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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Assessing Air-Sea Interaction in the Evolving NASA GEOS Model

In order to understand how the climate responds to variations in forcing, one necessary component is to understand the full distribution of variability of exchanges of heat and moisture between the atmosphere and ocean. Surface heat and moisture fluxes are critical to the generation and decay of many coupled air-sea phenomena. These mechanisms operate across a number of scales and contain contributions from interactions between the anomalous (i.e. non-mean), often extreme-valued, flux components. Satellite-derived estimates of the surface turbulent and radiative heat fluxes provide an opportunity to assess results from modeling systems. Evaluation of only time mean and variability statistics, however only provides limited traceability to processes controlling what are often regime-dependent errors. This work will present an approach to evaluate the representation of the turbulent fluxes at the air-sea interface in the current and evolving Goddard Earth Observing System (GEOS) model. A temperature and moisture vertical profile-based clustering technique is used to identify robust weather regimes, and subsequently intercompare the turbulent fluxes and near-surface parameters within these regimes in both satellite estimates and GEOS-driven data sets. Both model reanalysis (MERRA) and seasonal-to-interannual coupled GEOS model simulations will be evaluated. Particular emphasis is placed on understanding the distribution of the fluxes including extremes, and the representation of near-surface forcing variables directly related to their estimation. Results from these analyses will help identify the existence and source of regime-dependent biases in the GEOS model ocean surface turbulent fluxes. The use of the temperature and moisture profiles for weather-state clustering will be highlighted for its potential broad application to 3-D output typical of model simulations.

Clayson, Carol Anne↗
NASA NTRS1996

Statistical Challenges in Modern Astronomy II

Wavelets are the central idea of a broad framework for thinking about displaying, and analyzing data - not just a new specialized technique. They are localized basis functions that provide an extremely flexible and efficient representation of time series. Current developments in the theory and application of wavelets are yielding powerful multiresolution techniques for the analysis of time series and image data. Wavelet methods can effect noise removal. characterization of stochastic behavior, depiction of power spectrum time-variations, and data compression - for time series data, image data, and data of higher dimensions. I review published applications of wavelets in astronomy.

Scargle, Jeffrey D.↗
DOE OSTI2026

Performance evaluation of CMIP6 models on the Arctic-Siberian Plain teleconnection affecting the East Asian heat waves

The frequency and intensity of summer heat waves in East Asia have increased sharply in recent decades, significantly impacting public health and the economy. The Arctic-Siberian Plain (ASP) teleconnection pattern has been identified as a key driver, with ASP warming amplifying atmospheric circulation patterns conducive to extreme temperatures. This study evaluates the ability of Coupled Model Inter-comparison Project phase 6 models to simulate the ASP pattern across interannual variability (IAV) and intra-seasonal variability (ISV) timescales using the Common Basis Function method. The multi-model mean shows statistically significant pattern correlations with ERA5 reanalysis, with correlation coefficients of 0.90 and 0.99 for IAV and ISV, respectively. While the ASP pattern is generally well captured, models exhibit substantial inter-model diversity in the intensity and position of anticyclonic anomalies over the ASP and East Asia. Models with ASP pattern variability similar to reanalysis better reproduce extreme East Asian temperatures, whereas those over- or underestimating ASP variability exhibit lower skill. These performance differences are related to differences in simulating key variables associated with the development of the ASP pattern. Our findings highlight the role of the ASP pattern in modulating extreme heat events, as models with improved ASP simulations align more closely with observed temperature extremes. Refining ASP representations in models could enhance seasonal heat wave predictions, improving climate adaptation strategies.

Arctic-Siberian Plain (ASP)↗
DOE OSTI2021

Classification and computation of extreme events in turbulent combustion

In the design of practical combustion systems, ensuring safety and reliability is an important requirement. For instance, reliably avoiding lean blowout, flame flashback or inlet unstart is critical for ensuring safe operation. Currently, the science of predicting such events is based on prior experience, limited modeling or diagnostic tools and purely statistical approaches. Even though computational and experimental tools for studying combustion devices have vastly advanced in the last three decades, the analysis of such failure events has not been pursued widely. While the use of data for model development and calibration is being widely accepted, the extension to failure events introduces numerous challenges. In particular, the focus here is on so-called data-poor problems, where the cost of generating data is extremely high and is not easily amenable to existing computational and experimental approaches. Data-poor problems are particularly relevant when related to extreme events (also called anomalous events) that can lead to catastrophic failure of the system. It is argued that transient events that describe such failure can have different causal mechanisms. To develop the scientific inference process, a classification of such problems is used to determine specific modeling paths as well as computational tools needed. Research opportunities in the emerging field of extreme event prediction are highlighted in order to identify critical and immediate needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Effect of dust on rainfall over the Red Sea coast based on WRF-Chem model simulations

Water is the single most important element of life. Rainfall plays an important role in the spatial and temporal distribution of this precious natural resource, and it has a direct impact on agricultural production, daily life activities, and human health. One of the important elements that govern rainfall formation and distribution is atmospheric aerosol, which also affects the Earth's radiation balance and climate. Therefore, understanding how dust compositions and distributions affect the regional rainfall pattern is crucial, particularly in regions with high atmospheric dust loads such as the Middle East. Although aerosol and rainfall research has garnered increasing attention as both an independent and interdisciplinary topic in the last few decades, the details of various direct and indirect pathways by which dust affects rainfall are not yet fully understood. Here, we explored the effects of dust on rainfall formation and distribution as well as the physical mechanisms that govern these phenomena, using high-resolution WRF-Chem simulations (~1.5 km × 1.5 km) configured with an advanced double-moment cloud microphysics scheme coupled with a sectional eight-bin aerosol scheme. Our model-simulated results were realistic, as evaluated from multiple perspectives including vertical profiles of aerosol concentrations, aerosol size distributions, vertical profiles of air temperature, diurnal wind cycles, and spatio-temporal rainfall patterns. Rainfall over the Red Sea coast is mainly caused by warm rain processes, which are typically confined within a height of ~6 km over the Sarawat mountains and exhibit a strong diurnal cycle that peaks in the evening at approximately 18:00 local time under the influence of sea breezes. Numerical experiments indicated that dust could both suppress or enhance rainfall. The effect of dust on rainfall was calculated as total, indirect, and direct effects, based on 10-year August-average daily-accumulated rainfall over the study domain covering the eastern Red Sea coast. For extreme rainfall events (domain-average daily-accumulated rainfall of ≥ 1.33 mm), the net effect of dust on rainfall was positive or enhancement (6.05 %), with the indirect effect (4.54 %) and direct effect (1.51 %) both causing rainfall increase. At a 5 % significance level, the total and indirect effects were statistically significant whereas the direct effect was not. For normal rainfall events (domain-average daily-accumulated rainfall < 1.33 mm), the indirect effect enhanced rainfall (4.76 %) whereas the direct effect suppressed rainfall (-5.78 %), resulting in a negative net suppressing effect (-1.02 %), all of which were statistically significant. We investigated the possible physical mechanisms of the effects and found that the rainfall suppression by dust direct effects was mainly caused by the scattering of solar radiation by dust. The surface cooling induced by dust weakens the sea breeze circulation, which decreases the associated landward moisture transport, ultimately suppressing rainfall. For extreme rainfall events, dust causes net rainfall enhancement through indirect effects as the high dust concentration facilitates raindrops to grow when the water vapor is sufficiently available. Our results have broader scientific and environmental implications. Specifically, although dust is considered a problem from an air quality perspective, our results highlight the important role of dust on sea breeze circulation and associated rainfall over the Red Sea coastal regions. Our results also have implications for cloud seeding and water resource management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Pairing statistics for infrared-luminous galaxies

A knowledge of the pairing fraction of IR-selected galaxies is important in understanding the role of interactions in star formation and nuclear activity. It is clear that interactions are extremely common among the most IR-luminous systems, but results have been inconsistent for less luminous systems; this may result from using peculiar morphology as an indicator of an interaction. Since features associated with milder interactions (e.g., tidal tails) tend to be faint, their detection necessarily depends on the depth of the survey used to identify interacting pairs. We present a sample of IR- and optically-selected galaxies for which we have computed pairing fractions using strictly geometrical, quantitative criteria. For the analysis we used a likelihood ratio technique developed by Keel and van Soest (1992). We find that the pairing fraction for IR-selected galaxies is roughly 30 percent, comparable to that found by Keel and van Soest for optically-selected starbursts. We also detect a strong correlation (r above 0.99) between the 60 micron luminosity of a galaxy sample and its pairing fraction. We conclude that although tidal interactions do not guarantee enhanced activity (AGN or starburst), they can amplify internal properties that would feed such activity.

Gallimore, J. F.↗
DOE OSTI2025

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Abstract Machine‐learning (ML) parameterizations of subgrid processes (here of turbulence, convection, and radiation) may one day replace conventional parameterizations by emulating high‐resolution physics without the cost of explicit simulation. However, uncertainty about the relationship between offline and online performance (i.e., when integrated with a large‐scale general circulation model) hinders their development. Much of this uncertainty stems from limited sampling of the noisy, emergent effects of upstream ML design decisions on downstream online hybrid simulation. Our work rectifies the sampling issue via the construction of a semi‐automated, end‐to‐end pipeline for size ensembles of hybrid simulations, revealing important nuances in how systematic reductions in offline error manifest in changes to online error and online stability. For example, removing dropout and switching from a Mean Squared Error to a Mean Absolute Error loss both reduce offline error, but they have opposite effects on online error and online stability. Other design decisions, like incorporating memory, converting moisture input from specific humidity to relative humidity, using batch normalization, and training on multiple climates do not come with any such compromises. Finally, we show that ensemble sizes of may be necessary to reliably detect causally relevant differences online. By enabling rapid online experimentation at scale, we can empirically settle debates regarding subgrid ML parameterization design that would have otherwise remained unresolved in the noise.

Lin, Jerry [Department of Earth System Sciences Un↗
DOE OSTI2021

Efficient numerical method for evaluating normal and anomalous time-domain equilibrium Green's functions in inhomogeneous systems

In this work we develop EPOCH (equilibrium propagator by orthogonal polynomial chain), a computationally efficient method to calculate the time-dependent equilibrium Green's functions, including the anomalous Green's functions of superconductors, to capture the time evolution in large inhomogeneous systems. The EPOCH method generalizes the Chebyshev wave-packet propagation method from quantum chemistry and efficiently incorporates the Fermi-Dirac statistics that is needed for equilibrium quantum condensed matter systems. The computational cost of EPOCH scales only linearly in the system degrees of freedom, generating an extremely efficient algorithm also for very large systems. We demonstrate the power of the EPOCH method by calculating the time evolution of an excitation near a superconductor–normal metal interface in two and three dimensions, capturing transmission as well as normal and Andreev reflections.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Static and dynamic properties of multi-ionic plasma mixtures

Complex plasma mixtures with three or more components are often encountered in astrophysics or in inertial confinement fusion (ICF) experiments. For mixtures containing species with large differences in atomic number Z, the modeling needs to consider at the same time the kinetic theory for low-Z elements combined with the theory of strongly coupled plasma for high-Z elements, as well as all the intermediate situations that can appear in multi-component systems. For such cases, we study the pair distribution functions, self-diffusions, mutual diffusion and viscosity for ternary mixtures at extreme conditions. These quantities can be produced from first principles using orbital free molecular dynamics at the computational expense of very intensive simulations to reach good statistics. Utilizing the first-principles results as reference data, we assess the merit of a global analytic model for transport coefficients, "Pseudo-Ions in Jellium" (PIJ), based on an iso-electronic assumption (iso-n e ). With a multi-component hypernetted-chain integral equation, we verify the quality of the iso-n e prescription for describing the static structure of the mixtures. This semi-analytical modeling compares well with the simulation results and allows one to consider plasma mixtures not accessible to simulations. Further, applications are given for the mix of materials in ICF experiments. A reduction of a multicomponent mixture to an effective binary mixture is also established in the hydrodynamic limit and compared with PIJ estimations for ICF relevant mixtures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Optimal Power Flow With State Estimation in the Loop for Distribution Networks

Here in this article, we propose a framework for running optimal control-estimation synthesis in distribution networks. Our approach combines a primal-dual gradient-based optimal power flow solver with a state estimation feedback loop based on a limited set of sensors for system monitoring, instead of assuming exact knowledge of all states. The estimation algorithm reduces uncertainty on unmeasured grid states based on certain online state measurements and noisy "pseudomeasurements." We analyze the convergence of the proposed algorithm and quantify the statistical estimation errors based on a weighted least-squares estimator. The numerical results on a 4521-node network demonstrate that this approach can scale to extremely large networks and provide robustness to both large pseudomeasurement variability and inherent sensor measurement noise.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1986

The effect of Cr, Co, Al, Mo and Ta on a series of cast Ni-base superalloys on the stability of an aluminide coating during cyclic oxidation in Mach 0.3 burner rig

The influence of varying the content of Co, Cr, Mo, Ta, and Al in a series of cast Ni-based gamma/gamma'superalloys on the behavior of aluminide coatings was studied in burner rig cyclic oxidation tests at 1100 C. The alloys had nominally fixed levels of Ti, W, Cb, Zr, C, and B. The alloy compositions were based on a full 2(sup 5)-fractional statistical design supplemented by 10 star point alloys and a center point alloy. This full central composite design of 43 alloys plus two additional alloys with extreme Al levels allowed a complete second degree estimating equation to be derived from the 5-compositional variables. The weight change/time data for the coated samples fitted well to the paralinear oxidation model and enabled a modified oxidation attack parameter, K'(sub a) to be derived to rank the alloys and log K' (sub a ) to be used as the dependent variable in the estimating equation to determine the oxidation resistance of the coating as a function of the underlying alloy content. The most protective aluminide coatings are associated with the highest possible base ally contents of CR and Al and at a 4 percent Ta level. The Mo and Co effects interact but at fixed levels of 0, 5, or 10% Co. A 4% Mo level is optimum.

Zaplatynsky, I.↗
NASA NTRS1987

Hemispheric differences in the morphology of the high latitude ionosphere measured at about 500 km

Ambient electron density measurements made by the radio frequency capacitance probe on Ariel 4 have been analyzed in order to study the structures present at about 500 km altitude at latitudes poleward of + or - 50 deg Lambda during the 1971 Northern Hemisphere winter (December solstice) and the 1972 Southern Hemisphere winter (June solstice); data obtained on 94 days centered on each solstice have been used. The general morphology of, and the extreme densities within, the midlatitude electron density trough, the polar cap depletions, and the electron density enhancements associated with the cusp-auroral zone were determined statistically. Analyses of data acquired during quiet magnetic conditions show that the Northern and Southern Hemisphere winter ionospheres were significantly different; in particular, the Southern Hemisphere densities were lower than those in the Northern Hemisphere. The maximum electron densities observed in the Northern Hemisphere occurred in a magnetic-local-time range symmetrical about the 02-14 MLT meridian, whereas in the Southern Hemisphere the maxima were symmetrical with respect to the midnight-noon magnetic meridian.

Tulunay, Y. K.↗
NASA NTRS1988

Global environmental effects of impact-generated aerosols: Results from a general circulation model

Cooling and darkening at Earth's surface are expected to result from the interception of sunlight by the high altitude worldwide dust cloud generated by impact of a large asteroid or comet, according to the one-dimensional radioactive-convective atmospheric model (RCM) of Pollack et al. An analogous three-dimensional general circulation model (GCM) simulation obtains the same basic result as the RCM but there are important differences in detail. In the GCM simulation the heat capacity of the oceans, not included in the RCM, substantially mitigates land surface cooling. On the other hand, the GCM's low heat capacity surface allows surface temperatures to drop much more rapidly than reported by Pollack et al. These two differences between RCM and GCM simulations were noted previously in studies of nuclear winter; GCM results for comet/asteroid winter, however, are much more severe than for nuclear winter because the assumed aerosol amount is large enough to intercept all sunlight falling on Earth. In the simulation the global average of land surface temperature drops to the freezing point in just 4.5 days, one-tenth the time required in the Pollack et al. simulation. In addition to the standard case of Pollack et al., which represents the collision of a 10-km diameter asteroid with Earth, additional scenarios are considered ranging from the statistically more frequent impacts of smaller asteroids to the collision of Halley's comet with Earth. In the latter case the kinetic energy of impact is extremely large due to the head-on collision resulting from Halley's retrograde orbit.

Covey, C.↗
NASA NTRS1990

Interesting examples of supervised continuous variable systems

The authors analyze two simple deterministic flow models for multiple buffer servers which are examples of the supervision of continuous variable systems by a discrete controller. These systems exhibit what may be regarded as the two extremes of complexity of the closed loop behavior: one is eventually periodic, the other is chaotic. The first example exhibits chaotic behavior that could be characterized statistically. The dual system, the switched server system, exhibits very predictable behavior, which is modeled by a finite state automaton. This research has application to multimodal discrete time systems where the controller can choose from a set of transition maps to implement.

Chase, Christopher↗
NASA NTRS1992

Pervasive variability in the quiet solar transition region

Extreme UV spectroheliograms from an experimental time series are employed to investigate the nature of the quiet solar transition region with respect to temporal variability. A statistical treatment is developed to analyze the fraction of spatial elements that yield intensity variations significantly higher than the signal noise. The EUV intensity in every spatial resolution varies on a time scale of minutes by about 10-30 percent, and the fractional amplitude of the temporal variations is found to be nearly independent of mean intensity. The paper concludes that the quiet solar transition region is probably generated and modulated by small-scale magnetic activity, since the temporal variability in the transition region is spatially uniform and rather pervasive.

Rabin, Douglas↗
NASA NTRS2017

Trajectory Dispersed Vehicle Process for Space Launch System

The Space Launch System (SLS) vehicle is part of NASA's deep space exploration plans that includes manned missions to Mars. Manufacturing uncertainties in design parameters are key considerations throughout SLS development as they have significant effects on focus parameters such as lift-off-thrust-to-weight, vehicle payload, maximum dynamic pressure, and compression loads. This presentation discusses how the SLS program captures these uncertainties by utilizing a 3 degree of freedom (DOF) process called Trajectory Dispersed (TD) analysis. This analysis biases nominal trajectories to identify extremes in the design parameters for various potential SLS configurations and missions. This process utilizes a Design of Experiments (DOE) and response surface methodologies (RSM) to statistically sample uncertainties, and develop resulting vehicles using a Maximum Likelihood Estimate (MLE) process for targeting uncertainties bias. These vehicles represent various missions and configurations which are used as key inputs into a variety of analyses in the SLS design process, including 6 DOF dispersions, separation clearances, and engine out failure studies.

Statham, Tamara↗
DOE OSTI2021

Open-Loop Control of Adjustable Tuned Mass Dampers for Floating Wind Turbine Platforms

In this study, we demonstrate the ability of adjustable tuned mass dampers (TMDs) to reduce the platform motion of floating offshore wind turbines (FOWTs). The TMDs are located in the hull and provide control authority by varying the amount of water ballast and compressed air in a reservoir over time. The optimal TMD settings depend on the wind and wave conditions of the FOWT. We present an open-loop control scheme that changes the TMD natural frequency based on sea state and a simple method for estimating the peak wave period and significant wave height. The performance of this open-loop control is compared to ideal control of the TMDs (set knowing the exact sea state), a TMD with a constant natural frequency targeting the design load case with the greatest platform motion, and a baseline set of simulations of the platform without TMDs. The constant natural frequency case performs nearly as effectively as the actively controlled case, suggesting that the TMDs can be simply designed for extreme load conditions and provide consistent control over a range of environments; however, the methods used to find the optimal TMD parameters and estimate sea state statistics could be used in other aspects of FOWT control and design.

artificial intelligence↗
DOE OSTI2021

Hurricanes alter 10 Be concentrations in tropical river sediment but do not change regional erosion rate estimates

Tropical islands, including many in island arcs, are subjected to recurring disturbances from extreme storms such as tropical cyclones. To test whether such storms influence cosmogenic nuclide concentrations such that they do not reflect long-term rates of erosion, we measured meteoric and in situ 10Be in river sediment samples from Dominica, an andesitic island in the Caribbean, before and after category five Hurricane Maria (2017). Populations of before- and after-storm concentrations are statistically indistinguishable (n=7 pairs for in situ 10 Be, n=11 pairs for meteoric 10 Be). 10 Be concentrations vary from -138% to +73% within before-after sample pairs relative to the mean of the pair. These new data suggest that the effects of extreme storms on the depth and amount of near-surface erosion on Dominica vary spatially. Our data support calculations of Niemi, et al. (2005) and Yanites, et al. (2009) suggesting that basin-by-basin comparisons of erosion rates based on cosmogenic nuclides should be approached with caution in small (<~100 km 2 ) watersheds affected by mass movements and extreme storms. Erosion rates determined from in situ 10Be in Dominica (geometric mean=0.102 mm y-1, n=12) are low compared to similarly steep and wet areas globally and correlate positively with the spatial density of mass movements.

58 GEOSCIENCES↗