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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.

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Deconvolution of optically collected axisymmetric flame data is equivalent to solving an ill-posed problem subject to severe error amplification. Tikhonov regularization has recently been shown to be well suited for stabilizing this deconvolution, although the success of this method hinges on choosing a suitable regularization parameter. Incorporating a parameter selection scheme transforms this technique into a reliable automatic algorithm that outperforms unregularized deconvolution of a smoothed data set, which is currently the most popular way to analyze axisymmetric data. We review the discrepancy principle, L-curve curvature, and generalized cross-validation parameter selection schemes and conclude that the L-curve curvature algorithm is best suited to this problem.

Accurate particle sizing through time-resolved laser-induced incandescence (TR-LII) requires knowledge of the thermal accommodation coefficient, but the underlying physics of this parameter is poorly understood. If the particle size is known a priori, however, TR-LII data can instead be used to infer the thermal accommodation coefficient. Thermal accommodation coefficients measured between soot and different monatomic and polyatomic gases show that the accommodation coefficient increases with molecular mass for monatomic gases and is lower for polyatomic gases. This latter result indicates that surface energy is accommodated preferentially into translational modes over internal modes for these gases.

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