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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

TRMM Latent Heating Retrieval and Comparisons with Field Campaigns and Large-Scale Analyses

Rainfall production is a fundamental process within the Earth's hydrological cycle because it represents both a principal forcing term in surface water budgets, and its energetics corollary, latent heating (LH), is one of the principal sources of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The vertical distribution of LH has a strong influence on the atmosphere, controlling large-scale tropical circulations, exciting and modulating tropical waves, maintaining the intensities of tropical cyclones, and even providing the energetics of midlatitude cyclones and other mobile midlatitude weather systems. Moreover, the processes associated with LH result in significant non-linear changes in atmospheric radiation through the creation, dissipation and modulation of clouds and precipitation. Yanai et al. (1973) utilized the meteorological data collected from a sounding network to present a pioneering work on thermodynamic budgets, which are referred to as the apparent heat source (Q1) and apparent moisture sink (Q2). Yanai's paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q1 data have been used to generate the look-up tables used in LH algorithms. This paper examines the retrieval, validation, and application of LH estimates based on rain rate quantities acquired from the Tropical Rainfall Measuring Mission satellite (TRMM). TRMM was launched in November 1997 as a joint enterprise between the American and Japanese space agencies -- with overriding goals of providing accurate four-dimensional estimates of rainfall and LH over the global Tropics and subtropics equatorward of 35o. Other literature has acknowledged the achievement of the first goal of obtaining an accurate rainfall climatology. This paper describes the second major goal of obtaining credible LH estimates as well as their applications within TRMM's zone of coverage, the standard TRMM LH products, and areas for further improvement.

latent heating↗
DOE OSTI2020

Microphysical Sensitivity of Superparameterized Precipitation Extremes in the Contiguous United States Due to Feedbacks on Large-Scale Circulation

Superparameterized (SP) global climate models have been shown to better simulate various features of precipitation relative to conventional models, including its diurnal cycle as well as its extremes. While various studies have focused on the effect of differing microphysics parameterizations on precipitation within limited-area cloud-resolving models, we examine here the effect on contiguous U.S. (CONUS) extremes in a global SP model. We vary the number of predicted moments for hydrometeor distributions, the character of the rimed ice species, and the representation of raindrop self-collection and breakup. Using a likelihood ratio test and accounting for the effects of multiple hypothesis testing, we find that there are some regional differences, particularly during spring and summer in the Southwest and the Midwest, in both the current climate and a warmer climate with uniformly increased sea surface temperatures. These differences are most statistically significant and widespread when the number of moments is changed. To determine whether these results are due to (fast) local effects of the different microphysics or the (slower) ensuing feedback on the large-scale atmospheric circulation, we run a series of short, 5-day simulations initialized from reanalysis data. We find that the differences largely disappear in these runs and therefore infer that the different parameterizations impact precipitation extremes indirectly via the large-scale circulation. Finally, we compare the present-day results with hourly rain gauge data and find that SP underestimates extremes relative to observations regardless of which microphysics scheme is used given a fixed model configuration and resolution.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

CNES Large Scale SWOT Simulator: User's Tutorial for Terrestrial Surface Water Applications

The CNES Large Scale SWOT Hydrology Simulator creates proxy SWOT water surface elevations (WSE). A large portion of the effort required to run the CNES simulator is upfront in creating the simulator input. This tutorial describes the steps to create the simulator input and then run the CNES simulator. Since many applications will utilize a time series of proxy SWOT WSE, a short description of that process is included in the Appendix for advanced users.

Hydrology↗
NASA NTRS1990

Properties of large scale plasma flow during the early stage of the plasmaspheric refilling

The objective is to better characterize the macroscopic properties of the interhemisphere plasma flow by solving a more complete set of hydrodynamic equations than that solved previously. Specifically, the ion continuity, momentum and energy equations were solved for the plasma flow along the closed magnetic field lines. During the initial stage of the supersonic outflow in the equatorial region, the ions cool substantially. Using the hydrodynamic model for the large-scale plasma flow, the dynamics of shocks was examined which form in the geomagnetic flux tubes during the early stages of refilling. These shocks are more like those forming in neutral gases than the electrostatic shocks driven by microinstabilities involving ion-ion interaction. Therefore, the shocks seen in the hydrodynamic model are termed as hydrodynamic shocks. Such shocks are generally unsteady and therefore the usual shock jump conditions given by Rankine-Hugoniot relations are not strictly applicable to them. The density, flow velocity and temperature structures associated with the shocks are examined for both asymmetrical and symmetrical flows. In the asymmetrical flow the outflow from one of two conjugate ionospheres is dominant. On the other hand, in the symmetrical case outflows from the two ionospheric sources are identical. Both cases are treated by a two-stream model. In the late type of flow, the early-time refilling shows a relaxation type of oscillation, which is driven by the large-scale interactions between the two identical streams. After this early stage, the resulting temperature structure shows some interesting features. In the equatorial region the streams are isothermal, but in the off-equatorial regions the streams have quite different temperatures, and also densities and flow velocities. The dense and slow stream is found to be warmer than the low-density fast stream. In the late stage of refilling, the temperature is found to steadily increase from the conjugate ionospheres towards the equator; the equatorial temperature is found to be as high as about 8000 K compared to the ionospheric temperature of 3600 K.

Singh, Nagendra↗
DOE OSTI2021

An innovative digital image correlation technique for in-situ process monitoring of composite structures in large scale additive manufacturing

As additive manufacturing (AM) continues to develop and become a standardized manufacturing method, there will be a continued need to provide in-situ monitoring during the manufacturing of polymer composite printed components. Thermal residual stress is a primary cause of failures such as interlayer disbonds or delamination, micro cracking, and dimensional instability, which can occur during or after the build. Here, we report a novel digital image correlation (DIC) adaptation to monitor thermal residual stresses during the entire print process for large-scale AM. In this work, DIC has been investigated (a) by the natural speckle produced by the polymer surface for correlation, (b) to monitor AM build, and (c) to evaluate the effect of thermal residual stress on warpage of the printed component. The natural speckle pattern of the AM material resulted in a respectable 3.57% error compared to the traditional painted speckle pattern of 3.05% error. DIC measured a 190% increase in vertical displacement at the edge of the wall compared to the center, indicating warpage during AM. This work is a step towards a non-intrusive residual stress measuring technique using DIC for large-scale AM.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Experimental measurements of gas-particle flows in large-scale strippers

Measurements of gas–solid particle flow in a large-scale stripper unit are reported. The experiments target industrial (pilot) scale measurements of gas-particle flow that can be used to validate numerical methods for modeling multiphase flows, such as computational fluid dynamics coupled to the discrete element method (CFD-DEM). Specifically, experiments were performed with Geldart Group B (533 µm) glass beads in a stripper unit. In general, previous CFD-DEM validation datasets were performed in benchtop experimental systems and limited to O(10 5 ) particles. Here, in this work, the number of particles in the isolated section of the stripper is O(10 7 ) for all tests. Measurements are reported for a ~2 m tall section of the ~1 m diameter stripper. Radial mass flux profiles measured at five axial positions and three axial pressure drop measurements are reported for six operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1974

On the development of noise-producing large-scale wavelike eddies in a turbulent jet

The development of large-scale wavelike eddies in a two-dimensional turbulent jet was studied. The basic mean flow develops from a mixing region type with an initial specified boundary layer thickness into a fully developed jet. The role of the varicose and sinuous modes as these develop in a growing mean flow is brought out. In general, it was found, for a given frequency parameter, the varicose mode has a shorter streamwise lifetime than the sinuous mode. The latter, for lower frequency ranges, persists past the end of the potential core only to be subject to dissolution by the more enhanced fine scale turbulent activity in that region.

Merkine, L. O.↗
NASA NTRS1977

Soft X-ray observations of large-scale coronal active region brightenings

One hundred fifty-six large-scale enhancements of X-ray emission from solar active regions were studied on full-disk filterheliograms to determine characteristic morphology and expansion rates for heated coronal plasma. The X-ray photographs were compared with H-alpha observations of flares, sudden filament disappearances, sprays, and loop prominence systems (LPS). Eighty-one percent of the X-ray events were correlated with H-alpha filament activity, but only 44% were correlated with reported H-alpha flares. The X-ray enhancements took the form of loops or arcades of loops ranging in length from 60,000 km to 520,000 km and averaging 15,000 km in width. Lifetimes ranged from at least 3 hr to more than 24 hr. The event frequency was approximately 1.4 per day. X-ray loop arcades evolved from sharp-edged clouds in cavities vacated by rising H-alpha filaments. Expansion velocities of the loops were about 50 km/s immediately after excitation and 1-10 km/s several hours later. These long-lived loop arcades are identified with LPS, and it is suggested that the loops outlined magnetic fields which were reconnecting after filament eruptions. Another class of X-ray-enhanced loops stretched outside active regions and accompanied sprays or lateral filament ejections. It is suggested that these loops outlined closed magnetic fields guiding slow-mode shocks from flares and filament eruptions.

Rust, D. M.↗
NASA NTRS1980

The large-scale far-infrared structure of W3 and W4

The large-scale structure of the giant H II region complex W3/W4 has been mapped in two wavelength bands covering 60 to 120 microns at an angular resolution of 12 arc min. The only region of strong emission observed lies along a molecular ridge at an ionization/shock front in the sources. This structure supports the idea that a new generation of stars formed after neutral material ahead of the front became gravitationally unstable. These embedded stars are dominating the energetics of the molecular/infrared cloud, although the visible OCl 352 cluster in neighboring IC 1805 may supply much of the heating flux to the fainter regions. A simple model relating the far-infrared and CO emission is presented.

Thronson, H. A., Jr.↗
NASA NTRS1981

Definitive design of the solar total energy large-scale experiment at Shenandoah, Georgia

Construction of a Solar Total Energy Large Scale Experiment at Shenandoah, Georgia, is described. The Solar Total Energy System (STES) is designed with capacity to supply electricity and thermal energy to a knitwear plant at the Shenandoah site. The system will provide 400 kilowatts electrical and 3.5 megawatts thermal energy. The STES is a cascaded total energy system configuration. It uses parabolic disch collectors and a steam turbine-generator. The electrical system will be grid connected to the Georgia Power Company system.

Hunke, R. W.↗
NASA NTRS1988

Phase transitions as the origin of large scale structure in the universe

A review of the formation of large scale structure through gravitational growth of primordial perturbations is given. This is followed by a discussion of how symmetry breaking phase transitions in the early universe might have produced the required perturbations, in particular through the formation and evolution of a network of cosmic strings. Finally, the statistical mechanics of string networks, for both cosmic and fundamental strings is discussed, leading to some more speculative ideas on the possible role of fundamental strings (superstrings or heterotic strings) in the very early universe.

Turok, Neil↗
NASA NTRS1988

Large scale structure of the sun's corona

Results concerning the large-scale structure of the solar corona obtained by observations at meter-decameter wavelengths are reviewed. Coronal holes observed on the disk at multiple frequencies show the radial and azimuthal geometry of the hole. At the base of the hole there is good correspondence to the chromospheric signature in He I 10,830 A, but at greater heights the hole may show departures from symmetry. Two-dimensional imaging of weak-type III bursts simultaneously with the HAO SMM coronagraph/polarimeter measurements indicate that these bursts occur along elongated features emanating from the quiet sun, corresponding in position angle to the bright coronal streamers. It is shown that the densest regions of streamers and the regions of maximum intensity of type II bursts coincide closely. Non-flare-associated type II/type IV bursts associated with coronal streamer disruption events are studied along with correlated type II burst emissions originating from distant centers on the sun.

Kundu, Mukul R.↗
NASA NTRS1989

Phase transitions as the origin of large scale structure in the universe

A review of the formation of large scale structure through gravitational growth of primordial perturbations is given. This is followed by a discussion of how symmetry breaking phase transitions in the early universe might have produced the required perturbations, in particular through the formation and evolution of a network of cosmic strings.

Turok, Neil↗
NASA NTRS1995

Large-scale structure of the solar corona and inner heliosphere

The large-scale structure of the solar corona influences solar activity particularly coronal mass ejections (CMEs). The helmet streamers that are observed to dominate the structure of the inner corona are formed by the interaction of the solar wind with coronal magnetic fields. We have simulated this interaction in three dimensions using the magnetohydrodynamic (MHD) equations. In order to create a realistic model, we use the magnetic field that is observed at the Sun's surface (deduced from daily Wilcox Solar Observatory magnetograms) as input, in combination with specified density and temperature profiles at the surface. A self-consistent 3D solar-wind solution is developed by integrating the MHD equations in time to steady state. Such solutions can reproduce the observed structures that are seen in coronagraph images and eclipse photographs of the corona. This model allows us to accurately determine the position of the heliospheric current sheet. We will compare the results obtained from our model with Ulysses observations during the period May-June 1993, and with an eclipse photograph of the corona on November 3, 1994.

Mikic, Z.↗
DOE OSTI2025

A cross-dimensional analysis of data-driven short-term load forecasting methods with large-scale smart meter data

Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.

Li, Han↗
DOE OSTI2023

Precision engineering of biological function with large-scale measurements and machine learning

As synthetic biology expands and accelerates into real-world applications, methods for quantitatively and precisely engineering biological function become increasingly relevant. This is particularly true for applications that require programmed sensing to dynamically regulate gene expression in response to stimuli. However, few methods have been described that can engineer biological sensing with any level of quantitative precision. Here, we present two complementary methods for precision engineering of genetic sensors: in silico selection and machine-learning-enabled forward engineering. Both methods use a large-scale genotype-phenotype dataset to identify DNA sequences that encode sensors with quantitatively specified dose response. First, we show that in silico selection can be used to engineer sensors with a wide range of dose-response curves. To demonstrate in silico selection for precise, multi-objective engineering, we simultaneously tune a genetic sensor’s sensitivity (EC 50 ) and saturating output to meet quantitative specifications. In addition, we engineer sensors with inverted dose-response and specified EC 50 . Second, we demonstrate a machine-learning-enabled approach to predictively engineer genetic sensors with mutation combinations that are not present in the large-scale dataset. We show that the interpretable machine learning results can be combined with a biophysical model to engineer sensors with improved inverted dose-response curves.

59 BASIC BIOLOGICAL SCIENCES↗