A comparison of Generalized Eigensystem, truncated singular value decomposition, and Tikhonov regularization for the steady inverse heat conduction problem

We present new techniques for solving inverse boundary value problems in st eady heat conduction. These new Generalized Eigensystem techniques are vect or expansion methods which have previously been used in inverse electrocard iography applications. We compare the Generalized Eigensystem techniques to truncated singular value decomposition and Tikhonov regularization on two two-dimensional test geometries and four temperature/flux patterns. One of the Generalized Eigensystem methods (GES(L)) substantially outperforms the other techniques studied on the majority of the test cases, with inverse er rors up to 20 times smaller than other approaches. In addition, even when t he number of sensors on the boundary is reduced, GES(L) was still comparabl e to or superior to the other techniques with a full sensor set.