The impact of level of detail in 3d city models for cfd-based wind flow simulations

Saturday, Jul 10, 2021

Abstract: Climate change and urbanization rates are transforming urban environments, making the use of 3D city models in computational fluid dynamics (CFD) a fundamental ingredient to evaluate urban layouts before construction. However, current geometries used in CFD simulations tend to be built by CFD experts to test specific cases, most of the times oversimplifying their designs due to lack of information or in order to reduce complexity. In this work we explore what are the effects of oversimplifying geometries by comparing wind simulations of different level of detail geometries.

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Inclusion of Building-Resolving Capabilities Into the FastEddy® GPU-LES Model Using an Immersed Body Force Method

Friday, Oct 30, 2020

Abstract: As a first step toward achieving full physics urban weather simulation capabilities within the resident-GPU large-eddy simulation (LES) FastEddy® model, we have implemented and verified/validated a method for explicit representation of building effects. Herein, we extend the immersed body force method (IBFM) from Chan and Leach (2007, to (i) be scale independent and (ii) control building surface temperatures. Through a specific drag-like term in the momentum equations, the IBFM is able to enforce essentially zero velocities within the buildings, in turn resulting in a no-slip boundary condition at the building walls.

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Evaluating hypoxia alleviation through induced downwelling

Monday, Jan 6, 2020

Abstract: Hypoxia, a condition of low dissolved oxygen concentration, is a widespread problem in marine and freshwater ecosystems. To date, prevention and mitigation of hypoxia has centered on nutrient reduction to prevent eutrophication. However, nutrient reduction is often slow and sometimes insufficient to remedy hypoxia. We investigate the utility of a complementary strategy of pumping oxygenated surface water to depth, termed induced downwelling, as a technique to remedy hypoxia in the bottom water of marine and freshwater ecosystems.

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Predictive large eddy simulations for urban flows: Challenges and opportunities

Sunday, Jan 7, 2018

Abstract: Computational fluid dynamics predictions of urban flow are subject to several sources of uncertainty, such as the definition of the inflow boundary conditions or the turbulence model. Compared to Reynolds-averaged Navier-Stokes (RANS) simulations, large eddy simulations (LES) can reduce turbulence model uncertainty by resolving the turbulence down to scales in the inertial subrange, but the presence of other uncertainties will not be reduced. The objective of this study is to present an initial investigation of the relative importance of these different types of uncertainties by comparing urban flow predictions obtained using RANS and LES to field measurements.

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Optimizing turbulent inflow conditions for large-eddy simulations of the atmospheric boundary layer

Saturday, Jan 6, 2018

Abstract: Large-eddy simulations (LES) of the atmospheric boundary layer (ABL) require the specification of a turbulent inflow condition with appropriate turbulence intensities and length scales. When using a synthetic turbulence generator, the statistics obtained downstream of the inlet might deviate considerably from the intended values. In the present work we propose a fully automated approach to modify the input parameters for the turbulence generator such that the desired turbulence statistics are obtained at the downstream location of interest.

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Uncertainty quantification for microscale CFD simulations based on input from mesoscale codes

Friday, Jan 5, 2018

Abstract: Accurate predictions of wind and dispersion in the atmospheric boundary layer (ABL) can provide essential information to support design and policy decisions for sustainable urban areas. However, computational fluid dynamics (CFD) predictions of the ABL have several sources of uncertainty that can affect the results. An important uncertainty is the definition of the inflow boundary condition, which is influenced by larger scale weather phenomena. In this paper, we propose a method to quantify the effect of uncertainty in the inflow boundary conditions using input from an ensemble of mesoscale simulations.

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Bepalen luchtverontreiniging door verkeer met behulp van 3D-geo-informatie

Wednesday, Jan 3, 2018

Abstract: Eerder publiceerden we in Geo-Info over onze methode om 3D-data zoals nodig in geluidsimulaties automatisch te genereren uit landsdekkende gegevens zoals BAG, BGT en hoogtepunten [1]. Deze geluidsimulaties zijn gebaseerd op gestandaardiseerde rekenvoorschriften voor geluids- belasting. Ook het berekenen van de luchtkwaliteit ten gevolge van binnenstedelijk verkeer kent een Standaard Rekenmethode, beheerd door het RIVM. Deze methode is onder andere gebaseerd op de afstand tussen gebouwen en de weg en hoogtes van deze gebouwen, met andere woorden: een mooi 3D-geo informatievraagstuk.

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Improving urban flow predictions through data assimilation

Wednesday, Jan 3, 2018

Abstract: Detailed aerodynamic information of local wind flow patterns in urban canopies is essential for the design of sustainable and resilient urban areas. Computational Fluid Dynamics (CFD) can be used to analyze these complex flows, but uncertainties in the models can negatively impact the accuracy of the results. Data assimilation, using measurements from wind sensors located within the urban canopy, provides exciting opportunities to improve the quality of the predictions. The present study explores the deployment of several wind sensors on Stanford’s campus to support future validation of CFD predictions with uncertainty quantification and data assimilation.

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Quantifying inflow uncertainties in RANS simulations of urban pollutant dispersion

Saturday, Jan 7, 2017

Abstract: Numerical simulations of flow and pollutant dispersion in urban environments have the potential to support design and policy decisions that could reduce the population’s exposure to air pollution. Reynolds-averaged Navier-Stokes simulations are a common modeling technique for urban flow and dispersion, but several sources of uncertainty in the simulations can affect the accuracy of the results. The present study proposes a method to quantify the uncertainty related to variability in the inflow boundary conditions.

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Quantifying inflow and RANS turbulence model form uncertainties for wind engineering flows

Friday, Jan 9, 2015

Abstract: Reynolds-averaged Navier–Stokes (RANS) simulations are often used in the wind engineering practice for the analysis of turbulent bluff body flows. An approach that allows identifying the uncertainty related to the use of reduced-order turbulence models in RANS simulations would significantly increase the confidence in the use of simulation results as a basis for design decisions. In the present study we apply a strategy that enables quantifying these uncertainties by introducing perturbations in the Reynolds stress tensor to simulations of the flow in downtown Oklahoma City.

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RAMS and WRF sensitivity to grid spacing in large-eddy simulations of the dry convective boundary layer

Thursday, Jan 1, 2015

Abstract: Large-eddy simulations (LESs) are frequently used to model the planetary boundary layer, and the choice of the grid cell size, numerical schemes and sub grid model can significantly influence the simulation results. In the present paper the impact of grid spacing on LES of an idealized atmospheric convective boundary layer (CBL), for which the statistics and flow structures are well understood, is assessed for two mesoscale models: the Regional Atmospheric Modeling System (RAMS) and the Weather Research and Forecasting model (WRF).

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Nesting Turbulence in an Offshore Convective Boundary Layer Using Large-Eddy Simulations

Sunday, Jun 1, 2014

Abstract: The applicability of the one-way nesting technique for numerical simulations of the heterogeneous atmospheric boundary layer using the large-eddy simulation (LES) framework of the Weather Research and Forecasting model is investigated. The focus of this study is on LES of offshore convective boundary layers. Simulations were carried out using two subgrid-scale models (linear and non-linear) with two different closures [diagnostic and prognostic subgrid-scale turbulent kinetic energy (TKE) equations]. We found that the non-linear backscatter and anisotropy model with a prognostic subgrid-scale TKE equation is capable of providing similar results when performing one-way nested LES to a stand-alone domain having the same grid resolution but using periodic lateral boundary conditions.

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Quantifying inflow uncertainties for CFD simulations of the flow in downtown Oklahoma City

Wednesday, Jan 8, 2014

Abstract: Computational Fluid Dynamics (CFD) methods are widely used to investigate wind flow and dispersion in urban environments. Validation with field experiments that represent the full complexity of the problem should be performed to assess the predictive capabilities of the computations. In this context it will be necessary to quantify the effect of uncertainties in simulations of the full-scale problem. The present study aims at quantifying the uncertainty related to the variability in the inflow boundary conditions for Reynolds-averaged Navier–Stokes (RANS) simulations of the flow in downtown Oklahoma City to address validation with the Joint Urban 2003 field measurements.

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Advanced turbulence models and boundary conditions for flows around different configurations of ground-mounted buildings

Monday, Jan 1, 0001

Abstract: The use of multi-stage centrifugal compressors carries out a leading role in oil and gas process applications. Green operation and market competitiveness require the use of low-cost reliable compression units with high efficiencies and wide operating range. A methodology is presented for the design optimization of multi-stage centrifugal compressors with prediction of the compressor map and estimation of the uncertainty limits. A one-dimensional (1D) design tool has been developed that automatically generates a multi-stage radial compressor satisfying the target machine requirements based on a few input parameters.

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