Stable reduced-order models for pollutant dispersion in the built environment

摘要

In order to limit the impact of accidental releases of hazardous pollutants into the atmosphere, there is need for an accurate near-range atmospheric dispersion modeling approach that is suitable for on-line risk management. Computational Fluid Dynamics (CFD) has proven to be a promising tool for atmospheric dispersion studies at the near-range. However, the relatively long computing times currently prohibit the use of CFD for real-time purposes. Therefore, we present in this work an effective model reduction method that is based on the projection of the original model, which solves the transient advection-diffusion equation on a steady background velocity field, onto a Krylov subspace by means of the Arnoldi algorithm. This allows to construct a reduced order model (ROM) from an accurate CFD model that is guaranteed to be stable. The algorithm is formulated in such a way that the ROM can be derived using any CFD software package, commercial or non-commercial. The accuracy of the ROM is illustrated by performing a series of simulations of a time-dependent pollutant release at the Doel nuclear power station, located to the north of Antwerp (Belgium). A comparison between the results obtained using the ROM after initialization, and the original CM model shows a reduction of a factor of 2500 in computational time, leading to a ROM that runs 25 times faster than real-time without a significant loss in accuracy. In terms of computational cost, the ROM is a factor 105 less expensive than the original CFD model. (C) 2015 Elsevier Ltd. All rights reserved.