Abstract
We applied data-based recurrence CFD (rCFD) to model pollutant dispersion in near-field flow configurations. In case of complex topologies, the global-domain version of rCFD fails to account for local recurrent flow features. We therefore developed a novel island-based version of rCFD, which partitions the computational domain to isolate islands of high recurrence prominence, and subsequently defines a distinct recurrence path for each of these islands. We applied island-based rCFD to pollutant dispersion for two side-by-side cubical buildings with three different gap widths in between them and a real urban environment. We showed that numerical predictions of pollutant dispersion by island-based rCFD were in excellent agreement with full CFD simulations, thus outperforming the global-domain version of rCFD. In both applications, island-based rCFD simulations ran three orders of magnitude faster than corresponding full CFD simulations. In the second application, this speed-up enabled real-time simulations on a computational grid of 10 million cells.
Highlights
Over 50% of the population lives in urban areas today, and the world’s urban population will increase to 7.5 billion before 2050 (Giles-Corti et al, 2016)
Short-term full computational fluid dynamics (CFD) simulations are used to feed the database for subsequent recurrence CFD (rCFD) simula tions, while on the other hand, long-term full CFD simulation serve as numerical validation base for our novel rCFD method
In order to overcome the insufficient recurrence prominence of the global flow field, we developed a new methodology to decompose the computational domain into distinct islands of high recurrence prominence
Summary
Over 50% of the population lives in urban areas today, and the world’s urban population will increase to 7.5 billion before 2050 (Giles-Corti et al, 2016). Air pollution in urban envi ronments has increased significantly, posing a serious societal problem (Environmental Protection Agency, 2020; Zhong et al, 2016). For the investigation of pollutant dispersion in urban environments different approaches, like field measurements (Cui et al, 2017; Niu and Tung, 2007), wind tunnel tests (Gromke et al, 2016; Gromke and Ruck, 2012), and numerical simulations (Blocken, 2014; Blocken and Gualtieri, 2012; Tominaga and Stathopoulos, 2013) have been employed. Numerical simulations have been widely used because of their relatively low cost and for their ability to provide three-dimensional information in the whole computational domain, as opposed to point measurements in field measurements and wind tunnel tests
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