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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Do Machine Learning Approaches Offer Skill Improvement for Short-Term Forecasting of Wind Gust Occurrence and Magnitude?

Abstract Wind gusts, and in particular intense gusts, are societally relevant but extremely challenging to forecast. This study systematically assesses the skill enhancement that can be achieved using artificial neural networks (ANNs) for forecasting of wind gust occurrence and magnitude. Geophysical predictors from the ERA5 reanalysis are used in conjunction with an autoregressive term in regression and ANN models with different predictors, and varying model complexity. Models are derived and assessed for the warm (April–September) and cold (October–March) seasons for three high passenger volume airports in the United States. Model uncertainty is assessed by deriving models for 1000 different randomly selected training (70%) and testing (30%) subsets. Gust prediction fidelity in independent test samples is critically dependent on inclusion of an autoregressive term. Gust occurrence probabilities derived using five-layer ANNs exhibit consistently higher fidelity than those from regression models and shallower ANNs. Inclusion of the autoregressive term and increasing the number of hidden layers in ANNs from 1 to 5 also improve the model performance for gust magnitudes (lower RMSE, increased correlation, and model standard deviations that more closely approximate observed values). Deeper ANNs (e.g., 20 hidden layers) exhibit higher skill in forecasting strong (17–25.7 m s −1 ) and damaging (≥25.7 m s −1 ) wind gusts. However, such deep networks exhibit evidence of overfitting and still substantially underestimate (by 50%) the frequency of strong and damaging wind gusts at the three airports considered herein. Significance Statement Improved short-term forecasting of wind gusts will enhance aviation safety and logistics and may offer other societal benefits. Here we present a rigorous investigation of the relative skill of models of wind gust occurrence and magnitude that employ different statistical methods. It is shown that artificial neural networks (ANNs) offer considerable skill enhancement over regression methods, particularly for strong and damaging wind gusts. For wind gust magnitudes in particular, application of deeper learning networks (e.g., five or more hidden layers) offers tangible improvements in forecast accuracy. However, deeper networks are vulnerable to overfitting and exhibit substantial variability with the specific training and testing data subset used. Also, even deep ANNs reproduce only half of strong and damaging wind gusts. These results indicate the need for future work to elucidate the dynamical mechanisms of intense wind gusts and advance solutions to their prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Short–Term Forecasting of Wind Gusts at Airports Across CONUS Using Machine Learning

Short–term forecasting of wind gusts, particularly those of higher intensity, is of great societal importance but is challenging due to the presence of multiple gust generation mechanisms. Wind gust observations from eight high–passenger–volume airports across the continental United States (CONUS) are summarized and used to develop predictive models of wind gust occurrence and magnitude. These short–term (same hour) forecast models are built using multiple logistic and linear regression, as well as artificial neural networks (ANNs) of varying complexity. A suite of 19 upper–air predictors drawn from the ERA5 reanalysis and an autoregressive (AR) term are used. Stepwise procedures instruct predictor selection, and resampling is used to quantify model stability. All models are developed separately for the warm (April–September) and cold (October–March) seasons. Results show that ANNs of 3–5 hidden layers (HLs) generally exhibit higher hit rates than logistic regression models and also improve skill with respect to wind gust magnitudes. However, deeper networks with more HLs increase false alarm rates in occurrence models and mean absolute error in magnitude models due to model overfitting. For model skill, inclusion of the AR term is critical while the majority of the remaining skill derives from wind speeds and lapse rates. A predictive ceiling is also clearly demonstrated, particularly for the strong and damaging gust magnitudes, which appears to be partially due to ERA5 predictor characteristics and the presence of mixed wind climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Wind Turbine Gust Load Alleviation with Active Flow Control

Large wind turbine rotors are becoming more common in utility-scale wind power, especially for offshore wind plants. However, the trend toward large rotors can be limited by their ability to manage dynamic and extreme loads. To provide a safety margin for the rotor design and avoid catastrophic events such as tower strikes, extreme loads need to be controlled. The objective of this study is to develop and evaluate a feedback control system to alleviate extreme loads and reduce blade deflections under gust events using active flow control devices. We also propose a modification in the turbine controller to achieve further reduction in extreme loads. The extreme load reductions are evaluated under gust wind conditions with direction changes according to the IEC standard. The effects of the gust alleviation controller on turbine performance and fatigue loads are investigated as well. With the deployment of the gust alleviation controller and modified turbine baseline controller, the extreme loads and deflections reduce by up to 23%. The energy captured by the turbine is not affected by the proposed gust alleviation controller. The fatigue loads of various wind turbine components are either reduced or remain unchanged.

17 WIND ENERGY↗
DOE OSTI2024

Quantifying the compound hazard of freezing rain and wind gusts across CONUS

Abstract The co-occurrence of freezing rain, ice accumulation and wind gusts (FZG) poses a significant hazard to infrastructure and transportation. However, quantification of the frequency and intensity of FZG is challenged by the lack of direct icing measurements. In this work, we evaluate and then apply an energy balance model to high-frequency data collected during 2005–2022 to derive hourly ice accumulation at 883 stations across the contiguous USA. These estimates are combined with wind gust observations to compute time series of hourly FZG hazard magnitude using the Sperry–Piltz Ice Accumulation (SPIA) index. Results are evaluated using Storm Reports of damage and economic disruption. The hourly SPIA estimates are also used to (i) derive a geospatial atlas of the hazard including the 50 yr return period event intensities for each US state derived using superstations, and (ii) describe storylines of significant events in terms of meteorological drivers and socioeconomic impacts. The highest values of SPIA during the 18 yr study period occur in a region extending from the Southern Great Plains over the Midwest into the densely populated Northeast. States in these regions also have high 50 yr return period maximum radial ice accumulation of 3–5 cm and co-occurring wind gusts >30 ms −1 . These values are comparable to past estimates for the 500 yr event which may imply this hazard has been previously underestimated. This atlas can be used to inform optimal FZG hazard mitigation strategies for each state/region.

58 GEOSCIENCES↗
DOE OSTI2020

Characterizing Thunderstorm Gust Fronts near Complex Terrain

Fire safety, aviation, wind energy, and structural-engineering operations are impacted by thunderstorm outflow boundaries or gust fronts (GFs) particularly when they occur in mountainous terrain. For example, during the 2013 Arizona Yarnell Hill Fire, 19 firefighters were killed as a result of sudden changes in fire behavior triggered by a passing GF. Knowledge of GF behavior in complex terrain also determines departure and landing operations at nearby airports, and GFs can induce exceptional structural loads on wind turbines. Furthermore, while most examinations of GF characteristics focus on well-organized convection in areas such as the Great Plains, here the investigation is broadened to explore GF characteristics that evolve near the complex terrain of the Colorado Rocky Mountains. Using in situ observations from meteorological towers, as well as data from wind-profiling lidars and a microwave radiometer, 24 GF events are assessed to quantify changes in wind, temperature, humidity, and turbulence in the lowest 300 m AGL as these GFs passed over the instruments. The changes in magnitude for all variables are on average weaker in the Colorado Front Range than those typically observed from organized, severe storms in flatter regions. Most events from this study experience an increase in wind speed from 1 to 8 m s -1 , relative humidity from 1% to 8%, and weak vertical motion from 0.3 to 3.6 m s -1 during GF passage while temperature drops by 0.2°–3°C and turbulent kinetic energy peaks at >4 m2 s -2 . Vertical profiles reveal that these changes vary little with height in the lowest 300 m.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Characterization of Oscillatory Response of Light-Weight Wind Turbine Rotors under Controlled Gust Pulses

Given the industry-wide trend of continual increases in the size of utility-scale wind turbines, a point will come where reductions will need to be made in terms of the weight of the turbine’s blades to ensure they can be as long as needed without sacrificing structural stability. One such technique that may be considered is to decrease the material used for the shell and spar cap. While this will solve the weight issue, it creates a new one entirely—less material for the shell and spar cap will in turn create blades that are more flexible than what is currently used. This article aims to investigate how the oscillatory response of light-weight wind turbine rotors is affected by these flexibility changes. The object of our study is the Sandia National Lab National Rotor Testbed (SNL-NRT) wind turbine, which the authors investigated in the course of a research project supported by SNL. Using a reduced-order characterization (ROC) technique based on controlled gust pulses, introduced by the authors in a previous work, the aeroelastic dynamics of the NRT’s original baseline blade design and several of its flexible variations were studied via numerical simulations employing the CODEF multiphysics suite. Results for this characterization are presented and analyzed, including a generalization of the ROC of the SNL-NRT oscillatory dynamics to larger machines with geometrical similarity. The latter will prove to be valuable in terms of extrapolating results from the present investigation and other ongoing studies to the scale of current and future commercial machines.

Ponta, Fernando (ORCID:0000000321032864)↗
DOE OSTI2023

Effect of Wind Gusts on Local Run-of-River Hydro Plants

In this work, we focus on the integration of wind farms in a hydro dominated power system, and analyze the challenges and solutions associated with this integration. Due to sudden increase in wind power, the system frequency can increase, causing excessive reduction in the run-of-river (ROR) system’s power. This can result in damage to the physical structure due to water level violations and cause issues for downstream customers. To prevent excessive and prolonged ROR power deviations, and to prevent tie-line deviations, we are proposing a wind-hydro centralized coordination scheme, which is not existing currently. The controller showed promising results by reducing the system frequency extrema by 0.8Hz.

13 HYDRO ENERGY↗
DOE OSTI2024

Mitigating the Effect of Wind Gusts on Local Run-of-River Hydropower Plants Using Cooperative Control

This paper focuses on the challenges and solutions associated with the integration of wind farms in a hydro- dominated power system. Due to sudden increases in wind power, the system frequency can increase, causing excessive reduction in the run-of-river (ROR) system’s power. Considering their small pondage, this can result in damage to the physical structure due to water level violations which are also penalized by stakeholders. To prevent excessive ROR power deviations, ROR governor wear and tear, and to prevent tie-line deviations, a centralized, distributed, and hybrid scheme for coordinating the response from a cluster of ROR plants is examined. Both centralized and distributed control as well as their hybrids can reduce frequency peaks. However, the inclusion of decentralized cooperative controls leads to reduced governor actions from fast- acting plants while enhancing net response from the hydro unit cluster.

13 HYDRO ENERGY↗
DOE OSTI2024

How well are hazards associated with derechos reproduced in regional climate simulations?

Abstract. A 15-member ensemble of convection-permitting regional simulations of the fast-moving and destructive derecho of 29–30 June 2012 that impacted the northeastern urban corridor of the USA is presented. This event generated 1100 reports of damaging winds, generated significant wind gusts over an extensive area of up to 500 000 km2, caused several fatalities, and resulted in widespread loss of electrical power. Extreme events such as this are increasingly being used within pseudo-global-warming experiments to examine the sensitivity of historical, societally important events to global climate non-stationarity and how they may evolve as a result of changing thermodynamic and dynamic contexts. As such it is important to examine the fidelity with which such events are described in hindcast experiments. The regional simulations presented herein are performed using the Weather Research and Forecasting (WRF) model. The resulting ensemble is used to explore simulation fidelity relative to observations for wind gust magnitudes, spatial scales of convection (as is manifest in high composite reflectivity, cREF), and both rainfall and hail production as a function of model configuration (microphysics parameterization, lateral boundary conditions (LBCs), start date, use of nudging, compiler choice, damping, and number of vertical levels). We also examine the degree to which each ensemble member differs with respect to key mesoscale drivers of convective systems (e.g., convective available potential energy and vertical wind shear) and critical manifestations of deep convection, e.g., vertical velocities, cold-pool generation, and how those properties relate to the correct characterization of the associated atmospheric hazards (wind gusts and hail). Use of a double-moment, seven-class scheme with number concentrations for all species (including hail and graupel) results in the greatest fidelity of model-simulated wind gusts and convective structure to the observations of this event. All ensemble members, however, fail to capture the intensity of the event in terms of the spatial extent of convection and the production of high near-surface wind gusts. We further show very high sensitivity to the LBCs employed and specifically that simulation fidelity is higher for simulations nested within ERA-Interim compared to ERA5. Excess convective available potential energy (CAPE) in all ensemble members after the derecho passage leads to excess production of convective cells, wind gusts, cREF > 40 dBZ, and precipitation during a frontal passage on the subsequent day. This event proved very challenging to forecast in real time and to reproduce in the 15-member hindcast simulation ensemble presented here. Future work could examine if simulations with other initial and lateral boundary conditions can achieve greater fidelity.

Shepherd, Tristan (ORCID:0000000186276419)↗
DOE OSTI2026

Sensitivity Analysis of Numerical Modeling Input Parameters on Wind Turbine Loads in Deterministic Transient Load Cases

Aero-hydro-elastic-servo numerical models used to design and analyze wind turbines are based on thousands of variable input parameters that dictate the inflow, aerodynamic, structural, and control characteristics of the system as well as sea state, hydrodynamic, and mooring characteristics for fixed-bottom and floating offshore wind turbines. Each of these parameters has some level of uncertainty, which can significantly impact the predicted loads. Understanding the uncertainty in the inputs is critical to understanding the uncertainty in the outputs. This work demonstrates a screening technique to identify which parameters ultimate loads are most sensitive to so that more focus can be given to quantifying the possible range of those parameters. This technique has been demonstrated previously for different turbine and load case types and is extended here for a floating offshore wind turbine in design load cases with transient events both in the inflow and operations. Each load case features a deterministic gust, including variations in wind speed, direction, and shear. Load cases are considered with an operating turbine as well as with prescribed fault, startup, and shutdown procedures. The study found that key input parameters with a large impact on loads include the length of the gust, the magnitude of direction change and speed in the gust, the initial wind speed, and the shape of the gust profile.

17 WIND ENERGY↗
DOE OSTI2020

Simulating the Effects of Surface Energy Partitioning on Convective Organization: Case Study and Observations in the US Southern Great Plains

Realistic cloud-resolving simulations were performed to study the effects of surface energy partitioning (surface sensible and latent heat fluxes) on the organization of isolated convection into larger mesoscale convective systems (MCSs) near the US Southern Great Plains. The role of cold pools in mediating surface-convection interactions was explored. Better organized MCSs tended to occur in the experiments with perturbed wetter soil (and more active vegetation), regardless of the effects of soil moisture on the diurnal timing of convective triggering. Wetter soil led to shallower boundary layers and more convective available potential energy than drier soil. The roles of cold pools on convection are lifecycle-stage dependent: A dry surface allows more numerous colliding cold pools, thereby aiding in convective triggering by reducing entrainment in the early stages, and providing gust-front uplift in later stages. However, horizontal propagation of the cold-pool density current can outrun the convective system, creating a slantwise updraft and thus weakening the gust front uplift in later stages. This effect calls into question previous cold pool parameterizations, in which the gust front uplift is mainly proportional to the negative buoyancy of cold air. Finally, both the model and observation show an enhancement of surface latent heat flux during the passage of a gust front at night, suggesting that a positive feedback between the surface and convection helps MCSs to persist into the nighttime.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An Observational Evaluation of RKW Theory over the U.S. Southern Great Plains

The theory of Rotunno et al. (“RKW” theory) addresses the behavior of squall-line cold pools in vertically sheared flows. It predicts that, within a given thermodynamic environment, a balance between baroclinic vorticity generation by the cold pool and low-level environmental vertical wind shear induces an upright updraft along the gust front that maximizes the initiation of new convective cells. Although this theory has been evaluated numerically, its applicability to observed systems remains unclear and is limited by a lack of critical measurements, including high-frequency thermodynamic and wind profiles across the gust front. Herein, observations from the Atmospheric Radiation Measurement Southern Great Plains (ARM-SGP) observatory near Lamont, Oklahoma, are used to evaluate RKW theory for 10 well-observed squall lines over a 11-yr period. For this evaluation, RKW parameters including cold-pool intensity (c), low-level ambient, line-normal vertical shear (ΔV n ), subcloud and cloud-layer updraft tilts, and multiple measures of system intensity are estimated. Furthermore, the c estimates rely on thermodynamic retrievals from the Atmosphere Emitted Radiance Interferometer (AERI), which are uncertain but verify reasonably well against independent observations. As predicted by the theory, for c/ΔV n ≥ 1, c/ΔV n correlates positively with updraft tilt and negatively with system intensity, but these results are not always statistically significant and are also sensitive to the method by which ΔV n is evaluated. Specifically, ΔV n evaluations that extend above the cold-pool top yield greater consistency with RKW predictions. Also, some measures of intensity correlate more strongly with standard moist instability metrics than with RKW parameters.

Cold pools↗
DOE OSTI2024

Convectively Induced Secondary Circulations and Wind‐Driven Heat Fluxes in the Surface Energy Balance Over Land

Increased resolution has enabled kilometer-scale weather and climate models to partially resolve secondary circulations, including horizontal convective rolls (HCRs) and cold pool gust fronts. Although these circulations are ubiquitous in convective boundary layers over land, their impacts on the surface energy balance are largely unknown. Doppler lidar and surface observations were combined with DOE E3SM land model experiments, revealing increased surface winds (5 m/s) and heat fluxes (50 W/m 2 ) in convergent branches of HCRs. Larger wind-driven flux responses (up to 150 W/m 2 ) were found along gust fronts. Surface energy balance shifts to accommodate wind-driven fluxes, reducing ground heat conduction and longwave cooling. Our findings from the US Southern Great Plains are broadly relevant to modeling convective boundary layers. In particular, widely used subgrid wind gust parameterizations were found to be physically inconsistent with resolved secondary circulations and could worsen climate prediction biases at kilometer-scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Interactions Between Clouds and Wind-Driven Surface Heat Exchanges over Land

Earth system model experiments show that increasing horizontal resolution fundamentally alters the simulated soil-moisture-precipitation feedback. Kilometer-scale simulations often produce weaker or even negative feedback compared to coarse-resolution models. A key difference of kilometer-scale models is that they resolve mesoscale secondary circulations, including boundary layer horizontal rolls and cellular structures, in addition to cold pools and downdrafts associated with convective precipitation. However, because the relevant processes occur on yet-smaller scales, these circulations are often poorly resolved. This project demonstrated that boundary layer secondary circulations significantly affect surface heat exchanges and wind gusts, and that current model parameterizations can misrepresent these processes at kilometer-scale resolution. Using DOE Atmospheric Radiation Measurement (ARM) observations and targeted experiments with the DOE Energy Exascale Earth System Model (E3SM), we identified physically unrealistic wind gust and surface flux responses to secondary circulations, diagnosed a systematic overestimation of wind shear in convective cold pools, and uncovered a multivariate relationship between land surface fluxes and the scales of updrafts that form shallow cumulus clouds. These findings provide observation-based recommendations for improving parameterizations of surface fluxes and wind gusts in high-resolution Earth system models, thereby reducing uncertainty in convective storm prediction and land-atmosphere feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Towards Universal Non-Dimensional Characterization of the Oscillatory Dynamics of Wind Turbine Rotors of Multiple Sizes

One concern in the field of Horizontal Axis Wind Turbines (HAWTs) is what control strategies are needed to handle gust pulses in the wind to prevent extreme oscillations of the blades to reduce fatigue stress, prevent blade rupture, and extend the turbine’s operational life. In order to design innovative control strategies to modify the blade’s oscillatory response, it is crucial to establish the fundamental vibrational behavior of the blades when excited by gust pulses of different frequencies and amplitudes present in the fluctuating wind inflow. In a series of previous works, the authors presented a novel Reduced-Order Characterization (ROC) technique that provided an energy-based characterization of the fundamental modes of oscillation of wind turbine rotors when excited by combinations of wind gust pulses of different frequencies and amplitudes. The main focus of the present work is to extend these original notions of energy-based ROC to a universal technique expressed in terms of non-dimensional quantities that could be applied to turbines of any size, operating in any set of wind conditions, as long as they share geometrical and material similarity. The ROC technique provides a simple formula that is capable of predicting the dominant vibrational modes of a blade with sufficient precision to be useful in the determination of a control decision that can be computed in real time, an aspect of fundamental importance in dealing with rapid fluctuations in wind conditions.

Yates, North (ORCID:000900052204261X)↗
DOE OSTI2023

Advanced wind turbine control development using field test analysis for generator overspeed mitigation

Abstract Turbulent and gusty wind conditions can cause generator overspeed peaks to exceed a threshold that then lead to wind turbine shutdowns, which then decrease the energy production of the wind turbines. We derive so‐called “gust measures” that predict when generator overspeed peaks may occur. These gust measures are then used to develop advanced controllers to mitigate generator overspeed peaks so that wind turbines can operate more robustly in difficult wind conditions without exceeding generator overspeed thresholds that would lead to turbine shutdown events. The advanced controllers are demonstrated in nonlinear aeroelastic simulations using the open‐source wind turbine simulation tool OpenFAST. To increase the realism of the simulations, they are run using field‐replicated wind conditions and a wind turbine model based on data from an experimental field campaign on a downscaled demonstrator of a novel extreme‐scale, two‐bladed, downwind rotor design.

17 WIND ENERGY↗
DOE OSTI2023

The June 2012 North American Derecho: A Testbed for Evaluating Regional and Global Climate Modeling Systems at Cloud‐Resolving Scales

Abstract In this paper, we introduce a testbed for evaluating and comparing climate modeling systems at cloud resolving scales using hindcasts of the June 2012 North American derecho. To demonstrate its utility for model intercomparison, the testbed is applied to two models: the regionally‐refined Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) at 6.5, 3.25 and 1.625 km grid spacing and the Weather Research and Forecasting (WRF) model with 3.2 and 1.6 km grid spacing. We find the simulation results to be highly sensitive to the initial conditions (ICs), initialization time, and model configurations, with ICs from the Rapid Refresh producing the best simulation. Significant improvement is identified in both models as horizontal grid spacing is refined. While a propagation delay of approximately 2 hr is found in both models, SCREAM at 1.625 km simulates the observed bow echo structure of the derecho well and predicts strong surface gusts that exceed 30 m/s. In comparison, WRF has difficulty producing surface wind over 25 m/s, with wind gusts in WRF 42%–46% lower than in SCREAM. However, WRF has a lower bias in simulating cloud top temperature and extent, but overestimates precipitation intensity. Both models reproduce the observed outgoing longwave radiation spatial patterns well (Pearson correlation >0.88), but, compared with NEXRAD observations, simulate generally larger areas of composite radar reflectivity >40 dBZ and underestimate the precipitating area by ∼47%.

2012 North American derecho↗