Toward a GPU-Accelerated Immersed Boundary Method for Wind Forecasting Over Complex Terrain

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 boundary method and the Lagrangian dynamic large-eddy simulation model and extend them to atmospheric flows. The computations are accelerated on GPU clusters with a dual-level parallel implementation that interleaves MPI with CUDA. We evaluate the flow solver components against test problems and obtain preliminary results of flow over Bolund Hill, a coastal hill in Denmark

GPU-accelerated Modeling of Microscale Atmospheric Flows over Complex Terrain

With installed wind power capacities steadily on the rise, balancing the loads on electrical grids is challenging due to the intermittency of the wind. Short-term wind power forecasting can be a valuable tool for better informing grid operators on the available wind power. Current short-term wind forecasting techniques typically adopt mesoscale weather forecasting models with spatial resolutions on the order of a kilometer. On relatively flat terrain, use of mesoscale models may prove effective, but application to complex terrain induces large forecasting errors. To address this issue, a baseline incompressible flow solver for GPU (graphics processing unit) clusters is extended to simulate neutrally-stable atmospheric flows over complex terrain with the ultimate goal of developing a comprehensive short-term wind fore-casting capability that can resolve winds at turbine hub height. In the extended wind model, the large-eddy simulation (LES) technique with a Lagrangian dynamic subgrid-scale (SGS) model is implemented to better capture the effects of atmospheric turbulence over complex terrain. Additionally, the immersed boundary method (IBM) is adopted to numerically represent the complex terrain on a Cartesian mesh. Validation is performed using common benchmark cases. Performance results obtained from simulating the Bolund Hill Experiment demonstrates that faster than real-time computations are realized with GPU clusters. While the results are encouraging and justifies the foundation for a short-term wind forecasting capability, the work does not account for all factors in wind forecasting and the results can be considered as a first attempt requiring further improvements

An Immersed Boundary Geometric Preprocessor for Arbitrarily Complex Terrain and Geometry

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 field from the terrain is needed to implement various subgrid-scale turbulence models and to initialize wind fields over complex terrain. Despite the popularity of the immersed boundary method, procedures used in the geometric preprocessing stage have received less attention. The present study found that concave and convex regions of complex terrain are particularly challenging to process with existing procedures discussed in the literature. To address this issue, a geometric preprocessor with a distance field solver was presented, and the solver demonstrated its versatility for arbitrarily complex geometry, terrain, and urban environments. The distance field solver uses the initial distance field at the immersed boundaries and propagates it to the rest of the domain by solving the Eikonal equation with the fast sweeping method

Quantifying cerebral asymmetries for language in dextrals and adextrals with random-effects meta analysis

Speech and language-related functions tend to depend on the left hemisphere more than the right in most right-handed (dextral) participants. This relationship is less clear in non-right handed (adextral) people, resulting in surprisingly polarized opinion on whether or not they are as lateralized as right handers. The present analysis investigates this issue by largely ignoring methodological differences between the different neuroscientific approaches to language lateralization, as well as discrepancies in how dextral and adextral participants were recruited or defined. Here we evaluate the tendency for dextrals to be more left hemisphere dominant than adextrals, using random effects meta analyses. In spite of several limitations, including sample size (in the adextrals in particular), missing details on proportions of groups who show directional effects in many experiments, and so on, the different paradigms all point to proportionally increased left hemispheric dominance in the dextrals. These results are analyzed in light of the theoretical importance of these subtle differences for understanding the cognitive neuroscience of language, as well as the unusual asymmetry in most adextrals

A Novel Fix to Reduce the Log-Layer Mismatch in Wall-Modeled Large-Eddy Simulations of Turbulent Channel Flow

The log-layer mismatch arises when a Reynolds-averaged Navier-Stokes (RANS) model is blended with a large-eddy simulation (LES) model in a hybrid fashion. Numerous researchers have tackled this problem by simulating a turbulent channel flow. We show that the log-layer mismatch in hybrid RANS-LES can be reduced substantially by splitting the mean pressure gradient term in the wall-normal direction in a manner that keeps the mass flow rate constant. Additionally, an analysis of the wall-normal variation of the friction velocity shows a constant value is recovered in the resolved LES region different than the value at the wall. Second-order turbulence statistics agree very well with direct numerical simulation (DNS) benchmarks when scaled with the friction velocity extracted from the resolved LES region. In light of our findings, we suggest that the current convention to drive a turbulent periodic channel flow with a uniform mean pressure gradient be revisited in testing eddy-viscosity-based hybrid RANS-LES models as it appears to be the culprit behind the log-layer mismatch

Turbulent Inflow Generation for Large-Eddy Simulation of Incompressible Flows Through Buoyancy Perturbations

Turbulent inflow generation techniques for large-eddy simulation (LES) of turbulent boundary layers is an active area of research. Here, we investigate the use of the perturbation-box turbulent-inflow technique that feeds colored-noise perturbations to the velocity field through the Boussinesq buoyancy approximation. We use a bulk Richardson number based on the perturbation box height and the incoming mean velocity profile to estimate the amplitude of white noise added to the temperature channel flow at Rer = 395 and show good agreement with direct numerical simulation benchmarks. We also demonstrate the applicability of the method to the backward-facing step case

A Cartesian Immersed Boundary Method to Simulate Stably Stratified Turbulent Flows

Turbulent katabatic (downslope) flow under stable stratification over a cool surface remains a poorly understood subject, which finds application in geophysical flows. This work investigates an immersed boundary (IB) formulation within a multi-graphics-processing-unit (GPU) parallel incompressible flow solver to impose velocity and heat flux boundary conditions to simulate fundamental katabatic flows. Prandtl\u27s analytical solution for laminar katabatic flow is used to develop an IB formulation to impose heat flux boundary conditions, and to assess its formal order of accuracy. Direct numerical simulation of turbulent katabatic flow is then performed to investigate the applicability of proposed schemes in the turbulent regime. Results from first order statistics show that turbulent katabatic flow simulations are sensitive to the specifics of the IB formulation, and IB schemes that work well for the laminar regime do not readily apply to the turbulent regime. A reconstruction scheme is proposed that performs well in both the laminar and turbulent regime

Simulations of Turbulent Flow Over Complex Terrain Using an Immersed-Boundary Method

We present an immersed-boundary method to simulate high-Reynolds-number turbulent flow over the complex terrain of Askervein and Bolund Hills under neutrally-stratified conditions. We reconstruct both the velocity and the eddy-viscosity fields in the terrain-normal direction to produce turbulent stresses as would be expected from the application of a surface-parametrization scheme based on Monin–Obukhov similarity theory. We find that it is essential to be consistent in the underlying assumptions for the velocity reconstruction and the eddy-viscosity relation to produce good results. To this end, we reconstruct the tangential component of the velocity field using a logarithmic velocity profile and adopt the mixing-length model in the near-surface turbulence model. We use a linear interpolation to reconstruct the normal component of the velocity to enforce the impermeability condition. Our approach works well for both the Askervein and Bolund Hills when the flow is attached to the surface, but shows slight disagreement in regions of flow recirculation, despite capturing the flow reversal

Portable Solar Collector/Concentrator Design Project

The goal of the design team was to develop a portable unit to collect and concentrate solar energy to produce electricity. The purpose of the device will be to provide much needed power generation to remote areas which have no access to the electrical grid. The device could be used in many military, agricultural, and recreational applications. Some of the constraints for this project were to develop a method to collect the required amount of thermal energy, concentrate it, and transfer the heat into a power generating device. The device must be lightweight and have the ability to collapse into a compact form for transportation. For the purpose of collecting and concentrating the solar radiation, the device will be comprised of a reflective parabolic dish that will focus the sunlight to a central receiver. The receiving body will transfer the solar energy, in the form of heat, into a fluid which will be used to run a power generation device. In order to obtain consistent power generation, the device will contain a motorized tracking system enabling it to stay directed towards the sun. To ensure portability, the device will be constructed in a way that allows the support frame to be removed and taken apart. This will allow the device to have a compact form during transportation. The expected results of the project are to generate 750 W of power output, have a device weighing less than 15lbs, and have the compact size be comparable to that of a backpack