Digital Twins for Critical Infrastructures: Predicting Airborne Contaminant Dispersion

Abstract

During emergencies, timely predictions of airborne contaminant dispersion are imperative to assess the level of threat to civil security and to establish an informed real-time decision-making process. This is essential to effectively evacuate civilians and guarantee the functionality of critical infrastructures. To that end, a computational framework for a digital twin is presented and reduced-order models based on proper orthogonal decomposition in combination with the discrete empirical interpolation method are discussed to accelerate evaluations of the system.