A recursive least-squares algorithm for on-line 1-D inverse heat conduction estimation

Inverse heat transfer analysis of multi-layered tube using thermal resistance network and Kalman filter

“…The details of the description and derivation of this algorithm can be found elsewhere [19,22]. The calculation process of the Kalman filter was expressed as follows.…”

“…In previous studies, the system modeling was conducted using the finite element method [19][20][21][22]. The finite element method expresses approximate functions from unknown variables and determines small element values using the weighted residual method.…”

Groundwater contaminant boundary input flux estimation in a two-dimensional aquifer

“…The study takes precedence from inverse heat conduction problems (IHCP) being successfully solved with this technique. Ji et al [14] used RLSA for successful estimation of impulsive heat flux in one-dimensional Cartesian domain. Tuan and Ju [15] used the Kalman filter to derive a regression equation between the biased residual innovation and thermal unknown.…”

Estimation of Surface Conditions for Nonlinear Inverse Heat Conduction Problems Using the Hybrid Inverse Scheme

“…The main difficulty of the IHCP is that its solution is very sensitive to changes in the input data resulting from measurement errors [1][2][3]. To date, various methods [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20], such as the regularization, least-squares, sequential, conjugate gradient, function specification, Kalman filter, group-preserving, and hybrid inverse methods, have been developed for solving the IHCP. Most of the previous works were confined to problems with constant thermal properties.…”

“…Moreover, these investigators are often free to choose their required type of boundary condition in order to show the accuracy of their inverse schemes, such as the Dirichlet, Neumann, and mixed boundary conditions. Ji et al [18] applied a recursive least-squares algorithm to estimate the unknown surface heat flux of the one-dimensional IHCP from actual experimental data. Ji and Jang [19] provided experimental data to verify the stability of the Kalman filter technique for IHCPs.…”