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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Exploratory Precipitation Metrics: Spatiotemporal Characteristics, Process-Oriented, and Phenomena-Based

Abstract Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Remote sensing of ocean color in the Arctic

The main objectives of the research are: to increase the understanding of biological production (and carbon fluxes) along the ice edge, in frontal regions, and in open water areas of the Arctic and the physical factors controlling that production through the use of satellite and aircraft remote sensing techniques; and to develop relationships between measured radiances from the Multichannel Aircraft Radiometer System (MARS) and the bio-optical properties of the water in the Arctic and adjacent seas. Several recent Coastal Zone Color Scanner (CZCS) studies in the Arctic have shown that, despite constraints imposed by cloud cover, satellite ocean color is a useful means of studying mesoscale physical and biological oceanographic phenomena at high latitudes. The imagery has provided detailed information on ice edge and frontal processes such as spring breakup and retreat of the ice edge, influence of ice on ice effects of stratification on phytoplankton production, river sediment transport, effects of spring runoff, water mass boundaries, circulation patterns, and eddy formation in Icelandic waters and in the Greenland, Barents, Norwegian, and Bering Seas.

Maynard, N. G.↗
NASA NTRS2008

Online Visualization and Analysis of Merged Global Geostationary Satellite Infrared Dataset

The NASA Goddard Earth Sciences Data Information Services Center (GES DISC) is home of Tropical Rainfall Measuring Mission (TRMM) data archive. The global merged IR product also known as the NCEP/CPC 4-km Global (60 degrees N - 60 degrees S) IR Dataset, is one of TRMM ancillary datasets. They are globally merged (60 degrees N - 60 degrees S) pixel-resolution (4 km) IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 and GMS). The availability of data from METEOSAT-5, which is located at 63E at the present time, yields a unique opportunity for total global (60 degrees N- 60 degrees S) coverage. The GES DISC has collected over 8 years of the data beginning from February of 2000. This high temporal resolution dataset can not only provide additional background information to TRMM and other satellite missions, but also allow observing a wide range of meteorological phenomena from space, such as, mesoscale convection systems, tropical cyclones, hurricanes, etc. The dataset can also be used to verify model simulations. Despite that the data can be downloaded via ftp, however, its large volume poses a challenge for many users. A single file occupies about 70 MB disk space and there is a total of approximately 73,000 files (approximately 4.5 TB) for the past 8 years. In order to facilitate data access, we have developed a web prototype to allow users to conduct online visualization and analysis of this dataset. With a web browser and few mouse clicks, users can have a full access to over 8 year and over 4.5 TB data and generate black and white IR imagery and animation without downloading any software and data. In short, you can make your own images! Basic functions include selection of area of interest, single imagery or animation, a time skip capability for different temporal resolution and image size. Users can save an animation as a file (animated gif) and import it in other presentation software, such as, Microsoft PowerPoint. The prototype will be integrated into GIOVANNI and existing GIOVANNI capabilities, such as, data download, Google Earth KMZ, etc will be available. Users will also be able to access other data products in the GIOVANNI family.

Liu, Zhong↗
NASA NTRS1976

An equivalent potential vorticity theory applied to the analysis and prediction of severe storm dynamics

Potential vorticity theory is developed in a description of an equivalent potential temperature topography, and a new theory suited to the description of scale interaction is elaborated. Macroscale triggering of ageostrophic flow fields at the mesoscale, in turn leading to release of convective instability along narrow zones at the microscale, is examined. Correlation of appreciable decrease in potential vorticity with such phenomena as cumulonimbi, tornados, and duststorms is examined. The relevance of a multiscale energy-momentum cascade in numerical prediction of severe mesoscale and microscale phenomena from radiosonde data is reviewed. Hypotheses for mesoscale dynamics are constructed.

Paine, D. A.↗
NASA NTRS1983

Global mesoscale variability from collinear tracks of SEASAT altimeter data

Eight to nine sets of global collinear altimeter data with a cross-track grid spacing of approximately 900 km at the equator and 600 km at midlatitude have been obtained from the last 25 days of the 1978 SEASAT mission. Since the geoid is time-invariant, such observations can reveal sea surface height variability caused by dynamic ocean phenomena. Variations due to deep ocean mesoscale features are presently solved for by eliminating the longer wavelength deviations, yielding sea height profiles with an accuracy of a few cm, and a global variability map constructed from these data which reveal an exceptionally realistic perspective of mesoscale energetics. The dominance of exceedingly small variability over extensive regions of the oceans is noted. In both the Atlantic and the Pacific, the North Equatorial Current systems were clearly expressed as zonal bands of higher variability.

Cheney, R. E.↗
DOE OSTI2020

First-principles Modeling and Design of Solid-State Interfaces for the Protection and Use of Lithium Metal Anodes

Li-ion batteries are one of the most advanced energy storage technologies in use today. Li-ion batteries are used in a multitude of applications ranging from consumer electronics, medical devices, sensors and grid storage. However, improving the capacity and energy density delivered by current Li-ion technology requires advanced materials research into novel chemical systems. In this project we have focused particularly in the use of solid-state electrolytes with lithium metal electrodes. Research into all solid-state batteries (ASSB) with Li metal electrodes has significantly expanded in recent years, however most studies reported experimental findings, which left substantial room for theoretical and modeling work as a tool to understand and determine design principles allowing reliable and safe use of ASSBs with Li metal. Among the remaining obstacles preventing reliable use of ASSBs with a Li metal electrode, the stability of the interface between the solid electrolyte and Li metal, and the propagation/dendrite formation of Li metal and resulting mechanical degradation of the electrolyte are key phenomenon that are yet to be fully understood. In the current project we have addressed these two coupled phenomena using first principles calculations and mesoscale continuum modeling. We have obtained chemical and electrochemical stability windows for several solid electrolyte materials. Additionally, from mathematical and numerical modeling of Li protrusion and dendrite initiation during plating and stripping we have determined design criteria in terms of chemical, electrochemical, and mechanical properties and operating conditions for which stable deposition can occur. We also considered the effects of mixed electronic-ionic conduction in solid electrolytes, which has more recently been suggested as another important mechanism involved in ASSB failure. Throughout our work we have successfully addressed important questions necessary for the use of ASSB’s. We have determined guiding principles for materials properties and operating conditions necessary to operate ASSB’s. And have proposed novel solid electrolyte materials with predicted chemical stability an ionic conductivity. Although this represents significant progress in our understanding, open questions remain in order to fully develop reliable and safely operate ASSBs with Li metal. Future work, building on this project will require further experimental, theoretical and simulation efforts to address remaining questions.

25 ENERGY STORAGE↗
NASA NTRS1988

A mesoscale gravity wave event observed during CCOPE. I - Multiscale statistical analysis of wave characteristics

This paper presents a statistical analysis of the characteristics of the wavelike activity that occurred over the north-central United States on July 11-12, 1981, using data from the Cooperative Convective Precipitation Experiment in Montana. In particular, two distinct wave episodes of about 8-h duration within a longer (33 h) period of wave activity were studied in detail. It is demonstrated that the observed phenomena display features consistent with those of mesoscale gravity waves. The principles of statistical methods used to detect and track mesoscale gravity waves are discussed together with their limitations.

Koch, Steven E.↗
NASA NTRS1981

Hydrologic forecasting requirements for precipitation data from space measurements

The needs for precipitation information in severe storms research and in the operational detection and forecasting of such phenomena are described. The discussion will include thunderstorms, tropical cyclones, and regional and mesoscale numerical models used to analyze and forecast these and other regional scale phenomena.

Hudlow, M. D.↗
NASA NTRS1980

Sea surface temperature of the coastal zones of France

The various thermal gradients in the coastal zones of France were mapped with regard to natural phenomena and man made thermal effluents. The mesoscale thermal features of the English Channel, the Bay of Biscay, and the northwestern Mediterranean Sea were also studied. The evolution of the thermal gradients generated by the main estuaries of the French coastal zones was investigated along with the modeling of diurnal heating of the sea surface and its influence on the oceanic surface layers.

Deschamps, P. Y.↗
NASA NTRS2004

Evaluation and Application of Satellite-Based Latent Heating Profile Estimation Methods

In recent years, methods for estimating atmospheric latent heating vertical structure from both passive and active microwave remote sensing have matured to the point where quantitative evaluation of these methods is the next logical step. Two approaches for heating algorithm evaluation are proposed: First, application of heating algorithms to synthetic data, based upon cloud-resolving model simulations, can be used to test the internal consistency of heating estimates in the absence of systematic errors in physical assumptions. Second, comparisons of satellite-retrieved vertical heating structures to independent ground-based estimates, such as rawinsonde-derived analyses of heating, provide an additional test. The two approaches are complementary, since systematic errors in heating indicated by the second approach may be confirmed by the first. A passive microwave and combined passive/active microwave heating retrieval algorithm are evaluated using the described approaches. In general, the passive microwave algorithm heating profile estimates are subject to biases due to the limited vertical heating structure information contained in the passive microwave observations. These biases may be partly overcome by including more environment-specific a priori information into the algorithm s database of candidate solution profiles. The combined passive/active microwave algorithm utilizes the much higher-resolution vertical structure information provided by spaceborne radar data to produce less biased estimates; however, the global spatio-temporal sampling by spaceborne radar is limited. In the present study, the passive/active microwave algorithm is used to construct a more physically-consistent and environment-specific set of candidate solution profiles for the passive microwave algorithm and to help evaluate errors in the passive algorithm s heating estimates. Although satellite estimates of latent heating are based upon instantaneous, footprint- scale data, suppression of random errors requires averaging to at least half-degree resolution. Analysis of mesoscale and larger space-time scale phenomena based upon passive and passive/active microwave heating estimates from TRMM, SSMI, and AMSR data will be presented at the conference.

Olson, William S.↗
DOE OSTI2024

Can mesoscale models capture the effect from cluster wakes offshore?

Long wakes from offshore wind turbine clusters can extend tens of kilometers downstream, affecting the wind resource of a large area. Given the ability of mesoscale numerical weather prediction models to capture important atmospheric phenomena and mechanisms relevant to wake evolution, they are often used to simulate wakes behind large wind turbine clusters and their impact over a wider region. Yet, uncertainty persists regarding the accuracy of representing cluster wakes via mesoscale models and their wind turbine parameterizations. Here, we evaluate the accuracy of the Fitch wind farm parameterization in the Weather Research and Forecasting model in capturing cluster-wake effects using two different options to represent turbulent mixing in the planetary boundary layer. To this end, we compare operational data from an offshore wind farm in the North Sea that is fully or partially waked by an upstream array against high-resolution mesoscale simulations. In general, we find that mesoscale models accurately represent the effect of cluster wakes on front-row turbines of a downstream wind farm. However, the same models may not accurately capture cluster-wake effects on an entire downstream wind farm, due to misrepresenting internal-wake effects.

17 WIND ENERGY↗
NASA NTRS1994

Air pollutant transport in a coastal environment. Part 1: Two-dimensional simulations of sea-breeze and mountain effects

Over the southern California coastal region, observations of the vertical distributions of pollutants show that maximum concentrations can occur within temperature inversion layers well above the surface. A mesoscale model is used to study the dynamical phenomena that cause such layers, including sea breezes and mountain flows, and to study the characteristics of air pollutant transport in a coastal environment capped by a temperature inversion. The mathematical and physical structure of the model is described. Two-dimensional simulations corresponding to four configurations of coastal plains and mountains are discussed. The simulations reveal that pollutant transport over a coastal plain is strongly influenced by the topographic configuration, including the height of coastal mountains and their distance from the coastline. Sea breezes induced by land-sea thermal contrasts, as well as upslope winds induced along mountain flanks, both create vertical transport that can lead to the formation of elevated pollution layers. The sea-breeze circulation generates pollution layers by undercutting the mixed layer and lofting pollutants into the stable layer. Heating of mountain slopes acts to vent pollutants above the mountain ridge during the day; during the evening, pollutants can be injected directly into the inversion layer from the decaying upslope flows. In a land-sea configuration with mountains close to the coastline, the sea breeze and heated-mountain flow are strongly coupled. In the afternoon, this interaction can produce upslope flow from which polluted air is detrained into the inversion layer as a return circulation. When the mountains lie farther inland, however, pollutants may be trapped aloft when the mixed layer stabilizes in the late afternoon. As the nocturnal boundary layer forms over the coast in the evening, polluted mixed-layer air is effectively left behind in the inversion layer. In the Los Angeles Basin, the formation mechanism for elevated polluted layers is most similar to our cases with inland mountains.

Lu, Rong↗
NASA NTRS2014

ldentifying Episodes of Earth Science Phenomena Using a Big-Data Technology

A significant portion of Earth Science investigations is phenomenon- (or event-) based, such as the studies of Rossby waves, volcano eruptions, tsunamis, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. We have constructed a prototype Automated Event Service (AES) system that is used to methodically mine custom-defined events in the reanalysis data sets of atmospheric general circulation models. Our AES will enable researchers to specify their custom, numeric event criteria using a user-friendly web interface to search the reanalysis data sets. Moreover, we have included a social component to enable dynamic formation of collaboration groups for researchers to cooperate on event definitions of common interest and for the analysis of these events. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon (ES phenomenon). A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an El Nino, is each an episode of a named ES phenomenon, and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a duration (often finite) and an associated geo-location as a function of time; it's therefore an entity embedded in four-dimensional (4D) spatiotemporal space. Earth Science phenomena with the potential to cause massive economic disruption or loss of life often rivet the attention of researchers. But, broader scientific curiosity also drives the study of phenomena that pose no immediate danger, such as land/sea breezes. Due to Earth System's intricate dynamics, we are continuously discovering novel ES phenomena. We generally gain understanding of a given phenomenon by observing and studying individual events. This process usually begins by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, as mentioned previously, comprehensive records only exist for a very limited set of high-impact phenomena; aside from these, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. The reason for the lack of comprehensive records for most of the ES phenomena is mainly due to the perception that they do not pose immediate and/or severe threat to life and property. Thus they are not consistently tracked, monitored, and catalogued. Many phenomena even lack precise and/or commonly accepted criteria for definitions. Moreover, various Earth Science observations and data have accumulated to a previously unfathomable volume; NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data, which are steadily increasing. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. We have not only envisioned AES as an environment for identifying customdefined events but also aspired for it to be an interactive environment with quick turnaround time for revisions of query criteria and results, as well as a collaborative environment where geographically distributed experts may work together on the same phenomena. A Big Data technology is thus required for the realization of such a system. In the following, we first introduce the technology selected for AES in the next section. We then demonstrate the utility of AES using a use case, Blizzard, before we conclude.

Kuo, Kwo-Sen↗
NASA NTRS1990

Turbulence spectra of the FIRE stratocumulus-topped boundary layers

There are at least four physical phenomena which contribute to the FIRE boundary layer turbulence spectra: boundary layer spanning eddies resulting from buoyant and mechanical production of turbulent kinetic energy (the microscale subrange); inertial subrange turbulence which cascades this energy to smaller scales; quasi-two dimensional mesoscale variations; and gravity waves. The relative contributions of these four phenomena to the spectra depend on the altitude of observation and variable involved (vertical velocity, temperature and moisture spectra are discussed). The physical origins of these variations in relative contribution are discussed. As expected from the theory (Kaimal et al., 1976), mixed layer scaling of the spectra (i.e., nondimensionalizing wavelength by Z(sub i) and spectral density by Z(sub i) and the dissipation rates) is successful for the microscale subrange and inertial subrange but not for the mesoscale subrange. The most striking feature of the normalized vertical velocity spectra is the lack of any significant mesoscale contribution. The spectral peak results from buoyant and mechanical production on scales similar to the boundary layer depth. The decrease in spectral density at larger scales results from the suppression of vertical velocity perturbations with large horizontal scales by the shallowness of the atmosphere. The spectral density also decreases towards smaller scales following the well known inertial subrange slope. There is a significant variation in the shape of the normalized spectra with height.

Young, G. S.↗
DOE OSTI2020

Understanding Microstructure Variability in Vapor-Deposited Energetic Materials by Using Phase-Field Methods

Critical components, such as detonators, in Sandia's stockpile contain heterogeneous materials whose performance and reliability depend on accurate, predictive models of coupled, complex phenomena to predict their synthesis, processing, and operation. Ongoing research in energetic materials has shown that microstructural properties, such as density, pore-size, morphology, and specific surface area are correlated to their initiation threshold and detonation behavior. However, experiments to study these specific characteristics of energetic materials are challenging and time consuming. Therefore, in this work, we turn to mesoscale modeling methods that may be capable of reproducing some observed phenomena to refine and predict outcomes beforehand. Even so, we have no physics-based modeling capability to predict how the microstructure of an energetic material will evolve over near- and long-term time scales. Thus, the goal of this work is to (i) identify any knowledge gaps in how the underlying microstructure forms and evolves during the synthesis process, and (ii) develop and test a mesoscale phase-field model for vapor deposition to capture critical mechanisms of microstructure formation, evolution, and variability in vapor-deposited energetic materials, such as processing conditions, material properties, and substrate interactions. Based on this work, the phase-field method is shown to be a valuable tool for developing the necessary models containing coupled, complex phenomena to investigate and understand the synthesis and processing of energetic materials.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Hurricane Data Analysis Tool

In order to facilitate Earth science data access, the NASA Goddard Earth Sciences Data Information Services Center (GES DISC) has developed a web prototype, the Hurricane Data Analysis Tool (HDAT; URL: http://disc.gsfc.nasa.gov/HDAT), to allow users to conduct online visualization and analysis of several remote sensing and model datasets for educational activities and studies of tropical cyclones and other weather phenomena. With a web browser and few mouse clicks, users can have a full access to terabytes of data and generate 2-D or time-series plots and animation without downloading any software and data. HDAT includes data from the NASA Tropical Rainfall Measuring Mission (TRMM), the NASA Quick Scatterometer(QuikSCAT) and NECP Reanalysis, and the NCEP/CPC half-hourly, 4-km Global (60 N - 60 S) IR Dataset. The GES DISC archives TRMM data. The daily global rainfall product derived from the 3-hourly multi-satellite precipitation product (3B42 V6) is available in HDAT. The TRMM Microwave Imager (TMI) sea surface temperature from the Remote Sensing Systems is in HDAT as well. The NASA QuikSCAT ocean surface wind and the NCEP Reanalysis provide ocean surface and atmospheric conditions, respectively. The global merged IR product, also known as, the NCEP/CPC half-hourly, 4-km Global (60 N -60 S) IR Dataset, is one of TRMM ancillary datasets. They are globally-merged pixel-resolution IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 & GMS). The GES DISC has collected over 10 years of the data beginning from February of 2000. This high temporal resolution (every 30 minutes) dataset not only provides additional background information to TRMM and other satellite missions, but also allows observing a wide range of meteorological phenomena from space, such as, hurricanes, typhoons, tropical cyclones, mesoscale convection system, etc. Basic functions include selection of area of interest and time, single imagery, overlay of two different products, animation,a time skip capability and different image size outputs. Users can save an animation as a file (animated gif) and import it in other presentation software, such as, Microsoft PowerPoint. Since the tool can directly access the real data, more features and functionality can be added in the future.

Liu, Zhong↗
DOE OSTI2022

Uncertainty Quantification Framework for Predicting Material Response with Large Number of Parameters: Application to Creep Prediction in Ferritic-Martensitic Steels Using Combined Crystal Plasticity and Grain Boundary Models

This paper presents an uncertainty quantification (UQ) framework for the physics-based model prediction of material response with a large number of parameters. The application problem presented in this work is that of predicting creep in Grade 91 steel at 600°C. The material response is defined with a physically based microstructural model with constitutive equations emulating several observed phenomena in Grade 91 and embodied into an explicit geometry mesoscale finite element model for prior austenite grains and grain boundaries. Creep within the grains and in grain boundaries are represented by crystal plasticity for dislocation motion and a physics-based model for cavity growth and nucleation, respectively. The creep behavior of this material is influenced by several parameters, some of which have a wide range of variation based on experimental data. UQ combined with microstructural modeling can discover the core microstructural causes of experimental variability, leading to improved materials with lower variability in critical long-term material properties. In this study, we investigate the model's uncertainty to identify material properties that may be modified during production to increase creep life and analyze different components of the crystal plasticity model for improvements. For this purpose, a quantity of interest is defined as time to minimum creep rate, which correlates well to the creep failure of the material. A deep neural network model was trained and validated to be used as a surrogate for the finite element model. Then, a variance-based sensitivity analysis is performed on the surrogate model to find the Sobol indices of the input parameters in respect to the output quantity of interest. The Sobol indices are used to reduce the dimensionality of the model. Generalized polynomial chaos expansion is used on the reduced basis models to propagate the uncertainty from the input parameters to the quantity of interest using the deep neural network surrogate model. These results are benchmarked against uncertainty propagation using Monte Carlo simulations. In conclusion, the UQ performed through the reduced basis model captures almost all the uncertainty in the model with significantly fewer simulations, making it possible to perform the UQ directly via simulations with the finite element model rather than surrogate machine-learned models.

36 MATERIALS SCIENCE↗
NASA NTRS1976

The numerical prediction of tornadic windstorms

Rather than treating localized severe weather events as being purely statistical in nature, a mathematical framework was developed based on the concept of a deterministic cascade of energy-momentum which bridges the gap between the longest and shortest of atmospheric wave phenomena. This cascade relieves macroscale wavelengths ( 1000 km) of mass-momentum imbalances by exciting convective phenomena ( 10 km) through a sophisticated transfer process involving intermediate, mesoscale wavelengths.

Paine, D. A.↗