Abstract
In multiangle elastic light scattering (MAELS) experiments, the morphology of aerosolized particles is inferred by shining collimated radiation through the aerosol and then measuring the scattered light intensity over a set of angles. In the case of soot-laden aerosols MAELS can be used to recover, among other things, the size distribution of soot aggregates. This involves solving an ill-posed set of equations, however. While previous work focused on regularizing the inverse problem using Bayesian priors, this paper presents a design-of-experiment methodology for identifying the set of measurement angles that minimizes its ill-posedness. The inverse problem produced by the optimal angle set requires less regularization and is less sensitive to noise, compared with two other measurement angle sets commonly used to carry out MAELS experiments.
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