Combining the Monotonic Lagrangian Grid with a Direct Simulation Monte Carlo Model

Abstract

Using the monotonic Lagrangian grid (MLG) as a data structure in the direct simulation Monte Carlo (DSMC) methodology produces an approach that automatically adjusts grid resolution to time-varying densities in the flow. The MLG algorithm is an algorithm for tracking and sorting moving particles, and it has a monotonic data structure for indexing and storing the physical attributes of the particles. The DSMC method is a direct particle simulation technique widely used in predicting rarefied flows of dilute gases. Monotonicity features of the MLG ensure that particles close in physical space are stored in adjacent array locations so that particle interactions may be restricted to a "template" of near neighbors. The MLG templates provide a time-varying grid network that automatically adapts to local number densities within the flowfield. Computational advantages and disadvantages of this new implementation are demonstrated by a series of test problems.