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At least 577 records · Page 32
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DOE OSTI2024

Simplified Approximations of Direct Cumulus Entrainment and Detrainment

Abstract In recent years, direct calculations of simulated cumulus entrainment and detrainment have facilitated new physical insights into these highly elusive but critically important processes. However, these calculations require substantial computational resources that may limit their widespread usage. To facilitate such calculations, two simplified approximations of direct cumulus entrainment and detrainment are examined herein. The first approximation, termed the “semidirect” method, follows a standard bulk approach but makes more realistic assumptions about the sources of entrained and detrained air near the cloud edges. In contrast, the second approximation (the “projection” method) uses the governing equations of motion to project whether grid points near the cloud edge will entrain or detrain as the mean cloud ascends by one grid point. Verification exercises using large-eddy simulations reveal that both methods generally agree better with corresponding direct entrainment/detrainment estimates than the traditional bulk formulation, with the projection method outperforming the semidirect method. The two methods can be used in a synergistic fashion, with the semidirect method helping to optimize the projection method, to suit a wide range of applications. Because the latter incorporates the essential dynamics of entrainment and detrainment at the local scale, it can be used to gain physical insight into the causal mechanisms regulating these complex processes.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

Towards multiscale modeling of ocean surface turbulent mixing using coupled MPAS-Ocean v6.3 and PALM v5.0

A multiscale modeling approach for studying the ocean surface turbulent mixing is explored by coupling an ocean general circulation model (GCM) MPAS-Ocean with the Parallelized Large Eddy Simulation Model (PALM). The coupling approach is similar to the superparameterization approach that has been used to represent the effects of deep convection in atmospheric GCMs. However, the focus of this multiscale modeling approach is on the small-scale turbulent mixing and their interactions with the larger-scale processes in the ocean, so that a more flexible coupling strategy is used. To reduce the computational cost, a customized version of PALM is ported on the general-purpose graphics processing unit (GPU) with OpenACC, achieving 10–16 times overall speedup as compared to running on a single CPU. Even with the GPU-acceleration technique, a superparameterization-like approach to represent the ocean surface turbulent mixing in GCMs using embedded high fidelity and three-dimensional large eddy simulations (LESs) over the global ocean is still computationally intensive and infeasible for long simulations. However, running PALM regionally on selected MPAS-Ocean grid cells is shown to be a promising approach moving forward. The flexible coupling between MPAS-Ocean and PALM allows further exploration of the interactions between the ocean surface turbulent mixing and larger-scale processes, as well as future development and improvement of ocean surface turbulent mixing parameterizations for GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗
DOE OSTI2023

Effects of Wind Shear and Aerosol Conditions on the Organization of Precipitating Marine Stratocumulus Clouds

Here this study examines how wind shear affects precipitating marine stratocumulus clouds under different cloud droplet number concentrations (N d ). We performed a series of large eddy simulations (LES) of nocturnal marine stratocumulus clouds using Cloud Model 1 (CM1). The simulations show that N d is the dominant factor for cloud cellular organization in this cloud regime rather than wind shear. Low N d characterizes the open cellular structure with a high in-cloud liquid water path (LWP). When wind shear is increased, the cloud fraction tends to decrease along with LWP, suggesting the cloud top region is significantly influenced by the entrainment and mixing of dry air from the free troposphere. We also examine cold pools in open and closed cellular clouds. Open-cell clouds produce larger and deeper cold pools compared to closed-cell clouds. Interestingly, cold pools can exist without surface precipitation and are produced by evaporation of light precipitation (drizzle) below the cloud base with weak downdrafts. The evaporation of raindrops and drizzle play an important role in initiating new convection, particularly where colliding outflows occur downstream of the cloud. This secondary convection contributes to the development and maintenance of the cloud cellular organization and formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m -2 . The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m -2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Validation of Wind Power Plant Modeling Approaches in Complex Terrain: Preprint

The effect of terrain on wind-plant aerodynamics is often neglected due to the complex dynamics that make up terrain-atmosphere-turbine interactions and the computational effort required to adequately resolve the relevant physics. In this work, a comprehensive set of measurements (from the Wind Forecast Improvement Project 2) and two distinct modeling approaches are used to investigate the effects of topography on plant performance. The first approach consists of high-fidelity large-eddy simulations conducted for a one- hour period on a terrain-resolving mesh, and producing unsteady, heterogeneous flow that is sensitive to the local topography. The second approach makes use of a steady-state engineering model that has been modified to account for terrain effects. In situ and remote- sensing measurements upstream of the wind plant are used to prescribe initial and boundary conditions to the models, while wind turbine power measurements are used to assess the ability of the different models to capture the effects of terrain on turbine wake dynamics and therefore power production. The full paper will quantify the degree to which our high-fidelity and engineering models are able to capture realistic wind plant aerodynamics in complex terrain, and through improved understanding of the underlying physics, inform our model development efforts.

17 WIND ENERGY↗
DOE OSTI2021

The Area Localized Coupled Model for Analytical Mean Flow Prediction in Arbitrary Wind Farm Geometries

This work introduces the area localized coupled (ALC) model, which extends the applicability of approaches that couple classical wake superposition models and atmospheric boundary layer models to wind farms with arbitrary layouts. Coupling wake and top–down boundary layer models is particularly challenging since the latter requires averaging over planform areas associated with turbine-specific regions of the flow that need to be specified. The ALC model uses Voronoi tessellation to define this local area around each turbine. A top–down description of a developing internal boundary layer is then applied over Voronoi cells upstream of each turbine to estimate the local mean velocity profile. Coupling between the velocity at hub-height based on this localized top–down model and a wake model is achieved by enforcing a minimum least-square-error in mean velocity in each cell. The wake model in the present implementation takes into account variations in wind farm inflow velocity and represents the wake profile behind each turbine as a super-Gaussian function that smoothly transitions between a top-hat shape in the region immediately following the turbine to a Gaussian profile downstream. Detailed comparisons to large-eddy simulation (LES) data from two different wind farms demonstrate the efficacy of the model in accurately predicting both wind farm power output and local turbine hub-height velocity for different wind farm geometries. These validations using data generated from two different LES codes demonstrate the model's versatility with respect to capturing results from different simulation setups and wind farm configurations.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2017

Assessing state-of-the-art capabilities for probing the atmospheric boundary layer: The XPIA field campaign

To assess current capabilities for measuring flow within the atmospheric boundary layer, including within wind farms, the U.S. Dept. of Energy sponsored the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign at the Boulder Atmospheric Observatory (BAO) in spring 2015. Herein, we summarize the XPIA field experiment, highlight novel measurement approaches, and quantify uncertainties associated with these measurement methods. Line-of-sight velocities measured by scanning lidars and radars exhibit close agreement with tower measurements, despite differences in measurement volumes. Virtual towers of wind measurements, from multiple lidars or radars, also agree well with tower and profiling lidar measurements. Estimates of winds over volumes from scanning lidars and radars are in close agreement, enabling assessment of spatial variability. Strengths of the radar systems used here include high scan rates, large domain coverage, and availability during most precipitation events, but they struggle at times to provide data during periods with limited atmospheric scatterers. In contrast, for the deployment geometry tested here, the lidars have slower scan rates and less range, but provide more data during non-precipitating atmospheric conditions. Microwave radiometers provide temperature profiles with approximately the same uncertainty as Radio-Acoustic Sounding Systems (RASS). Using a motion platform, we assess motion-compensation algorithms for lidars to be mounted on offshore platforms. As a result, we highlight cases for validation of mesoscale or large-eddy simulations, providing information on accessing the archived dataset. We conclude that modern remote sensing systems provide a generational improvement in observational capabilities, enabling resolution of fine-scale processes critical to understanding inhomogeneous boundary-layer flows.

17 WIND ENERGY↗
DOE OSTI2023

Uniform momentum and temperature zones in unstably stratified turbulent flows

Wall-bounded turbulent flows exhibit a zonal arrangement, in which streamwise velocity organizes into uniform momentum zones (UMZs), separated by thin layers of elevated interfacial shear. While significant research efforts have focused on these structural features in neutrally stratified flows, the effects of unstable thermal stratification on UMZs and on analogous uniform temperature zones (UTZs) have not been considered previously. In this article, statistical properties of UMZs and UTZs are investigated using a suite of large eddy simulations of unstably stratified turbulent channel flow spanning weakly to highly convective conditions. When normalized by the friction velocity and stability-dependent mixing length, the mean velocity gradient based on UMZ interfacial velocity jumps and the vorticity thickness exhibits good collapse for all stabilities, establishing a link between UMZ properties and scaling predictions from Monin–Obukhov similarity theory. A similar relationship is found between UTZ properties and surface-layer scaling of the mean temperature gradient. In the mixed layer, mean UMZ depth is quasi-constant with wall-normal distance, while the deepest UTZs are found in the centre of the boundary layer. These instantaneous structures are found to be linked to the well-mixed velocity and temperature profiles in the convective mixed layer. Conditional averaging indicates that both UMZ and UTZ interfaces are associated with ejections of momentum and warm updrafts below the interface and sweeps of momentum and cool downdrafts above the interface. These results demonstrate a tangible connection between instantaneous structural features, mean properties and scaling laws in unstably stratified flows.

Mechanics↗
DOE OSTI2021

Describing the Mechanism of Instability Suppression Using a Central Pilot Flame With Coupled Experiments and Simulations

Pilot flames are commonly used to extend combustor operability limits and suppress combustion oscillations in low-emissions gas turbines. Combustion oscillations, a coupling between heat release rate oscillations and combustor acoustics, can arise at the operability limits of low-emissions combustors where the flame is more susceptible to perturbations. While the use of pilot flames is common in land-based gas turbine combustors, the mechanism by which they suppress instability is still unclear. In this study, we consider the impact of a central jet pilot on the stability of a swirl-stabilized flame in a variable-length, single-nozzle combustor. Previously, the pilot flame was found to suppress the instability for a range of equivalence ratios and combustor lengths. We hypothesize that combustion oscillation suppression by the pilot occurs because the pilot provides hot gases to the vortex breakdown region of the flow that recirculate and improve the static, and hence dynamic, stability of the main flame. This hypothesis is based on a series of experimental results that show that pilot efficacy is a strong function of pilot equivalence ratio but not pilot flow rate, which would indicate that the temperature of the pilot products as well as the combustion intensity of the pilot flame play more of a role in oscillation stabilization than the length of the pilot flame relative to the main flame. Further, the pilot-flame efficacy increases with pilot-flame equivalence ratio until it matches the main-flame equivalence ratio; at pilot equivalence ratios greater than the main equivalence ratio, the pilot-flame efficacy does not change significantly with pilot equivalence ratio. To understand these results, we use large-eddy simulation (LES) to provide a detailed analysis of the flow in the region of the pilot flame and the transport of radical species in the region between the main flame and pilot flame. Furthermore, the simulation, using a flamelet/progress variable-based chemistry tabulation approach and standard eddy viscosity/diffusivity turbulence closure models, provides detailed information that is inaccessible through experimental measurements.

42 ENGINEERING↗
DOE OSTI2023

Grounding our Understanding of the Impacts of Boreal Forest Expansion on Shallow Cumulus Clouds with a Simple Modeling Framework

Abstract The expansion of the boreal forest poleward is a potentially important driver of feedbacks between the land surface and Arctic climate. A growing body of work has highlighted the importance of differences in evaporative resistance between different possible future Arctic land covers, which in turn alters humidity and cloudiness in the boundary layer, for these feedbacks. While thus far this problem has been studied primarily with complex Earth system models, we turn to a locally focused, idealized model capable of diagnosing and testing the sensitivity of first-order processes connecting vegetation, the atmospheric boundary layer, and low clouds in this critical region. This allows us to benchmark the mechanisms and results at the center of predictions from larger-scale simulations. A surface dominated by broadleaf trees, characterized by higher albedo and lower surface evaporative resistance, drives cooling and moistening of the boundary layer relative to a surface of needleleaf trees, characterized by lower albedo and higher surface evaporative resistance. Differences in evaporative resistance between these hypothetical Arctic vegetation covers are of equal importance to changes in albedo for the initial response of the boundary layer to boreal expansion, even with our idealized approach. However, compensation between the elevation of the lifting condensation level (LCL) and more rapid growth of the mixed layer over higher evaporative resistance surfaces can minimize changes in the favorability of shallow clouds over different land cover types under some conditions. We then perform two tests on the sensitivity of this compensating effect, to changes in water availability, represented first by a reduction in boundary layer humidity and then by both a reduction in humidity and soil moisture available to our vegetation surface. Finally, given the importance of this potential LCL–mixed-layer height compensation in our idealized modeling results, we look to determine its relevance in observational data from a field campaign in boreal Finland. These observations do confirm that such a coupling plays an important role in cumulus-topped boundary layers over a needleleaf forest surface. While our results confirm some underlying mechanisms at the center of prior work with Earth system models, they also provide motivation for future work to constrain the impact of boreal forest expansion. This will include both large eddy simulations to examine the impact of processes and feedbacks not resolved by a mixed-layer model, as well as a more systematic evaluation and comparison of relevant observations at the site in Finland and sites from prior boreal field campaigns. Significance Statement Clouds and vegetation are both important components of the climate system that interact across a range of scales. These interactions are central to understanding how changes at the land surface feedback on climate. For example, if a forest expands or recedes, diagnosing how that will impact clouds will determine whether you predict warming or cooling temperatures from that shift in the forest area. These predictions are often made with complex Earth system models, but we look to a more idealized representation of the land–atmosphere system to diagnose how shallow clouds should respond to changes in surface properties with different scenarios of boreal forest expansion at a more foundational level. This both grounds our understanding of previous analysis and provides helpful direction for future studies of this relevant and impactful land cover change.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Machine Learning for Improving Surface-Layer-Flux Estimates

Abstract Flows in the atmospheric boundary layer are turbulent, characterized by a large Reynolds number, the existence of a roughness sublayer and the absence of a well-defined viscous layer. Exchanges with the surface are therefore dominated by turbulent fluxes. In numerical models for atmospheric flows, turbulent fluxes must be specified at the surface; however, surface fluxes are not known a priori and therefore must be parametrized. Atmospheric flow models, including global circulation, limited area models, and large-eddy simulation, employ Monin–Obukhov similarity theory (MOST) to parametrize surface fluxes. The MOST approach is a semi-empirical formulation that accounts for atmospheric stability effects through universal stability functions. The stability functions are determined based on limited observations using simple regression as a function of the non-dimensional stability parameter representing a ratio of distance from the surface and the Obukhov length scale (Obukhov in Trudy Inst Theor Geofiz AN SSSR 1:95–115, 1946), $$z/L$$ z / L . However, simple regression cannot capture the relationship between governing parameters and surface-layer structure under the wide range of conditions to which MOST is commonly applied. We therefore develop, train, and test two machine-learning models, an artificial neural network (ANN) and random forest (RF), to estimate surface fluxes of momentum, sensible heat, and moisture based on surface and near-surface observations. To train and test these machine-learning algorithms, we use several years of observations from the Cabauw mast in the Netherlands and from the National Oceanic and Atmospheric Administration’s Field Research Division tower in Idaho. The RF and ANN models outperform MOST. Even when we train the RF and ANN on one set of data and apply them to the second set, they provide more accurate estimates of all of the fluxes compared to MOST. Estimates of sensible heat and moisture fluxes are significantly improved, and model interpretability techniques highlight the logical physical relationships we expect in surface-layer processes.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Modification of wind turbine wakes by large-scale, convective atmospheric boundary layer structures

In this study, we consider the impact of large-scale, convective structures in an unstable atmospheric boundary layer on wind turbine wakes. Simulation data from a high-fidelity large-eddy simulation (LES) of the AWAKEN wind farm site matching unstable atmospheric conditions were analyzed, and both turbine performance and wake behavior were affected based on their location relative to the convective structures. Turbines located in updraft regions of the flow experienced lower inflow velocity and generated less power, but their wakes were observed to recover faster and saw greater turbulent kinetic energy mixing higher in the boundary layer. The opposite effect was found for turbines in the downdraft regions of the convective structures. A simplified model of this wake behavior was also developed based on a two-dimensional k–ε Reynolds-Averaged Navier–Stokes formulation. This simplified model included the effects of vertical transport, but could be efficiently solved as a parabolic system, and was found to capture similar wake modifications observed in the high-fidelity LES computations.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Simulating effects of a wind-turbine array using LES and RANS

Growth in wind power production has motivated investigation of wind-farm impacts on in situ flow fields and downstream interactions with agriculture and other wind farms. These impacts can be simulated with both large-eddy simulations (LES) and mesoscale wind-farm parameterizations (WFP). The Weather Research and Forecasting (WRF) model offers both approaches. We used the validated generalized actuator disk (GAD) parameterization in WRF-LES to assess WFP performance. A 12-turbine array was simulated using the GAD model and the WFP in WRF. We examined the performance of each scheme in both convective and stable conditions. The GAD model and WFP produced qualitatively similar wind speed deficits and turbulent kinetic energy (TKE) production across the array in both stability regimes, though the magnitudes of velocity deficits and TKE production levels were underestimated and overestimated, respectively. While wake growth slowed in the latter half of the WFP array as expected, wakes did not approach steady state by the end of the array as simulated by the GAD model. A sensitivity test involving the deactivation of explicit TKE production by the WFP resulted in turbulence levels within the array well that were below those produced by the GAD in both stable and unstable conditions. Finally, the WFP overestimated downwind power production deficits in stable conditions because of the lack of wake stabilization in the latter half of the array.

17 WIND ENERGY↗
DOE OSTI2025

An airfoil-based synthetic actuator disk model for wind turbine aerodynamic and structural analysis

Here, this study introduces an airfoil-based refinement technique to enhance the Actuator Disk Model (ADM) for improved wind turbine aerodynamic load prediction and structural simulation in conjunction with Large Eddy Simulations of the wind flow. While ADM offers higher computational efficiency than the more detailed but resource-intensive Actuator Line Model (ALM), it traditionally lacks the resolution needed to capture the localized blade forces accurately. To address this limitation, we introduce a refinement technique that uses airfoil-specific data and employs interpolation-based grid point refinement, achieving ALM-comparable accuracy while preserving ADM's efficiency. Unlike conventional ADM that provides only rotor-disk averaged forces, our synthetic method tracks transient aerodynamic load variations over multiple blade revolutions, allowing us to calculate the distributions of maximum and minimum loads during typical cycles. Applied to the NREL 5 MW reference turbine, our enhanced ADM accurately predicts key aerodynamic parameters (angle of attack, axial velocity, lift, drag, axial and tangential forces along the blades) as well as structural responses (blade tip deflection, maximum stress, and stress concentration). Our results show that the tip deflection ranges from 2.33m (3.69 % of blade length) to 4.28m (6.79 %), with maximum stress concentration occurring near the blade root. This research demonstrates that a refined synthetic ADM approach can serve as a computationally efficient alternative for both aerodynamic analysis and structural simulation of wind turbine blades subjected to realistic wind fields.

17 WIND ENERGY↗
DOE OSTI2026

Assessing Cloud and Precipitation Properties on Temporal and Spatial Scales Using LASSO Simulations over ENA

Low clouds and precipitation representation remain a major source of uncertainty in Earth System Models (ESMs), particularly due to challenges in representing their sub-grid variability and scale-dependent sampling. This study evaluates the performance of preliminary simulations from the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project over the Eastern North Atlantic (ENA), with a focus on liquid water path (LWP), ice water path (IWP), cloud fraction (CF), and surface precipitation simulated across closed-cell, open-cell, and transitional cloud regimes. Using LES (100 m horizontal grid spacing) driven by ERA5 and MERRA-2 reanalyses, we assess the representativeness of ground-based point observations by analyzing their correspondence to model-resolved spatial and temporal means. Results suggest that observational sampling of at least 6 hours is required to achieve consistency with domain-scale averages, in particular for observations that exhibit pronounced sub-grid heterogeneity, such as precipitation. ERA5-forced simulations exhibit improved spatial coherence and agreement with domain-averaged quantities when compared to MERRA-2 runs, with performance discrepancies largest for convective cloud conditions due to differences in forcing fidelity and temporal resolution. These findings highlight the importance of regime-aware model evaluation strategies and potentially demonstrate how LES can inform observation-model comparison practices and the development of cloud and precipitation parameterizations in ESMs.

Liang, Jiakun [University of Hawai'i at Manoa] (OR↗
DOE OSTI2014

The Effect of Various Actuator-Line Modeling Approaches on Turbine-Turbine Interactions and Wake-Turbulence Statistics in Atmospheric Boundary-Layer Flow

When using an actuator-line representation of a wind turbine for computational fluid dynamics, it is common practice to volumetrically project the line force onto the flow field to create a body force in the fluid momentum equation. The objective of this study is to investigate how different volumetric projection techniques of the body force created by an actuator-line wind turbine rotor model affect the generated wake characteristics and blade loads in a turbine-turbine interaction problem. Two techniques for the body-force projection width are used , and they are based on either i) the grid spacing, or ii) the combination of grid spacing and an equivalent elliptic blade planform. An array of two NREL 5-MW turbines separated by seven rotor diameters is simulated within a large-eddy simulation solver subject to offshore neutral and moderately-convective atmospheric boundary-layer inflow. Power, thrust,and bending moment histories of both turbines, the statistics of angle of attack and blade loads over 2000 sec, variations in the mean and fluctuating velocity components, and turbulent kinetic energy and selected Reynolds stresses along vertical and spanwise sampling locations in the wake are analyzed. Comparisons for the different techniques of determining the body-force projection width of the actuator-line method are made and their effect on different physical quantities are assessed.

Atmospheric boundary layer, wind turbine wake↗