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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 397 records · Page 22

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NASA NTRS1990

Severely reduced gravitropism in dark-grown hypocotyls of a starch-deficient mutant of Nicotiana sylvestris

Gravitropism in dark-grown hypocotyls of the wild type was compared with a starch-deficient Nicotiana sylvestris mutant (NS 458) to test the effects of starch deficiency on gravity sensing. In a time course of curvature measured using infrared video, the response of the mutant was greatly reduced compared to the wild type; 72 hours after reorientation, curvature was about 10 degrees for NS 458 and about 70 degrees for wild type. In dishes maintained in a vertical orientation, wild-type hypocotyls were predominantly vertical, whereas NS 458 hypocotyls were severely disoriented with about 5 times more orientational variability than wild type. Since the growth rates were equal for both genotypes and phototropic curvature was only slightly inhibited in NS 458, the mutation probably affects gravity perception rather than differential growth. Our data suggest that starch deficiency reduces gravitropic sensitivity more in dark-grown hypocotyls than in dark- or light-grown roots in this mutant and support the hypothesis that amyloplasts function as statoliths in shoots as well as roots.

Non-NASA Center↗

NASA NTRS1999

The Influence of Airmass Histories on Radical Species during POLARIS

The Goddard trajectory chemistry model was used with ER-2 aircraft data to test our current knowledge of radical photochemistry during the POLARIS (Polar Ozone Loss in the Arctic Region In Summer) campaign. The results of the trajectory chemistry model with and without trajectories are used to identify cases where steady state does not accurately describe the measurements. Over the entire mission, using trajectory chemistry reduces the variability in the modeled NO(x) comparisons to data by 25% with respect to the same model simulating steady state. Although the variability is reduced, NO(x)/NO(y) trajectory model results were found to be systematically low relative to the observations by 20-30% as seen in previous studies. Using new rate constants for reactions important in NO(y) partitioning improves the agreement of NO(x)/NO(y) with the observations but a 5-10% bias still exists. OH and HO2 individually are underpredicted by 15% of the standard steady state model and worsen with the new rate constants. Trajectory chemistry model results of OH/HO2 were systematically low by 10-20% but improve using the new rates constants because of the explicit dependence on NO. This suggests that our understanding of NO(x) is accurate to the 20% level and HO(x) chemistry is accurate to the 30% level in the lower stratosphere or better for the POLARIS regime. The behavior of the NO(x) and HO(x) comparisons to data using steady state versus trajectory chemistry and with updated rate coefficients is discussed in ten-ns of known chemical mechanisms and lifetimes.

Pierson, J. M.↗

NASA NTRS2021

Burning and Suppression of Solids–II (BASS-II) Summary Report

The Burning and Suppression of Solids (BASS) experiment hardware is a small flow duct that provides containment for small scale burning of solid samples within the Microgravity Science Glovebox (MSG) aboard the International Space Station (ISS). A video camera with a data overlay and a 35-mm still camera record the combustion events. The controls (ignition, fan speed, etc.) are operated by an astronaut while the principal investigator team monitors the experiment from the ground and communicates directly with the astronaut. For the first time on ISS, BASS–II utilized MSG working volume dilution with gaseous N2. We developed a perfectly stirred reactor model to determine the N2 flow time and flow rate to obtain the desired reduced O2 concentration in the working volume for each test. We calibrated the model with the Compound Specific Analyzer-Combustion Products (CSA-CP) O2 readings offset using the Major Constituents Analyzer reading of the ISS ambient atmosphere data for that day. This worked out extremely well for operations, and added a new vital variable, ambient O2 level, to our test matrices. The main variables tested in BASS–II were ambient O2 concentration, ventilation flow velocity, and fuel type, thickness, and geometry. BASS–II also utilized the onboard CSA-CP for O2 and CO readings, and the Carbon Dioxide Monitor for CO2 readings before and after each test. Readings from these sensors allow us to evaluate the completeness of the combustion. The O2 and CO2 readings before and after each test were analyzed and compared very well to stoichiometric ratios for a one-step gas-phase reaction. The CO versus CO2 followed a linear trend for some datasets, but not for all the different geometries of fuel and flow tested. We calculated the heat release rates during each test from the O2 consumption and burn times, using the constant 13.1 kJ of heat released per gram of O2 consumed. The results showed that most of the tests had heat release rates well below 100 W. Lastly, the global equivalence ratio for the tests is estimated to be fuel rich, 1.3 on average using mass loss and O2 consumption data.

Microgravity↗

DOE OSTI2024

Prediction of Distributed River Sediment Respiration Rates Using Community-Generated Data and Machine Learning

River sediment microbial respiration is a key indicator of ecosystem functioning and the biogeochemical fluxes across this critical zone link surface and subsurface waters. As such, there is tremendous interest in measuring and mapping these respiration rates. Respiration observations are expensive and labor intensive; there is limited data available to the community. An open science, collaborative initiative is collecting samples for respiration rate analysis and multi-scale metadata; this evolving data set is being used for making machine learning (ML) predictions at unsampled sites to help inform continued community engagement. However, it is a challenge to find an optimum configuration for ML models to work with this feature-rich (i.e., 100+ possible input variables) data set. Here, we present results from a two-tiered approach to managing the analysis of this complex data set: (a) a stacked ensemble of models that automatically optimizes hyperparameters and manages the training of many models and (b) feature permutation importance to detect the most important features in the models. The major elements of this workflow are modular, portable, open, and cloud-based thus making this implementation a potential template for other applications. The models developed here predict that sediment organic matter chemistry is one of the most important features for predicting sediment respiration rate. Other larger-scale, important features fall into the categories of climatic, ecological, geological, and fluvial settings. Leveraging these larger-scale features to generate data-driven estimates of river sediment respiration rates reveals spatially consistent but heterogeneous patterns across the river network of the Columbia River Basin.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2013

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

TRMM↗

NASA NTRS1977

Liquid-circulating garment controls thermal balance

Experimental data and mathematical model of human thermoregulatory system have been used to investigate use of liquid-circulatory garment (LCG) to control thermal balance. Model proved useful as accurate simulator of such variables as sweat rate, skin temperature, core temperature, and radiative, evaporative, and LCG heat loss.

Kuznetz, L. H.↗

NASA NTRS1979

HEAO 1 observations of high-energy X-rays from 3C273

The first detection of high energy (13 to 120 keV) X rays from the quasar 3C273, made by the HEAO 1 satellite, is reported. Observations were made with the 13 to 180 keV slat collimated detectors of the high energy X-ray and low energy gamma-ray (A4) experiment during December 1977-January 1978 and June-July 1978. Results are consistent with the previously observed X-ray flux variability on a scale of months. Photon count rates are presented for each of five energy bands and count rate and photon spectra for the June through July 1978 observations are derived. A comparison of the data obtained with that at lower X-ray energies and higher gamma-ray energies indicates that there is an overall spectral steepening from low to high energies and a possible break near 20 keV, which may be due to the gamma rays originating from a different region than that of the X rays.

Primini, F. A.↗

NASA NTRS1978

A comprehensive solar energy system analysis data base in Huntsville, Alabama

The history of a comprehensive solar energy system analysis data base developed by NASA/Marshall Space Flight Center and the University of Alabama is presented, along with its current status. The Marshall Information Retrieval and Data Storage (MIRADS) system was chosen for the data base, and feedback systems were arranged to cope with changes in the needs of the program management for the type of data gathered. The final structure of the data base consists of 22 files divided into 6 topical sections: summaries, climatological, utility rates, architectural, equipment, and economics. The data base offers help to the solar industry in two ways: it provides information and it serves as a model for users trying to establish the climatic and socioeconomic variables they should take into account when they examine a potential market for solar energy equipment.

Goddard, J. P.↗

NASA NTRS1994

TRMM-related research: Tropical rainfall and energy analysis experiment

The overall science objective of the participation in TRMM is the determination of daily rainfall and latent heating in the tropical atmosphere using TRMM and complementary spacecraft observations. The major focus these first three years has been to extend, in space and time, the TRMM satellite observations of rainfall. Observations from TRMM active and passive microwave radiometers will provide the fundamental observations for understanding the hydrological cycle of the tropics. Due to the orbit of the TRMM satellite and the extreme variability of convective rain systems, the TRMM observations provide rainfall estimates representative of a one month period. Monthly mean rainfall rates provide valuable information; however, this time scale limitation neglects the great value of the data towards a better understanding of the physics of tropical convection. Many tropical periodicities will not be characterized by these monthly averages, e.g. diurnal cycles, the 4-6 day easterly waves, and the 30 to 60 day cycle. In the spatial domain, due to its orbit, the TRMM satellite will over-fly many convective systems only once. Indeed, some precipitating systems will not be sampled at all. Observations from geostationary satellites can be used to extend the TRMM observations to smaller time and space scales. Although geostationary satellites cannot probe the interiors of precipitating systems, they do observe their life cycles. To acquire information on cloud water content and rain rate, it is proposed to combine geostationary and other satellite observations with the TRMM satellite measurements.

Suomi, Verner E.↗

NASA NTRS2001

The Role of Mesoscale Variability on Plankton Dynamics in the North Atlantic

The intensive field observational phase of JGOFS in the North Atlantic Ocean has shown the importance of oceanic mesoscale variability on biogeochemical cycles and on the strength of the ocean biological pump. Mesoscale physical dynamics govern the major time/space scales of bulk biological variability (biomass, production, and export). Mesoscale eddies seem to have a strong impact on the ecosystem structure and functioning, but observational evidence is rather limited. For the signature of the mesoscale features to exist in the ecosystem, the comparison of temporal scales of formation and evolution of mesoscale features and reaction of the ecosystem is a key factor. Biological patterns are driven by active changes in biological source and sink terms rather than simply by passive turbulent mixing. A first modelling assessment of the regional balances between horizontal and vertical eddy-induced nutrient supplies in the euphotic zone shows that the horizontal transport predominates over the vertical route in the subtropical gyre, whereas the reverse holds true for the other biogeochemical provinces of the North Atlantic. Presently, despite some difference in numbers, the net impact of modelled eddies yields an enhancement of the biological productivity in most provinces of the North Atlantic Ocean. Key issues remaining include variation on the mesoscale of subsurface particle and dissolved organic matter remineralization, improved knowledge of the ecological response to patterns of variability, synopticity in mesoscale surveys along with refining measures of biogeochemical time/space variability. Eventual success of assimilation of in situ and satellite data, still in its infancy in coupled physical/biogeochemical models, will be crucial to achieve JGOFS synthesis in answering which data are most informative, standing stocks or rates, and which ones are relevant. Depending on which end of the spectrum quantification of the effect of mesoscale features on production and community structure is required, complementary strategies are offered. Either one may choose to increase resolution of models up to the very fine mesoscale features scale (a few kms) for the high end, or to include a parametric representation of eddies for the low end.

Garcon, Veronique C.↗

NASA NTRS2002

The Role of Mesoscale Variability on Plankton Dynamics in the North Atlantic

The intensive field observational phase of JGOFS in the North Atlantic Ocean has shown the importance of oceanic mesoscale variability on biogeochemical cycles and on the strength of the ocean biological pump. Mesoscale physical dynamics govern the major time/space scales of bulk biological variability (biomass, production and export). Mesoscale eddies seem to have a strong impact on the ecosystem structure and functioning, but observational evidence is rather limited. For the signature of the mesoscale features to exist in the ecosystem, the comparison of temporal scales of formation and evolution of mesoscale features and reaction of the ecosystem is a key factor. Biological patterns are driven by active changes in biological source and sink terms rather than simply by passive turbulent mixing. A first modelling assessment of the regional balances between horizontal and vertical eddy-induced nutrient supplies in the euphotic zone shows that the horizontal transport predominates over the vertical route in the subtropical gyre, whereas the reverse holds true for the other biogeochemical provinces of the North Atlantic. Presently. despite some difference in numbers, the net impact of modelled eddies yields an enhancement of the biological productivity in most provinces of the North Atlantic Ocean. Key issues remaining include variation on the mesoscale of subsurface particle and dissolved organic matter remineralization, improved knowledge of the ecological response to patterns of variability, synopticity in mesoscale surveys along with refining measures of biogeochemical time/space variability. Eventual success of assimilation of in situ and satellite data, still in its infancy in coupled physical/biogeochemical models, will be crucial to achieve JGOFS synthesis in answering which data are most informative, standing stocks or rates, and which ones are relevant. Depending on which end of the spectrum quantification of the effect of mesoscale features on production and community structure is required, complementary strategies are offered. Either one may choose to increase resolution of models up to the very fine mesoscale features scale (a few kms) for the high end, or to include a parametric representation of eddies for the low end.

Garcon, Veronique, C.↗

NASA NTRS2005

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

MCKissick, Burnell T.↗

NASA NTRS2011

Development of the Sasquatch Drop Test Footprint Tool

The Crew Exploration Vehicle Parachute Assembly System (CPAS) is the parachute system for NASA s Orion spacecraft. CPAS is currently in the design and testing phase of development. The test program consists of numerous drop tests, wherein a test article rigged with parachutes is extracted or released from an aircraft. During such tests, range safety is paramount, as is the recoverability of the parachutes and test article. It is crucial to establish an aircraft release point that will ensure that the article and all items released from it will land in safe locations. Early in the CPAS project, a legacy tool (previously used on the X-38 project) was used to determine a safe release point and to predict the landing locations (the footprint) of the payload and all released objects. Due to increasing test complexity and the need for a more flexible tool, a new footprint predictor tool, called Sasquatch, was created in MATLAB. This tool takes in a simulated trajectory for the test article, information about all released objects, and atmospheric wind data (simulated or actual) to calculate the trajectories of the released objects. Dispersions are applied to the landing locations of those objects, taking into account the variability of winds, aircraft release point, and object descent rate. A safe aircraft release point is determined based on the landing locations of the payload and released objects. The release point, landing locations, and dispersions are plotted on a simple map of the drop zone for easy reference. To date, Sasquatch has been used for thirteen drop tests. Comparing the predictions with actual test results has allowed for significant improvements in the tool s predictive capabilities, especially the incorporation of a well-correlated horizontal throw model. Intended future improvements to the tool include tighter dispersions on the landing locations, Monte Carlo capability, direct input from trajectory simulations, and a graphical user interface.

Bledsoe, Kristin J.↗

NASA NTRS1991

High-precision timing of millisecond pulsars. II - Astrometry, orbital evolution, and eclipses of PSR 1957 + 20

Pulse time-of-arrival measurements have been acquired for PSR 1957 + 20 on 61 days over a 2.7 yr interval, including the times of 44 eclipse disappearance or reappearance events. The timing data provide a reliable measurement of the pulsar's proper motion, 29 +/- 3 mas/yr, at position angle 216 +/- 6 deg; this direction is in excellent agreement with that suggested by the cometlike shape of a surrounding optical emission nebula. The rate of change of the orbital period has been measured: a surprisingly large (-3.9 +/- 0.9) x 10 exp -11, implying that significant orbital evolution must take place on a time scale of 30 Myr. Finally, the present observations extend the eclipse measurements to higher frequencies and provide better statistics for these highly variable phenomena. The eclipse data are used to compute a column-density profile of free electrons in the outer parts of the eclipsing region, and thereby provide an important glimpse into the material being ablated from the companion star.

Ryba, M. F.↗

NASA NTRS1991

Infrared measurements of HF and HCl total column abundances above Kitt Peak, 1977-1990 - Seasonal cycles, long-term increases, and comparisons with model calculations

The paper deals with hydrogen-chloride and hydrogen-fluoride total column measurements, their estimated long-term rates of increase, seasonal cycles, and variability, deduced from the analysis of a set of high-resolution infrared solar spectra recorded at Kitt Peak. The Kitt Peak observations and methods of analysis are described, the results are presented and compared with previously reported measurements and trends. The data is analyzed by using a multilayer nonlinear least-squares spectral fitting procedure and a consistent set of spectroscopic line parameters. Model-calculated hydrogen-chloride and hydrogen-fluoride total columns obtained with a two-dimensional model are discussed, and the model results are compared with the measured hydrogen-chloride and hydrogen-fluoride total columns, seasonal cycles, and trends. It is pointed out that the observed trends of both molecules are in satisfactory agreement with the model results calculated from emission histories and photooxidation rates for the source molecules.

Rinsland, C. P.↗

DOE OSTI2026

Synthesis of ARM User Facility Surface Rainfall Datasets to Construct a Best Estimate Value Added Product (PrecipBE)

Surface precipitation measurements are essential for Earth system model (ESM) evaluation and understanding cloud processes. An ever-growing need for robust, temporally evolving, and easy-to-use statistical datasets provides motivation for a baseline ground-based precipitation properties data product. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility operates an extensive suite of precipitation instruments with various sensitivities and operating mechanisms, which render the decision of which instrument to use based on one or more fixed thresholds challenging and prone to errors and bias. Using a long-term instrument inter-comparison from a unique per-precipitation event perspective, rather than instantaneous sample comparison, we demonstrate that ARM rainfall-measuring instruments are generally consistent with each other at the statistical level. Inter-instrument deviations at the single event level can be large, especially for specific rainfall event properties such as maximum precipitation rates. A machine-learning (ML) analysis using a random forest regressor indicates that in some cases, depending on instrument, local site climatology, and/or specific deployment configuration, certain atmospheric state variables influence the measured quantities in an unpredictable manner. Thus, a-priori weighting of different instruments does not necessarily lead to more accurate and less biased synthesis of instrument data. These results motivate the design of the ARM precipitation best-estimate (PrecipBE) value-added product, which incorporates all valid precipitation data while considering data quality and other instrument limitations. PrecipBE consists of time series and tabular statistics datasets in an easy-to-use and insightful per-precipitation event format. It provides a large set of precipitation event properties supplemented with ancillary data from ARM datasets that correspond to the detected precipitation events. We describe the PrecipBE algorithm and demonstrate its use via the examination of a single-day output as well as a long-term trend analysis of precipitation events at the ARM Southern Great Plains (SGP) site, covering more than 30 years of data. The trend analysis tentatively suggests a long-term temporal tendency for mainly shorter and less intense precipitation events at the SGP site, but a long-term increase in annual rainfall by more than 36 mm (5 %) per decade. This rainfall trend is catalyzed primarily by more extreme event properties of relatively rare, intense precipitation events, with event total and 1 min maximum precipitation rate at a 1 year timeframe increasing up to 5 mm and 9 mm h −1 (several percent) per decade, respectively. While the currently available PrecipBE datasets (at https://adc.arm.gov/discovery/, last access: 8 December 2025) cover rainfall from multiple ARM deployments up to March 2025, PrecipBE is planned to be expanded to include solid-phase precipitation and will soon become an operational product with a several-day lag from real-time. We invite the ARM user community to leverage this new product and welcome user feedback to further enhance the dataset.

Silber, Israel [Pacific Northwest National Laborat↗

NASA NTRS2001

Correlation and Trend Studies of the Sea Ice Cover and Surface Temperatures in the Arctic

Co-registered and continuous satellite data of sea ice concentrations and surface ice temperatures from 1981 to 1999 are analyzed to evaluate relationships between these two critical climate parameters and what they reveal in tandem about the changing Arctic environment. During the 18-year period, the actual Arctic ice area is shown to be declining at a rate of 3.1 +/- 0.4 % /decade while the surface ice temperature has been increasing at 0.4 +/- 0.2 K /decade. Yearly anomaly maps also show that the ice concentration anomalies are predominantly positive in the 1980s and negative in the 1990s while surface temperature anomalies were mainly negative in the 1980s and positive in the 1990s. The yearly ice concentration and surface temperature anomalies are shown to be highly correlated indicating a strong link especially in the seasonal region and around the periphery of the perennial ice cover. The surface temperature data are also especially useful in providing the real spatial scope of each warming (or cooling) phenomenon that usually extends beyond the boundaries of the sea ice cover. Studies of the temporal variability of the summer ice minimum also reveal that the perennial ice cover has been declining at the rate of 6.6% /decade while the summer surface ice temperature has been increasing at the rate of 1.3 K /decade. Moreover, high year-to-year fluctuations in the minimum ice cover in the 1990s may have caused reductions in average thickness of the Arctic sea ice cover.

Comiso, Josefino C.↗

DOE OSTI2024

Dynamic Modeling and Simulation of a Subcritical Coal-Fired Power Plant under Load-Following Conditions

Dynamic models for power plants that capture realistic general process trends and effects of manipulated variables are needed to improve load-following, while minimizing carbon footprint. In this work, a dynamic modeling approach and simulation results for subcritical coal-fired power plant components are presented. These encompass simulation of the dynamics in the fireside, including the effects of fuel, air combustion, and the dynamics of the entire waterside and power generation sections. This model development enables the simulation and analysis of the important short and long-time scale dynamics of components such as heaters, evaporative loop, and power generation units. Furthermore, additional variables in the power generation section are introduced to improve model accuracy, extending the prediction capability of subcritical power plant models and opening new opportunities for research in operator training, optimization, and advanced model-based controller design that are based on these models. The change in process gain for different ramp rates associated with disturbance signals that affect process variables is also explored and a correlation developed. This provides opportunities to study disturbance rejection control implementation and adaptation for scenarios with such variations in ramp rates. The prediction capabilities of selected components are compared to data available in literature, with the obtained root mean squared error ranges that reflect the model performance and quality of predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗