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Direct Numerical Simulation Of Turbulent Katabatic Slope Flows With An Immersed-Boundary Method, Clancy Umphrey, Ray Deleon, Inanc Senocak Jun 2017

Direct Numerical Simulation Of Turbulent Katabatic Slope Flows With An Immersed-Boundary Method, Clancy Umphrey, Ray Deleon, Inanc Senocak

Inanc Senocak

We investigate a Cartesian-mesh immersed-boundary formulation within an incompressible flow solver to simulate laminar and turbulent katabatic slope flows. As a proof-of-concept study, we consider four different immersed-boundary reconstruction schemes for imposing a Neumann-type boundary condition on the buoyancy field. Prandtl’s laminar solution is used to demonstrate the second-order accuracy of the numerical solutions globally. Direct numerical simulation of a turbulent katabatic flow is then performed to investigate the applicability of the proposed schemes in the turbulent regime by analyzing both first- and second-order statistics of turbulence. First-order statistics show that turbulent katabatic flow simulations are noticeably sensitive to ...


Dynamic Rating Of Overhead Transmission Lines Over Complex Terrain Using A Large-Eddy Simulation Paradigm, Tyler Phillips, Ray Deleon, Inanc Senocak Jun 2017

Dynamic Rating Of Overhead Transmission Lines Over Complex Terrain Using A Large-Eddy Simulation Paradigm, Tyler Phillips, Ray Deleon, Inanc Senocak

Inanc Senocak

Dynamic Line Rating (DLR) enables rating of power line conductors using real-time weather conditions. Conductors are typically operated based on a conservative static rating that assumes worst case weather conditions to avoid line sagging to unsafe levels. Static ratings can cause unnecessary congestion on transmission lines. To address this potential issue, a simulation-based dynamic line rating approach is applied to an area with moderately complex terrain. A micro-scale wind solver — accelerated on multiple graphics processing units (GPUs) — is deployed to compute wind speed and direction in the vicinity of powerlines. The wind solver adopts the large-eddy simulation technique and the ...


An Immersed Boundary Geometric Preprocessor For Arbitrarily Complex Terrain And Geometry, Inanc Senocak, Micah Sandusky, Rey Deleon, Derek Wade, Kyle Felzien, Marianna Budnikova Feb 2016

An Immersed Boundary Geometric Preprocessor For Arbitrarily Complex Terrain And Geometry, Inanc Senocak, Micah Sandusky, Rey Deleon, Derek Wade, Kyle Felzien, Marianna Budnikova

Inanc Senocak

There is a growing interest to apply the immersed boundary method to compute wind fields over arbitrarily complex terrain. The computer implementation of an immersed boundary module into an existing flow solver can be accomplished with minor modifications to the rest of the computer program. However, a versatile preprocessor is needed at the first place to extract the essential geometric information pertinent to the immersion of an arbitrarily complex terrain inside a 3D Cartesian mesh. Errors in the geometric information can negatively impact the correct implementation of the immersed boundary method as part of the solution algorithm. Additionally, the distance ...


Toward A Gpu-Accelerated Immersed Boundary Method For Wind Forecasting Over Complex Terrain, Rey Deleon, Kyle Felzien, Inanc Senocak Sep 2013

Toward A Gpu-Accelerated Immersed Boundary Method For Wind Forecasting Over Complex Terrain, Rey Deleon, Kyle Felzien, Inanc Senocak

Inanc Senocak

A short-term wind power forecasting capability can be a valuable tool in the renewable energy industry to address load-balancing issues that arise from intermittent wind fields. Although numerical weather prediction models have been used to forecast winds, their applicability to micro-scale atmospheric boundary layer flows and ability to predict wind speeds at turbine hub height with a desired accuracy is not clear. To address this issue, we develop a multi-GPU parallel flow solver to forecast winds over complex terrain at the micro-scale, where computational domain size can range from meters to several kilometers. In the solver, we adopt the immersed ...


Stochastic Reconstruction Of Multiple Source Atmospheric Contaminant Dispersion Events, Derek Wade, Inanc Senocak Mar 2013

Stochastic Reconstruction Of Multiple Source Atmospheric Contaminant Dispersion Events, Derek Wade, Inanc Senocak

Inanc Senocak

Reconstruction of intentional or accidental release of contaminants into the atmosphere using concentration measurements from a sensor network constitutes an inverse problem. An added complexity arises when the contaminant is released from multiple sources. Determining the correct number of sources is critical because an incorrect estimation could mislead and delay response efforts. We present a Bayesian inference method coupled with a composite ranking system to reconstruct multiple source contaminant release events. Our approach uses a multi-source data-driven Gaussian plume model as the forward model to predict the concentrations at sensor locations. Bayesian inference with Markov chain Monte Carlo (MCMC) sampling ...


Gpu-Accelerated Large-Eddy Simulation Of Turbulent Channel Flows, Rey Deleon, Inanc Senocak Mar 2012

Gpu-Accelerated Large-Eddy Simulation Of Turbulent Channel Flows, Rey Deleon, Inanc Senocak

Inanc Senocak

High performance computing clusters that are augmented with cost and power efficient graphics processing unit (GPU) provide new opportunities to broaden the use of large-eddy simulation technique to study high Reynolds number turbulent flows in fluids engineering applications. In this paper, we extend our earlier work on multi-GPU acceleration of an incompressible Navier-Stokes solver to include a large-eddy simulation (LES) capability. In particular, we implement the Lagrangian dynamic subgrid scale model and compare our results against existing direct numerical simulation (DNS) data of a turbulent channel flow at Reτ = 180. Overall, our LES results match fairly well with the DNS ...


Application Of A Bayesian Inference Method To Reconstruct Short-Range Atmospheric Dispersion Events, Inanc Senocak Apr 2011

Application Of A Bayesian Inference Method To Reconstruct Short-Range Atmospheric Dispersion Events, Inanc Senocak

Inanc Senocak

In the event of an accidental or intentional release of chemical or biological (CB) agents into the atmosphere, first responders and decision makers need to rapidly locate and characterize the source of dispersion events using limited information from sensor networks. In this study the stochastic event reconstruction tool (SERT) is applied to a subset of the Fusing Sensor Information from Observing Networks (FUSION) Field Trial 2007 (FFT 07) database. The inference in SERT is based on Bayesian inference with Markov chain Monte Carlo (MCMC) sampling. SERT adopts a probability model that takes into account both positive and zero-reading sensors. In ...


A Full-Depth Amalgamated Parallel 3d Geometric Multigrid Solver For Gpu Clusters, Dana A. Jacobsen, Inanc Senocak Mar 2011

A Full-Depth Amalgamated Parallel 3d Geometric Multigrid Solver For Gpu Clusters, Dana A. Jacobsen, Inanc Senocak

Inanc Senocak

Numerical computations of incompressible flow equations with pressure-based algorithms necessitate the solution of an elliptic Poisson equation, for which multigrid methods are known to be very efficient. In our previous work we presented a dual-level (MPI-CUDA) parallel implementation of the Navier-Stokes equations to simulate buoyancy-driven incompressible fluid flows on GPU clusters with simple iterative methods while focusing on the scalability of the overall solver. In the present study we describe the implementation and performance of a multigrid method to solve the pressure Poisson equation within our MPI-CUDA parallel incompressible flow solver. Various design decisions and algorithmic choices for multigrid methods ...


Investigation Of Reynolds Stresses In A 3d Idealized Urban Area Using Large Eddy Simulation, Akshay A. Gowardhan, E. R. Pardyjak, Inanc Senocak, M. J. Brown Mar 2011

Investigation Of Reynolds Stresses In A 3d Idealized Urban Area Using Large Eddy Simulation, Akshay A. Gowardhan, E. R. Pardyjak, Inanc Senocak, M. J. Brown

Inanc Senocak

High resolution, large eddy simulation (LES) of neutral flow through an array of cubes has been conducted with periodic boundary conditions in lateral and longitudinal directions. In this paper, we first describe the model formulation and validate the simulation by comparing the mean flow and turbulence statistics with wind-tunnel experimental data from a cube array of buildings. The LES model is then used to investigate the physical mechanisms that lead to the low turbulent stresses that have been reported in the lower half of the urban canopy layer. To do this, the urban boundary layer is conceptually broken down into ...


Rapid-Response Urban Cfd Simulations Using A Gpu Computing Paradigm On Desktop Supercomputers, Inanc Senocak, Julien C. Thibault, Matthew Caylor Mar 2011

Rapid-Response Urban Cfd Simulations Using A Gpu Computing Paradigm On Desktop Supercomputers, Inanc Senocak, Julien C. Thibault, Matthew Caylor

Inanc Senocak

In the event of chemical or biological (CB) agent attacks or accidents, first-responders need hazard prediction data to launch effective emergency response action. Accurate and timely knowledge of the wind fields in urban areas is critically important to identify and project the extent of CB agent dispersion to determine the hazard-zone. In their 2008 report (GAO-08-180), U.S. Government Accountability Office has reported that first responders are limited in their ability to detect and model hazardous releases in urban environments. The current set of modeling tools for contaminant dispersion in urban environments rely on empirical assumptions with diagnostic equations (Wang ...


Cuda Implementation Of A Navier-Stokes Solver On Multi-Gpu Desktop Platforms For Incompressible Flows, Julien C. Thibault, Inanc Senocak Jan 2010

Cuda Implementation Of A Navier-Stokes Solver On Multi-Gpu Desktop Platforms For Incompressible Flows, Julien C. Thibault, Inanc Senocak

Inanc Senocak

Graphics processor units (GPU) that are traditionally designed for graphics rendering have emerged as massively-parallel "co-processors" to the central processing unit (CPU). Small-footprint desktop supercomputers with hundreds of cores that can deliver teraflops peak performance at the price of conventional workstations have been realized. A computational fluid dynamics (CFD) simulation capability with rapid computational turnaround time has the potential to transform engineering analysis and design optimization procedures. We describe the implementation of a Navier-Stokes solver for incompressible fluid flow using desktop platforms equipped with multi-GPUs. Specifically, NVIDIA’s Compute Unified Device Architecture (CUDA) programming model is used to implement the ...


An Mpi-Cuda Implementation For Massively Parallel Incompressible Flow Computations On Multi-Gpu Clusters, Dana A. Jacobsen, Julien C. Thibault, Inanc Senocak Jan 2010

An Mpi-Cuda Implementation For Massively Parallel Incompressible Flow Computations On Multi-Gpu Clusters, Dana A. Jacobsen, Julien C. Thibault, Inanc Senocak

Inanc Senocak

Modern graphics processing units (GPUs) with many-core architectures have emerged as general-purpose parallel computing platforms that can accelerate simulation science applications tremendously. While multi-GPU workstations with several TeraFLOPS of peak computing power are available to accelerate computational problems, larger problems require even more resources. Conventional clusters of central processing units (CPU) are now being augmented with multiple GPUs in each compute-node to tackle large problems. The heterogeneous architecture of a multi-GPU cluster with a deep memory hierarchy creates unique challenges in developing scalable and efficient simulation codes. In this study, we pursue mixed MPI-CUDA implementations and investigate three strategies to ...


Stochastic Event Reconstruction Of Atmospheric Contaminant Dispersion Using Bayesian Inference, Inanc Senocak, Nicolas W. Hengartner, Margaret B. Short, W. Brent Daniel Jan 2010

Stochastic Event Reconstruction Of Atmospheric Contaminant Dispersion Using Bayesian Inference, Inanc Senocak, Nicolas W. Hengartner, Margaret B. Short, W. Brent Daniel

Inanc Senocak

Environmental sensors have been deployed in various cities for early detection of contaminant releases into the atmosphere. Event reconstruction and improved dispersion modeling capabilities are needed to estimate the extent of contamination, which is required to implement effective strategies in emergency management. To this end, a stochastic event reconstruction capability that can process information from an environmental sensor network is developed. A probability model is proposed to take into account both zero and non-zero concentration measurements that can be available from a sensor network because of a sensor’s specified limit of detection. The inference is based on the Bayesian ...