Summary: | Sprays and other industrially relevant turbid media can be quantitatively and qualitatively characterized using modern optical diagnostics. However, current laser
based techniques generate errors in the dense region of sprays due to the multiple scattering of laser radiation e ected by the surrounding cloud of droplets. In most industrial
sprays, the scattering of light occurs within the so-called intermediate scattering regime
where the average number of scattering events is too great for single scattering to be
assumed, but too few for the di usion approximation to be applied. An understanding
and adequate prediction of the radiative transfer in this scattering regime is a challenging
and non-trivial task that can significantly improve the accuracy and e ciency of optical
measurements. A novel technique has been developed for the modelling of optical radiation propagation in inhomogeneous polydisperse scattering media such as sprays. The
computational model is aimed to provide both predictive and reliable information, and
to improve the interpretation of experimental results in spray diagnostics. Results from
simulations are verified against the analytical approach and validated against the experiment by the means of homogeneous solutions of suspended polystyrene spheres. The
ability of the technique to simulate various detection conditions, to di erentiate scattering orders and to generate real images of light intensity distributions with high spatial
resolution is demonstrated. The model is used for the real case of planar Mie imaging
through a typical hollow cone water spray. Versatile usage of this model is exemplified
with its applications to image transfer through turbid media, correction of experimental
Beer-Lambert measurements, the study of light scattering by single particles in the farfield region, and to simulate the propagation of ultra-short laser pulses within complex
scattering media. The last application is fundamental for the development and testing
of future optical spray diagnostics; particularly for those based on time-gating detection
such as ballistic imaging.
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