SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The solar wind is a direct manifestation of the coronal heating processes which continue to elude us. For over three decades, observations in interplanetary space have identified two types of wind: a slow component with highly variable physical properties also characterized by speeds typically beow 500 kn/s, and a much less variable fast wind flowing on average at 750 km/s1.
Sea surface turbulent heat flux is one of the key components in global freshwater and energy balances and plays an important role in atmospheric dynamics, thermodynamics and general circulation. This turbulent heat flux is dominantly decided by sea surface latent heat release with some contribution from sensible heat exchange. The flux and its anomaly could significantly affect ocean heat storage and ocean circulation. They are part of and have great impacts on climate variability. Though the turbulent heat flux is extremely important for the climate and weather systems, only very limited ship and buoy observations of the flux are available over open oceans. There are no global, operational, direct measurements of this crucial meteorological variable. Global estimates are, basically, indirectly calculated from bulk turbulent flux parameterization with a combination of satellite column water vapor, sea surface water temperature, and wind speed observations. Critical parameters such as sea surface air temperature and humidity are estimated from empirical relations of theses variables with the water vapor and sea surface water temperature, respectively. Lacking accurate knowledge on surface air temperature and humidity, uncertainties in the parameterization and potential changes in the non-linear turbulent processes with long-term climate variations could cause large errors in estimated long-term turbulent fluxes from the indirect method as shown in current global sea surface turbulent flux datasets. This study uses synergized data of satellite global radiation, precipitation, and other meteorological variable observations to estimate sea surface turbulent heat fluxes. The radiation observations are made by the satellite Clouds and the Earth’s Radiant Energy System (CERES) sensors, while the global precipitation data is from NASA’s satellite Global Precipitation Climatology Project (GPCP). Other data includes satellite sea surface water temperature and wind speed observations. These datasets are obtained from a wide range of space sensors from passive to active instruments and from visible and near infrared to thermal infrared and microwave spectral sounders. One significant feature of these datasets is that they have multi-decades long climate records. Top-of-atmosphere (TOA) radiation and its anomaly represents the net heat energy input to the climate system, and the oceanic precipitation and ocean-land moisture transport can be used to quantify sea surface latent heat release. Based on the synergized datasets and the principle of global water and energy balances, global mean turbulent heat fluxes are estimated. The turbulent heat anomalies for the first two decades of the 21st century are, then, obtained mainly from global CERES radiation and GPCP precipitation anomalies, along with CERES derived ocean-land heat transports. Analysis indicates that the uncertainties in the estimated turbulent flux anomalies may be reduced considerably. The results suggest a strong needs in synchronized and synergized observations of atmospheric radiation, precipitation, and oceanic meteorological variables for long-term climate studies.
A wind-tunnel investigation has been made of the longitudinal aerodynamic characteristics and jet-interference effects of a model of a jet V/STOL variable-sweep fighter airplane that employs four direct-lift engines which swing out from the fuselage and two lift-cruise engines located in the rear part of the fuselage. Data were obtained with two wing areas for various forward speeds and power conditions in the transition speed range. The data are presented without analysis or discussion.
Measurements of the interplanetary magnetic field (IMF) from the ACE (Advanced Composition Explorer), Wind, IMP-8 (Interplanetary Monitoring Platform), and Geotail spacecraft have revealed that the IMF variations are contained in phase planes that are tilted with respect to the propagation direction, resulting in continuously variable changes in propagation times between spacecraft, and therefore, to the Earth. Techniques for using 'minimum variance analysis' have been developed in order to be able to measure the phase front tilt angles, and better predict the actual propagation times from the L1 orbit to the Earth, using only the real-time IMF measurements from one spacecraft. The use of empirical models with the IMF measurements at L1 from ACE (or future satellites) for predicting 'space weather' effects has also been demonstrated.
Site-specific fatigue estimation is an essential part of wind turbine lifetime extension, with various methods depending on data availability. The present study compares probabilistic lifetime extension assessment results for rotor blades with and without load measurements. It also addresses two key questions in such assessments: the applicability of the Frandsen model for estimating waked turbulence under complex and mixed wake conditions and the extrapolation of mid-term data over longer time periods. The case study wind turbine is SWT-2.3-93, located at the edge of the Lillgrund wind farm, situated in the Øresund Strait between Denmark and Sweden. The turbine is extensively instrumented, with 5 years of data available from its supervisory control and data acquisition (SCADA) system. Although the Frandsen turbulence estimates deviate in a different manner from measurements at below- and above-rated mean wind speeds, the model remains a conservative approach for fatigue load prediction and reliability. In the current case study, the site-specific assessment using strain gauge measurements yields a 33 % higher annual fatigue reliability index after 35 years compared to a scenario based on the Frandsen estimation combined with ambient environmental data and a generic aeroelastic model. The results also demonstrate that the sensitivity of fatigue reliability to load uncertainty is negligible when load measurements are used directly but relatively high when relying on the Frandsen model in combination with a generic aeroelastic model. Overall, the high variability of the lifetime extension in different scenarios of data availability and accuracy shows the importance and added value of high-quality measurements combined with wind-farm-level SCADA and a model updated in real time (digital twins).
The acoustic radiation patterns from a 1/15th scale model of the Ames 80- by 120-Ft Wind Tunnel test section and inlet have been measured with a noise source installed in the test section. Data were acquired without airflow in the duct. Sound-absorbent inlet vanes oriented parallel to each other, or splayed with a variable incidence relative to the duct long axis, were evaluated along with duct wall linings. Results show that splayed vans tend to spread the sound to greater angles than those measured with the open inlet. Parallel vanes narrowed the high-frequency radiation pattern. Duct wall linings had a strong effect on acoustic directivity by attenuating wall reflections. Vane insertion loss was measured. Directivity results are compared with existing data from square ducts. Two prediction methods for duct radiation directivity are described: one is an empirical method based on the test data, and the other is a analytical method based on ray acoustics.
Wind plants operate in stochastic environments characterized by complex turbulent flow dynamics and high-dimensional random variables. A key step in uncertainty quantification studies is sensitivity analysis and dimension reduction that can facilitate the development of surrogate models to be used for forward and inverse propagation or optimization under uncertainty. Prior work has shown active subspaces are an effective tool for identifying important directions in the space of stochastic inputs; however, they have only been applied to single-fidelity wind plant models. In this study, we investigate the efficacy of a multi-fidelity active subspace method for analyzing the uncertainty in wind plant power output. The multi-fidelity active subspace estimator offers the promise of increased accuracy in identifying active subspaces as compared to a single-fidelity estimator for the same computational cost, or a reduction in cost for the same accuracy. This makes the study of uncertainty in larger wind plants and with higher fidelity physics tractable. The multi-fidelity active subspace method is applied to gridded and existing wind plant layouts with single and multiple inflow conditions and its performance for surrogate modeling and uncertainty propagation is compared against a single-fidelity active subspace method. This multi-fidelity approach yields substantial computational speedups of 2x - 3.4x across the test cases along with acceptable accuracy in surrogate modeling and computing statistical moments.
The particle size distribution (PSD) of mineral dust has a strong effect on the impacts of dust on climate. However, our understanding of the emitted dust PSD, including its variability and the fraction of super-coarse dust (diameter >10 µm), remains limited. Here, we provide new insights into the size-resolved dust emission process based on a field campaign performed in the Moroccan Sahara in September 2019 in the context of the FRontiers in dust minerAloGical coMposition and its Effects upoN climaTe (FRAGMENT) project. The obtained dust concentration and diffusive flux PSDs show significant dependencies upon the friction velocity (u*), wind direction and type of event (regular events versus haboob events). For instance, the number fraction of sub-micrometre particles increases with u*, along with a large decrease in the mass fraction of super-coarse dust. We identify dry deposition, which is modulated by u* and fetch length, as a potential cause for this PSD variability. Using a resistance model constrained with field observations to estimate the dry deposition flux and thereby also the emitted dust flux, we show that deposition could represent up to ∼90 % of the emission of super-coarse particles (>10 µm) and up to ∼65 % of the emission of particles as small as ∼5 µm in diameter. Importantly, removing the deposition component significantly reduces the variability with u* in the PSD of the emitted dust flux compared with the diffusive flux, particularly for super-coarse dust. The differences between regular and haboob event concentration and diffusive flux PSDs are suspected to result from a smaller and variable dust source fetch during the haboob events, and/or an increased resistance of soil aggregates to fragmentation associated with the observed increase in relative humidity along the haboob outflow. Finally, compared to the invariant emitted dust flux PSD estimated based on brittle fragmentation theory, we obtain a substantially higher proportion of super-micrometre particles in the dust flux. Overall, our results suggest that dry deposition needs to be adequately considered to estimate the emitted PSD, even in studies limited to the fine and coarse size ranges (<10 µm).
In this work, we present multi-epoch optical spectra of the Seyfert 1.9 galaxy Mrk 883. Data were obtained with the Gran Telescopio Canarias and the MEGARA Integral Field Unit mode, archival data from the SDSS-IV MaNGA Survey and the SDSS-I Legacy Survey, and new spectroscopic observations obtained at San Pedro Mártir Observatory. We report the appearance of the broad component of Hβ emission line, showing a maximum FWHM ∼ 5927 ± 481 km s−1 in the MaNGA spectra, finding evidence for a change from Seyfert 1.9 (23 June 2003) to Seyfert 1.8 (18 May 2018). The observed changing-look variation from Sy1.9 to Sy1.8 has a timescale Δt ∼15 y. In addition, we observe profile and flux broad emission line variability from 2018 to 2023, and a wind component in [OIII]5007 Å, with a maximum FWHM = 1758 ± 178 km s−1, detected on 15 April 2023. In all epochs, variability of the broad lines was found to be disconnected from the optical continuum emission, which shows little or no variations. These results suggest that an ionized-driven wind in the polar direction could be a possible scenario to explain the observed changing-look variations.
Data from an array of bottom pressure gauges and a string of current meters in the vicinity of 47 deg N, 139 deg W, are used to examine the deep-ocean variability forced by ocean surface wind stress curl from August 1987 to June 1988. Bottom geostrophic currents are computed from the pressure gauge array, and these correspond well to the long-period directly measured currents at 3000 m. The supratidal-period bottom pressure variations are coherent at 95% confidence with the wind stress curl in period bands of 3-4 days and 15-60 days but removed in distances of 400 and 700 km to the northwest and the southeast, respectively. A linear, two-layer hydrodynamic model is used to examine the theoretical forcing produced by random-phased surface wind fields for the conditions of the eastern north Pacific and the 15- to 60-day-period observed response is reproduced credibly. To model 3- to 15-day variations, more realistic models are required.
We propose to review measurements of the solar wind proton and alpha particle flow velocities and densities made since launch with the WIND SWE instrument. The SWE Faraday cup ion sensors are designed to be able to determine accurately flow vector directions, and thus can be used to detect proton-alpha particle differential flow. Instances of differential flow, and the solar wind features with which they are associated will be discussed. Additionally, the variability of the percentage of alpha particles as a fraction of the total solar wind ion density will be presented.
Between 2012 July and 2013 February, NuSTAR and XMM-Newton performed four long-look joint observations of the type 1.8 Seyfert, NGC 1365. We have analyzed the variable absorption seen in these observations in order to characterize the geometry of the absorbing material. Two of the observations caught NGC 1365 in an unusually low absorption state, revealing complexity in the multi-layer absorber that had previously been hidden. We find the need for three distinct zones of neutral absorption in addition to the two zones of ionized absorption and the Compton-thick torus previously seen in this source. The most prominent absorber is likely associated with broad-line region clouds with column densities of around approximately 10 (sup 23) per square centimeter and a highly clumpy nature as evidenced by an occultation event in 2013 February. We also find evidence of a patchy absorber with a variable column around approximately 10 (sup 22) per square centimeter and a line-of-sight covering fraction of 0.3-0.9, which responds directly to the intrinsic source flux, possibly due to a wind geometry. A full-covering, constant absorber with a low column density of approximately 1 by 10 (sup 22) per square centimeter is also present, though the location of this low density haze is unknown.
Low-cost green hydrogen can be achieved by integrating utility-scale wind farms to an electrolyzer. The power produced by a wind farm depends on spatial and temporal changes in the wind, and this variability can affect the electrolyzer's performance. This study examines the trade-offs between two electrolyzer configurations: a large centralized electrolyzer connected to the wind farm versus several smaller distributed electrolyzers connected directly to each wind turbine. The results show that a centralized configuration generates more hydrogen because turbines that are waked and produce less power are compensated but other un-waked turbines.
The airport runway configuration is defined as a combination set of runways for arrivals and departures used at a point during operation of the airport. An optimal configuration of these runways depends on a number of factors, including traffic demand, wind magnitude and direction, other adverse weather conditions, and noise restrictions, among others. Based on the current state of these factors and predictions of traffic demand and weather conditions, runway configuration changes are made and coordinated between tower controller, other air traffic control facilities, pilots, and ground personnel. Reconfigurations can be quite disruptive to airport operations; minimizing their frequency and scheduling them well in advance is essential for mitigating some of the added workload for controllers and pilots. Unfortunately, deciding on an appropriate time to change is challenging for human decision makers. Not only do multiple factors need to be evaluated, but the uncertainty in their forecasts must also be considered. Previous optimization methods, such as mixed linear integer programming, have been proposed. Although these methods can reason over a large set of variables, they do not systematically handle the uncertainty associated with weather movement, traffic demands, and other variables. In this work, we introduce a Markov Decision Process (MDP)-based decision making framework which can reason effectively over the inherent uncertainties and make optimal decisions on if/when to change the airport configuration. In a prototype implementation, we present a single runway with three aircraft and utilize knowledge of the forecasted wind speed and direction to determine whether to keep or change the current runway configuration. Our aim through this work is to present a framework for airport reconfiguration which can be scalable to additional aircraft, multiple runways, and various input parameters. This technique will optimize the airport reconfiguration procedure by providing a proactive approach, optimizing not just at the next optimal opportunity for a reconfiguration based on varying atmospheric and traffic conditions in the terminal airspace, but also anticipating future necessary reconfigurations. This will eliminate the inefficiencies of frequent changes currently associated with runway reconfiguration procedures.
We discuss 16 days of intensive International Ultraviolet Explorer (IUE) observations of the Si iv doublet (lambda1400) in the spectrum of the O4 I(n) f star zeta Pup. The data show continuous variability throughout the greater part of the blueshifted absorption. Time series analysis of these data reveals significant power at periods of 19.2 hr and 5.2 days, which we identify with the mean recurrence time of Discrete Absorption Components (DACs) and the photospheric rotation period, respectively. These results indicate that the wind has a global longitudinal asymmetry (approaching a factor 2 in optical depth), possibly associated with large-scale magnetic structures, but suggest that the DACs are not directly associated with specific stellar longitudes in this star. There is no significant power in the lines at the 8.5 hr period identified in photospheric absorption-line variability, nor at the 16.7 hr period reported in X-ray observations.
Misaligned and/or variable coil airgaps cause coupling coefficient variation in wireless power transfer (WPT) systems, resulting in a decrease in the system’s transmitted power and efficiency. This paper presents sensitivity analyses of a three-phase, Y-Y connected, series-tuned WPT system in the frequency domain in terms of several different electric vehicle wireless charging off-nominal conditions (misalignments in Δ x and Δ y directions, change of airgap Δ z , and the roll Δψ, pitch Δθ, and yaw ΔΦ angles) as specified in Society of Automotive Engineers (SAE) J2954 Standard. Coil inductance matrices were obtained by measuring the self- and mutual inductances of the primary and secondary coil phase windings at variable airgap classes (from 5 cm to 30 cm) for five different charging positions as identified in SAE J2954. These 6 × 6 inductance matrices were used in sensitivity and Plexim/PLECS simulation analyses. The sensitivity of the WPT system was analyzed analytically using the input impedance and phase angle, voltage gain, current gain, quality factor, and coupling coefficient parameters of the series-tuned WPT system. The results were confirmed experimentally on a 50 kW WPT system.
A wind-tunnel investigation has been made of the effects of ground proximity on the longitudinal and lateral-directional aerodynamic characteristics and jet-interference effects of a model of a jet V/STOL variable-sweep fighter airplane that employs four direct-lift engines which swing out from the fuselage ahead of the wing and two lift-cruise engines located in the rear part of the fuselage. Data were obtained through a range of angles of attack and sideslip at simulated speeds from hover through transition at various heights of the model above a moving-belt ground plane. Power-off data and power-on data at several power conditions are presented. The data are presented without analysis or discussion.
In this study, aircraft observations from the Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter are used to characterize the variability in drizzle, cloud, and aerosol properties associated with cloud rifts and the surrounding solid clouds observed off the coast of California. A flight made on 16 July 1999 provided measurements directly across an interface between solid and rift cloud conditions. Aircraft instrumentation allowed for measurements of aerosol, cloud droplet, and drizzle spectra. CCN concentrations were measured in addition to standard thermodynamic variables and the winds. A Forward Scatter Spectrometer Probe (FSSP) measured size distribution of cloud-sized droplets. A Cloud Imaging Probe (CIP) was used to measure distributions of drizzle-sized droplets. Aerosol distributions were obtained from a Cloud Aerosol Scatterprobe (CAS). The CAS probe measured aerosols, cloud droplets and drizzle-sized drops; for this study. The CAS probe was used to measure aerosols in the size range of 0.5 micron - 1 micron. Smaller aerosols were characterized using an Ultrafine Condensation Particle Counter (CPC) sensor. The CPC was used to measure particles with diameters greater than 0.003 micron. By subtracting different count concentrations measured with the CPC, this probe was capable of identifying ultrafine particles those falling in the size range of 3 nanometers - 7 nanometers that are believed to be associated with new particle production.