Document Type
Article
Publication Date
8-27-2021
Department
Department of Engineering Physics
School or Division
Graduate School of Engineering and Management
Digital Object Identifier
Source Publication
Atmosphere (eISSN 2073-4433)
Abstract
Fast and accurate predictions of the flow and transport of materials in urban and complex terrain areas are challenging because of the heterogeneity of buildings and land features of different shapes and sizes connected by canyons and channels, which results in complex patterns of turbulence that can enhance material concentrations in certain regions. To address this challenge, we have developed an efficient three-dimensional computational fluid dynamics (CFD) code called Aeolus that is based on first principles for predicting transport and dispersion of materials in complex terrain and urban areas. The model can be run in a very efficient Reynolds average Navier–Stokes (RANS) mode or a detailed large eddy simulation (LES) mode. The RANS version of Aeolus was previously validated against field data for tracer gas and radiological dispersal releases. As a part of this work, we have validated the Aeolus model in LES mode against two different sets of data: (1) turbulence quantities measured in complex terrain at Askervein Hill; and (2) wind and tracer data from the Joint Urban 2003 field campaign for urban topography. As a third set-up, we have applied Aeolus to simulate cloud rise dynamics for buoyant plumes from high-temperature explosions. For all three cases, Aeolus LES predictions compare well to observations and other models. These results indicate that Aeolus LES can be used to accurately simulate turbulent flow and transport for a wide range of applications and scales.
Recommended Citation
Gowardhan, A. A., McGuffin, D. L., Lucas, D. D., Neuscamman, S. J., Alvarez, O., & Glascoe, L. G. (2021). Large eddy simulations of turbulent and buoyant flows in urban and complex terrain areas using the aeolus model. Atmosphere, 12(9), 1107. https://doi.org/10.3390/atmos12091107
Comments
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Co-author S. Neuscamman was enrolled in an AFIT PhD program at the time of this article's publication. (March 2024 graduate)