Abstract
A numerical procedure recently presented by the authors for linear inverse heat conduction problems is extended to nonlinear cases. The method is well conditioned in the sense that it always generates bounded solutions and never generates heat fluxes oscillating with increasing amplitude. The convergence of the algorithm is studied, and a set of examples shows convergence for a wide range of nonlinear problems. In the case of perfect data the accuracy of the estimated heat fluxes increases as the time step is decreased without need for additional stabilization or regularization. Filters allow perturbed data to be treated and facilitate attaining a balance between accuracy and resolving power.
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