Light scattering in a spatially-correlated particle field: Role of the radial distribution function

Packard, Corey D.; Larsen, Michael L.; Cantrell, Will; Shaw, Raymond A.

doi:10.1016/j.jqsrt.2019.106601

Cited by 6 publications

(25 citation statements)

References 32 publications

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“…The Monte Carlo scattering software used for our analysis, referred to as 'mcScatter', is a ballistic photon simulation code [10,16] created to explore radiative transfer through scattering media, such as light transport through an atmospheric cloud [12]. The construction of this Monte Carlo Ray Tracing (MCRT) code was motivated, in part, by a desire to eventually compare numerical results with experiments performed in a laboratory cloud chamber [14].…”

Section: Overview Of the Mcrt Code ('Mcscatter')mentioning

confidence: 99%

“…The majority of work focusing on radiative transfer through correlated media has been theoretical and computational in nature [9][10][11], at least in part due to the difficulty of such measurements. For example, in recent published work [12], we numerically examined various aspects of radiative transfer through idealized homogeneous and clustered monodisperse particle distributions of discrete particles. We found that while direct transmission is increased in the presence of spatial correlation, diffuse forward transmission is reduced by a similar amount (nearly offsetting the increase in direct transmission).…”

Section: Introductionmentioning

confidence: 99%

“…We found that while direct transmission is increased in the presence of spatial correlation, diffuse forward transmission is reduced by a similar amount (nearly offsetting the increase in direct transmission). In Packard et al [12], the particle clustering was idealized in order to give clear results; the purpose of this paper is to take a step toward experimental verification by exploring computationally whether deviations from standard radiative transfer for a homogeneous medium can plausibly be detected in a laboratory-generated cloud containing more realistic spatial correlations in droplet position due to turbulent mixing.…”

Section: Introductionmentioning

confidence: 99%

“…We consider polydisperse distributions of discrete particles within a turbulent cloud generated in a laboratory convection cloud chamber as our motivating context. We address the problem of predicting radiative transfer through both homogeneous and inhomogeneous media using a Monte Carlo Ray Tracing (MCRT) methodology previously shown [12] to be consistent with standard radiative transfer [13]. To limit scope, we focus this work on the transmission of visible light (e.g., nominal wavelength 550 nm) through an atmospheric cloud generated under laboratory conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, we consider what measurable quantities would be most beneficial for a study of the influence of spatial correlations. In a previous publication [12], we focused on monodisperse distributions with somewhat extreme Matérn clustering and optical thickness near unity; a single particle size and rather small, dense collections of droplets were used for much of our analysis as we evaluated the role of radial distribution functions. In this work, a primary interest is the extent of deviation from the spatially homogeneous case expected when more realistic (as generated by turbulent convection) spatial correlations, smaller optical thicknesses, and polydisperse size distributions are present.…”

Section: Introductionmentioning

confidence: 99%

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Light Scattering in a Turbulent Cloud: Simulations to Explore Cloud-Chamber Experiments

et al. 2020

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Radiative transfer through clouds can be impacted by variations in particle number size distribution, but also in particle spatial distribution. Due to turbulent mixing and inertial effects, spatial correlations often exist, even on scales reaching the cloud droplet separation distance. The resulting clusters and voids within the droplet field can lead to deviations from exponential extinction. Prior work has numerically investigated these departures from exponential attenuation in absorptive and scattering media; this work takes a step towards determining the feasibility of detecting departures from exponential behavior due to spatial correlation in turbulent clouds generated in a laboratory setting. Large Eddy Simulation (LES) is used to mimic turbulent mixing clouds generated in a laboratory convection cloud chamber. Light propagation through the resulting polydisperse and spatially correlated particle fields is explored via Monte Carlo ray tracing simulations. The key finding is that both mean radiative flux and standard deviation about the mean differ when correlations exist, suggesting that an experiment using a laboratory convection cloud chamber could be designed to investigate non-exponential behavior. Total forward flux is largely unchanged (due to scattering being highly forward-dominant for the size parameters considered), allowing it to be used for conditional sampling based on optical thickness. Direct and diffuse forward flux means are modified by approximately one standard deviation. Standard deviations of diffuse forward and backward fluxes are strongly enhanced, suggesting that fluctuations in the scattered light are a more sensitive metric to consider. The results also suggest the possibility that measurements of radiative transfer could be used to infer the strength and scales of correlations in a turbulent cloud, indicating entrainment and mixing effects.

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