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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Spatial Variation of Methane and Other Trace Gases Detected on Mars: Interpretation with a General Circulation Model

Several teams have recently reported the detection of methane in the Martian atmosphere [1-3]. Although the detection is at the limit of the instrument capacities, one of the most surprising findings by some of these teams is the apparent strong spatial variations observed in spite of the fact that a gas like methane was expected to have a relatively long lifetime in the Martian atmosphere and thus be well mixed. To better quantitatively understand how such spatial variations can form on Mars, we have performed multiple realistic 3D general circulation model simulations in which gases with different sources, lifetime or sinks are released and transported in the Martian atmosphere.

Forget, F.↗
DOE OSTI2024

Toward Enhancing Wastewater Treatment with Resource Recovery in Integrated Assessment and Computable General Equilibrium Models

Sustainable water management is essential to increasing water availability and decreasing water pollution. The wastewater sector is expanding globally and beginning to incorporate technologies that recover nutrients from wastewater. Nutrient recovery increases energy consumption but may reduce the demand for nutrients from virgin sources. We estimate the increase in annual global energy consumption (1,100 million GJ) and greenhouse gas emissions (84 million t CO2e) for wastewater treatment in the year 2030 compared to today’s levels to meet sustainable development goals. To capture these trends, integrated assessment and computable general equilibrium models that address the energy-water nexus must evolve. We reviewed 16 of these models to assess how well they capture wastewater treatment plant energy consumption and GHG emissions. Only three models include biogas production from the wastewater organic content. Four explicitly represent energy demand for wastewater treatment, and eight include explicit representation of wastewater treatment plant greenhouse gas emissions. Of those eight models, six models quantify methane emissions from treatment, five include representation of emissions of nitrous oxide, and two include representation of emissions of carbon dioxide. Our review concludes with proposals to improve these models to better capture the energy-water nexus associated with the evolving wastewater treatment sector.

42 ENGINEERING↗
NASA NTRS1999

Seasonal Water Transport in the Atmosphere of Mars: Applications of a Mars General Circulation Model Using Mars Global Surveyor Data

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. We present below a summary of progress made during the duration of this JRI. The focus of this JRI has been to investigate seasonal water vapor transport in the atmosphere of Mars and its effects on the planet's present climate. To this end, the primary task has been to adapt a new dynamical processor for the adiabatic tendencies of the atmospheric circulation into the NASA Ames Mars general circulation model (MGCM). Using identical boundary and initial conditions, several comparative tests between the new and old MGCMs have been performed and the nature of the simulated circulations have been diagnosed. With confidence that the updated version of the Ames MGCM produces quite similar mean and eddy circulation statistics, the new climate model is well poised as a tool to pursue fundamental questions related to the spatial and seasonal variations of atmospheric water vapor on Mars, and to explore exchanges of water with non-atmospheric reservoirs and transport within its atmosphere. In particular, the role of surface sources and sinks can be explored, the range of water-vapor saturation altitudes can be investigated, and plausible precipitation mechanisms can be studied, for a range of atmospheric dust loadings, such future investigations can contribute to a comprehensive study of surface inventories, exchange mechanisms, and the relative importance of atmospheric transport Mars' water cycle. A listing of presentations made and manuscripts submitted during the course of this project is provided.

Hollingsworth, Jeffery L.↗
NASA NTRS1999

Seasonal Water Transport in the Atmosphere of Mars: Applications of a Mars General Circulation Model Using Mars Global Surveyor Data

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. We present below a summary of progress made during the duration of this JRI. The focus of this JRI has been to investigate seasonal water vapor transport in the atmosphere of Mars and its effects on the planet's present climate. To this end, the primary task has been to adapt a new dynamical processor for the adiabatic tendencies of the atmospheric circulation into the NASA Ames Mars general circulation model (MGCM). Using identical boundary and initial conditions, several comparative tests between the new and old MGCMs have been performed and the nature of the simulated circulations have been diagnosed. With confidence that the updated version of the Ames MGCM produces quite similar mean and eddy circulation statistics, the new climate model is well poised as a tool to pursue fundamental questions related to the spatial and seasonal variations of atmospheric water vapor on Mars, and to explore exchanges of water with non-atmospheric reservoirs and transport within its atmosphere. In particular, the role of surface sources and sinks can be explored, the range of water-vapor saturation altitudes can be investigated, and plausible precipitation mechanisms can be studied, for a range of atmospheric dust loadings. Such future investigations can contribute to a comprehensive study of surface inventories, exchange mechanisms, and the relative importance of atmospheric transport Mars' water cycle. A listing of presentations made and manuscripts submitted during the course of this project is provided.

Hollingsworth, Jeffery L.↗
NASA NTRS1994

A general circulation model study of the climatic effect of observed stratospheric ozone depletion between 1980 and 1990

The total ozone mapping spectrometer (TOMS) and stratospheric aerosol and gas experiment (SAGE) measurements show a significant reduction in the stratospheric ozone over the middle and high latitudes of both hemispheres between the years 1979 and 1991 (WMO, 1992). This change in ozone will effect both the solar and longwave radiation with climate implications. However, recent studies (Ramaswamy et al., 1992; WMO, 1992) indicate that the net effect depends not only on latitudes and seasons, but also on the response of the lower stratospheric temperature. In this study we use a general circulation model (GCM) to calculate the climatic effect due to stratospheric ozone depletion and compare the effect with that due to observed increases of trace gases CO2, CH4, N2O, and CFC's for the period 1980-1990. In the simulations, we use the observed changes in ozone derived from the TOMS data. The GCM used is a version of the NCAR community climate model referenced in Wang et al. (1991). For the present study we run the model in perpetual January and perpetual July modes in which the incoming solar radiation and climatological sea surface temperatures are held constant.

Dudek, Michael P.↗
NASA NTRS1981

Preliminary regime diagram on a sphere with a simplified general circulation model

Numerical model studies useful design considerations and which can be accumulated to form the body of basic knowledge necessary for application of the atmospheric general circulation experiment (AGCE) data to understanding of atmospheric problems are reported. The most efficient way to obtain a computer model suitable for this objective is to modify an existing general circulation model (GCM) of the atmosphere rather than to develop such a model from first principles. The GCM and its modification is outlined.

Pitcher, E. J.↗
NASA NTRS1982

Models for evaluating the performability of degradable computing systems

Recent advances in multiprocessor technology established the need for unified methods to evaluate computing systems performance and reliability. In response to this modeling need, a general modeling framework that permits the modeling, analysis and evaluation of degradable computing systems is considered. Within this framework, several user oriented performance variables are identified and shown to be proper generalizations of the traditional notions of system performance and reliability. Furthermore, a time varying version of the model is developed to generalize the traditional fault tree reliability evaluation methods of phased missions.

Wu, L. T.↗
NASA NTRS1992

Astronomical variation experiments with a Mars general circulation model

In time scales of a hundred thousand to a million years, the eccentricity of Mars orbit varies in a quasi-periodic manner between extremes as large as 0.14 and as small as 0 and the tilt of its axis of rotation with respect to the orbit normal also varies quasi-periodically between extremes as large as 35 deg and as small as 15 deg. In addition, the orientation of the axis precesses on comparable time scales. These astronomical variations are much more extreme than those experienced by the Earth. These variations are thought to have strongly modulated the seasonal cycles of dust, carbon dioxide, and water. One manifestation of the induced quasiperiodic climate changes may be the layered terrain of the polar regions, with individual layers perhaps recording variations in the absolute and/or relative deposition rates of dust and water in the polar regions, most likely in association with the winter time deposition of carbon dioxide ice. In an attempt to understand the manner in which atmospheric temperatures and winds respond to the astronomical forcings, we have initiated a series of numerical experiments with the NASA/Ames general circulation model of the Martian Atmosphere.

Pollack, J. B.↗
NASA NTRS1978

Experiments in monthly mean simulation of the atmosphere with a coarse-mesh general circulation model

The Hansen atmospheric model was used to compute five monthly forecasts (October 1976 through February 1977). The comparison is based on an energetics analysis, meridional and vertical profiles, error statistics, and prognostic and observed mean maps. The monthly mean model simulations suffer from several defects. There is, in general, no skill in the simulation of the monthly mean sea-level pressure field, and only marginal skill is indicated for the 850 mb temperatures and 500 mb heights. The coarse-mesh model appears to generate a less satisfactory monthly mean simulation than the finer mesh GISS model.

Lutz, R. J.↗
NASA NTRS1989

Generalized mathematical models in design optimization

The theory of optimality conditions of extremal problems can be extended to problems continuously deformed by an input vector. The connection between the sensitivity, well-posedness, stability and approximation of optimization problems is steadily emerging. The authors believe that the important realization here is that the underlying basis of all such work is still the study of point-to-set maps and of small perturbations, yet what has been identified previously as being just related to solution procedures is now being extended to study modeling itself in its own right. Many important studies related to the theoretical issues of parametric programming and large deformation in nonlinear programming have been reported in the last few years, and the challenge now seems to be in devising effective computational tools for solving these generalized design optimization models.

Papalambros, Panos Y.↗
DOE OSTI2024

SDYN-GANs: Adversarial learning methods for multistep generative models for general order stochastic dynamics

We introduce adversarial learning methods for data-driven generative modeling of dynamics of nth-order stochastic systems. Our approach builds on Generative Adversarial Networks (GANs) with generative model classes based on stable m-step stochastic numerical integrators. From observations of trajectory samples, we introduce methods for learning long-time predictors and stable representations of the dynamics. Our approaches use discriminators based on Maximum Mean Discrepancy (MMD), training protocols using both conditional and marginal distributions, and methods for learning dynamic responses over different time-scales. We show how our approaches can be used for modeling physical systems to learn force-laws, damping coefficients, and noise-related parameters. Our adversarial learning approaches provide methods for obtaining stable generative models for dynamic tasks including long-time prediction and developing simulations for stochastic systems.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2025

Challenges in predicting protein-protein interactions of understudied viruses: Arenavirus-human interactions

Understanding protein-protein interactions (PPIs) between viruses and host organisms is crucial for uncovering infection mechanisms and identifying potential therapeutic targets. The ability to generalize PPI predictive models across understudied viruses presents a significant challenge. In this work, we use arenavirus-human PPIs to illustrate the difficulties associated with model generalization, which are compounded by a lack of both positive and negative data. We employ a Transfer Learning approach to investigate arenavirus-human PPIs by utilizing models trained on better-studied virus-human and human-human PPIs. Additionally, we curate and assess four types of negative sampling datasets to evaluate their impact on model performance. Despite the overall high accuracies (93–99 %) and AUPRC scores (0.8–0.9) appearing promising, further analysis indicates that these performance metrics can be misleading due to data leakage, data bias, and overfitting, especially concerning under-represented viral proteins. We reveal these gaps and assess the impact of data imbalance using standard k-fold cross-validation and Independent Blind Testing with a Balanced Dataset, resulting in a drop in accuracy below 50 %. We propose a viral protein-specific evaluation framework that categorizes viral proteins into majority and minority classes based on their representation in the dataset, enabling comparison of model performance across these groups using balanced accuracies. This framework offers a more robust evaluation of model generalizability, addressing biases inherent in standard evaluation techniques and paving the way for more reliable PPI prediction models for understudied viruses.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

The simulated features of heliospheric cosmic-ray modulation with a time-dependent drift model. I - General effects of the changing neutral sheet over the period 1985-1990

A time-dependent drift model is used to simulate the heliospheric modulation of galactic cosmic rays, with emphasis on the effects of the wavy heliospheric neutral sheet (HNS) as a function of time during the period 1985-1990. The model predicted a clearly defined time difference between the time when minimum modulation occurred at earth and at radial distances farther away from the sun, indicating that the HNS plays an important part in establishing this observed time delay. The movements of the Voyager 1 and 2 and Pioneer 10 spacecraft were simulated in order to calculate instantaneous radial and latitudinal gradients. The time dependencies of these gradients were found to follow the observations well. The model study indicates that the HNS cannot be ignored, especially during periods of low to moderate solar activity, when the modulation of cosmic rays is described.

Potgieter, M. S.↗
DOE OSTI2025

Unsupervised Process Anomaly Detection and Identification Using the Leave-One-Variable-Out Approach

Automated anomaly detection and identification can signal equipment issues and pinpoint causes in large-scale industrial systems. For systems with limited failure history, unsupervised machine learning methods can be utilized as they do not require past failures. This study introduces the leave-one-variable-out (LOVO) model, which masks one variable at a time to predict the others, learning underlying process correlations. Detection performance was assessed with synthetic and experimental data, while identification performance used only synthetic data due to its ability to generate labeled anomaly types. For detection using synthetic data, the LOVO model generally outperformed comparative models; while using experimental data, the comparative methods outperformed the LOVO model. However, the comparative methods required selecting a latent size, and these conclusions pertain to using the optimal size. In practice, it would not be feasible to always select the optimal value, and incorrect selections impacted performance. In contrast, the LOVO model does not require a latent space. For identification using synthetic data, the LOVO model was slightly outperformed in interpretability and repeatability but still demonstrated impressive results. These outcomes suggest that the LOVO model is an effective model and may be more easily implemented without the challenging tuning process of selecting a latent size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1971

Characterization of impulse noise and analysis of its effect upon correlation receivers

A noise model is formulated to describe the impulse noise in many digital systems. A simplified model, which assumes that each noise burst contains a randomly weighted version of the same basic waveform, is used to derive the performance equations for a correlation receiver. The expected number of bit errors per noise burst is expressed as a function of the average signal energy, signal-set correlation coefficient, bit time, noise-weighting-factor variance and probability density function, and a time range function which depends on the crosscorrelation of the signal-set basis functions and the noise waveform. A procedure is established for extending the results for the simplified noise model to the general model. Unlike the performance results for Gaussian noise, it is shown that for impulse noise the error performance is affected by the choice of signal-set basis functions and that Orthogonal signaling is not equivalent to On-Off signaling with the same average energy.

Houts, R. C.↗
NASA NTRS1977

The effect of clear-air turbulence on a model of the general circulation of the atmosphere

Mixing coefficients due to clear-air turbulence are estimated from turbulence observations from aircraft, and from large-scale dissipation estimates from the large-scale energy budgets. Maximum coefficients occur near middle-latitude jet streams, and eddy viscosity there is of order of 10 sq m/sec; eddy conductivity is estimated to be about ten times smaller. These coefficients are introduced into the 12-layer general circulation model of the National Center of Atmospheric Research. They produce an apparently significant, though small reduction in maximum speed of the jet, and a reduction in eddy energy. Further, the stratospheric polar-night jet is produced at about the correct location with about the correct intensity.

Heck, W. J.↗
NASA NTRS1981

Durability/life of fiber composites in hygrothermomechanical environments

Statistical analysis and multiple regression were used to determine and quantify the significant hygrothermomechanical variables which infuence the tensile durability/life (cycle loading, fatigue) of boron-fiber/epoxy-matrix (B/E) and high-modulus-fiber/epoxy-matrix (HMS/E) composites. The use of the multiple regression analysis reduced the variables from fifteen, assumed initially, to six or less with a probability of greater than 0.999. The reduced variables were used to derive predictive models for compression an intralaminar shear durability/life of B/E and HMS/E composites assuming isoparametric fatigue behavior. The predictive models were subsequently generalized to predict the durability/life of graphite-fiber-r generalized model is of simple form, predicts conservative values compared with measured data and should be adequate for use in preliminary designs.

Chamis, C. C.↗
NASA NTRS1982

Durability/life of fiber composites in hygrothermomechanical environments

Statistical analysis and multiple regression were used to determine and quantify the significant hygrothermomechanical variables which influence the tensile durability/life (cycle loading, fatigue) of boron-fiber/epoxy-matrix (B/E) and high-modulus-fiber/epoxy-matrix (HMS/E) composites. The use of the multiple regression analysis reduced the variables from fifteen, assumed initially, to six or less with a probability of greater than 0.999. The reduced variables were used to derive predictive models for compression and intralaminar shear durability/life of B/E and HMS/E composites assuming isoparametric fatigue behavior. The predictive models were subsequently generalized to predict the durability/life of graphite/fiber-r generalized model is of simple form, predicts conservative values compared with measured data and should be adequate for use in preliminary designs. Previously announced in STAR as N82-14287

Chamis, C. C.↗