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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Developing an Air Quality Index for Microgravity Indoor Environments/Space Missions

Indoor pollution sources (on Earth) that release gases or particles into the air are the primary cause of air quality problems in indoor environments. The development of an adequate tool to understand pollution levels in a certain location is of high importance. This tool must be able to inform about the levels of pollution in a simple and understandable way but also, used to take a series of predetermined measures to protect the health of the exposed population. One of the most useful and up to date approaches for characterizing air pollution is the Air Quality Index (AQI). It is an easily-calculated powerful data-driven tool, that summarizes a complex phenomenon, such as air pollution, in straightforward indicators. The AQI system has been developed in different countries around the world, mainly for outdoor environments, based on the results of risk assessments, epidemiology studies, and current local air pollution regulations and standards.Air quality in microgravity indoor environments is of fundamental importance to crew health, with concerns encompassing both gaseous contaminants and particulate matter. Although the concentration of gases in the microgravity indoor environment is well studied, aerosols remain one of the major pollutants that affect air quality and has reported adverse health effects and hasn't been reported under these unique conditions. Earth-based AQIs can't be extrapolated to microgravity indoor environments due to different aerosol characteristics and altered lung deposition in low gravity.Concurrent with the aerosol-focused AQI effort, we assess and document how the process would apply for combining particles & gases into a composite index, with the ability to query each AQI independently. All this information can be combined in a spacecraft-specific AQI for future space missions and habitats. The objective of this work are to determine what areas of expertise will contribute, what research and data will be required, and explore the scope of effort needed to formulate a spacecraft AQI in addition to analyzing ISS aerosol sampling data and incorporate results from both aerosol Sampling experiments (the only relevant data available from space).

Sorek-Hamer, Meytar↗
DOE OSTI2021

Atomic-Level Features for Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics Simulations

The high computational cost of evaluating atomic interactions recently motivated the development of computationally inexpensive kinetic models, which can be parametrized from MD simulations of complex chemistry of thousands of species or other processes and accelerate the prediction of the chemical evolution by up to four order of magnitude. Such models go beyond the commonly employed potential energy surface fitting methods in that they are aimed purely at describing kinetic effects. So far, such kinetic models utilize molecular descriptions of reactions and have been constrained to only reproduce molecules previously observed in MD simulations. Therefore, these descriptions fail to predict the reactivity of unobserved molecules, for example in the case of large molecules or solids. In this work, we propose a new approach for the extraction of reaction mechanisms and reaction rates from MD simulations, namely the use of atomic-level features. Using the complex chemical network of hydrocarbon pyrolysis as example, it is demonstrated that kinetic models built using atomic features are able to explore chemical reaction pathways never observed in the MD simulations used to parametrize them, a critical feature to describe rare events. Atomic-level features are shown to construct reaction mechanisms and estimate reaction rates of unknown molecular species from elementary atomic events. Through comparisons of the model ability to extrapolate to longer simulation timescales and different chemical compositions than the ones used for parameterization, it is demonstrated that kinetic models employing atomic features retain the same level of accuracy and transferability as the use of features based on molecular species, while being more compact and parametrized with less data. We also find that atomic features can better describe the formation of large molecules enabling the simultaneous description of small molecules and condensed phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A neural master equation framework for multiscale modeling of molecular processes: application to atomic-scale plasma processes

Plasma-surface interactions (PSI) play a crucial role in microelectronics fabrication; however, their multiscale nature and array of complex, often unknown interactions make computational modeling of PSIs extremely difficult. To this end, we propose a general neural master equation (NME) framework that uses master equations to describe the dynamics of a molecular process, wherein neural networks learned from atomistic simulations represent unknown transitions between different system states. By leveraging the physics-based structure of master equations and data-driven state transitions, the NME framework promotes generalizability and physics interpretability, and can bridge disparate length and time scales. The framework is demonstrated for multiscale modeling of Si atomic layer etching and reactive ion etching, where the learned NME-based surface kinetic models exhibit good predictive and extrapolative capabilities for predicting experimentally relevant observables as a function of process parameters. The NME-based surface kinetic models obey physical constraints, which are violated in models based on neural ordinary differential equations. The proposed NME framework for multiscale modeling of molecular processes can pave the way for the discovery of new chemistries and materials in atomic-scale plasma processes.

Chemical engineering↗
DOE OSTI2022

Hydride-based thermal energy storage

Abstract The potential and research surrounding metal hydride (MH) based thermal energy storage is discussed, focusing on next generation thermo-chemical energy storage (TCES) for concentrated solar power. The site availability model to represent the reaction mechanisms of both the forward and backward MH reaction is presented, where this model is extrapolated to a small pilot scale reactor, detailing how a TCES could function/operate in a real-world setting using a conventional shell & tube reactor approach. Further, the important parameter of effective thermal conductivity is explored using an innovative multi-scale model, to providing extensive and relevant experimental data useful for reactor and system design. Promising high temperature MH material configurations may be tuned by either destabilisation, such as using additions to Ca and Sr based hydrides, or by stabilisation, such as fluorine addition to NaH, MgH 2 , or NaMgH 3 . This versatile thermodynamic tuning is discussed, including the challenges in accurately measuring the material characteristics at elevated temperatures (500 –700 °C). Attention to scale up is explored, including generic design and prototype considerations, and an example of a novel pilot-scale pillow-plate reactor currently in development; where materials used are discussed, overall tank design scope and system integration.

25 ENERGY STORAGE↗
NASA NTRS1983

A program in global biology

NASA's Global Biology Research Program and its goals for greater understanding of planetary biological processes are discussed. Consideration is given to assessing major pathways and rates of exchange of elements such as carbon and nitrogen, extrapolating local rates of anaerobic activities, determining exchange rates of ocean nutrients, and developing models for the global cycles of carbon, nitrogen, sulfur, and phosphorus. Satellites and sensors operating today are covered: the Nimbus, NOAA, and Landsat series. Block diagrams of the software and hardware for a typical ground data processing and analysis system are provided. Samples of the surface cover data achieved with the Advanced Very High Resolution Radiometer, the Multispectral Scanner, and the Thematic Mapper are presented, as well as a productive capacity model for coastal wetlands. Finally, attention is given to future goals, their engineering requirements, and the necessary data analysis system.

Mooneyhan, D. W.↗
NASA NTRS1989

Constructor selection system

Future space construction missions will involve both human and machine constructors. Selection of the optimum constructor mix requires a model of constructor capabilities and requirements. The database for that model is developed via extrapolation from current literature. Optimization is done via minimization of total mission cost using a linear programming approach. This prototype is the first cut at producing a general tool for choosing a near-optimum constructor mix for any space construction mission. It illuminates some significant representational and data-gathering problems with the modelling approach.

Johnson, Richard↗
NASA NTRS2011

The Atacama Cosmology Telescope: High-Resolution Sunyaev-Zel'dovich Array Observations of ACT SZE-Selected Clusters from the Equatorial Strip

We present follow-up observations with the Sunyaev-Zel'dovich Array (SZA) of optically-confirmed galaxy clusters found in the equatorial survey region of the Atacama Cosmology Telescope (ACT): ACT-CL J0022-0036, ACT-CL J2051+0057, and ACT-CL J2337+0016. ACT-CL J0022-0036 is a newly-discovered, massive (10(exp 15) Msun), high-redshift (z=0.81) cluster revealed by ACT through the Sunyaev-Zel'dovich effect (SZE). Deep, targeted observations with the SZA allow us to probe a broader range of cluster spatial scales, better disentangle cluster decrements from radio point source emission, and derive more robust integrated SZE flux and mass estimates than we can with ACT data alone. For the two clusters we detect with the SZA we compute integrated SZE signal and derive masses from the SZA data only. ACT-CL J2337+0016, also known as Abell 2631, has archival Chandra data that allow an additional X-ray-based mass estimate. Optical richness is also used to estimate cluster masses and shows good agreement with the SZE and X-ray-based estimates. Based on the point sources detected by the SZA in these three cluster fields and an extrapolation to ACT's frequency, we estimate that point sources could be contaminating the SZE decrement at the less than = 20% level for some fraction of clusters.

Reese, Erik D.↗
NASA NTRS2011

The Atacama Cosmology Telescope: High-Resolution Sunyaev-Zeldovich Array Observations of ACT SZE-Selected Clusters from the Equatorial Strip

We present follow-up observations with the Sunyaev-Zel'dovich Array (SZA) of optically-confirmed galaxy clusters found in the equatorial survey region of the Atacama Cosmology Telescope (ACT): ACT-CL J0022-0036, ACT-CL J2051+0057, and ACT-CL J2337+0016. ACT-CL J0022-0036 is a newly-discovered, massive ( approximately equals 10(exp 15) Solar M), high-redshift (z = 0.81) cluster revealed by ACT through the Sunyaev-Zeldovich effect (SZE). Deep, targeted observations with the SZA allow us to probe a broader range of cluster spatial scales, better disentangle cluster decrements from radio point source emission, and derive more robust integrated SZE flux and mass estimates than we can with ACT data alone. For the two clusters we detect with the SZA we compute integrated SZE signal and derive masses from the SZA data only. ACT-CL J2337+0016, also known as Abell 2631, has archival Chandra data that allow an additional X-ray-based mass estimate. Optical richness is also used to estimate cluster masses and shows good agreement with the SZE and X-ray-based estimates. Based on the point sources detected by the SZA in these three cluster fields and an extrapolation to ACT's frequency, we estimate that point sources could be contaminating the SZE decrement at the approx < 20% level for some fraction of clusters.

galaxies↗
DOE OSTI2022

Increased Arctic NO3− Availability as a Hydrogeomorphic Consequence of Permafrost Degradation and Landscape Drying

Climate-driven permafrost thaw alters the strongly coupled carbon and nitrogen cycles within the Arctic tundra, influencing the availability of limiting nutrients including nitrate (NO3−). Researchers have identified two primary mechanisms that increase nitrogen and NO3− availability within permafrost soils: (1) the ‘frozen feast’, where previously frozen organic material becomes available as it thaws, and (2) ‘shrubification’, where expansion of nitrogen-fixing shrubs promotes increased soil nitrogen. Through the synthesis of original and previously published observational data, and the application of multiple geospatial approaches, this study investigates and highlights a third mechanism that increases NO3− availability: the hydrogeomorphic evolution of polygonal permafrost landscapes. Permafrost thaw drives changes in microtopography, increasing the drainage of topographic highs, thus increasing oxic conditions that promote NO3− production and accumulation. We extrapolate relationships between NO3− and soil moisture in elevated topographic features within our study area and the broader Alaskan Coastal Plain and investigate potential changes in NO3− availability in response to possible hydrogeomorphic evolution scenarios of permafrost landscapes. These approximations indicate that such changes could increase Arctic tundra NO3− availability by ~250–1000%. Thus, hydrogeomorphic changes that accompany continued permafrost degradation in polygonal permafrost landscapes will substantially increase soil pore water NO3− availability and boost future fertilization and productivity in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Fluid mechanics of dynamic stall. II - Prediction of full scale characteristics

Analytical extrapolations are made from experimental subscale dynamics to predict full scale characteristics of dynamic stall. The method proceeds by establishing analytic relationships between dynamic and static aerodynamic characteristics induced by viscous flow effects. The method is then validated by predicting dynamic test results on the basis of corresponding static test data obtained at the same subscale flow conditions, and the effect of Reynolds number on the static aerodynamic characteristics are determined from subscale to full scale flow conditions.

Ericsson, L. E.↗
NASA NTRS1995

Integrated planning and scheduling for Earth science data processing

Several current NASA programs such as the EOSDIS Core System (ECS) have data processing and data management requirements that call for an integrated planning and scheduling capability. In this paper, we describe the experience of applying advanced scheduling technology operationally, in terms of what was accomplished, lessons learned, and what remains to be done in order to achieve similar successes in ECS and other programs. We discuss the importance and benefits of advanced scheduling tools, and our progress toward realizing them, through examples and illustrations based on ECS requirements. The first part of the paper focuses on the Data Archive and Distribution (DADS) V0 Scheduler. We then discuss system integration issues ranging from communication with the scheduler to the monitoring of system events and re-scheduling in response to them. The challenge of adapting the scheduler to domain-specific features and scheduling policies is also considered. Extrapolation to the ECS domain raises issues of integrating scheduling with a product-generation planner (such as PlaSTiC), and implementing conditional planning in an operational system. We conclude by briefly noting ongoing technology development and deployment projects being undertaken by HTC and the ISTB.

Boddy, Mark↗
NASA NTRS1997

Formation and Combustion of Unconfined Drop Clusters in Microgravity

Single-drop and droplet array studies have become common methods to isolate and investigate the effects of any of the complexities that enter into the drop combustion process. Microgravity environments are required to allow larger drops to be studied while minimizing or eliminating the confounding effects of buoyancy. Based on the results from current isolated drop, drop array, and spray studies funded through the Microgravity Science and Applications Division, it has become clear that even with the effects of buoyancy removed, the extrapolation of results from droplet array studies to spray flames is difficult. The problem occurs because even the simplest spray systems introduce complexities of multi-disperse drop sizes and drop-drop interactions, coupled with more complicated fluid dynamics. Not only do these features make the interpretation of experimental data difficult, they also make the problem very difficult to analyze computationally. Group combustion models, in which the interaction between droplets is treated on a statistical manner, have become a popular method to investigate the behavior of large numbers of interacting droplets, particularly through the work of Ryan et al. and Bellan and co-workers. While these models idealize the actual spray systems to a point where they can be treated computationally, the experimental analogy to these models is difficult to achieve because it requires the formation and Combustion of drop clusters without the effects of buoyancy. Therefore, even though these models have provided useful and insightful information, the verification of the results by direct comparison with experimental data is still lacking.

Liu, S.↗
NASA NTRS2010

Preliminary Investigation of Civil Tiltrotor in NextGen Airspace

Presentation intro: Tiltrotor aircraft have long been envisioned as being a potentially viable means of commercial aviation transport. Preliminary results from an ongoing study into the operational and technological considerations of Civil Tiltrotor (CTR) operation in the Next Generation airspace, circa the 2025 time-frame, are presented and discussed. In particular, a fleet of CTR aircraft has been conceptually designed. The performance characteristics of this CTR fleet was subsequently translated into BADA (Base of Aircraft DAta) models that could be used as input to emulate CTR aircraft operations in the ACES and AvTerminal airspace and terminal area simulation tools. A network of nine North-Eastern corridor airports is the focus of the airspace simulation effort; the results from this airport network viII then be extrapolated to provide insights into systemic impact of CTRs on the National Airspace System (NAS). Future work will also be detailed as to attempts to model the systemic effects of noise and emissions from this fleet of new aircraft as well as assess their leveraged impact on public service missions, in time of need, such as major regional/national disaster relief efforts. The ideal outcome of this study is a set of results whereby Next Gen airspace CONOPs can be refined to reflect potential CTR capabilities and, conversely, CTR technology development efforts can be better informed as to key performance requirement thresholds needed to be met in order to successfully introduce these aircraft into civilian aviation operation.

Young, Larry A.↗
NASA NTRS2000

Timing Noise in SGR 1806-20

We have phase-connected a sequence of Rossi X-Ray Timing Explorer Proportional Counter Array observations of SGR 1806-20 covering 178 days. We find that a simple secular spin-down model does not adequately fit the data. The period derivative varies gradually during the observations between 8.1 x 10(exp -11) and 11.7 x 10(exp -11) s/s (at its highest, approximately 40% larger than the long-term trend), while the average burst rate as seen with the Burst and Transient Source Experiment drops throughout the time interval. The phase residuals give no compelling evidence for periodicity, but more closely resemble timing noise as seen in radio pulsars. The magnitude of the timing noise, however, is large relative to the noise level typically found in radio pulsars (Delta(sub 8) = 4.8; frequency derivative average power approximately 7 x 10(exp -20) sq cycles/cubic s). Combining these results with the noise levels measured for some anomalous X-ray pulsars, we find that all magnetar candidates have Delta(sub 8) values larger than those expected from a simple extrapolation of the correlation found in radio pulsars. We find that the timing noise in SGR 1806-20 is greater than or equal to the levels found in some accreting systems (e.g., Vela X-1, 4U 1538-52, and 4U 1626-67), but the spin-down of SGR 1806-20 has thus far maintained coherence over 6 yr. Alternatively, an orbital model with a period P(sub orb) = 733 days provides a statistically acceptable fit to the data. If the phase residuals are created by Doppler shifts from a gravitationally bound companion, then the allowed parameter space for the mass function (small) and orbital separation (large) rule out the possibility of accretion from the companion sufficient to power the persistent emission from the SGR.

Woods, P. M.↗
DOE OSTI2019

Message-passing neural networks for high-throughput polymer screening

Machine learning methods have shown promise in predicting molecular properties, and given sufficient training data, machine learning approaches can enable rapid high-throughput virtual screening of large libraries of compounds. Graph-based neural network architectures have emerged in recent years as the most successful approach for predictions based on molecular structure and have consistently achieved the best performance on benchmark quantum chemical datasets. However, these models have typically required optimized 3D structural information for the molecule to achieve the highest accuracy. These 3D geometries are costly to compute for high levels of theory, limiting the applicability and practicality of machine learning methods in high-throughput screening applications. In this study, we present a new database of candidate molecules for organic photovoltaic applications, comprising approximately 91,000 unique chemical structures. Compared to existing datasets, this dataset contains substantially larger molecules (up to 200 atoms) as well as extrapolated properties for long polymer chains. We show that message-passing neural networks trained with and without 3D structural information for these molecules achieve similar accuracy, comparable to state-of-the-art methods on existing benchmark datasets. Furthermore, these results therefore emphasize that for larger molecules with practical applications, near-optimal prediction results can be obtained without using optimized 3D geometry as an input. We further show that learned molecular representations can be leveraged to reduce the training data required to transfer predictions to a new density functional theory functional.

14 SOLAR ENERGY↗
DOE OSTI2025

Low-lying states and total internal partition sums of CH

The electronic structure and spin-orbit states of the CH radical have been systematically investigated using multi-reference configuration interaction (MRCI) and single-reference coupled-cluster (CC) methods. These calculations were performed in conjunction with large correlation-consistent basis sets of quadruple-, quintuple-, and sextuple-ζ quality. To achieve high accuracy, electronic energies for all states were extrapolated to the complete basis set (CBS) limit, enabling the detailed construction of potential energy curves and determination of reliable spectroscopic constants. Spin-orbit coupling effects were explicitly incorporated, and vibrational energy levels were computed via Numerov analysis. Furthermore, the resulting values exhibit good to excellent agreement with available experimental data. Dipole moment and transition dipole moment curves were evaluated to assess the opacity characteristics of CH, revealing that transitions such as Χ 2 Π (u′′ = 0) → Α 2 Δ (u′ = 0), Χ 2 Π (u′′ = 0) → Β 2 Σ − (u′ = 0), Χ 2 Π (u′′ = 0) → C 2 Σ + (u′ = 0), and Χ 2 Π (u′′ = 0) → D 2 Σ + (u′ = 3) are particularly probable. Finally, the total internal partition function sum (TIPS) of CH was computed over a broad temperature range (10–30,000 K) based on our high-accuracy ab initio results.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Transport coefficients of warm dense matter from Kohn-Sham density functional theory

We present a comprehensive study of transport coefficients including DC electrical conductivity and related optical properties, electrical contribution to the thermal conductivity, and the shear viscosity via ab initio molecular dynamics and density functional theory calculations on the “priority 1” cases from the “Second Charged-Particle Transport Coefficient Workshop” [Stanek et al., Phys. Plasmas (to be published 2024)]. The purpose of this work is to carefully document the entire workflow used to generate our reported transport coefficients, up to and including our definitions of finite size and statistical convergence, extrapolation techniques, and choice of thermodynamic ensembles. In pursuit of accurate optical properties, we also present a novel, simple, and highly accurate algorithm for evaluating the Kramers–Kronig relations. These heuristics are often not discussed in the literature, and it is hoped that this work will facilitate the reproducibility of our data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A consistent, Bayesian, approach to the cross section probability distribution in the unresolved resonance region

The cross sections of neutron-induced reactions can be divided into three energy ranges: the resolved resonance region (RRR), the unresolved resonance region (URR), and the fast region. In general, the cross sections in the URR show significant fluctuations that cannot be predicted and cannot be experimentally resolved, thus, it is commonly assumed that the cross section at a specific energy is given by a probability distribution function (PDF) over a range of values that can span several orders of magnitude. The current methodology used to describe such behavior is to construct the PDF by stochastically generating resonance ladders and numerically measuring the PDF. The resonance ladders are sampled using known resonance statistical properties and average resonance widths and spacings extrapolated from the RRR. Although this is a standard and widely used technique, it is computationally very expensive, therefore, an alternative, analytical, approach would be preferable due to the considerable speed up of the computational time in real life applications. Moreover, the current methodology does not take into account existing experimental data, such for total and capture cross sections, that are available for many nuclei. Finally, this approach was developed to be used in reactor-scale applications and it is not suited for use in single-event applications. In this work we will rethink the entire approach to the PDF construction using a Bayesian mindset. This will allow us to provide a different definition of the PDF that allows a much faster calculation of the higher-temperature PDFs and a proper combination of theoretical and experimental PDFs following the probability theory. We will also show that our definition is well suited for single-event applications and we will make an explicit connection between our method and the standard approach. We do this by showing that the central limit theorem applies and our method leads to the same PDF obtained with the standard methodology, for a large number of events per history.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗