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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 199 records · Page 11

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NASA NTRS1990

Minimal spectrum of long-wave perturbations - Is linear growth correct only in the nonlinear regime?

Very high resolution two-dimensional simulations are used to test the generation and growth of the so-called 'minimal' k exp 4 power spectrum which develops from initial conditions which have power only on small scales, such as might result from some process in the early universe. It is confirmed that the amplitude of minimal long-wave power grows proportionally to a exp 4, not a-squared, where a is the scale factor of the expanding universe. It reverts to a-squared only after the short-wave modes are effectively saturated, and by that time an effective long-wave power law closer to k-cubed is found. Small-scale perturbations may result in much more long-wave power than has been generally assumed.

Shandarin, Sergei F.↗

NASA NTRSDate not supplied

Plasma Assisted Nutrient Recovery from Inedible Biomass via Ash Leaching

Sustaining a human presence on the Moon, Mars, or deep space will require closing loops on many life support systems. Some form of agriculture will be required because plants produce the vitamins, antioxidants, and essential oils in our diets that degrade over time in stored foods. In addition, they provide dietary fiber, revitalize air and purify water. It is estimated that 93 kg of plant nutrients are required to support one crew member per year. Growing plants will require recycling nutrients trapped in inedible plant stems, leaves and debris. We examined the effects of using thermal plasma and various carrier gases to breakdown inedible plant biomass and aid in nutrient recovery. Previous work demonstrated a thermally degrading environment such as a muffle furnace improved nutrient recovery from inedible biomass prior to an acid leaching process, however, a muffle furnace is an inefficient process. We tested the ability of a small scale, thermal plasma using carbon dioxide, nitrogen, or air as plasma carrier gases to degrade pelleted plant biomass. The gases were chosen to explore variations in recovery and potential chemical by-products. Plasma treated and untreated biomass was leached with different concentrations of acid to determine the extraction of nutrients (potassium, magnesium, calcium, and. phosphorus) for reuse in the crop production cycle. Results are presented showing the impact of plasma processing prior to acid leaching on recovery of plant nutrients.

Plasma↗

DOE OSTI2022

Chemistry-mediated Ostwald ripening in carbon-rich C/O systems at extreme conditions

Abstract There is significant interest in establishing a capability for tailored synthesis of next-generation carbon-based nanomaterials due to their broad range of applications and high degree of tunability. High pressure (e.g., shockwave-driven) synthesis holds promise as an effective discovery method, but experimental challenges preclude elucidating the processes governing nanocarbon production from carbon-rich precursors that could otherwise guide efforts through the prohibitively expansive design space. Here we report findings from large scale atomistically-resolved simulations of carbon condensation from C/O mixtures subjected to extreme pressures and temperatures, made possible by machine-learned reactive interatomic potentials. We find that liquid nanocarbon formation follows classical growth kinetics driven by Ostwald ripening (i.e., growth of large clusters at the expense of shrinking small ones) and obeys dynamical scaling in a process mediated by carbon chemistry in the surrounding reactive fluid. The results provide direct insight into carbon condensation in a representative system and pave the way for its exploration in higher complexity organic materials. They also suggest that simulations using machine-learned interatomic potentials could eventually be employed as in-silico design tools for new nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

Plasmaspheric Plume Turbulence: Signature of an Electrostatic Corotation Convection Shear-Layer Instability

As demonstrated by IMAGE-EUV observations, plasmaspheric drainage plumes are a common feature emanating from the plasmasphere during periods of enhanced convection. Concurrent IMAGE-EUV and LANL-MPA observations reveal that plasmaspheric plumes are not a uniform density structure that extends out to geosynchronous orbit and beyond. Instead, in–situ observations reveal a large spatial-scale structure populated by small-scale density structures suggestive of the presence of a turbulent process. Here, we investigate the occurrence and nature of plasmaspheric drainage plumes as observed by concurrent EUV-MPA observations, as well as explore the possibility that the in–situ observed small-scale density structures are the signature of an instability produced by the sheared velocity found within the plasmaspheric layers separating the corotation of the main plasmasphere from the convection-driven flow generating the plume. Particle-in-cell simulations indicate that the generation of shear-flow driven instabilities is possible under plasmaspheric plasma conditions. The initial results of these simulations indicate that the plasmaspheric instabilities generated are electrostatic in nature, consist with in–situ plume observations.

Mark L Adrian↗

DOE OSTI2024

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗

DOE OSTI2020

Learning from existing photovoltaic technologies to identify alternative perovskite module designs

Perovskite solar cells have now become the most efficient of all multicrystalline thin film photovoltaic technologies, reaching 25.2% in 2019. This outstanding figure of merit has only been achieved on small lab-scale devices, with significantly lower performance when processed on larger more industrially relevant substrate sizes. Perovskite modules, connecting several smaller area cells together, are commonly demonstrated with a superstrate monolithic interconnection method. However, several other module designs exist and remain largely unexplored by the perovskite community. In this work, we review and highlight those alternatives and discuss their advantages and limitations. We propose that a singulated substrate-oriented module design, using metallic substrates, could provide a quicker path to seeing highly efficient, lightweight, and flexible perovskite modules on the market, while mitigating near-term technical risks. Finally, as an experimental starting-point towards this design, we demonstrate a substrate-oriented all-perovskite 2-terminal tandem with 18% efficiency.

14 SOLAR ENERGY↗

NASA NTRS1981

Acoustic and turbulence measurements of a tone-excited jet with and without flight simulation

Acoustic as well as turbulence measurements were made of tone-excited jets to obtain an understanding of the broadband noise augmentation mechanism. Results for both heated and unheated jets with and without flight simulation are presented for a range of excitation frequencies and levels, as well as for the zero order and first order spinning modes. It is argued that although the phase-locked large-scale turbulence structure is at the root of the noise amplification process, the actual noise generation mechanism lies in the small-scale turbulence. Results show that (1) the phase velocity of the excited large scale instability waves is subsonic relative to the ambient fluid and (2) broadband jet noise is almost uniform at all frequencies. Moreover, when the large-scale and small-scale structures are plotted against forward velocity (for a given upstream excitation level of 141 dB), the change in large-scale turbulence is negligible with forward velocity, whereas the small-scale turbulence decreases for both excited and unexcited jets. Also, the corresponding difference in far-field noise does not appear to change significantly, indicating that the changes in small-scale turbulence are responsible for jet noise amplification.

Ahuja, K. K.↗

NASA NTRS1992

Pulsed thrust propellant reorientation - Concept and modeling

The use of pulsed thrust to optimize the propellant reorientation process is proposed. The ECLIPSE code is used to study the performance of pulsed reorientation in small-scale and full-scale propellant tanks. A dimensional analysis of the process is performed and the resulting dimensionless groups are used to present and correlate the computational predictions of reorientation performance. Based on the results obtained from this study, it is concluded that pulsed thrust reorientation seems to be a feasible technique for optimizing the propellant reorientation process across a wide range of spacecraft, for a variety of missions, for the entire duration of a mission, and with a minimum of hardware design and qualification.

Hochstein, John I.↗

NASA NTRS1980

Low-cost LANDSAT processing system

LANDSAT analysis system is assembled from commercially available components at relatively low cost. Small-scale system is put together for price affordable for state agencies and universities. It processes LANDSAT data for subscene areas on repetitive basis. Amount of time required for processing decreases linearly with number of classifications desired. Computer programs written in FORTRAN IV are available for analyzing data.

Faust, N. L.↗

NASA NTRS1993

A pattern recognition system for locating small volvanoes in Magellan SAR images of Venus

The Magellan data set constitutes an example of the large volumes of data that today's instruments can collect, providing more detail of Venus than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations put together. However, data analysis technology has not kept pace with data collection and storage technology. Due to the sheer size of the data, complete and comprehensive scientific analysis of such large volumes of image data is no longer feasible without the use of computational aids. Our progress towards developing a pattern recognition system for aiding in the detection and cataloging of small-scale natural features in large collections of images is reported. Combining classical image processing, machine learning, and a graphical user interface, the detection of the 'small-shield' volcanoes (less than 15km in diameter) that constitute the most abundant visible geologic feature in the more that 30,000 synthetic aperture radar (SAR) images of the surface of Venus are initially targeted. Our eventual goal is to provide a general, trainable tool for locating small-scale features where scientists specify what to look for simply by providing examples and attributes of interest to measure. This contrasts with the traditional approach of developing problem specific programs for detecting Specific patterns. The approach and initial results in the specific context of locating small volcanoes is reported. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanoes visible in the Magellan data. Identifying and studying these volcanoes is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is forbiddingly time-consuming. Hence, the development of techniques to partially automate this task were undertaken. The primary constraints for this particular problem are that the method must be reasonably robust and fast. Unlike most geological features, the small volcanoes of Venus can be ascribed to a basic process that produces features with a short list of readily defined characteristics differing significantly from other surface features on Venus. For pattern recognition purposes the relevant criteria include (1) a circular planimetric outline, (2) known diameter frequency distribution from preliminary studies, (3) a limited number of basic morphological shapes, and (4) the common occurrence of a single, circular summit pit at the center of the edifice.

Burl, M. C.↗

NASA NTRS2004

On Efficient Multigrid Methods for Materials Processing Flows with Small Particles

Multiscale modeling of materials requires simulations of multiple levels of structural hierarchy. The computational efficiency of numerical methods becomes a critical factor for simulating large physical systems with highly desperate length scales. Multigrid methods are known for their superior efficiency in representing/resolving different levels of physical details. The efficiency is achieved by employing interactively different discretizations on different scales (grids). To assist optimization of manufacturing conditions for materials processing with numerous particles (e.g., dispersion of particles, controlling flow viscosity and clusters), a new multigrid algorithm has been developed for a case of multiscale modeling of flows with small particles that have various length scales. The optimal efficiency of the algorithm is crucial for accurate predictions of the effect of processing conditions (e.g., pressure and velocity gradients) on the local flow fields that control the formation of various microstructures or clusters.

Thomas, James↗

NASA NTRS2022

Plasma Assisted Nutrient Recovery from Inedible Biomass via Ash Leaching

Sustaining a human presence on the Moon, Mars, or deep space will require closing loops on many life support systems. Some form of agriculture will be required because plants produce the vitamins, antioxidants, and essential oils in our diets that degrade over time in stored foods. In addition, they provide dietary fiber, restore air, and purify water. Growing plants will require recycling nutrients trapped in inedible vegetation. Researchers at KSC have investigated the use of a thermal plasma with various carrier gases to thermally degrade inedible plant biomass for nutrient recovery. Previous work demonstrated a thermally degrading environment such as a muffle furnace improved nutrient recovery from inedible biomass prior to an acid leaching process. However, a muffle furnace is an inefficient process. We have explored the use of a small scale, thermal plasma for degradation of pellets to enhance the breakdown of plant stems, leaves, and debris to further close the nutrient loop. Plasma carrier gases such as carbon dioxide (CO2), nitrogen (N2), and air were used to explore variations in recovery and potential chemical by-products. Plasma processed inedible biomass was added to varying concentrations of acid solution for leaching of nutrients (e.g. potassium (K) , magnesium (Mg), calcium (Ca), and phosphorus (P)) for reuse in the crop production cycle. We also examined total N2 recovery. Results are presented showing the impact of plasma processing prior to acid leaching on recovery of plant nutrients.

Kenneth Engeling↗

DOE OSTI2023

Advanced Processing of Rare Earth Elements and Critical Minerals from Acid Mine Drainage Feedstocks

Ongoing work by the project team identified a process for extracting rare earths and critical mineral (REE/CM) concentrates from acid mine drainage from coal mines, a major stream pollutant. The process removes harmful metals and separates REE/CM into economically attractive concentrates. This project explored the processing of those concentrates into individually separated, high purity metals, suitable for domestic manufacturers. The team brought unique experience in working with AMD-based feedstocks since the inception of USDOE’s coal-based REE/CM program in 2016. The project team has pioneered the recovery of rare earth/critical minerals (REE/CM) from acid mine drainage (AMD). This environmentally beneficial strategy will incentivize AMD treatment while recovering materials critical to the Nation’s defense and advanced manufacturing industries. In addition, the project will investigate the co-production of five high purity CMs from AMD, namely Co, Mn, Li, Cr, Ge. This team’s upstream and midstream recovery and processing technology has been demonstrated at the continuous, small scale pilot scale. In conjunction with the West Virginia Department of Environmental Protection, the team is constructing a full-scale, integrated, 500 gpm AMD treatment plant coupled with an REE/CM facility that will produce 21 tons REE/CM per year. Commissioning is scheduled for September 2021. This will provide feedstock for the team’s proprietary downstream processes that met the project objective: production of individually separated, high purity (ISHP) REE/CM oxides and their further processing to elemental metals (REM). To facilitate entry into the U.S. market, we have teamed up with companies that would use our products to strengthen their domestic supply chains and grow REE/CM based manufacturing in the U.S. They include Rockwell Automation, Rivian, Endress+Hauser, Inc., Northrop Grumman and Hela Novel Metals.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Making coal relevant for small scale applications: Modular gasification for syngas/engine CHP applications in challenging environments

Small-scale coal gasification technology, coupled to a reciprocating engine generator, has the potential for making coal a cost competitive resource for meeting the flexible energy needs and resiliency requirements of utilities across the United States. To maintain grid stability and reliability, electrical generation must be regulated to match the load at the proper voltage and frequency. With the expansion of intermittent sources into the grid, such as wind and solar, frequency and voltage regulation become increasingly important and challenging. This work presents the results of a Front End Engineering Design (FEED) effort to detail the engineering and preliminary economics of a small-scale, air blown, fixed-bed gasification process, operating at near-atmospheric pressure, with gas cleanup to provide syngas and pyrolysis liquid fuels for use in reciprocating engine generators for combined heat and power at the University of Alaska Fairbanks. A very detailed assessment of capital and operating costs allows the evaluation of a levelized cost of electricity of 208.06 $/MWh, which can be reduced through the selling of by-products (steam for heating purposes and pyrolysis liquids to be used for power generation in an existing diesel engine). Here, a combined sensitivity analysis, based on the Monte Carlo approach, has been carried out to evaluate the effects of the uncertainties (capital and operating costs and plant annual availability) on the LCOE.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

1 H chemical shift anisotropy: a high sensitivity solid-state NMR dynamics probe for surface studies?

We report dynamics play significant roles in chemistry and biochemistry-molecular motions impact both large- and small-scale chemical reactions in addition to biochemical processes. In many systems, including heterogeneous catalysts, the characterization of dynamics remains a challenge. The most common approaches involve the solid-state NMR measurement of anisotropic interactions, in particular 2 H quadrupolar coupling and 1 H–X dipolar coupling, which generally require isotope enrichment. Due to the high sensitivity of 1 H NMR, 1 H chemical shift anisotropy (CSA) is a particularly enticing, and underexplored, dynamics probe. We carried out 1 H CSA and 1 H– 13 C dipolar coupling measurements in a series of model supported complexes to understand how 1 H CSA can be leveraged to gain dynamic information for heterogeneous catalysts. Mathematical descriptions are given for the dynamic averaging of the CSA tensor, and its dependence on orientation and asymmetry. The variability of the orientation of the tensor in the molecular frame, in addition to its magnitude and asymmetry, negatively impacts attempts to extract quantitative dynamic information. Nevertheless, 1 H CSA measurements can reveal useful qualitative insights into the motions of a particularly dilute site, such as from a surface species.

1H chemical shift anisotropy↗

DOE OSTI2021

HED Hydrodynamics in the Common Modeling Framework

Within the Common Modeling Framework (CMF), the HED Hydrodynamics Project has implemented a common methodology, or "Authority", for modeling high energy density (HED) experiments by extending development of the Eulerian Applications Project code Authority, "EAPA," to include relevant physics models, customization tools and templates, and in situ and post-processing capabilities. Additionally, several models for small-scale HED experiments were successfully added to the CMF and simulations reproduce the results of preexisting, benchmarked input decks. We expect use of the CMF to improve our effectiveness in developing predictive capabilities for experiments ranging from small-scale planar single-interface, single-shock to multi-interface, multi-shock configurations and up through multi-shell inertial confinement fusion (ICF) implosions. Additionally, this will strengthen our ability to design future targeted experiments. Using the CMF infrastructure and Authorities for HED modeling has three key impacts. First, it enables a version-controlled, pedigreed and archived base model for each experiment with tools that allow easy setup, execution and analysis of simulations to assess and/or expose sensitivities to various parameters. Second, having a common base set of inputs and physics definitions helps identify systematic differences between models in the codes and experimental data to support code validation, and build confidence in our predictive capabilities. Finally, designed to work in concert with multiple programs and projects including PEM, IC, OES, V&V and DSW, the CMF supports improved collaboration and integration through shared model definitions, data, simulations and results, enhancing the workflow required to underwrite the knowledge base and capabilities ultimately required for stockpile stewardship

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

The Aemulus Project. VI. Emulation of Beyond-standard Galaxy Clustering Statistics to Improve Cosmological Constraints

Abstract There is untapped cosmological information in galaxy redshift surveys in the nonlinear regime. In this work, we use the Aemulus suite of cosmological N -body simulations to construct Gaussian process emulators of galaxy clustering statistics at small scales (0.1–50 h −1 Mpc) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics—the projected correlation function w p ( r p ), the redshift-space monopole of the correlation function ξ 0 ( s ), and the quadrupole ξ 2 ( s )—we emulate statistics that include information about the local environment, namely the underdensity probability function P U ( s ) and the density-marked correlation function M ( s ). This extends the model of Aemulus III for redshift-space distortions by including new statistics sensitive to galaxy assembly bias. In recovery tests, we find that the beyond-standard statistics significantly increase the constraining power on cosmological parameters of interest: including P U ( s ) and M ( s ) improves the precision of our constraints on Ω m by 27%, σ 8 by 19%, and the growth of structure parameter, f σ 8 , by 12% compared to standard statistics. We additionally find that scales below ∼6 h −1 Mpc contain as much information as larger scales. The density-sensitive statistics also contribute to constraining halo occupation distribution parameters and a flexible environment-dependent assembly bias model, which is important for extracting the small-scale cosmological information as well as understanding the galaxy–halo connection. This analysis demonstrates the potential of emulating beyond-standard clustering statistics at small scales to constrain the growth of structure as a test of cosmic acceleration.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1976

Spectral and spatial energetics of the GISS model atmosphere

A calculation of the spectral and spatial energetics of the Goddard Institute for Space Studies (GISS) 9-level model of the global atmosphere is given. Results are presented from a model simulation of January 1973 and compared with previous model studies and an observational analysis for the Northern Hemisphere. The spectral analysis permits detailed study of those physical processes of scale larger than the grid spacing and allows indirect conclusions concerning unresolved subgrid-scale processes. Major conclusions for larger-than-grid-scale processes are that (1) the GISS model with a relatively coarse resolution of 4 deg latitude by 5 deg longitude produces significant nonlinear energy transfers; and (2) baroclinic conversion is large near planetary wave-number 6, but both the GISS model and another orographic model show a less peaked structure than nonorographic models and observations. A linear fit to the kinetic energy spectrum yields a power law of -2.6 in the wavenumber region 8 to 15. For subgrid-scale processes, the turbulence theory result of very small energy flux cascade is obtained.

Tenenbaum, J.↗