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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 1,117 records · Page 62

Architecting Systems for Human Space Flight

Human-system interactions have been largely overlooked in the traditional systems engineering process. Awareness of human factors (HF) has increased in the past few years, but the involvement of HF specialists is still often too little and too late. In systems involving long-duration human space flight, it is essential that the human component be properly considered in the initial architectural definition phase, as well as throughout the system design process. HF analysis must include not only the strengths and limitations of humans in general, but the variability between individuals and within an individual over time, and the dynamics of group interactions.

Wocken, Gerald↗

Wind Tunnel Flow Field Visualizations of the Space Launch System Vehicle Ascent

A series of wind tunnel tests were conducted to characterize the force-and-moment, and aeroacoustic environment of several configurations of the Space Launch System during ascent. The tests were conducted in the 11-by-11 foot transonic and 9-by-7 foot supersonic test sections at NASA Ames research center. Throughout these experiments data was collected from several types of instrumentation including: multicomponent force-and-moment strain gage balances, dynamic and steady-state pressure sensors, unsteady and steady pressure-sensitive paint, time-resolved shadowgraph and infrared imaging. The following details results and analysis from the time-resolved shadowgraph and infrared imaging data systems. The time-resolved shadowgraph and infrared imaging provided a qualitative measurement of the near-field turbulent fluctuations. These results helped provide context to the relative magnitude and frequency content of the fluid-structure-interaction driving the surface pressure phenomena characterized by the discrete pressure transducers and unsteady pressure sensitive paint.

Garbeff, Theodore J., II↗

Newly Available Single Field-of-view Sounder Atmospheric Product (SiFSAP) and Its Derivative Product

The Single Field-of-view Sounder Atmospheric product (SiFSAP) has been developed and delivered to NASA GES DISC. The SiFSAP Algorithm Theoretical Basis Documents (ATBD) and users manuals are ready to be released to public. This novel data product supplements other operational products such as AIRS version 7 and the Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) from two main perspectives: 1) improving the spatial resolution of sounder Level-2 data to extend its usage in weather and dynamics focus area; 2) establishing radiance closure between Level-2 data and directly measured Level-1 radiances to facilitate the climate trend analysis. SiFSAP has 3-times higher spatial resolution and 9-times denser data products comparing to current NASA and NOAA operational IR sounder products. SiFSAP is derived using the optimal estimation method based physical retrieval algorithm. The Principal Component-based Radiative Transfer Model (PCRTM) which includes the cloud scattering simulation is used for the forward model so that the solution can fit the spectral radiances under all-sky conditions for individual single field-of-view (SFOV) measurements. A general introduction of the SiFSAP algorithm and corresponding validation work will be presented. Also introduced here is the Climate Fingerprinting Sounder product (ClimFiSP) that is the derivative product of SiFSAP and will be released in the near future. The ClimFiSP algorithm uses pre-constructed fingerprinting relationship to achieve a low-latency Level-3 data production and facilitate the fusion of data of different sounders.

Wan Wu↗

A dynamic satellite simulation testbed based on CLIPS and CLIPS-derived tools

We were motivated to define and build a sophisticated satellite simulation capability for the evaluation at a satellite operations automated environment called IntelliSTAR. This architecture, and associated prototype, addresses the entire spacecraft operations cycle including planning, scheduling, task execution, and analysis. It is aimed at increasing the autonomous capability of current and future spacecraft. It utilizes advanced software techniques to address incomplete and conflicting data for making decisions. It also encompasses critical response time requirements, complex relationships among multiple systems, and dynamically changing objectives. Given the extreme scope of activities that are targeted, a sophisticated, flexible, and dynamic simulation environment was required to drive this prototype. In particular the derived requirements for evaluating the IntelliSTAR prototype include realistic and dynamic environment, easily reconfigurable, and multiple levels of fidelity.

Gathmann, Thomas P.↗

Unsteady deflagration speed of an auto-ignitive dimethyl-ether (DME)/air mixture at stratified conditions

The propagation speed of an auto-ignitive dimethyl-ether (DME)/air mixture at elevated pressures and subjected to monochromatic temperature oscillations is numerically evaluated in a one-dimensional statistically stationary configuration using fully resolved numerical simulations with reduced kinetics and transport. Two sets of conditions with temperatures within and slightly above the negative temperature coefficient (NTC) regime are simulated to investigate the fundamental aspects of auto-ignition and flame propagation along with the transition from auto-ignitive deflagration to spontaneous propagation regimes under thermal stratification. Contrary to the standard laminar flame speed, the steady propagation speed of an auto-ignitive front is observed to scale proportionally to its level of upstream reactivity. It is shown that this interdependence is primarily influenced by the characteristic residence time and the homogeneous auto-ignition delay. Furthermore, the unsteady reaction front in either of the two cases responds distinctly to the imposed stratification. Specifically, the results in both cases show that the dynamic flame response depends on the mean temperature at the flame base Tb and the time-scale of thermal stratification. It is also found that, based on Tb and the propensity of the mixture to two-stage chemistry, the instantaneous peak propagation speed and the overall time taken to achieve that speed differs considerably. A displacement speed analysis is carried out to elucidate the underlying combustion modes that are responsible for such a variation in flame response.

Energy & Fuels↗

Dynamic infrared gas analysis from longleaf pine fuel beds burned in a wind tunnel: observation of phenol in pyrolysis and combustion phases

Pyrolysis is the first step in a series of chemical and physical processes that produce flammable organic gases from wildland fuels that can result in a wildland fire. We report results using a new time-resolved Fourier transform infrared (FTIR) method that correlates the measured FTIR spectrum with an infrared thermal image sequence, enabling the identification and quantification of gases within different phases of the fire process. The flame from burning fuel beds composed of pine needles (Pinus palustris) and mixtures of sparkleberry, fetterbush, and inkberry plants was the natural heat source for pyrolysis. Extractive gas samples were analyzed and identified in both static and dynamic modes synchronized to thermal infrared imaging: a total of 29 gases were identified including small alkanes, alkenes, aldehydes, nitrogen compounds, and aromatics, most previously measured by FTIR in wildland fires. This study presents one of the first identifications of phenol associated with both pre-combustion and combustion phases using ca. 1 Hz temporal resolution. Preliminary results indicate ~2.5× greater phenol emissions from sparkleberry and inkberry compared to fetterbush, with differing temporal profiles.

09 BIOMASS FUELS↗

Energy exchange dynamics across L–H transitions in NSTX

Here, we studied the energy exchange dynamics across the low-to-high-confinement (L–H) transition in NSTX discharges using the gas-puff imaging (GPI) diagnostic. The investigation focused on the energy exchange between flows and turbulence to help clarify the mechanism of the L–H transition. We applied this study to three types of heating schemes, including a total of 17 shots from the NSTX 2010 campaign run. Results show that the edge fluctuation characteristics (fluctuation levels, radial and poloidal correlation lengths) measured using GPI do not vary just prior to the H-mode transition, but change after the transition. Using a velocimetry approach (orthogonal-dynamics programming), velocity fields of a $24\times 30$ cm GPI view during the L–H transition were obtained with good spatial (~1 cm) and temporal (~2.5 μs) resolutions. Analysis using these velocity fields shows that the production term is systematically negative just prior to the L–H transition, indicating a transfer from mean flows to turbulence, which is inconsistent with the predator–prey paradigm. Moreover, the inferred absolute value of the production term is two orders of magnitude too small to explain the observed rapid L–H transition. These discrepancies are further reinforced by consideration of the ratio between the kinetic energy in the mean flow to the thermal free energy, which is estimated to be much less than 1, suggesting again that the turbulence depletion mechanism may not play an important role in the transition to the H-mode. Although the Reynolds work therefore appears to be too small to directly deplete the turbulent free energy reservoir, order-of-magnitude analysis shows that the Reynolds stress may still make a non-negligible contribution to the observed poloidal flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Morphology and Dynamics of Bottlebrush Polymers

This thesis makes significant advances to the understanding of bottlebrush polymers. While bottlebrushes have received much attention due to the recent discovery of their unprecedented properties, including supersoftness, ultra-low viscosity, and hyperelasticity, this thesis is the first fundamental investigation at the molecular level that comprises structure and dynamics. Neutron scattering experiments, detailed within, reveal spherical or cylindrical shapes, instead of a random coil conformation. Another highlight is the analysis of the fast dynamics at the sub nm-length scale. The combination of three neutron spectrometers and the development of a new analysis technique enabled the calculation of the mean-square displacement over seven orders of magnitude in time scale. This unprecedented result can be applied to a broad class of samples, including polymers and other materials. The thesis is accessible to scientists from other fields, provides the reader with easily understandable guidelines for applying this analysis to other materials, and has the potential to make a significant impact on the analysis of neutron scattering data.

36 MATERIALS SCIENCE↗

Singular perturbation techniques for on-line optimal flight path control

This paper presents a partial evaluation on the use of singular perturbation methods for developing computer algorithms for on-line optimal control of aircraft. The evaluation is based on a study of the minimum time intercept problem using F-4 aerodynamic and propulsion data as a base line. The extensions over previous work on this subject are that aircraft turning dynamics (in addition to position and energy dynamics) are included in the analysis, the algorithm is developed for a moving end point and is adaptive to unpredictable target maneuvers, and short range maneuvers that do not have a cruise leg are included. Particular attention is given to identifying those quantities that can be precomputed and stored (as a function of aircraft total energy), thus greatly reducing the onboard computational load. Numerical results are given that illustrate the nature of the optimal intercept flight paths, and an estimate is given for the execution time and storage requirements of the control algorithm.

Calise, A. J.↗

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns, emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns.

60 APPLIED LIFE SCIENCES↗

Modeling and Cost Benefit Analysis to Guide Deployment of POC Diagnostics for Non-typhoidal Salmonella Infections with Antimicrobial Resistance

Invasive non-typhoidal Salmonella (NTS) is among the leading causes of blood stream infections in sub-Saharan Africa and other developing regions, especially among pediatric populations. Invasive NTS can be difficult to treat and have high case-fatality rates, in part due to emergence of strains resistant to broad-spectrum antibiotics. Furthermore, improper treatment contributes to increased antibiotic resistance and death. Point of care (POC) diagnostic tests that rapidly identify invasive NTS infection, and differentiate between resistant and non-resistant strains, may greatly improve patient outcomes and decrease resistance at the community level. Here we present for the first time a model for NTS dynamics in high risk populations that can analyze the potential advantages and disadvantages of four strategies involving POC diagnostic deployment, and the resulting impact on antimicrobial treatment for patients. Our analysis strongly supports the use of POC diagnostics coupled with targeted antibiotic use for patients upon arrival in the clinic for optimal patient and public health outcomes. We show that even the use of imperfect POC diagnostics can significantly reduce total costs and number of deaths, provided that the diagnostic gives results quickly enough that patients are likely to return or stay to receive targeted treatment.

59 BASIC BIOLOGICAL SCIENCES↗

Transient dynamics of terrestrial carbon storage: Mathematical foundation and its applications

Terrestrial ecosystems have absorbed roughly 30% of anthropogenic CO 2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Altogether, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.

54 ENVIRONMENTAL SCIENCES↗

Application of Detectability Analysis for Power System Dynamic State Estimation

To guide the measurement placement and selection for dynamic state estimation in power systems, it is important to determine the existence of an observer that can estimate the dynamic states. Past studies have been focused on observability analysis, which determines whether the initial states can be uniquely determined. In this paper, detectability analysis is proposed to determine whether the current states can be estimated as time involving. Through the proposed detectability analysis, the states of an unobservable system can be categorized into the detectable states and undetectable states. It is shown that if the eigenvalues corresponding to the unobservable states are stable, the states are detectable and their estimates will converge to the true ones asymptotically. The study can be used to guide measurement placement and selection.

Detectability, dynamic state estimation↗

Design and architecture of the Mars relay network planning and analysis framework

In this paper we describe the design and architecture of the Mars Network planning and analysis framework that supports generation and validation of efficient planning and scheduling strategy. The goals are to minimize the transmitting time, minimize the delaying time, and/or maximize the network throughputs. The proposed framework would require (1) a client-server architecture to support interactive, batch, WEB, and distributed analysis and planning applications for the relay network analysis scheme, (2) a high-fidelity modeling and simulation environment that expresses link capabilities between spacecraft to spacecraft and spacecraft to Earth stations as time-varying resources, and spacecraft activities, link priority, Solar System dynamic events, the laws of orbital mechanics, and other limiting factors as spacecraft power and thermal constraints, (3) an optimization methodology that casts the resource and constraint models into a standard linear and nonlinear constrained optimization problem that lends itself to commercial off-the-shelf (COTS)planning and scheduling algorithms.

Mars relay network planning analysis↗

Using Digital Trace Data to Identify Regions and Cities

A greater understanding of human dynamics as they play out in both physical space and through inter-personal communication is vital for the design and development of intelligent and resilient cities. Physical context provides insight in to the space-time distribution of population and their activity patterns, while inter-personal communication can, for the first time, be measured at scale through virtual interactions. The confluence of these two enables spatial social network analysis in the built environment for edge computing, knowledge discovery, and artificial intelligence activities. In this work, we propose a novel method to discover such dynamics. We use a dataset of 72 million tweets to develop a spatially embedded network of communication, and then use community detection algorithms to explore regional and urban delineation in the United States. We find that the broad spatial delineation of communities and community sub-structure is consistent with major United States socio-cultural regions, states, and major metropolitan areas. We describe how these methods could be extended to generate a measure of socially cohesive regions that can be consistently applied anywhere there is a sufficiently rich data source. We hope the proposed methods will generate new perspectives on smart and resilient cities.

Brelsford, Christa↗

Bidentate Lewis bases are preferred for passivation of MAPbI 3 surfaces: A time-domain ab initio analysis

We report chemical passivation is a predominant approach to inhibit intrinsic defects responsible for electron–hole recombination in perovskite solar cells. Using time-domain density functional theory combined with nonadiabatic molecular dynamics, we demonstrate defect passivation by separation of electrons and holes in metal halide perovskites (MHPs), and show that bidentate ligands exhibit the best performance. Defects in traditional semiconductors create deep midgap states, and passivation eliminates these states. In contrast, common defects produce no deep midgap states in MHPs. Instead, defects localize electrons and holes around defect sites, enhancing electron–hole interaction. Defect passivation in MHPs acts to separate charges, decreasing electron–hole and charge–phonon interactions, and increasing charge lifetimes. Bidentate ligands work best, because they can passivate both unsaturated chemical bonds created due to vacancy defects. Bidentate ligands with spatially separated binding sites are preferred, since they provide better match to the sparse inorganic lattice of MHPs. Similar to the Lewis base ligands, water also acts as a ligand and extends charge lifetimes, with the oxygen atom donating its lone electron pair to the defect site. However, water accelerates chemical degradation of MHPs. The binding energy of most ligands is larger than that of water, and therefore, the ligands displace water, increase MHP stability and prolong carrier lifetimes. The established physical mechanism of defect passivation, and the specific principles guiding the choice of passivating molecules advance our understanding of the exceptional properties of MHPs and suggest routes for further improvement of MHP performance in solar energy and optoelectronic applications.

36 MATERIALS SCIENCE↗

Fluid dynamics analysis of a gas attenuator for X-ray FELs under high-repetition-rate operation

Newtonian fluid dynamics simulations were performed using the Navier–Stokes–Fourier formulations to elucidate the short time-scale (µs and longer) evolution of the density and temperature distributions in an argon-gas-filled attenuator for an X-ray free-electron laser under high-repetition-rate operation. Both hydrodynamic motions of the gas molecules and thermal conductions were included in a finite-volume calculation. It was found that the hydrodynamic wave motions play the primary role in creating a density depression (also known as a filament) by advectively transporting gas particles away from the X-ray laser–gas interaction region, where large pressure and temperature gradients have been built upon the initial energy deposition via X-ray photoelectric absorption and subsequent thermalization. Concurrent outward heat conduction tends to reduce the pressure in the filament core region, generating a counter gas flow to backfill the filament, but on an initially slower time scale. If the inter-pulse separation is sufficiently short so the filament cannot recover, the depth of the filament progressively increases as the trailing pulses remove additional gas particles. Since the rate of hydrodynamic removal decreases while the rate of heat conduction back flow increases as time elapses, the two competing mechanisms ultimately reach a dynamic balance, establishing a repeating pattern for each pulse cycle. Finally, by performing simulations at higher repetition rates but lower per pulse energies while maintaining a constant time-averaged power, the amplitude of the hydrodynamic motion per pulse becomes smaller, and the evolution of the temperature and density distributions approach asymptotically towards, as expected, those calculated for a continuous-wave input of the equivalent power.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dynamic analysis of straight and involute tooth forms

The effect of load speed on straight and involute tooth forms is studied using several finite-element models. It is found that for rapidly rotating gears and sprockets, the load speed along the tooth surface can significantly affect the tooth vibration. Indeed, it is found that for sufficiently high load speeds and for sufficiently slender tooth forms, the tooth deflection can, at times, be directed opposite to the load direction. Comparisons are made of various dynamic models of gear and sprocket teeth. It is shown that for stubby tooth forms there is considerable difference between results obtained with finite element models and results obtained with Timoshenko beam models. Finally, it is shown that gear or sprocket vibrations can be induced by the shape of the tooth form itself. This effect becomes increasingly significant at higher speeds.

Lin, H. H.↗