title: Deconvolution of axisymmetric flame properties using Tikhonov regularization.
abstract: We present a method based on Tikhonov regularization for solving one-dimensional inverse tomography problems that arise in combustion applications. In this technique, Tikhonov regularization transforms the ill-conditioned set of equations generated by onion-peeling deconvolution into a well-conditioned set that is less susceptible to measurement errors that arise in experimental settings. The performance of this method is compared to that of onion-peeling and Abel three-point deconvolution by solving for a known field variable distribution from projected data contaminated with an artificially generated error. The results show that Tikhonov deconvolution provides a more accurate field distribution than onion-peeling and Abel three-point deconvolution and is more stable than the other two methods as the distance between projected data points decreases.
authors.affiliation: National Research Council of Canada. kyle.daun@nrc-cnrc.gc.ca
authors.forename: Kyle J
authors.initials: KJ
authors.lastname: Daun
authors.forename: Kevin A
authors.initials: KA
authors.lastname: Thomson
authors.forename: Fengshan
authors.initials: F
authors.lastname: Liu
authors.forename: Greg J
authors.initials: GJ
authors.lastname: Smallwood