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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 217 records · Page 12

Data for "Integrated Green Biorefinery for the Production of Anthocyanins, Fermentable Sugars, and High Pure Lignin from Miscanthus × giganteus "

Miscanthus x giganteus (Mxg) is a promising perennial crop for producing natural colorants, renewable fuels, and bioproducts. However, natural recalcitrance and high pretreatment cost are major barriers to their complete conversion. In this study, a green processing method has been investigated for efficient recovery of natural pigments (anthocyanins), fermentable sugars, and pure lignin from Mxg genotypes using choline chloride-based natural deep eutectic solvents (NADES) systems. Interestingly, choline chloride: lactic acid (ChCl: LA) NADES-processed biomass resulted in 67.8 ± 2.1 μg g−1 of anthocyanins from dry biomass. A maximum of 87.4%–94.1% glucose yield was achieved after enzymatic saccharification. The effective extraction of lignin with high purity with higher β-aryl ether (βO4) bonds from advanced crops is crucial for lignin valorization. Notably, highly pure lignin (≈93.4% ± 1.4%) is achieved after low-temperature NADES pretreatment while retaining lignin’s native structure. 31P nuclear magnetic resonance demonstrated that total phenolics for ChCl: LA-lignin resulted in 1.20 mmol g−1 hydroxyls. The relative monolignol composition of syringyl (S), guaiacyl (G), and p-hydroxyphenyl (H) is 19.0, 65.7, and 14.3%, respectively, as evidenced by heteronuclear single quantum coherence analysis. This study provides a novel approach for obtaining high-purity lignin for catalytic depolymerization for oligomers and bifunctional monoaromatics production and leverages current cellulosic biorefinery technologies.

biomass analytics

Continuous integration data-driven platform of industrial-scale subsurface storage for real-time analytics

This project helped address the growing need for efficient and scalable models to support geological carbon and energy storage, which are crucial for achieving net-zero emissions. Traditionally accurate high-fidelity numerical models have been used to simulate relevant storage processes under a handful of processes, however such models are computationally demanding, making uncertainty quantification impractical. Consequently, we first developed a machine learning framework, based on Graph Neural Operators (GNOs), to improving the accuracy of model predictions for a fixed computational budget. We then developed an Ensemble of Improved Neural Operators (ENO), which uses bagging and Monte Carlo dropout techniques, to further improve prediction accuracy. Lastly, we developed the way to explain progressive transfer learning methods to reduce the amount of training data and computational cost of training (i.e., reduce trainable parameters) when using our models for multiple storage sites. Our numerical investigation, which used real-world case studies, demonstrated that our framework can significantly improve the safety and efficiency of geological storage operations, with potential applications in other domains such as geothermal reservoirs and climate modeling.

54 ENVIRONMENTAL SCIENCES

Data for "Integrated ab initio modelling of atomic order and magnetic anisotropy for rare-earth-free magnet design: effects of alloying additions in L1 0 FeNi."

We describe an integrated modelling approach to accelerate the search for novel, single-phase, multicomponent materials with high magnetocrystalline anisotropy (MCA). For a given system we predict the nature of atomic ordering, its dependence on the magnetic state, and then proceed to describe the consequent MCA, magnetisation, and magnetic critical temperature (Curie temperature). Crucially, within our modelling framework, the same ab initio description of a material’s electronic structure determines all aspects. We demonstrate this holistic method by studying the effects of alloying additions in FeNi, examining systems with the general stoichiometries Fe 4 Ni 3 X and Fe 3 Ni 4 X, for additives including X = Pt, Pd, Al, and Co. The atomic ordering behaviour predicted on adding these elements, fundamental for determining a material’s MCA, is rich and varied. Equiatomic FeNi has been reported to require ferromagnetic order to establish the tetragonal L1 0 order suited for significant MCA. Our results show that when alloying additions are included in this material, annealing in an applied magnetic field and/or below a material’s Curie temperature may also promote tetragonal order, along with an appreciable effect on the predicted hard magnetic properties.

36 MATERIALS SCIENCE

An integrated LANDSAT/ancillary data classification of desert rangeland

Range inventorying methods using LANDSAT MSS data, coupled with ancillary data were examined. The study area encompassed nearly 20,000 acres in Rush Valley, Utah. The vegetation is predominately desert shrub and annual grasses, with some annual forbs. Three LANDSAT scenes were evaluated using a Kauth-Thomas brightness/greenness data transformation (May, June, and August dates). The data was classified using a four-band maximum-likelihood classifier. A print map was taken into the field to determine the relationship between print symbols and vegetation. It was determined that classification confusion could be greatly reduced by incorporating geomorphic units and soil texture (coarse vs fine) into the classification. Spectral data, geomorphic units, and soil texture were combined in a GIS format to produce a final vegetation map identifying 12 vegetation types.

Price, K. P.

An integrated Landsat/ancillary data classification of desert rangeland

Range inventorying methods using Landsat MSS data, coupled with ancillary data were examined. The study area encompassed nearly 20,000 acres in Rush Valley, UT. The vegetation is predominately desert shrub and annual grasses, with same annual forbs. Three Landsat scenes were evaluated using a Kauth-Thomas brightness/greenness data transformation (May, June, and August dates). The data was classified using a four-band maximum-likelihood classifier. A print map was taken into the field to determine the relationship between print symbols and vegetation. It was determined that classification confusion could be greatly reduced by incorporating geomorphic units and soil texture (coarse vs fine) into the classification. Spectral data, geomorphic units, and soil texture were combined in a GIS format to produce a final vegetation map identifying 12 vegetation types.

Price, K. P.

An ethnographic object-oriented analysis of explorer presence in a volcanic terrain environment: Claims and evidence

An ethnographic field study was conducted to investigate the nature of presence in field geology, and to develop specifications for domain-based planetary exploration systems utilizing virtual presence. Two planetary geologists were accompanied on a multi-day geologic field trip that they had arranged for their own scientific purposes, which centered on an investigation of the extraordinary xenolith/nodule deposits in the Kaupulehu lava flow of Hualalai Volcano, on the island of Hawaii. The geologists were observed during the course of their field investigations and interviewed regarding their activities and ideas. Analysis of the interview resulted in the identification of key domain entities and their attributes, relations among the entities, and explorer interactions with the environment. The results support and extend the author's previously reported continuity theory of presence, indicating that presence in field geology is characterized by persistent engagement with objects associated by metonymic relations. The results also provide design specifications for virtual planetary exploration systems, including an integrating structure for disparate data integration. Finally, the results suggest that unobtrusive participant observation coupled with field interviews is an effective research methodology for engineering ethnography.

Mcgreevy, Michael W.

Operationally Efficient Propulsion System Study (OEPSS) Data Book: Integrated Booster Propulsion Module (BPM) Engine Start Dynamics - Volume 8

A fluid-dynamic, digital-transient computer model of an integrated, parallel propulsion system was developed for the CDC mainframe and the SUN workstation computers. Since all STME component designs were used for the integrated system, computer subroutines were written characterizing the performance and geometry of all the components used in the system, including the manifolds. Three transient analysis reports were completed. The first report evaluated the feasibility of integrated engine systems in regards to the start and cutoff transient behavior. The second report evaluated turbopump out and combined thrust chamber/turbopump out conditions. The third report presented sensitivity study results in staggered gas generator spin start and in pump performance characteristics.

Kemp, Victoria R.

D3: A Collaborative Infrastructure for Aerospace Design

DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid dynamics) model executions. DARWIN captures, stores and indexes data, manages derived knowledge (such as visualizations across multiple data sets) and provides an environment for designers to collaborate in the analysis of the results of testing. DARWIN is an interesting application because it supports high volumes of data, integrates multiple modalities of data display (e.g. images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and view of data.

Walton, Joan

(abstract) Science-Project Interaction in the Low-Cost Mission

Large, complex, and highly optimized missions have performed most of the preliminary reconnaisance of the solar system. As a result we have now mapped significant fractions of its total surface (or surface-equivalent) area. Now, however, scientific exploration of the solar system is undergoing a major change in scale, and existing missions find it necessary to limit costs while fulfilling existing goals. In the future, NASA's Discovery program will continue the reconnaisance, exploration, and diagnostic phases of planetary research using lower cost missions, which will include lower cost mission operations systems (MOS). Historically, one of the more expensive functions of MOS has been its interaction with the science community. Traditional MOS elements that this interaction have embraced include mission planning, science (and engineering) event conflict resolution, sequence optimization and integration, data production (e.g., assembly, enhancement, quality assurance, documentation, archive), and other science support services. In the past, the payoff from these efforts has been that use of mission resources has been highly optimized, constraining resources have been generally completely consumed, and data products have been accurate and well documented. But because these functions are expensive we are now challenged to reduce their cost while preserving the benefits. In this paper, we will consider ways of revising the traditional MOS approach that might save project resources while retaining a high degree of service to the Projects' customers. Pre-launch, science interaction can be made simplier by limiting numbers of instruments and by providing greater redundancy in mission plans. Post launch, possibilities include prioritizing data collection into a few categories, easing requirements on real-time of quick-look data delivery, and closer integration of scientists into the mission operation.

mission operation science community interaction co