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Zbl 0858.65098
Frankel, J.I.
Residual-minimization least-squares method for inverse heat conduction. (English)
[J] Comput. Math. Appl. 32, No.4, 117-130 (1996). ISSN 0898-1221

Summary: A numerical method is systematically developed for resolving an inverse heat conduction problem in the presence of noisy discrete data. This paper illustrates the effect of imposing constraints on the unknown function of interest. A Volterra integral equation of the first kind is derived and used as the starting point for residual-minimization, least squares methodology. Symbolic manipulation is exploited for purposes of augmenting the computational methodology.\par Preliminary indications suggest that the imposition of physical constraints on the system drastically reduces the level of mathematical sophistication needed for accurately approximating the unknown function of interest. These constraints are actually available in many design studies or from models which are derived by physical processes.

MSC 2000:: *65M30 Improperly posed problems (IVP of PDE, numerical methods)
35K05 Heat equation
65R20 Integral equations (numerical methods)
45D05 Volterra integral equations
35R30 Inverse problems for PDE
65M60 Finite numerical methods (IVP of PDE)

Keywords: radial basis functions; symbolic computation; inverse heat conduction problem; noisy discrete data; Volterra integral equation of the first kind; residual-minimization; least squares; spline approximation

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