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Identification of an unknown time-dependent heat source term from overspecified Dirichlet boundary data by conjugate gradient method

机译:共轭梯度法从超规定Dirichlet边界数据中识别未知的时变热源项

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The inverse problem of identifying the unknown time-dependent heat source H(t) of the variable coefficient heat equation u_t = (k(x)u_x)_x + F(x)H(t), with separable sources of the form F(x)H(t), from supplementary temperature measurement h(t) := u(0, t) at the left end of the rod, is investigated. The Fourier method is employed to illustrate the comparison of spacewise (F(x)) and time-dependent (H(r) heat source identification problems. An explicit formula for the Frechet gradient of the cost functional J(H) = ||u(0, ?; H) - h||_(L_2(0.T_f))~2 is derived via the unique solution of the appropriate adjoint problem. The Conjugate Gradient Algorithm, based on the gradient formula for the cost functional, is then proposed for numerical solution of the inverse source problem. The algorithm is examined through numerical examples related to reconstruction of continuous and discontinuous heat sources H(t), when heat is transferred through non-homogeneous as well as composite structures. Numerical analysis of the algorithm applied to the inverse source problem in typical classes of source functions is presented. Computational results, obtained for random noisy output data, show how the iteration number of the Conjugate Gradient Algorithm can be estimated. Based on these results it is shown that this iteration number plays a role of a regularization parameter. Numerical results illustrate bounds of applicability of the proposed algorithm, and also its efficiency and accuracy.
机译:确定可变系数热方程u_t =(k(x)u_x)_x + F(x)H(t)的未知时变热源H(t)的反问题,其中可分形式为F(根据辅助温度测量值h(t):= u(0,t)对x)H(t)进行了研究。傅里叶方法用于说明空间方向(F(x))和时间相关(H(r)热源识别问题的比较。成本函数J(H)= || u的Frechet梯度的显式公式(0,?; H)-h || _(L_2(0.T_f))〜2是通过适当的伴随问题的唯一解导出的。基于成本函数梯度公式的共轭梯度算法为然后提出了求解逆源问题的数值解决方案,并通过与连续和不连续热源H(t)重构相关的数值示例(当热量通过非均质结构和复合结构传递时)对算法进行了检验。给出了在典型的源函数类中应用到逆源问题的算法,针对随机噪声输出数据获得的计算结果表明了如何估计共轭梯度算法的迭代次数,并根据这些结果表明n该迭代编号起着正则化参数的作用。数值结果说明了该算法的适用范围,以及其有效性和准确性。

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