Reduced order modelling of an unstructured mesh air pollution model and application in 2D/3D urban street canyons

Abstract

A novel reduced order model (ROM) based on proper orthogonal decomposition (POD) has been developed for a finite-element (FE) adaptive mesh air pollution model. A quadratic expansion of the non-linear terms is employed to ensure the method remained efficient. This is the first time such an approach has been applied to air pollution LES turbulent simulation through three dimensional landscapes. The novelty of this work also includes POD's application within a FE-LES turbulence model that uses adaptive resolution. The accuracy of the reduced order model is assessed and validated for a range of 2D and 3D urban street canyon flow problems. By comparing the POD solutions against the fine detail solutions obtained from the full FE model it is shown that the accuracy is maintained, where fine details of the air flows are captured, whilst the computational requirements are reduced. In the examples presented below the size of the reduced order models is reduced by factors up to 2400 in comparison to the full FE model while the CPU time is reduced by up to 98% of that required by the full model.