , Dinh Nguyen Duy Hai , Nguyen Dang Minh , Nguyen Nhu Lan
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引用次数: 0

Abstract

This paper deals with a fractional sideways problem of determining the surface temperature of a heat body from two interior temperature measurements. Mathematically, it is formulated as a problem for the one-dimensional heat equation with Caputo fractional time derivative of order α(0,1], where the data are given at two interior points, namely x=x1 and x=x2, and the solution is determined for x(0,L),0<x1<x2L. The problem is challenging since it is severely ill-posed for x[x1,x2]. For the ill-posed problem, we apply the Tikhonov regularization method in Hilbert scales to construct stable approximation problems. Using the two-parameter Tikhonov regularization, we obtain the order optimal convergence estimates in Hilbert scales by using both a priori and a posteriori parameter choice strategies. Numerical experiments are presented to show the validity of the proposed method.
具有两个内部温度测量值的分数侧向问题的双参数提霍诺夫正则化
本文讨论的是根据两次内部温度测量值确定热体表面温度的分数侧向问题。在数学上,它被表述为具有阶数 α∈(0,1] 的卡普托分数时间导数的一维热方程问题,其中数据是在两个内部点给出的,即 x=x1 和 x=x2,并确定 x∈(0,L),0<x1<x2≤L 的解。这个问题具有挑战性,因为对于 x∉[x1,x2]来说,它是一个严重的问题。对于这个问题,我们采用希尔伯特尺度下的 Tikhonov 正则化方法来构造稳定的近似问题。利用双参数 Tikhonov 正则化,我们通过先验和后验参数选择策略获得了希尔伯特尺度下的阶次最优收敛估计值。数值实验证明了所提方法的有效性。
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来源期刊
ACS Applied Energy Materials
ACS Applied Energy Materials Materials Science-Materials Chemistry
CiteScore
10.30
自引率
6.20%
发文量
1368
期刊介绍: ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.
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