Adaptive step-size forward advection method for aerosol process simulation

Abstract

Outdoor aerosol processes are often associated with disasters and diseases, which threaten human life and health. Outdoor aerosols are a fluid system affected by meteorological conditions and three-dimensional complex terrain. Their variable wind speed and direction and complex terrain boundary conditions make simulating advection processes difficult. Based on incompressible flow conditions, we designed an adaptive time step algorithm for forward advection for the rapid simulation of aerosol processes. The method is based on the first-order forward semi-Lagrangian advection method with unconditional mass conservation. The first-order truncated error coefficient function theory generates an adaptive time step to control the accuracy of forward advection. Smoke aerosol simulation experiments in two small outdoor scenes were designed, and the effects of the traditional backward advection and forward fixed step methods were compared with the algorithm in this study. The proposed simulation method showed improved accuracy compared with the other two methods in experimental scenarios; moreover, compared with those of the traditional backward method, the computation time was significantly reduced and the conservation of mass was significantly improved. Thus, the proposed method is a fast simulation method for outdoor aerosol numerical prediction.

Keywords

• virtual geographical environments
• aerosol prediction
• finite difference method
• fluid simulation
• adaptive algorithms