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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Wake steering optimization under uncertainty

Turbines in wind power plants experience significant power losses when wakes from upstream turbines affect the energy production of downstream turbines. A promising plant-level control strategy to reduce these losses is wake steering, where upstream turbines are yawed to direct wakes away from downstream turbines. However, there are significant uncertainties in many aspects of the wake steering problem. For example, infield sensors do not give perfect information, and inflow to the plant is complex and difficult to forecast with available information, even over short time periods. Here, we formulate and solve an optimization under uncertainty (OUU) problem for determining optimal plant-level wake steering strategies in the presence of independent uncertainties in the direction, speed, turbulence intensity, and shear of the incoming wind, as well as in turbine yaw positions. The OUU wake steering strategy is first examined for a two-turbine test case to explore the impacts of different types of inflow uncertainties, and it is then demonstrated for a more realistic 11-turbine wind power plant. Of the sources of uncertainty considered, we find that wake steering strategies are most sensitive to uncertainties in the wind speed and direction. When maximizing expected power production, the OUU strategy also tends to favor smaller yaw angles, which have been shown in previous work to reduce turbine loading. Ultimately, the plant-level wake steering strategy formulated using an OUU approach yields 0.48?% more expected annual energy production for the 11-turbine wind plant than a strategy that neglects uncertainty when considering stochastic inputs. Thus, not only does the present OUU strategy produce more power in realistic conditions, but it also reduces risk by prescribing strategies that call for less extreme yaw angles.

17 WIND ENERGY↗
NASA NTRS1979

Simulation studies of the application of SEASAT data in weather and state of sea forecasting models

The design and analysis of SEASAT simulation studies in which the error structure of conventional analyses and forecasts is modeled realistically are presented. The development and computer implementation of a global spectral ocean wave model is described. The design of algorithms for the assimilation of theoretical wind data into computers and for the utilization of real wind data and wave height data in a coupled computer system are presented.

Cardone, V. J.↗
NASA NTRS2007

Observational Evidence of a Hemispheric-wide Ice-ocean Albedo Feedback Effect on Antarctic Sea-ice Decay

The effect of ice-ocean albedo feedback (a kind of ice-albedo feedback) on sea-ice decay is demonstrated over the Antarctic sea-ice zone from an analysis of satellite-derived hemispheric sea ice concentration and European Centre for Medium-Range Weather Forecasts (ERA-40) atmospheric data for the period 1979-2001. Sea ice concentration in December (time of most active melt) correlates better with the meridional component of the wind-forced ice drift (MID) in November (beginning of the melt season) than the MID in December. This 1 month lagged correlation is observed in most of the Antarctic sea-ice covered ocean. Daily time series of ice , concentration show that the ice concentration anomaly increases toward the time of maximum sea-ice melt. These findings can be explained by the following positive feedback effect: once ice concentration decreases (increases) at the beginning of the melt season, solar heating of the upper ocean through the increased (decreased) open water fraction is enhanced (reduced), leading to (suppressing) a further decrease in ice concentration by the oceanic heat. Results obtained fi-om a simple ice-ocean coupled model also support our interpretation of the observational results. This positive feedback mechanism explains in part the large interannual variability of the sea-ice cover in summer.

Nihashi, Sohey↗
NASA NTRS2012

The Influence of Pickup Protons, from Interstellar Neutral Hydrogen, on the Propagation of Interplanetary Shocks from the Halloween 2003 Solar Events to ACE and Ulysses: A 3-D MHD Modeling Study

We describe our 3-D, time ]dependent, MHD solar wind model that we recently modified to include the physics of pickup protons from interstellar neutral hydrogen. The model has a time-dependent lower boundary condition, at 0.1 AU, that is driven by source surface map files through an empirical interface module. We describe the empirical interface and its parameter tuning to maximize model agreement with background (quiet) solar wind observations at ACE. We then give results of a simulation study of the famous Halloween 2003 series of solar events. We began with shock inputs from the Fearless Forecast real ]time shock arrival prediction study, and then we iteratively adjusted input shock speeds to obtain agreement between observed and simulated shock arrival times at ACE. We then extended the model grid to 5.5 AU and compared those simulation results with Ulysses observations at 5.2 AU. Next we undertook the more difficult tuning of shock speeds and locations to get matching shock arrival times at both ACE and Ulysses. Then we ran this last case again with neutral hydrogen density set to zero, to identify the effect of pickup ions. We show that the speed of interplanetary shocks propagating from the Sun to Ulysses is reduced by the effects of pickup protons. We plan to make further improvements to the model as we continue our benchmarking process to 10 AU, comparing our results with Cassini observations, and eventually on to 100 AU, comparing our results with Voyager 1 and 2 observations.

Detman, T. R.↗
DOE OSTI2022

How Generalizable is a Machine-Learning Approach for Modeling Hub-Height Turbulence Intensity?

Hub-height turbulence intensity is essential for a variety of wind energy applications. However, simulating it is a challenging task. Simple analytical models have been proposed in the literature, but they all come with significant limitations. Even state-of-the-art numerical weather prediction models, such as the Weather Research and Forecasting model, currently struggle to predict hub-height turbulence intensity. Here, we propose a machine-learning-based approach to predict hub-height turbulence intensity from other hub-height and ground-level atmospheric measurements, using observations from the Perdigao field campaign and the Southern Great Plains atmospheric observatory. We consider a random forest regression model, which we validate first at the site used for training and then under a more robust round-robin approach, and compare its performance to a multivariate linear regression. The random forest successfully outperforms the linear regression in modeling hub-height turbulence intensity, with a normalized root-mean-square error as low as 0.014 when using 30-minute average data. In order to achieve such low root-mean-square error values, the knowledge of hub-height turbulence kinetic energy (which can instead be modeled in the Weather Research and Forecasting model) is needed. Interestingly, we find that the performance of the random forest generalizes well when considering a round-robin validation (i.e., when the algorithm is trained at one site such as Perdigao or Southern Great Plains) and then applied to model hub-height turbulence intensity at the other location.

17 WIND ENERGY↗
DOE OSTI2025

The Remarkable 2024 North Atlantic Mid‐Season Hurricane Lull

Abstract The 2024 North Atlantic (hereafter Atlantic) hurricane season started quickly, with the earliest Category 5 on record (Beryl) and three hurricanes forming through 14 August. Following Ernesto's dissipation on 20 August, the Atlantic hurricane season became extremely quiet during the climatological peak of hurricane season, with only one Category 2 hurricane (Francine) and one tropical storm through 23 September. Several environmental factors likely contributed to this unexpected, prolonged lull. During mid‐to‐late August, subseasonal conditions were broadly favorable for Atlantic hurricanes, but a northward shift in African easterly wave emergence latitude yielded fewer tropical cyclone seed disturbances that also traversed unfavorably cool ocean water. During early‐to‐mid September, subseasonal variability driven by the Madden‐Julian oscillation was less conducive to hurricane activity, with several bouts of increased vertical wind shear across the central Atlantic. Throughout most of the lull, the tropical Atlantic was anomalously dry and subsident, suppressing hurricane formation chances. Plain Language Summary The 2024 North Atlantic (hereafter Atlantic) hurricane season was anticipated to be extremely active, with seasonal forecasts calling for a potentially historic season. Following a busy start including the earliest Category 5 Atlantic hurricane on record (Beryl), the season became very quiet between 20 August–23 September, with only one Category 2 hurricane (Francine) and one tropical storm forming. Following the lull, the Atlantic became extremely busy again, with seven hurricanes forming from 25 September through the end of the season–the most on record for this period. This paper focuses on the surprising lull and attributes it to several different factors, including a late‐August northward shift in African easterly wave tracks (organized thunderstorm complexes spanning thousands of kilometers that often serve as Atlantic hurricane seeds). This northward shift brought these systems out over colder water and into a drier airmass, suppressing their hurricane formation chances. During the first 3 weeks of September, a large‐scale tropical phenomenon known as the Madden‐Julian oscillation, resulted in increased sinking motion, drier mid‐levels and increased vertical wind shear–all of which typically reduce Atlantic hurricane activity. Overall, the lull demonstrates how seed disturbances and other environmental factors can strongly modulate aggregate seasonal tropical cyclone activity. Key Points Following an active start, the 2024 Atlantic hurricane was quiet during the climatological peak with only 1 tropical storm and 1 hurricane The lull was not anticipated by seasonal forecasting agencies, which called for an extremely active 2024 Atlantic hurricane season Factors reducing storm count included a northward shift in African easterly waves, broad‐scale subsidence, and reduced mid‐level moisture

Klotzbach, P J↗
DOE OSTI2019

A Probability-based Model for Cost-effective Integration of Renewables into the Electricity Grid (Final Technical Report)

Funded by the U.S. Department of Energy during 2017-2019, the resource adequacy evaluation and production costing tool, called MATPLAN (MATlab and probability-based PLANning), was developed. MATPLAN can take into account the variable nature of renewable energy sources (both solar PV and wind farms), rather than considering deterministic data as in the current practice. It combines both probabilistic and optimization techniques to allow the determination of optimal system expansion policy and perform effective load carrying capacity (ELCC) analysis of a system with high renewable penetration. This is in contrast to the current practice that treats these variable sources as negative loads. This tool expects to benefit system planners by enabling them to consider renewable energy sources as options for their expansion plans. System operators can use MATPLAN to calculate the capacity credit for each solar/wind farm using probabilistic forecasts, thus enabling quantification of the operating reserve requirements to cope with uncertainty and variability of solar/wind output committed in the market.

14 SOLAR ENERGY↗
DOE OSTI2018

Improving BA Control Performance Through Advanced Regulation Requirements Prediction

The paper presents a comprehensive approach to predict balancing authority (BA) regulation requirements in order to improve BAs control performance. The proposed probabilistic approach takes into account multiple uncertain and time dependent factors affecting the system balance (e.g., wind and solar generation, electrical loads). A set of methods to predict the regulation has been developed: (1) probabilistic analysis of regulation requirements with respect to time of the day, (2) linear or nonlinear regression models linking regulation requirements to different influencing factors, (3) adopting time series forecasting techniques (e.g., autoregressive integrated moving average (ARIMA)) to account for temporal continuity and auto-correlation in the regulation requirements data. Proposed methodology has been tested and validated using actual California Independent System Operator (ISO) data.

Solar Generation, Wind Generation, Area Control Er↗
DOE OSTI2022

Understanding Low Level Jets in the US Atlantic Offshore

Low level jets (LLJs) in the atmosphere exhibit a local windspeed maximum in the boundary layer, with positive shear beneath the jet and negative shear above the jet. Wind turbines tend to experience increased loads with varying wake recovery characteristics in the presence of an LLJ, therefore understanding the mechanism and impact of LLJs is crucial to wind energy development. The US Mid-Atlantic offshore region is a huge potential wind energy resource, yet LLJs in this area are poorly understood. In particular, the coastal offshore environment does not exhibit the same diurnal cycle that leads to strong LLJs in the well-characterized Great Plains region. In this study, we use the Weather Research and Forecasting model (WRF) plus lidar buoy data to identify case studies for LLJ events in 2020 in the New York Bight. A reduced order model is presented to explain the onset of these events based on the competing effects of baroclinicity and eddy diffusivity. Finally, using the macro-scale WRF, we drive a micro-scale large eddy simulation (LES) to generate a more detailed characterization of the Marine Boundary Layer during an LLJ. Gaining a better understanding of LLJs and their impacts on offshore wind in the mid-Atlantic is crucial for a transition toward renewable energy.

atmospheric boundary layer↗
DOE OSTI2020

Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model

Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Building and Running TDAAPS Models: Nudged WRF Hindcasts

This work is a follow-on guide to running the Weather Research and Forecasting (WRF) model from Aur et al, (2018), Building and Running 1 DAAPS Models: IFRF Postdictions. This guide details running WRF in a nudged configuration, where the u and v wind components, temperature, and moisture within a specified spatial and temporal window, are adjusted towards the observations, radiosonde observations in this case, using WRF's observation nudging technique. The primary modification to this methodology from Aur et al. (2018), is the use of the OBSGRID program to generate the nudging files and the updates to the namelist.input file. These steps, combined with those outlined in Aur et al. (2018), will generate a nudged WRF hindcast (or postdiction) simulation.

58 GEOSCIENCES↗
DOE OSTI2023

Balancing renewable energy and river resources by moving from individual assessments of hydropower projects to energy system planning

As governments and non-state actors strive to minimize global warming, a primary strategy is the decarbonization of power systems which will require a massive increase in renewable electricity generation. Leading energy agencies forecast a doubling of global hydropower capacity as part of that necessary expansion of renewables. While hydropower provides generally low-carbon generation and can integrate variable renewables, such as wind and solar, into electrical grids, hydropower dams are one of the primary reasons that only one-third of the world’s major rivers remain free-flowing. This loss of free-flowing rivers has contributed to dramatic declines of migratory fish and sediment delivery to agriculturally productive deltas. Further, the reservoirs behind dams have displaced tens of millions of people. Thus, hydropower challenges the world’s efforts to meet climate targets while simultaneously achieving other Sustainable Development Goals. In this paper, we explore strategies to achieve the needed renewable energy expansion while sustaining the diverse social and environmental benefits of rivers. These strategies can be implemented at scales ranging from the individual project (environmental flows, fish passage and other site-level mitigation) to hydropower cascades to river basins and regional electrical power systems. While we review evidence that project-level management and mitigation can reduce environmental and social costs, we posit that the most effective scale for finding balanced solutions occurs at the scale of power systems. We further hypothesize that the pursuit of solutions at the system scale can also provide benefits for investors, developers and governments; evidence of benefits to these actors will be necessary for achieving broad uptake of the approaches described in this paper. We test this hypothesis through cases from Chile and Uganda that demonstrate the potential for system-scale power planning to allow countries to meet low-carbon energy targets with power systems that avoid damming high priority rivers (e.g., those that would cause conflicts with other social and environmental benefits) for a similar system cost as status quo approaches. We also show that, through reduction of risk and potential conflict, strategic planning of hydropower site selection can improve financial performance for investors and developers, with a case study from Colombia.

Opperman, Jeffrey J.↗
DOE OSTI2017

The plasma depletion layer beyond the heliopause: evidence, implications, and predictions for Voyager 2 and new horizons

A plasma depletion layer (PDL) is predicted beyond the heliopause, analogous to the PDLs observed sunwards of planetary magnetopauses: draping of interstellar medium (ISM) magnetic field lines over the heliopause should increase the magnetic field strength and, perpendicular ion temperature, cause density depletions by allowing plasma ions (and electrons) with large parallel temperatures to escape along B, and increase the temperature anisotropy until limited by wave instabilities. Published Voyager 1 magnetometer and plasma wave data provide strong evidence for the coupled magnetic amplification (≈30%) and density depletion (≈50%) expected for a weak PDL. The predicted reduction in parallel temperature is ≈50%. The locations on the sky of the PDL and the points on the heliopause of maximum magnetic draping and total pressure are predicted using the ISM magnetic field direction obtained from the Interstellar Boundary Explorer (IBEX) ribbon. The IBEX ribbon overlies the former, as expected, while the latter lies within the ridge of maximum, non-ribbon, globally distributed flux. The PDL should be strongest along the ISM field line passing through these points and the Sun–ISM velocity vector. Based on their trajectories, Voyager 2 and New Horizons should observe a much stronger PDL (stronger magnetic amplification, density depletion, and changes in temperature) than Voyager 1. Finally, the reduced cosmic ray fluxes observed near 90° pitchangle by Voyager 1 beyond the heliopause appear qualitatively consistent with wave–particle interactions transferring perpendicular particle energy to parallel energy where the PDL is strong, followed by magnetic focusing as particles propagate into weaker magnetic field regions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2002

Solar Wind and Interplanetary Disturbances

This report describes basic knowledge of solar wind and interplanetary disturbances first, and then it discussed recent results from new observations and theories. At the end it presented research activities to predict interplanetary disturbances for space weather forecast.

Watari, Shinichi↗
NASA NTRS2015

The Unusual Evolution of Hurricane Arthur 2014

Hurricane Arthur (2014) was an early season hurricane that had its roots in a convective complex in the Southern Plains of the U.S. As the complex moved into northern Texas, a Mesoscale Convective Vortex (MCV) formed and drifted towards the east of the southern U.S. for a few days before emerging over the southwest Atlantic near South Carolina. The MCV drifted south and slowly acquired tropical characteristics, eventually becoming a Category 2 hurricane that would affect much of eastern North Carolina prior to the 4th of July holiday weekend. Arthur continued up the coast, brushing portions of southeast New England and merged with an upper-level low, completing a full tropical to extratropical-transition in the process, producing damaging wind gusts in portions of the Canadian Maritimes. As part of the GOES-R and JPSS Satellite Proving Grounds, multiple proxy and operational products were available to analyze and forecast this complex evolution. The Storm Prediction Center had products available to monitor the initial severe thunderstorm aspect, while the National Hurricane Center and Ocean Prediction Center were able to monitor the tropical and extratropical transition of Arthur using various convective and red, green, blue (RGB) products that have been introduced in recent years. This paper will discuss Arthur's evolution through the eyes of the various Satellite Proving Ground demonstrations.

Folmer, Michael↗
NASA NTRS2017

Earth Global Reference Atmospheric Model (Earth-GRAM) GRAM Virtual Meeting

What is Earth-GRAM? Provide monthly mean and standard deviation for any point in atmosphere; Monthly, Geographic, and Altitude Variation. Earth-GRAM is a C++ software package; Currently distributed as Earth-GRAM 2016. Atmospheric variables included: pressure, density, temperature, horizontal and vertical winds, speed of sound, and atmospheric constituents. Used by engineering community because of ability to create dispersions inatmosphere at a rapid runtime; Often embedded in trajectory simulation software. Not a forecast model. Does not readily capture localized atmospheric effects.

White, Patrick↗
DOE OSTI2020

Updraft and Downdraft Core Size and Intensity as Revealed by Radar Wind Profilers: MCS Observations and Idealized Model Comparisons

This study explores the updraft and downdraft properties of mature stage mesoscale convective systems (MCSs) in terms of draft core width, shape, intensity, and mass flux characteristics. The observations use extended radar wind profiler (RWP) and surveillance radar datasets from the U.S. Department of Energy Atmospheric Radiation Measurement program for midlatitude (Oklahoma, USA) and tropical (Amazon, Brazil) sites. MCS drafts behave qualitatively similar to previous aircraft and RWP cloud summaries. The Oklahoma MCSs indicate larger and more intense convective up- and downdraft cores, and greater mass flux than Amazon MCS counterparts. However, similar size-intensity relationships and draft vertical profile behaviors are observed for both regions. Additional similarities include weak positive correlations between core intensity and core width (correlation coefficient r ~ 0.5), and increases in draft intensity with altitude. A model-observational intercomparison for draft properties (core width, intensity, mass flux) is also performed to illustrate the potential usefulness of statistical observed draft characterizations. Idealized simulations with the Weather Research and Forecasting model aligned with midlatitude MCS conditions are performed at model grid spacings (?x) that range from 4 km to 250 m. It is shown that the simulations performed at ?x = 250 m at similar mature MCS lifecycle stages are those that exhibit draft intensity, width, mass flux, and shape parameter performances best matching with observed properties.

radar, arm, wind profiler, goamazon↗