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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

The Spectral Radiance of Indirectly Illuminated Surfaces in Regions of Permanent Shadow on the Moon

Regions of permanent shadow at the lunar poles have been suggested to host water ice and potentially other volatile compounds owing to their extremely low temperatures. Imaging in permanent shadow using indirect lighting from nearby topographic highs illuminated by the Sun has demonstrated the feasibility of optical remote sensing of permanent shadow surfaces, and a near-IR detection of water ice spectral features demonstrates the ability to collect usable spectroscopic data. The infrared emission of the lunar surface is largely in radiative equilibrium, so the temperature of surfaces in permanent shadow is driven by the intensity of the indirect illumination. This means that surfaces at very low temperatures, of high interest owing to their ability to trap and retain volatile compounds, will be the most challenging to measure. We provide estimates of indirect spectral radiance as a function of permanent shadow temperature from 400 nm to 14 μm using empirical data on permanent shadow temperature and broadband visible and near IR radiance, coupled with known reflectance properties of lunar materials. The relationships show there is ample radiance and photon radiance for reflectance imaging and spectroscopy from 400 nm to 8 μm at temperatures of regions of permanent shadow above 60K with appropriately designed instruments. Beyond 8 μm lunar spectral properties reduce the available radiance substantially, making reflectance observations challenging.

P. G. Lucey↗
NASA NTRSDate not supplied

AMMPER: a user-friendly agent-based model that recapitulates simple metabolic responses of yeast to deep-space radiation

For humans venturing to deep space, radiation exposure poses a major health risk. Fundamental research into the biological effects of space radiation are essential for enabling exploration, and the first experimental organisms we send to deep space will be microbial. Yet there are many ways in which microorganisms are likely to experience the effects of high-energy particle radiation (such as Galactic Cosmic Rays) differently from multicellular animals, partly due to the simple fact that microbes are small and unicellular-- less likely to get hit in the first place, and less likely to communicate damage between cells. Computational modeling can aid in designing experiments and predicting the biological effects of radiation, but thus far particle radiation models have not focused on microbes. Here we present the latest developments in AMMPER, the Agent-based Model for Microbial Populations Exposed to Radiation. Originally written in 2021, AMMPER is a Python-based model that incorporates radiation track data from NASA's RITRACKS software and simulates the growth, damage, and death of yeast cells in 3D. It is now freely available as an open-source package on NASA's GitHub repository. Recent improvements include the ability to simulate the dynamics of alamarBlue, a color-changing redox dye commonly used to track metabolic activity in microbial spaceflight experiments. We demonstrate that a simple blue-pink-clear transition model is able to recapitulate key features observed in empirical data from ground studies. AMMPER also includes a new graphical user interface and introductory tutorial to facilitate ease of use by a wider audience. AMMPER can help us to understand how spatially heterogeneous particle radiation damage at the single-cell level can translate to growth differences at the population level, ultimately allowing us to better interpret experiments using microbes as model organisms and how well their results apply to humans.

yeast↗
DOE OSTI2021

Searching for fat tails in CRISPR-Cas systems: Data analysis and mathematical modeling

Understanding CRISPR-Cas systems—the adaptive defence mechanism that about half of bacterial species and most of archaea use to neutralise viral attacks—is important for explaining the biodiversity observed in the microbial world as well as for editing animal and plant genomes effectively. The CRISPR-Cas system learns from previous viral infections and integrates small pieces from phage genomes called spacers into the microbial genome. The resulting library of spacers collected in CRISPR arrays is then compared with the DNA of potential invaders. One of the most intriguing and least well understood questions about CRISPR-Cas systems is the distribution of spacers across the microbial population. Here, using empirical data, we show that the global distribution of spacer numbers in CRISPR arrays across multiple biomes worldwide typically exhibits scale-invariant power law behaviour, and the standard deviation is greater than the sample mean. We develop a mathematical model of spacer loss and acquisition dynamics which fits observed data from almost four thousand metagenomes well. In analogy to the classical ‘rich-get-richer’ mechanism of power law emergence, the rate of spacer acquisition is proportional to the CRISPR array size, which allows a small proportion of CRISPRs within the population to possess a significant number of spacers. Our study provides an alternative explanation for the rarity of all-resistant super microbes in nature and why proliferation of phages can be highly successful despite the effectiveness of CRISPR-Cas systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Accelerating the rate of discovery: toward high-repetition-rate HED science

As high-intensity short-pulse lasers that can operate at high-repetition-rate (HRR) (>10 H z ) come online around the world, the high energy density (HED) science they enable will experience a radical paradigm shift. The >10 3 increase in shot rate over today's shot-per-hour drivers translates into dramatically faster data acquisition, more experiments, and the ability to exploit machine learning, and thus the potential to significantly accelerate the advancement of HED science. A wide range of HED experiments, from opacity investigations to secondary source generation to plasma nuclear physics, will benefit from the increased statistics, precision, and exploration of phase space. Besides increasing the rate at which scientific experiments can be performed, HRR also allows for the rapid delivery of optimal experiments supported by simulations and modeling augmented by close coupling to empirical data. To fully realize such an HRR framework, numerous subsystems must be developed and brought together, including feedback laser control loops, high-throughput targetry and diagnostics, cognitive simulation, enhanced HED codes, and advanced data analytics. This paper describes the vision for an integrated HRR laser experimental HED system and outlines some of the major considerations and challenges for realizing it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

State-Space Model to Estimate Salmon Escapement Using Multiple Data Sources

Abstract Accurate estimates of salmonids passing Lower Granite Dam on the Snake River, by species and origin, are a critical input to assessing the status and trends of various populations as well as successful management of fisheries in the Snake River basin. Here, we describe a state-space model that estimates such escapement past a dam by using window counts, PIT tag observations, and data from an adult fish trap, accounting for issues such as nighttime passage, fallback and reascension, potential observation error at the window, and uncertainty in the adult trap rate. We tested the approach using a simulation framework that mimicked several levels of observation error, differences between nighttime passage and reascension rates, and the possibility of the adult trap being closed for some period of time. Our results demonstrate that the model produced unbiased estimates across all tested scenarios. We also applied this model to empirical data from Lower Granite Dam to produce estimates of wild, clipped hatchery, and unclipped hatchery spring/summer-run Chinook Salmon Oncorhynchus tshawytscha and steelhead O. mykiss from spawn years 2010–2019.

See, Kevin E. (ORCID:0000000297626442)↗
DOE OSTI2021

Quantifying Turbine-Level Risk to Golden Eagles Using a High-Fidelity Updraft Model and a Stochastic Behavioral Model

To minimize the effects of wind farms on Golden Eagle (Aquila chrysaetos) populations while enabling sustainable development of renewable energy resources, it is important to understand how eagles interact with atmospheric flows, terrain features, and anthropogenic structures. Models that predict migratory flight paths provide one tool that helps us grasp how the location of wind farms may influence interactions and impacts on migrating Golden Eagles. The current state-of-the-art in predicting migratory flight paths uses a deterministic fluid-flow analogy to predict eagle trajectory using only an orographic updraft potential computed from topographical features. This model does not take into account variables, such as thermal updrafts and time varying atmospheric conditions that are known to influence migratory behavior. In this work, we improve on the model with the objective of developing tools that advance our understanding of how atmospheric flows and terrain features affect migratory eagle behavior and their interactions with wind farms. Specifically, we 1) incorporate both orographic and thermal updraft information in simulating eagle flight paths; 2) incorporate stochasticity into eagle travel patterns to better capture the influence of exogenous factors on, and the inherent stochasticity of eagle behavior; 3) consider spatio-temporal atmospheric data at wind-farm-scale when computing updraft potential; and 4) account for how atmospheric conditions and the direction of migration change seasonally and how these changes affect eagle migratory flight behavior. We tested the model using a 50km by 50km region with 50 m resolution in the western United States. We simulated 900 independent, probabilistic eagle tracks during southerly and northerly migration, assuming eagles solely rely on orographic updrafts. The preliminary results indicate that the inclusion of finer resolution atmospheric data allows for the inclusion of realistic conditions that an eagle experiences. The stochasticity in eagle tracks provides a platform to include uncertainty in eagle decision making and help produce robust eagle presence maps. We will deploy updraft and downdraft velocities computed using a high-fidelity, wind farm scale, computational fluid dynamics solver under development at National Renewable Energy Laboratory. This work is a first step in the development of a predictive and generalizable eagle behavior model at the wind farm scale that does not rely on empirical data collection. Although the current model is intended for migratory eagles, we will extend and refine this model to inform the development of additional behavioral modes, including resident eagle behavior. This modeling approach improves our ability to understand eagle use of the landscape at a fine scale, and it is our hope that this work will ultimately help advance strategies that minimize the impact of wind development on Golden Eagle populations.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2025

Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification

In numerous applications, the integration of prior knowledge and historical information is essential, particularly for tasks requiring the solution of ordinary or partial differential equations (ODEs/PDEs) in data-sparse or noisy environments. For instance, achieving accurate solutions to time-dependent PDEs with limited initial condition measurements necessitates an effective strategy for embedding prior knowledge. Hard-parameter sharing architectures in neural networks (NNs) have demonstrated success in both traditional and scientific machine learning domains, facilitating the learning of informative representations. Here, in this study, we introduce a novel, yet efficient, method to enhance physics-informed neural networks (PINNs) by incorporating a multi-head structure that enables the learning of functional priors from both empirical data and governing physical laws. This prior information can then be used to address data sparsity and high-level noise in solving ODE/PDE problems with uncertainty quantification (UQ). The approach, termed Multi-Head PINN (MH-PINN), consists of a shared body NN and multiple head NNs, each corresponding to an individual PINN instance. Our framework for functional prior learning is carried out in two stages: (1) training the MH-PINNs to develop a shared body NN alongside multiple head NNs, and (2) employing these trained head NNs to estimate a prior distribution through a normalizing flow-based density estimator. The learned functional prior can then be applied as a regularization mechanism in deterministic contexts or as an informative prior within a Bayesian inference framework, aiding in the resolution of subsequent ODE/PDE tasks. We evaluate the efficacy of MH-PINNs across five benchmark problems, including a high-dimensional parametric PDE, all characterized by data sparsity or substantial noise levels. Our findings reveal that MH-PINNs deliver accurate solutions and robust UQ, demonstrating adaptability across a range of complex and challenging scenarios.

Bayesian inference↗
NASA NTRS1979

Mercurian crater rim heights and some interplanetary comparisons

Rim height (Re) data have been gathered through shadow measurements for 30 fresh mercurian craters with diameters (D) between 2.6 and 39 km. Small mercurian craters (i.e., those less than about 16 km in diameter) have higher rims than do lunar craters of the same diameter; on the basis of Re/D measurements alone, however, mercurian craters larger than about 16 km appear to be indistinguishable from their lunar counterparts (those greater than about 21 km in diameter). Apparent crater depths (Ra, the crater depth measured from the initial target surface) derived from empirical data allude to a decrease in Ra/D with calculated modal impact velocity. This is consistent with the hypothesis that higher impact velocities place the effective depth of burst of the event closer to the surface, thus causing a shallower crater.

Cintala, M. J.↗
NASA NTRSDate not supplied

Transfer Function Models and Sensitivity Analysis

In many situations, real or induced flaws such as tight cracks with known morphology cannot be manufactured in part configuration specimens or in real parts. Typically, fatigue cracks are manufactured in simple geometry specimens such as flat plates, dog-bone shaped flat or round specimens. If a nondestructive evaluation (NDE) technique is required to provide a reliably detectable target flaw size denoted as α_(90/95) for induced flaws in real part, then the direct method for qualifying the NDE procedure is to use the appropriate induced flaw specimens and perform probability of detection analysis using these flaws. This can be described as direct POD demonstration testing, which may follow guidelines of MIL-HDBK-1823. This paper considers a case, where induced flaws are not available in part configuration specimens. Therefore, a direct POD demonstration study cannot be undertaken. In such situation, general practice for NDE procedure qualification is to use artificial flaws in simple geometry and part configuration specimens, and induced flaws in the chosen simple geometry specimens. Signal response data is taken on all sets of artificial and induced flaws. NDE procedure testing on induced flaw in simple geometry specimen is called NDE demonstration testing here. A transfer function NDE procedure qualification method for forward case calculates predicted induced flaw size for demonstration using a chosen target flaw size. Another transfer function method for inverse case, calculates the target flaw size using a given demonstration flaw size. The transfer function analysis assumes relationship of artificial flaw signal responses in real parts and simple geometry specimens; and induced flaw responses in simple geometry specimens to induced flaws in real parts. The signal response transfer relationships model should be defined before transfer function models can be devised. Assuming that the signal response transfer relationships model is valid, forward and inverse case transfer function methods have been devised. Because of lack of signal response data from induced flaws in real part, 90/95% POD/confidence (P/C) cannot be demonstrated directly. However, the transfer function method may be assessed using simulation to evaluate whether the resulting target flaw size or demonstration flaw size provides adequate confidence to the assumed signal response transfer relationships model. Therefore, the transfer function approach is a risk assessment approach. Both the signal response transfer relationships model and the transfer function model are important in managing risk in results provided by the transfer function NDE technique qualification or assessment. The signal response transfer relationships model needs to be validated with empirical data and then transfer function model needs to be validated for desired P/C on case-by-case basis.

Nondestructive evaluation↗
NASA NTRS1999

ACTS Ka-band Propagation Research in a Spatially Diversified Network with Two USAT Ground Stations

Congestion in the radio spectrum below 18 GHz is stimulating greater interest in the Ka (20/30 GHz) frequency band. Transmission at these shorter wavelengths is greatly influenced by rain resulting in signal attenuation and decreased link availability. The size and projected cost of Ultra Small Aperture Terminals (USATS) make site diversity methodology attractive for rain fade compensation. Separation distances between terminals must be small to be of interest commercially. This study measures diversity gain at a separation distance <5 km and investigates utilization of S-band weather radar reflectivity in predicting diversity gain. Two USAT ground stations, separated by 2.43 km for spatial diversity, received a continuous Ka-band tone sent from NASA Glenn Research Center via the Advanced Communications Technology Satellite (ACTS) steerable antenna beam. Received signal power and rainfall were measured, and Weather Surveillance Radar-1998 Doppler (WSR-88D) data were obtained as a measure of precipitation along the USAT-to-ACTS slant path. Signal attenuation was compared for the two sites, and diversity gain was calculated for fades measured on eleven days. Correlation of WSR-88D S-band reflectivity with measured Ka-band attenuation consisted of locating radar volume elements along each slant path, converting reflectivity to Ka-band attenuation with rain rate calculation as an intermediate step. Specific attenuation for each associated path segment was summed, resulting in total attenuation along the slant path. Derived Ka-band attenuation did not correlate closely with empirical data (r = 0.239), but a measured signal fade could be matched with an increase in radar reflectivity in all fade events. Applying a low pass filter to radar reflectivity prior to deriving Ka-band attenuation improved the correlation between measured and derived signal attenuation (r = 0.733). Results indicate that site diversity at small separation distances is a viable means of rain fade compensation, and that existing models underestimate diversity gain for a subtropical climate such as Florida. Also, filtered WSR-88D reflectivity can be used for optimizing diversity terminal placement by comparing derived Ka- band attenuation between the diversity sites.

Kalu, Alex↗
NASA NTRS2010

An Acoustical Comparison of Sub-Scale and Full-Scale Far-Field Measurements for the Reusable Solid Rocket Motor

Recently, members of the Marshall Space Flight Center (MSFC) Fluid Dynamics Branch and Wyle Labs measured far-field acoustic data during a series of three Reusable Solid Rocket Motor (RSRM) horizontal static tests conducted in Promontory, Utah. The test motors included the Technical Evaluation Motor 13 (TEM-13), Flight Verification Motor 2 (FVM-2), and the Flight Simulation Motor 15 (FSM-15). Similar far-field data were collected during horizontal static tests of sub-scale solid rocket motors at MSFC. Far-field acoustical measurements were taken at multiple angles within a circular array centered about the nozzle exit plane, each positioned at a radial distance of 80 nozzle-exit-diameters from the nozzle. This type of measurement configuration is useful for calculating rocket noise characteristics such as those outlined in the NASA SP-8072 "Acoustic Loads Generated by the Propulsion System." Acoustical scaling comparisons are made between the test motors, with particular interest in the Overall Sound Power, Acoustic Efficiency, Non-dimensional Relative Sound Power Spectrum, and Directivity. Since most empirical data in the NASA SP-8072 methodology is derived from small rockets, this investigation provides an opportunity to check the data collapse between a sub-scale and full-scale rocket motor.

Haynes, Jared↗
NASA NTRS1995

Integrated Cryogenic Satellite Communications Cross-Link Receiver Experiment

An experiment has been devised which will validate, in space, a miniature, high-performance receiver. The receiver blends three complementary technologies; high temperature superconductivity (HTS), pseudomorphic high electron mobility transistor (PHEMT) monolithic microwave integrated circuits (MMIC), and a miniature pulse tube cryogenic cooler. Specifically, an HTS band pass filter, InP MMIC low noise amplifier, HTS-sapphire resonator stabilized local oscillator (LO), and a miniature pulse tube cooler will be integrated into a complete 20 GHz receiver downconverter. This cooled downconverter will be interfaced with customized signal processing electronics and integrated onto the space shuttle's 'HitchHiker' carrier. A pseudorandom data sequence will be transmitted to the receiver, which is in low Earth orbit (LEO), via the Advanced Communication Technology Satellite (ACTS) on a 20 GHz carrier. The modulation format is QPSK and the data rate is 2.048 Mbps. The bit error rate (BER) will be measured in situ. The receiver is also equipped with a radiometer mode so that experiment success is not totally contingent upon the BER measurement. In this mode, the receiver uses the Earth and deep space as a hot and cold calibration source, respectively. The experiment closely simulates an actual cross-link scenario. Since the receiver performance depends on channel conditions, its true characteristics would be masked in a terrestrial measurement by atmospheric absorption and background radiation. Furthermore, the receiver's performance depends on its physical temperature, which is a sensitive function of platform environment, thermal design, and cryocooler performance. This empirical data is important for building confidence in the technology.

Romanofsky, R. R.↗
NASA NTRS2011

Empirical Tests of the Predicted Footprint for Uncontrolled Satellite Reentry Hazards

A number of statistical tools have been developed over the years for assessing the risk of reentering object to human populations. These tools make use of the characteristics (e.g., mass, material, shape, size) of debris that are predicted by aerothermal models to survive reentry. The statistical tools use this information to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of the analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. Because this information is used in making policy and engineering decisions, it is important that these assumptions be tested using empirical data. This study uses the latest database of known uncontrolled reentry locations measured by the United States Department of Defense. The predicted ground footprint distributions of these objects are based on the theory that their orbits behave basically like simple Kepler orbits. However, there are a number of factors in the final stages of reentry - including the effects of gravitational harmonics, the effects of the Earth s equatorial bulge on the atmosphere, and the rotation of the Earth and atmosphere - that could cause them to diverge from simple Kepler orbit behavior and possibly change the probability of reentering over a given location. In this paper, the measured latitude and longitude distributions of these objects are directly compared with the predicted distributions, providing a fundamental empirical test of the model assumptions.

Matney, Mark↗
NASA NTRS2011

Statistical Issues for Uncontrolled Reentry Hazards Empirical Tests of the Predicted Footprint for Uncontrolled Satellite Reentry Hazards

A number of statistical tools have been developed over the years for assessing the risk of reentering objects to human populations. These tools make use of the characteristics (e.g., mass, material, shape, size) of debris that are predicted by aerothermal models to survive reentry. The statistical tools use this information to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of the analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. Because this information is used in making policy and engineering decisions, it is important that these assumptions be tested using empirical data. This study uses the latest database of known uncontrolled reentry locations measured by the United States Department of Defense. The predicted ground footprint distributions of these objects are based on the theory that their orbits behave basically like simple Kepler orbits. However, there are a number of factors in the final stages of reentry - including the effects of gravitational harmonics, the effects of the Earth s equatorial bulge on the atmosphere, and the rotation of the Earth and atmosphere - that could cause them to diverge from simple Kepler orbit behavior and possibly change the probability of reentering over a given location. In this paper, the measured latitude and longitude distributions of these objects are directly compared with the predicted distributions, providing a fundamental empirical test of the model assumptions.

Matney, Mark↗
DOE OSTI2022

PyOECP: A flexible open-source software library for estimating and modeling the complex permittivity based on the open-ended coaxial probe (OECP) technique

Here, we present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on three different methods. The software library contains the dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) in the field of science and engineering are required only so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov Chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, electrode polarization, a typical measurement artifact for interpreting dielectric spectra, can be incorporated into the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem), is also included. This open-source software enables users to freely adjust the physical parameters to obtain physical insight into their materials under test and will be consistently updated for more accurate measurement and interpretation of dielectric spectra in an automated manner. This work describes the theoretical and mathematical background of the software, lays out the workflow, and validates the software functionality based on both synthetic and empirical data included in the software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Metabolic tradeoffs and heterogeneity in microbial responses to temperature determine the fate of litter carbon in simulations of a warmer world

Abstract. Climate change has the potential to destabilize the Earth's massive terrestrial carbon (C) stocks, but the degree to which models project this destabilization to occur depends on the kinds and complexities of microbial processes they simulate. Of particular note is carbon use efficiency (CUE), which determines the fraction of C processed by microbes that is anabolized into microbial biomass rather than lost to the atmosphere and soil as carbon dioxide and extracellular products. The temperature sensitivity of CUE is often modeled as an intrinsically fixed (homogeneous) property of the community, which contrasts with empirical data and has unknown impacts on projected changes to the soil C cycle under global warming. We used the Decomposition Model of Enzymatic Traits (DEMENT) – which simulates taxon-level litter decomposition dynamics – to explore the effects of introducing organism-level heterogeneity into the CUE response to temperature for decomposition of leaf litter under 5 ∘C of warming. We found that allowing the CUE temperature response to differ between taxa facilitated increased loss of litter C, unless fungal taxa were specifically restricted to decreasing CUE with temperature. Litter C loss was exacerbated by variable and elevated CUE at higher temperature, which effectively lowered costs for extracellular enzyme production. Together these results implicate a role for diversity of taxon-level CUE responses in driving the fate of litter C in a warmer world within DEMENT, which should be explored within the framework of additional model structures and validated with empirical studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Bubble Generation in a Flowing Liquid Medium and Resulting Two-Phase Flow in Microgravity

The present investigation reports a study of bubble generation under reduced gravity conditions, using both a co-flow and a cross-flow configuration. This study may be used in the conceptual design of a space-based thermal management system. Ensuing two-phase flow void fraction can be accurately monitored using a single nozzle gas injection system within a continuous liquid flow conduit, as utilized in the present investigation. Accurate monitoring of void fraction leads to precise control of heat and mass transfer coefficients related to a thermal management system; hence providing an efficient and highly effective means of removing heat aboard spacecraft or space stations. Our experiments are performed in parabolic flight aboard the modified DC-9 Reduced Gravity Research Aircraft at NASA Lewis Research Center, using an air-water system. For the purpose of bubble dispersion in a flowing liquid, we use both a co-flow and a cross-flow configuration. In the co-flow geometry, air is introduced through a nozzle in the same direction with the liquid flow. On the other hand, in the cross-flow configuration, air is injected perpendicular to the direction of water flow, via a nozzle protruding inside the two-phase flow conduit. Three different flow conduit (pipe) diameters are used, namely, 1.27 cm, 1.9 cm and 2.54 cm. Two different ratios of nozzle to pipe diameter (D(sub N))sup * are considered, namely (D(sub N))sup * = 0.1 and 0.2, while superficial liquid velocities are varied from 8 to 70 cm/s depending on flow conduit diameter. It is experimentally observed that by holding all other flow conditions and geometry constant, generated bubbles decrease in size with increase in superficial liquid velocity. Detached bubble diameter is shown to increase with air injection nozzle diameter. Likewise, generated bubbles grow in size with increasing pipe diameter. Along the same lines, it is shown that bubble frequency of formation increases and hence the time to detachment of a forming bubble decreases, as the superficial liquid velocity is in-creased. Furthermore, it is shown that the void fraction of the resulting two-phase flow increases with volumetric gas flow rate Q(sub d), pipe diameter and gas injection nozzle diameter, while they decrease with surrounding liquid flow. The important role played by flowing liquid in detaching bubbles in a reduced gravity environment is thus emphasized. We observe that the void fraction can be accurately controlled by using single nozzle gas injection, rather than by employing multiple port injection, since the later system gives rise to unpredictable coalescence of adjacent bubbles. It is of interest to note that empirical bubble size and corresponding void fraction are somewhat smaller for the co-flow geometry than the cross-flow configuration at similar flow conditions with similar pipe and nozzle diameters. In order to supplement the empirical data, a theoretical model is employed to study single bubble generation in the dynamic (Q(sub d) = 1 - 1000 cu cm/s) and bubbly flow regime within the framework of the co-flow configuration. This theoretical model is based on an overall force balance acting on the bubble during the two stages of generation, namely the expansion and the detachment stage. Two sets of forces, one aiding and the other inhibiting bubble detachment are identified. Under conditions of reduced gravity, gas momentum flux enhances, while the surface tension force at the air injection nozzle tip inhibits bubble detachment. In parallel, liquid drag and inertia can act as both attaching and detaching forces, depending on the relative velocity of the bubble with respect to the surrounding liquid. Predictions of the theoretical model compare well with our experimental results. However, at higher superficial liquid velocities, as the bubble loses its spherical form, empirical bubble size no longer matches the theoretical predictions. In summary, we have developed a combined experimental and theoretical work, which describes the complex process of bubble generation and resulting two-phase flow in a microgravity environment. Results of the present study can be used in a wide range of space-based applications, such as thermal energy and power generation, propulsion, cryogenic storage and long duration life support systems, necessary for programs such as NASA's Human Exploration for the Development of Space (HEDS).

Pais, S. C.↗
NASA NTRS2017

The Substorm Cycle as Reproduced by Global MHD Models

Recently, Gordeev et al. (2015) suggested a method to test global MHD models against statistical empirical data. They showed that four community-available global MHD models supported by the Community Coordinated Modeling Center (CCMC) produce a reasonable agreement with reality for those key parameters (the magnetospheric size, magnetic field, and pressure) that are directly related to the large-scale equilibria in the outer magnetosphere. Based on the same set of simulation runs, here we investigate how the models reproduce the global loading-unloading cycle. We found that in terms of global magnetic flux transport, three examined CCMC models display systematically different response to idealized2 h north then 2 h south interplanetary magnetic field (IMF) Bz variation. The LFM model shows a depressed return convection and high loading rate during the growth phase as well as enhanced return convection and high unloading rate during the expansion phase, with the amount of loaded unloaded magnetotail flux and the growth phase duration being the closest to their observed empirical values during isolated substorms. Two other models exhibit drastically different behavior. In the BATS-R-US model the plasma sheet convection shows a smooth transition to the steady convection regime after the IMF southward turning. In the Open GGCM a weak plasma sheet convection has comparable intensities during both the growth phase and the following slow unloading phase. We also demonstrate potential technical problem in the publicly available simulations which is related to post processing interpolation and could affect the accuracy of magnetic field tracing and of other related procedures.

Gordeev, E.↗