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Event Details

  • Wednesday, May 24, 2017
  • 08:30 - 09:25

Quantifying Inflow and Turbulence Model Form Uncertainties in (RANS) Simulations of the Flow and Dispersion of a Passive Tracer in Downtown Oklahoma City

Computational Fluid Dynamics (CFD) methods are increasingly used for the design of buildings and cities. CFD enables the detailed investigation of flow and dispersion patterns, and can for example be used to design for optimal pedestrian wind comfort, air quality, thermal comfort, renewable energy resources and wind loading. The use of CFD to inform design decisions is however complicated by the large natural variability and complex physics that are characteristic of these flow problems. Quantifying the resulting uncertainties in the simulations is essential to assess and improve the predictive capabilities of the computational tools. This presentation will focus on quantifying inflow and turbulence model form uncertainties in Reynolds-averaged Navier-Stokes (RANS) simulations of the flow and dispersion of a passive tracer in downtown Oklahoma City. The inflow uncertainties are governed by influences from the larger-scale environment, and are characterized using the meso-scale weather forecasting model WRF. The linear eddy-viscosity turbulence model form uncertainty is investigated using high-fidelity model results. The potential for application to other flow problems of interest at the urban and building scale, and the benefits of integrating large- and small-scale and low- and high-fidelity modeling strategies in innovative computational tools will be highlighted.