Estimation of surface temperatures from interior measurements using Tikhonov regularization

DOI10.1016/J.RINAM.2020.100140zbMath1473.35565OpenAlexW3120688072MaRDI QIDQ2040580

Fredrik Berntsson, Japhet Niyobuhungiro, Jean Pierre Ngendahayo

Publication date: 14 July 2021

Published in: Results in Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.rinam.2020.100140

zbMATH Keywords

inverse problemheat conductionTikhonov regularizationheat treatmentmultiple measurements

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Inverse problems for PDEs (35R30) Eigenvalues, singular values, and eigenvectors (15A18) Finite difference methods for initial value and initial-boundary value problems involving PDEs (65M06) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Experimental work for problems pertaining to classical thermodynamics (80-05) Numerical methods for inverse problems for initial value and initial-boundary value problems involving PDEs (65M32) Inverse problems in thermodynamics and heat transfer (80A23) Second-order parabolic equations (35K10) Numerical methods for ill-posed problems for initial value and initial-boundary value problems involving PDEs (65M30) PDEs in connection with classical thermodynamics and heat transfer (35Q79)

Related Items (3)

Solving stationary inverse heat conduction in a thin plate ⋮ On the stabilization of singular identification problem of an unknown discontinuous diffusion parameter in elliptic equation ⋮ \textit{A posteriori} regularization method for the two-dimensional inverse heat conduction problem

Cites Work

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• Numerical solution of generalized IHCP by discrete mollification
• Numerical Solution of First-Kind Volterra Equations by Sequential Tikhonov Regularization
• Wavelet and Fourier Methods for Solving the Sideways Heat Equation
• A spectral method for solving the sideways heat equation
• Approximation of Ill-Posed Volterra Problems via Predictor–Corrector Regularization Methods

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