Adaptive step-size forward advection method for aerosol process simulation

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.

Automated summary

Outdoor aerosol processes are often associated with disasters and diseases, posing threats to human life and health. Simulating advection processes of outdoor aerosols is challenging due to variable wind speed, direction, and complex terrain conditions. In this study, an adaptive time step algorithm was designed for forward advection simulation, which showed improved accuracy, reduced computation time, and enhanced mass conservation compared to traditional methods.