Monte Carlo particle dispersion (MoCaPD) model of battlefield obscuration

The essential input for an optical study of short-term dispersion of battlefield obscurants is the number density spatial distribution for each particle size at a particular line of sight. These number density distributions should account for ground-level source effect and must be spatially and temporally dependent. The basic Monte Carlo particle dispersion (MoCaPD) model approach consists of computing an ensemble or collection of time histories of random particle trajectories referenced to a fixed coordinate system. These random functions of position and time and of prevailing meteorological conditions are stored in a data file and then used to carry out statistical analyses or "real-time" simulations. The motion of particles is statistically consistent with the elementary Lagrangian turbulence properties of the lower atmospheric boundary layer. Moreover, the wind fields encountered by nearby particles are coherent (spatially correlated). The MoCaPD model includes all of these features and can predict temporal and spatial particle size distributions and number density probabilities of smoke or dust obscuring the view of a target detection system located relative to a smoke source.

The capabilities of the model are shown by comparison of the computed results with data measured from obscurant field trials. The obscurant material examined include red phosphorus (RP), hexachlorethane (HC), and Arizona road dust. Reasonable agreement between theory and experiment is demonstrated.