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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

The Impact of QuikScat on Weather Analysis and Forecasting

Scatterometer observations of the ocean surface wind speed and direction improve the depiction and prediction of storms at sea. These data are especially valuable where observations are otherwise sparse, mostly in the Southern Hemisphere and tropics, but also on occasion in the North Atlantic and North Pacific The SeaWinds scatterometer on the QuikScat satellite was launched in June 1999 and it represents a dramatic departure in design from the other scatterometer instruments launched during the past decade (ERS-1,2 and NSCAT). More details on the SeaWinds instrument can be found in Atlas et al. (2001) and Bloom et al. (1999). This presentation shows the influence of QuikScat data in data assimilation systems both from the NASA Data Assimilation Office (GEOS-3) and from NCEP (GDAS).

Atlas, Robert↗
NASA NTRS1996

Responses of the Tropical Pacific to Wind Forcing as Observed by Spaceborne Sensors and Simulated by an Ocean General Circulation Model

In this study, satellite observations, in situ measurements, and model simulations are combined to assess the oceanic response to surface wind forcing in the equatorial Pacific. The surface wind fields derived from observations by the spaceborne special sensor microwave imager (SSM/I) and from the operational products of the European Centre for Medium-Range Weather Forecasts (ECMWF) are compared. When SSM/I winds are used to force a primitive-equation ocean general circulation model (OGCM), they produce 3 C more surface cooling than ECMWF winds for the eastern equatorial Pacific during the cool phase of an El Nino-Southern Oscillation event. The stronger cooling by SSM/I winds is in good agreement with measurements at the moored buoys and observations by the advanced very high resolution radiometer, indicating that SSM/I winds are superior to ECMWF winds in forcing the tropical ocean. In comparison with measurements from buoys, tide gauges, and the Geosat altimeter, the OGCM simulates the temporal variations of temperature, steric, and sea level changes with reasonable realism when forced with the satellite winds. There are discrepancies between model simulations and observations that are common to both wind forcing fields, one of which is the simulation of zonal currents; they could be attributed to model deficiencies. By examining model simulations under two winds, vertical heat advection and uplifting of the thermocline are found to be the dominant factors in the anomalous cooling of the ocean mixed layer.

Liu, W. Timothy↗
DOE OSTI2011

Mesoscale Simulations of a Wind Ramping Event for Wind Energy Prediction

Ramping events, or rapid changes of wind speed and wind direction over a short period of time, present challenges to power grid operators in regions with significant penetrations of wind energy in the power grid portfolio. Improved predictions of wind power availability require adequate predictions of the timing of ramping events. For the ramping event investigated here, the Weather Research and Forecasting (WRF) model was run at three horizontal resolutions in 'mesoscale' mode: 8100m, 2700m, and 900m. Two Planetary Boundary Layer (PBL) schemes, the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) schemes, were run at each resolution as well. Simulations were not 'tuned' with nuanced choices of vertical resolution or tuning parameters so that these simulations may be considered 'out-of-the-box' tests of a numerical weather prediction code. Simulations are compared with sodar observations during a wind ramping event at a 'West Coast North America' wind farm. Despite differences in the boundary-layer schemes, no significant differences were observed in the abilities of the schemes to capture the timing of the ramping event. As collaborators have identified, the boundary conditions of these simulations probably dominate the physics of the simulations. They suggest that future investigations into characterization of ramping events employ ensembles of simulations, and that the ensembles include variations of boundary conditions. Furthermore, the failure of these simulations to capture not only the timing of the ramping event but the shape of the wind profile during the ramping event (regardless of its timing) indicates that the set-up and execution of such simulations for wind power forecasting requires skill and tuning of the simulations for a specific site.

17 WIND ENERGY↗
DOE OSTI2022

Storm DEPART(Damage Estimate Prediction And Recovery Tool)

Damage prediction, materials needed, and resource allocation modeling capability in order to support pre-incident planning and preparation by predicting damage to the power generation capacity, transmission grids, distribution networks, and communications assets. The capabilities will be developed by multiple factors to include wind bands, storm surge, and flooding forecasts to participant’s assets which will result in a report of predicted damages. Additional factors to include available participants infrastructure data to include class, age, construction, location, wind rating, and additional information not in the public domain. Based on predicted damages, the output will be a bill of materials (BOM) to support short-term recovery operations. The extensiveness and level of detail for this BOM will depend on the replacement configuration specifications provided for each individual participant asset. Any limiting factors for the model will be applied related supply chain and resource constraints.

Klett, Mary↗
DOE OSTI2017

2016 Wind Technologies Market Report

The U.S. Department of Energy (DOE)’s Wind Technologies Market Report provides an annual overview of trends in the U.S. wind power market. You can find the report, a presentation, and a data file on the Files tab, below. Additionally, several data visualizations are available in the Data Visualizations tab. Highlights of this year’s report include: -Wind power additions continued at a rapid clip in 2016: $13 billion was invested in new wind power plants in 2016. In 2016, wind energy contributed 5.6% of the nation’s electricity supply, more than 10% of total electricity generation in fourteen states, and 29% to 37% in three of those states—Iowa, South Dakota, and Kansas. -Bigger turbines are enhancing wind project performance: Increased blade lengths, in particular, have dramatically increased wind project capacity factors, one measure of project performance. For example, the average 2016 capacity factor among projects built in 2014 and 2015 was 42.6%, compared to an average of 32.1% among projects built from 2004 to 2011 and 25.4% among projects built from 1998 to 2001. -Low wind turbine pricing continues to push down installed project costs: Wind turbine prices have fallen from their highs in 2008, to $800–$1,100/kW. Overall, the average installed cost of wind projects in 2016 was $1,590/kW, down $780/kW from the peak in 2009 and 2010. -Wind energy prices remain low: After topping out at nearly 7¢/kWh for power purchase agreements (PPAs) executed in 2009, the national average price of wind PPAs has dropped to around 2¢/kWh—though this nationwide average is dominated by projects that hail from the lowest-priced Interior region of the country (such as Texas, Iowa, Oklahoma). These prices, which are possible in part due to federal tax support, compare favorably to the projected future fuel costs of gas-fired generation. -The supply chain continued to adjust to swings in domestic demand for wind equipment: Wind sector employment reached a new high of more than 101,000 full-time workers at the end of 2016. For wind projects recently installed in the U.S., domestically manufactured content is highest for nacelle assembly (>90%), towers (65-80%), and blades and hubs (50-70%), but is much lower (<20%) for most components internal to the turbine. -Continued strong growth in wind capacity is anticipated in the near term: With federal tax incentives still available, though declining, various forecasts for the domestic market show expected wind power capacity additions averaging more than 9,000 MW/year from 2017 to 2020.

17 WIND ENERGY↗
NASA NTRS1978

A study of the atmospheric energetics of a six-layer operational forecast model

Verification data for twice-daily analyses of horizontal wind and temperature are compared with 00, 12, 24, 36, 60, and 84 hour forecasts prepared for winter 1975-76 from a six-layer operational forecast model; the comparison focuses on certain energy components in the forecast fields. Significant losses (15 to 20%) of zonal available potential energy and zonal kinetic energy appear beyond the 36-hour forecasts; the zonal kinetic energy loss is associated with a large increase in this parameter during the first 12-hour forecast period, due to a downward and northward movement of the mean jet-stream core. In addition, energy losses in the eddy potential and kinetic energy components are noted in the initialization procedure.

Hauser, R. K.↗
DOE OSTI2022

Uncertainty-Informed Operation Coordination in a Water-Energy Nexus

The widespread deployment of smart heterogeneous technologies and the growing complexity in our modern society calls for effective coordination of the interdependent lifeline networks. In particular, operation coordination of electric power and water infrastructures is urgently needed as the water system is one of the most energy-intensive networks, an interruption in which may quickly evolve into a dramatic societal concern. This paper develops a novel analytic for uncertainty-aware day-ahead operation optimization of the interconnected power and water systems (PaWS). Joint probabilistic constraint (JPC) programming is employed to capture the uncertainties in wind resources and water demand forecasts. The proposed integrated stochastic model is presented as a non-linear non-convex optimization problem, where the non-linear hydraulic constraints in the water network are linearized using piece-wise linearization technique, and the non-convexity is efficiently tackled with a solution methodology to convert the proposed model with JPCs to a tractable mixed-integer linear programming (MILP) formulation that can be quickly solved to optimality. Here, the suggested framework is applied to a 15-node commercial-scale water network jointly operated with a power transmission system using a modified IEEE 57-bus test system. The numerical results demonstrate the of the proposed stochastic framework, resulting in cost reduction (13% on average when compared to the traditional setting) and energy saving of the integrated model under different realizations of uncertain renewable energy sources (RESs) and water demand scenarios. Additionally, the scalability of the proposed model is tested on a modified IEEE 118-bus test system connected to five water networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1977

Applications of Seasat to the offshore oil, gas and mining industries

The NASA satellite Seasat-A (to be launched in 1978) has applications to the offshore oil, gas, and mining industries including: (1) improvements in weather and wave forecasting, (2) studies of past wind and wave statistics for planning design requirements, and (3) monitoring ice formation, breakup, and movement in arctic regions. The primary geographic areas which will be monitored by Seasat-A include: the Beaufort Sea, the Labrador Sea, the Gulf of Mexico, the U.S. east coast, West Africa, Equatorial East Pacific, the Gulf of Alaska, and the North Sea. Seasat-A instrumentation used in ocean monitoring consists of a radar altimeter, a radar scatterometer, a synthetic aperture radar, a microwave radiometer, and a visible and infrared radiometer. The future outlook of the Seasat program is planned in three phases: measurement feasibility demonstration (1978-1980), data accessibility/utility demonstration (1980-1983), and operational system demonstration (1983-1985).

Mourad, A. G.↗
NASA NTRS1985

Hurricane Debby - An illustration of the complementary nature of VAS soundings and cloud and water vapor motion winds

The utility of VISSR Atmospheric Sounder (VAS) temperature and moisture soundings and cloud and water vapor motion winds in defining a storm and its surroundings at subsynoptic scales has been examined using a numerical analysis and prognosis system. It is shown that the VAS temperature and moisture data, which specify temperature and moisture well in cloud-free areas, are complemented by cloud and water vapor motion data generated in the cloudy areas. The cloud and water vapor 'winds' provide thermal gradient information for interpolating the soundings across cloudy regions. The loss of analysis integrity due to the reduction of VAS sounding density in the cloudy regions associated with synoptic activity is ameliorated by using cloud and water vapor motion winds. The improvement in numerical forecasts resulting from the addition of these data to the numerical analysis is recorded.

Le Marshall, J. F.↗
NASA NTRS1989

Chemistry and transport in a three-dimensional stratospheric model - Chlorine species during a simulated stratospheric warming

The distributions in the stratosphere of a variety of chemical species were calculated for a 6-day period during the February 1979 stratospheric major warming, using winds derived from a spectral forecast model which included O(x), NO(x), HO(x), and ClO(x) chemistries as well as longitudinally varying reaction rate coefficients and photolysis rates for these molecules. The results obtained indicate a particular importance of chemistry and transport for the Cl-containing species ClO, ClONO2, HCl, and HOCl. Dynamical effects dominate the variability of HCl, while diurnal effects dominate that of ClONO2 and ClO. The effects of strong planetary wave activity may be seen in terms of large longitudinal variability of the total HCl and ClONO columns in the stratosphere; in the middle and high northern latitudes, it is sufficiently large to exceed the diurnal variability of the column.

Kaye, Jack A.↗
NASA NTRS1989

Optimized variational analysis scheme of single Doppler radar wind data

A computer scheme for extracting singularities has been developed and applied to single Doppler radar wind data. The scheme is planned for use in real-time wind and singularity analysis and forecasting. The method, known as Doppler Operational Variational Extraction of Singularities is outlined, focusing on the principle of local symmetry. Results are presented from the application of the scheme to a storm-generated gust front in Oklahoma on May 28, 1987.

Sasaki, Yoshi K.↗
NASA NTRS1992

Hurricane risk assessment to rollback or ride out a cost versus loss decision making approach

The potential exists that a hurricane striking the Kennedy Space Center while a Space Shuttle is on the pad. Winds in excess of 74.5 knots could cause the failure of the holddown bolts bringing about the catastrophic loss of the entire vehicle. Current plans call for the rollback of the shuttle when winds of that magnitude are forecast to strike the center. As this is costly, a new objective method for making rollback/rideout decisions based upon Bayesian Analysis and economic cost versus loss is presented.

Wohlman, Richard A.↗
NASA NTRS1993

The gust-front detection and wind-shift algorithms for the Terminal Doppler Weather Radar system

The Federal Aviation Administration's (FAA) Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.

Hermes, Laurie G.↗
NASA NTRS1994

Forecast skill of a high-resolution real-time mesoscale model designed for weather support of operations at Kennedy Space Center and Cape Canaveral Air Station

NASA funded Mesoscale Environmental Simulations and Operations (MESO), Inc. to develop a version of the Mesoscale Atmospheric Simulation System (MASS). The model has been modified specifically for short-range forecasting in the vicinity of KSC/CCAS. To accomplish this, the model domain has been limited to increase the number of horizontal grid points (and therefore grid resolution) and the model' s treatment of precipitation, radiation, and surface hydrology physics has been enhanced to predict convection forced by local variations in surface heat, moisture fluxes, and cloud shading. The objective of this paper is to (1) provide an overview of MASS including the real-time initialization and configuration for running the data pre-processor and model, and (2) to summarize the preliminary evaluation of the model's forecasts of temperature, moisture, and wind at selected rawinsonde station locations during February 1994 and July 1994. MASS is a hydrostatic, three-dimensional modeling system which includes schemes to represent planetary boundary layer processes, surface energy and moisture budgets, free atmospheric long and short wave radiation, cloud microphysics, and sub-grid scale moist convection.

Taylor, Gregory E.↗
NASA NTRS2008

Will We Soon Have a Geostationary Microwave Sounder and What Can We Do with It?

This slide presentation reviews the Geostationary Microwave Sounder (GEO/MW). GEO/MW applications include weather forecasting, hurricane diagnostics, rain, tropospheric wind profiling, and climate research. The presentation also includes information on prototype development, system tests, the notational PATH mission, and data products.

hurricanes↗
NASA NTRS2018

Modeling Key Predictors of Airport Runway Configurations Using Learning Algorithms

Advanced traffic flow management automation will need accurate predictions of airport runway configurations. Terminal area weather and traffic demand are generally considered to be the most significant factors in predicting runway configuration. Weather information is forecasted across multiple features, including wind direction, wind speed, gusts, cloud ceilings, visibility, temperature, and precipitation, among many others. We use machine learning techniques on historical weather and runway data to determine weather features that correlate well with runway configurations. We analyze the predictive capability of weather features using different learning models trained on data from four major U.S. airports: Atlanta (ATL), Washington – Dulles (IAD), New York – Kennedy (JFK), and San Francisco (SFO). Wind direction alone is strongly correlated with runway configurations above all other examined factors, as expected. This correlation is the most significant component of the ~80% prediction accuracy in selecting between the two most frequently used runway configurations. However, individual airports show variations on how well the runway configuration decisions correlate with wind direction. While wind direction was identified as the most significant indicator of configuration decisions in ATL, IAD, and JFK, it did not emerge as such at SFO. Traffic demand was not found to be a strong factor in predicting runway configurations at any of the airports analyzed. In rare instances, when high demand cannot be accommodated within the current configuration, temporary changes are likely to be attributable to demand. However, these occurrences are so limited in number that their overall effect is not sufficient to consider traffic demand as a major indicator of runway configuration at the airports analyzed.

Bilimoria, Karl D.↗
DOE OSTI2015

Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual model has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗