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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Reduced Order Model to Predict Dispersion of Flammable Refrigerant into a Space

As the HVAC&R industry mobilizes to deploy more low-GWP refrigerants, relevant standards are being continually reviewed and updated. Those include the general safety standards ISO 5149 and ASHRAE 15, and the equipment standards IEC and UL. The standards systematically set the allowable maximum amount of refrigerant that should be used in different equipment types and different applications. To do so, they rely on predictions of how a leaked refrigerant mass will disperse into a space. Dispersion characteristics, such as total flammable volume and its residence time, determine the risk associated with the presence of the flammable refrigerant. The standards have included provisions for the use of flammable refrigerants for approximately two decades. They relied on limited analytical analyses and test cases in their development. Dispersion of a refrigerant into a space is complex. Computational fluid dynamics (CFD) are the most accurate in predicting a given problem. However, CFD is computationally expensive and requires specialized expertise and resources and is not suitable for use by standards development working group as prediction tool. This paper presents the development of a reduced order model (ROM) that predicts the key dispersion characteristics relevant to the dispersion of a leaked refrigerant into a space for any combination of input variables. The inputs are the refrigerant release height, the total released refrigerant mass and its release flow rate, the refrigerant molecular weight, the ventilation flow rate, the floor area and height of the space, recirculation air flow rate, and the tightness of the space. The outputs are histograms of volume fraction of the room in prescribed concentration bins and the total mass of the refrigerant in each bin normalized by the total refrigerant charge at 13 prescribed simulation time stamps between 1 and 900 seconds. The ROM is constructed from a set of CFD simulations with carefully chosen combinations of input parameters. The selection if done using a multidimensional sparse grid which is a generalization of the classical tensor approach but offers additional flexibility and thus can be more carefully tuned towards a specific model. The tuning is done to improve the accuracy, measured in the difference between the output values of the ROM and the CFD model, while minimizing the computational cost, measured in number of CFD simulations which is orders of magnitude more expensive than the processing the training data.

Edwards, Dean↗
DOE OSTI2025

Simultaneous prediction of structural properties in epitaxially–grown GaN with quantum and conventional multi–output learning algorithms

Hundreds of GaN thin film crystal plasma–assisted molecular beam epitaxy synthesis experiment records spanning two decades were organized into a dataset correlating the growth experiment design parameters with discrete, binary determinations of crystallinity and surface morphology. Conventional data science techniques as well as both quantum and classical multi–output supervised machine learning algorithms were implemented to investigate the relationships between the operating parameter data and the structural figures of merit. Correlation coefficients, decision tree nodes, p–values, and SHAP values all support substrate temperature and gallium effusion cell conditions as being statistically significant for simultaneously influencing GaN crystallinity and surface morphology. Here, a conventional deep neural network learned best from the data, followed by a quantum–classical hybrid gradient boosting algorithm. When combined with calculations of uncertainty intervals based on VennAbers predictors, machine learning predictions of both structural properties show good agreement with results reported in published experimental literature.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Sea Ice Prediction Has Easy and Difficult Years

Arctic sea ice follows an annual cycle, reaching its low point in September each year. The extent of sea ice remaining at this low point has been trending downwards for decades as the Arctic warms. Around the long-term downward trend, however, there is significant variation in the minimum extent from one year to the next. Accurate forecasts of yearly conditions would have great value to Arctic residents, shipping companies, and other stakeholders and are the subject of much current research. Since 2008 the Sea Ice Outlook (SIO) (http://www.arcus.org/search-program/seaiceoutlook) organized by the Study of Environmental Arctic Change (SEARCH) (http://www.arcus.org/search-program) has invited predictions of the September Arctic sea ice minimum extent, which are contributed from the Arctic research community. Individual predictions, based on a variety of approaches, are solicited in three cycles each year in early June, July, and August. (SEARCH 2013).

Years↗
DOE OSTI2021

Phases of the hydrogen isotopes under pressure: metallic hydrogen

Hydrogen is the simplest molecule in nature. One of the key problems and challenges in condensed matter physics is to understand the phases, properties, and structure of hydrogen as a function of pressure and temperature. Over 80 years ago Wigner and Huntington predicted that if solid molecular hydrogen was sufficiently compressed, it would transform to an atomic metal. Later, a second pathway emerged; it was predicted that if heated to high temperatures under pressure it would transform to liquid atomic hydrogen; this form of metallic hydrogen makes up ~90% of the planet Jupiter. The prediction of high temperature superconductivity of solid atomic metallic hydrogen stimulated the experimental community to produce this material . For decades hydrogen defied the experimental efforts to transform it. Using diamond anvil cells, metallic hydrogen has recently been produced at a pressure of ~5 million atmospheres, significantly greater than the pressure at the center of the earth. Liquid atomic metallic hydrogen has been produced at temperatures of a few thousand degrees Kelvin in diamond anvil cells, as well as in dynamic experiments. We review the seemingly simple, but actually complex properties of this quantum solid and metal and the decades of development and progress to achieve this important fundamental result.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Application of molecular convergent close-coupling cross sections in a collisional radiative model for the triplet system of molecular hydrogen

Collisional radiative (CR) models for molecular hydrogen are of high relevance for performing qualitative and quantitative analysis of excited-state population densities measured in plasmas or predicting the dependence of plasma emission on parameter variations. Although the development of such models for H 2 started decades ago, major uncertainties still exist regarding the most important set of input parameters, namely the cross sections for electron-impact excitation. The deviations between cross sections from different datasets are particularly pronounced in the energy region close to the threshold energy, strongly increasing the uncertainty of CR models applied to low-temperature plasmas. This paper presents experimental validation of a set of newly calculated non ro-vibrationally resolved electron-impact cross sections calculated for the triplet system of H 2 using the molecular convergent close-coupling method in the adiabatic-nuclei formulation. These cross sections are implemented into a CR model based on the flexible solver Yacora. A first comparison of CR calculations with the different datasets to experimentally-determined population densities is performed at a planar ICP discharge for varying pressure (between 1 and 10 Pa) and RF power (between 700 and 1100 W). For the experimentally-accessible electron temperature and density range (2.5–10 eV and 1.8–3.3 × 10 16 m –3 , respectively), very good agreement between the model and experiment is obtained using the new data set, in contrast to previously used cross sections.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Kronecker-structured covariance models for multiway data

Many applications produce multiway data of exceedingly high dimension. Modeling such multi-way data is important in multichannel signal and video processing where sensors produce multi-indexed data, e.g. over spatial, frequency, and temporal dimensions. We will address the challenges of covariance representation of multiway data and review some of the progress in statistical modeling of multiway covariance over the past two decades, focusing on tensor-valued covariance models and their inference. We will illustrate through a space weather application: predicting the evolution of solar active regions over time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Efficient high-dimensional variational data assimilation with machine-learned reduced-order models

Abstract. Data assimilation (DA) in geophysical sciences remains the cornerstone of robust forecasts from numerical models. Indeed, DA plays a crucial role in the quality of numerical weather prediction and is a crucial building block that has allowed dramatic improvements in weather forecasting over the past few decades. DA is commonly framed in a variational setting, where one solves an optimization problem within a Bayesian formulation using raw model forecasts as a prior and observations as likelihood. This leads to a DA objective function that needs to be minimized, where the decision variables are the initial conditions specified to the model. In traditional DA, the forward model is numerically and computationally expensive. Here we replace the forward model with a low-dimensional, data-driven, and differentiable emulator. Consequently, gradients of our DA objective function with respect to the decision variables are obtained rapidly via automatic differentiation. We demonstrate our approach by performing an emulator-assisted DA forecast of geopotential height. Our results indicate that emulator-assisted DA is faster than traditional equation-based DA forecasts by 4 orders of magnitude, allowing computations to be performed on a workstation rather than a dedicated high-performance computer. In addition, we describe accuracy benefits of emulator-assisted DA when compared to simply using the emulator for forecasting (i.e., without DA). Our overall formulation is denoted AIEADA (Artificial Intelligence Emulator-Assisted Data Assimilation).

58 GEOSCIENCES↗
NASA NTRS1995

The soft X-ray turnoff of Nova Muscae 1983

Nova GQ Muscae 1983 was detected by ROSAT as a luminous 'supersoft' X-ray source in 1992, nearly a decade after outburst. Further, this is the only classical postnova known to have maintained constant luminosity on a timescale predicted by theoretical models. Follow-up observations were made with the ROSAT position-sensitive proportional counter in 1993 January and September, and complemented with B-band photometry taken in 1993 January. By 1993 January, the X-ray count rate had declined by a factor of 17, while there was neither an appreciable decrease in the optical magnitude nor a change in the amplitude of modulation. In 1993 September the soft X-ray flux was below the ROSAT threshold limit, implying a decrease of a factor greater than or equal to 30 in the count rate. This decline can be interpreted by the turnoff of nuclear processes due to the complete consumption of the residual hydrogen-rich envelope. However, the optical luminosity of the system is not simply coupled to the X-ray luminosity (e.g., through reprocessing).

Shanley, L.↗
NASA NTRS1994

Climatic implications of the seasonal variation of upper troposphere water vapor

Satellite observations indicate that the humidity of the upper troposphere is higher in summer than in winter. We use general circulation model (GCM) simulations to explore the processes that maintain upper troposphere water vapor and determine its seasonal cycle. In the subtropics, drying by Hadley cell subsidence and stratiform condensation is offset primarily by moistening by eddies, with moist convection playing a minor role. Elsewhere, both mean meridional circulation and eddies moisten the upper troposphere and are balanced primarily by stratiform condensation drying. The effect of the seasonal shift of the Hadley cell is limited to latitudes equatorward of 30 deg. At higher latitudes where the largest observed summer moistening occurs, eddy moisture fluxes are primarily responsible despite the eddies being weaker in summer than winter. The same mechanism causes upper level humidity to increase in GCM climate warming simulations. The observed seasonal variation may thus be a good proxy for decadal climate change. This suggests that upper troposphere water vapor feedback is positive at all latitudes, consistent with GCM predictions.

Del Genio, Anthony D.↗
NASA NTRS2008

Air Quality Study Using Satellites - Current Capability and Future Plans

Satellite instruments have had great success in monitoring the stratospheric ozone and in understanding the processes that control its daily to decadal scale variations. This field is now reaching its zenith with a number of satellite instruments from the US, Europe and Canada capping several decades of active research in this field. The primary public policy imperative of this research was to make reliable prediction of increases in biologically active surface UV radiation due to human activity. By contrast retrieval from satellite data of atmospheric constituents and photo-chemically active radiation that affect air quality is a new and growing field that is presenting us with unique challenges in measurement and data interpretation. A key distinction compared to stratospheric sensors is the greatly enhanced role of clouds, aerosols, and surfaces (CAS) in determining the quality and quantity of useful data that is available for air quality research. In our presentation we will use data from several sensors that are currently flying on the A-train satellite constellation, including OMI, MODIS, CLOUDSAT, and CALIPSO, to highlight that CAS can have both positive and negative effects on the information content of satellite measurements. This is in sharp contrast to other fields of remote sensing where CAS are usually considered an interference except in those cases when they are the primary subject of study. Our analysis has revealed that in the reflected wavelengths one often sees much further down into the atmosphere, through most cirrus, than one does in the emitted wavelengths. The lower level clouds provide a nice background against which one can track long-range transport of trace gases and aerosols. In addition, differences in trace gas columns estimated over cloudy and adjacent clear pixels can be used to measure boundary layer trace gases. However, in order to take full advantage of these features it will be necessary to greatly advance our understanding of how CAS affect the radiation at wavelengths that are used to derive the atmospheric constituents that affect air quality as well as the radiation that controls the photolysis of chemically active trace gases. We will discuss how we are using these new insights to design future satellite missions to study air quality.

Bhartia, Pawan K.↗
NASA NTRSDate not supplied

An Overview of Plume-Surface Interaction Testing and Research

NASA has studied rocket plume-surface interactions caused by spacecraft since the Apollo era to reduce risk to landing vehicles. The study of plume-surface interactions is a multi-discipline effort, spanning aerospace engineering to planetary science. Historical testing for Apollo and Viking produced methods, terms, and datasets that influence the field today. Research conducted over the past two decades has expanded our understanding of plume-surface interaction phenomena, but the problem remains resistant to a robust predictive capability. Contemporary experimental and modeling efforts to understand and retire strategic knowledge gaps will be discussed, with a focus on work conducted under NASA’s Plume-Surface Interaction Project and the upcoming Human Landing System Plume-Surface Interaction Risk Reduction Ground Test.

Wesley A Chambers↗
DOE OSTI2024

Accelerating FEM-Based Corrosion Predictions Using Machine Learning

Atmospheric corrosion of metallic parts is a widespread materials degradation phenomena that is challenging to predict given its dependence on many factors (e.g. environmental, physiochemical, and part geometry). For materials with long expected service lives, accurately predicting the degree to which corrosion will degrade part performance is especially difficult due to the stochastic nature of corrosion damage spread across years or decades of service. The Finite Element Method (FEM) is a computational technique capable of providing accurate estimates of corrosion rate by numerically solving complex differential Eqs. characterizing this phenomena. Nevertheless, given the iterative nature of FEM and the computational expense required to solve these complex equations, FEM is ill-equipped for an efficient exploration of the design space to identify factors that accelerate or deter corrosion, despite its accuracy. In this work, a machine learning based surrogate model capable of providing accurate predictions of corrosion with significant computational savings is introduced. Specifically, this work leverages AdaBoosted Decision trees to provide an accurate estimate of corrosion current per width given different values of temperature, water layer thickness, molarity of the solution, and the length of the cathode for a galvanic couple of aluminum and stainless steel.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Quantum prediction of ultra-low thermal conductivity in lithium intercalation materials

Lithium-intercalated layered transition-metal oxides, Li x TMO 2, brought about a paradigm change in rechargeable batteries in recent decades and show promise for use in memristors, a type of device for future neural computing and on-chip storage. Thermal transport properties, although being a crucial element in limiting the charging/discharging rate, package density, energy efficiency, and safety of batteries as well as the controllability and energy consumption of memristors, are poorly managed or even understood yet. Here, for the first time, we employ quantum calculations including high-order lattice anharmonicity and find that the thermal conductivity κ of Li x TMO 2 materials is significantly lower than hitherto believed. More specifically, the theoretical upper limit of κ of LiCoO 2 is 6 W/m-K, 2–6 times lower than the prior theoretical predictions. Delithiation further reduces κ by 40–70% for LiCoO 2 and LiNbO 2 . Grain boundaries, strain, and porosity are yet additional causes of thermal-conductivity reduction, while Li-ion diffusion and electrical transport are found to have only a minor effect on phonon thermal transport. The results elucidate several long-standing issues regarding the thermal transport in lithium-intercalated materials and provide guidance toward designing high-energy-density batteries and controllable memristors.

25 ENERGY STORAGE↗
NASA NTRS2020

Supersonic Technology Concept Aeroplanes for Environmental Studies

The International Civil Aviation Organization is considering new environmental standards for future supersonic civil aircraft. NASA is supporting this effort by analyzing several notional, near-term supersonic transports. NASA’s performance, noise, and exhaust emission predictions for these transports are being used to inform a larger study that will determine the global environmental and economic impact of adding supersonic aircraft to the fleet beginning this decade. A supersonic business jet with a maximum takeoff gross weight of 55 tonnes is the focus of this paper. A smaller business jet weighing 45 tonnes is also discussed. Both airplanes use supersonic engines derived from a common contemporary commercial subsonic turbofan core. Aircraft performance, airport-vicinity noise, and exhaust emissions are predicted using NASA tools. Also investigated are some of the anticipated behaviors and requirements of these aircraft in the commercial airspace. The sensitivity of noise to system uncertainties is presented and alternative engine studies are discussed.

Berton, Jeffrey J.↗
NASA NTRS2021

Sensitivity of modeled Indian monsoon to Chinese and Indian aerosol emissions

The South Asian summer monsoon supplies over 80 % of India's precipitation. Industrialization over the past few decades has resulted in severe aerosol pollution in India. Understanding monsoonal sensitivity to aerosol emissions in general circulation models (GCMs) could improve predictability of observed future precipitation changes. The aims here are (1) to assess the role of aerosols in India's monsoon precipitation and (2) to determine the roles of local and regional emissions. For (1), we study the Precipitation Driver Response Model Intercomparison Project experiments. We find that the precipitation response to changes in black carbon is highly uncertain with a large intermodel spread due in part to model differences in simulating changes in cloud vertical profiles. Effects from sulfate are clearer; increased sulfate reduces Indian precipitation, a consistency through all of the models studied here. For (2), we study bespoke simulations, with reduced Chinese and/or Indian emissions in three GCMs. A significant increase in precipitation (up to ∼20 %) is found only when both countries' sulfur emissions are regulated, which has been driven in large part by dynamic shifts in the location of convective regions in India. These changes have the potential to restore a portion of the precipitation losses induced by sulfate forcing over the last few decades.

Indian monsoons↗
NASA NTRS2010

Roles of Engineering Correlations in Hypersonic Entry Boundary Layer Transition Prediction

Efforts to design and operate hypersonic entry vehicles are constrained by many considerations that involve all aspects of an entry vehicle system. One of the more significant physical phenomenon that affect entry trajectory and thermal protection system design is the occurrence of boundary layer transition from a laminar to turbulent state. During the Space Shuttle Return To Flight activity following the loss of Columbia and her crew of seven, NASA's entry aerothermodynamics community implemented an engineering correlation based framework for the prediction of boundary layer transition on the Orbiter. The methodology for this implementation relies upon the framework of correlation techniques that have been in use for several decades. What makes the Orbiter boundary layer transition correlation implementation unique is that a statistically significant data set was acquired in multiple ground test facilities, flight data exists to assist in establishing a better correlation and the framework was founded upon state of the art chemical nonequilibrium Navier Stokes flow field simulations. The basic tenets that guided the formulation and implementation of the Orbiter Return To Flight boundary layer transition prediction capability will be reviewed as a recommended format for future empirical correlation efforts. The validity of this approach has since been demonstrated by very favorable comparison of recent entry flight testing performed with the Orbiter Discovery, which will be graphically summarized. These flight data can provide a means to validate discrete protuberance engineering correlation approaches as well as high fidelity prediction methods to higher confidence. The results of these Orbiter engineering and flight test activities only serve to reinforce the essential role that engineering correlations currently exercise in the design and operation of entry vehicles. The framework of information-related to the Orbiter empirical boundary layer transition prediction capability will be utilized to establish a fresh perspective on this role, to illustrate how quantitative statistical evaluations of empirical correlations can and should be used to assess accuracy and to discuss what the authors' perceive as a recent heightened interest in the application of high fidelity numerical modeling of boundary layer transition. Concrete results will also be developed related to empirical boundary layer transition onset correlations. This will include assessment of the discrete protuberance boundary layer transition onset data assembled for the Orbiter configuration during post-Columbia Return To Flight. Assessment of these data will conclude that momentum thickness Reynolds number based correlations have superior coefficients and uncertainty in comparison to roughness height based Reynolds numbers, aka Re(sub k) or Re(sub kk). In addition, linear regression results from roughness height Reynolds number based correlations will be evaluated, leading to a hypothesis that non-continuum effects play a role in the processes associated with incipient boundary layer transition on discrete protuberances.

Campbell, Charles H.↗
NASA NTRS2002

Tether Impact Rate Simulation and Prediction with Orbiting Satellites

Space elevators and other large space structures have been studied and proposed as worthwhile by futuristic space planners for at least a couple of decades. In June 1999 the Marshall Space Flight Center sponsored a Space Elevator workshop in Huntsville, Alabama, to bring together technical experts and advanced planners to discuss the current status and to define the magnitude of the technical and programmatic problems connected with the development of these massive space systems. One obvious problem that was identified, although not for the first time, were the collision probabilities between space elevators and orbital debris. Debate and uncertainty presently exist about the extent of the threat to these large structures, one in this study as large in size as a space elevator. We have tentatively concluded that orbital debris although a major concern not sufficient justification to curtail the study and development of futuristic new millennium concepts like the space elevators.

Harrison, Jim↗
NASA NTRSDate not supplied

SPACE: Three Decades of Spacecraft Power Systems Analysis with Fortran

The SPACE (System Power Analysis for Capability Evaluation) Fortran program developed at NASA Glenn Research Center has enabled power generation predictions and energy balance analyses for spacecraft electrical power systems (EPS) since 1988. SPACE was originally designed to analyze the EPS of the Space Station Freedom and continues to support certifications for visiting vehicles and extravehicular activities on the International Space Station today. Another version of SPACE currently supports design and mission planning operations for the Orion and Gateway vehicles as part of NASA’s Artemis program. In total, over 50 engineers have contributed to the development and use of SPACE on various platforms throughout its history. Ongoing code modernization efforts aim to generalize the program for use with different vehicles and configurations. While SPACE team analysts currently interact with the program via the command line, future development work also includes the creation of a graphical user interface for use by flight operations personnel. The SPACE code thus has a long legacy in spacecraft EPS analysis and will continue to play a critical role in future human spaceflight missions by leveraging the computational power of Fortran.

Fortran↗