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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 757 records · Page 42

Spread spectrum fiber-optic local area network using optical processing

Spread spectrum code division multiple access (CDMA) allows asynchronous multiple access to a local area network (LAN) with no waiting. The additional bandwidth required by spread spectrum can be accommodated by using a fiber-optic channel and incoherent optical signal processing. New CDMA sequences are designed specifically for optical processing. It is shown that increasing the number of chips per bit, by using optical processing, allows an increase in capacity of a CDMA LAN. An experiment is performed demonstrating the performance of an optical CDMA LAN, operating at 100 Mbd with three users.

Prucnal, P. R.↗

Orbit Transfers for Dawn's Vesta Operations : Navigation and Mission Design Experience

Dawn, a mission belonging to NASA's Discovery Program, was launched on September 27, 2007 to explore main belt asteroids in order to yield insights into important questions about the formation and evolution of the solar system. From July of 2011 to August of 2012, the Dawn spacecraft successfully returned valuable science data, collected during the four planned mapping orbits at its first target asteroid, Vesta. Each mapping orbit was designed to enable a different set of scientific observations. Such a mission would have been impossible without the low thrust ion propulsion system (IPS). Maneuvering a spacecraft using only the IPS for the transfers between the mapping orbits posed many technical challenges to Dawn's flight team at NASA's Jet Propulsion Laboratory. Each transfer needs a robust plan that accounts for uncertainties in maneuver execution, orbit determination, and physical characteristics of Vesta. This paper discusses the mission design and navigational experience during Dawn's Vesta operations. Topics include requirements and constraints from Dawn's science and spacecraft teams, orbit determination and maneuver design and building process for transfers, developing timelines for thrust sequence build cycles, and the process of scheduling very demanding coverage with ground antennae at NASA's Deep Space Network.

low thrust↗

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗

Experiment S051: Daytime sodium cloud

Daytime wind velocity measurements of the upper atmosphere as function of altitude were supposed to be gathered by Gemini 12 sequential photography of rocket made sodium clouds. Evaluation of the film was indicative that all 26 photographs were overexposed during the photographic sequences. The overexposures were caused by a camera shutter locked in the open position. Therefore, useful photographic data were not obtained for analysis.

Blamont, J. E.↗

Conclusion of Viking Lander Imaging Investigation: Picture catalog of experiment data record

The images returned by the two Viking landers during the Viking Survey Mission are presented in this report. Listing of supplemental information which describe the conditions under which the images were acquired are included. Subsets of the images are listed in a variety of sequences to aid in locating images of interest. The format and organization of the digital magnetic tape storage of the images are described. A brief description of the mission and the camera system is also included.

Wall, S. D.↗

Data-driven prediction of geometry- and toolpath sequence-dependent intra-layer process conditions variations in laser powder bed fusion

Geometrical features and toolpath sequence are two important factors that cause process condition variations, such as variations in the meltpool temperature or meltpool size, that might lead to undesired material properties in the laser powder bed fusion (LPBF) process. Due to the high dynamics and complex physics of the LPBF process, it is difficult to predict variations in process conditions with simulations alone. Advances in measurement technology and computational technologies open up new possibilities for smart manufacturing. In this paper, a data-driven method to predict intra-layer variations in the processing conditions that source from the toolpath sequence and part geometry is presented. The approach is demonstrated using two-color on-axis pyrometer measurements. Three demonstration cases are presented in which it is demonstrated (1) how the trained predictive model can be used as a filter to ease the interpretation of process variations and discover patterns related to toolpath and part geometry, and (2) how to generate predictions that can be used for feedforward control, i.e., for adjusting laser power or scanning speed along the toolpath using a meltpool temperature prediction model generated based on on-axis measurements. Results show that the developed prediction model is able to meaningfully predict process variations resulted from toolpath sequence and geometry. Predictions are aligned with the results from the related work of others and for the case of 180° laser path turnarounds in our high-speed X-ray imaging experiments. In conclusion, the potential issues related to the current maturity status of the process and measuring equipment that could in practice affect the performance of the proposed solutions are also discussed.

42 ENGINEERING↗

Short-term load demand forecasting through rich features based on recurrent neural networks

With the emerging penetration of renewables and dynamic loads, the understanding of grid edge loading conditions becomes increasingly substantial. Load modelling researches commonly consist of explicitly expressed load models and non-explicitly expressed techniques, of which artificial intelligence approaches turn out to be the major path. This paper reveals the artificial intelligence-based load modelling technique to enhance the knowledge of current and future load information considering geographical and weather dependencies. This paper presents a recurrent neural network based sequence to sequence (Seq2Seq) model to forecast the short-term power loads. Also, a feature attention mechanism, which is along channel and time directions, is developed to improve the efficiency of feature learning. The experiments over three publicly available datasets demonstrate the accuracy and effectiveness of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The atomic gas sequence and mass–metallicity relation from dwarfs to massive galaxies

Galaxy scaling relations provide insights into the processes that drive galaxy evolution. The extension of these scaling relations into the dwarf galaxy regime is of particular interest. This is because dwarf galaxies represent a crucial stage in galaxy evolution, and understanding them could also shed light on their role in reionizing the early Universe. There is currently no consensus on the processes that dominate the evolution of dwarfs. In this work, we constrain the atomic gas sequence (stellar mass versus atomic gas fraction) and mass–metallicity relation (stellar mass versus gas-phase metallicity) from dwarf (⁠10 6.5 M ⊙ ⁠) to massive (⁠10 11.5 M ⊙ ) galaxies in the local Universe. The combined optical and 21-cm spectroscopic observations of the Dark Energy Spectroscopic Instrument and Arecibo Legacy Fast ALFA surveys allow us to constrain both scaling relations simultaneously. We find a slope change of the atomic gas sequence at a stellar mass of ~10 9 M ⊙ ⁠. We also find that the shape and scatter of the atomic gas sequence and mass–metallicity relation are strongly linked for both dwarfs and more massive galaxies. Consequently, the low-mass slope change of the atomic gas sequence is imprinted onto the mass–metallicity relation of dwarf galaxies. The mass scale of the measured slope change is consistent with a predicted escape velocity threshold below which low-mass galaxies experience significant supernova-driven gas loss, as well as with a reduction in cold gas accretion onto more massive galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Experimental quantum learning of a spectral decomposition

Currently available quantum hardware allows for small-scale implementations of quantum machine learning algorithms. Such experiments aid the search for applications of quantum computers by benchmarking the near-term feasibility of candidate algorithms. Here we demonstrate the quantum learning of a two-qubit unitary by a sequence of three parameterized quantum circuits containing a total of 21 variational parameters. Moreover, we variationally diagonalize the unitary to learn its spectral decomposition, i.e., its eigenvalues and eigenvectors. We illustrate how this can be used as a subroutine to compress the depth of dynamical quantum simulations. One can view our implementation as a demonstration of entanglement-enhanced machine learning, as only a single (entangled) training data pair is required to learn a 4 × 4 unitary matrix.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Unbalancing Symbiotic Nitrogen Fixation: Can We Make Effectiveness More Effective?

One of the most critical uses of carbon fuels is in generating nitrogen fertilizer. Atmospheric dinitrogen is too stable to be used directly by plants, so plants need other chemical forms of nitrogen. Nitrogen fertilizer production uses ~4% of the world’s natural gas. Making N fertilizers leverages methane’s energy content by enabling additional energy to be captured into food and fiber through increased photosynthesis. Manufacturing fertilizer is essential—without it there would only be enough combined nitrogen to feed ~3 billion of the world’s ~7 billion people. How to alter this addiction is not obvious, but the best chance to secure substantial and sustainable amounts of future N might be through symbiotic nitrogen fixation (SNF). SNF describes mutualistic interactions where nitrogen-fixing bacteria provide fixed nitrogen to their plant hosts, freeing them from the need for nitrogen fertilizers. SNF already occurs on a large scale; "biological nitrogen” contributes about 5 Tg N/yr to American agriculture, a quarter of the nitrogen needed. Improving SNF and replacing inorganic fertilizers are both important goals in establishing sustainable and more energy-efficient farming. SNF has been used in agriculture for millennia, largely by using legumes like beans or alfalfa in mixed cropping systems. Legume SNF occurs in root nodules, organs that develop after a growing root is infected by bacteria called rhizobia. In the plant cells of a legume nodule, specialized forms of rhizobia fix nitrogen and can produce enough ammonia to supply the growing plant. The exchange of photosynthetically derived plant carbon compounds for nitrogen reduced by the bacteria is the engine that drives the symbiosis. Important details about the organization of development and metabolism in SNF remain to be determined, such as how plant and bacterial metabolism are coordinated as nitrogen is being fixed and what governs the overall level of nitrogen fixation. Most bacterial mutations that affect SNF completely block fixation (e.g. are Fix – ), providing a limited window into the feedback interactions that must be part of the process. We have investigated an unusual mutant of Sinorhizobium meliloti, a symbiotic partner of alfalfa, that fixes dinitrogen at a normal rate (i.e., it is Fix + ) but is not effective in supporting plant growth (i.e., it is ineffective or Eff – ). We have shown that the mutant has a specific mutation in the glnD gene, which codes for a protein that regulates the bacterial response to nitrogen stress, among other key pathways. A Fix + Eff – phenotype contains an unavoidable puzzle—how is it possible for the bacteria to fix nitrogen at a normal rate and without benefiting the nitrogen starved plant host? After eliminating other possibilities, we proposed that the bacteria synthesize a nitrogen-containing compound that the plant can’t use so that acquiring this compound does not relieve plant nitrogen stress. Extracts of nodules made by glnD mutant strains have high concentrations of pyruvate canaline oxime (PCO), a derivative of the plant defensive compound canaline, a toxic analog of ornithine, an amino acid. Many legumes produce canaline and the related arginine mimic canavanine. For reasons we do not yet understand, the mutation in glnD appears to trigger significant overproduction of canaline in a defense response that leads to substantial synthesis of PCO. We expected the bacteria to be able to use PCO, but we have not been able to grow S. meliloti on PCO under several conditions. PCO thus appears to be a metabolic dead end for both the plant and bacteria. We also examined bacterial catabolic pathways that degrade arginine and canavanine and showed that mutation of these did not alter the symbiosis in an obvious way. In related experiments to examine the metabolic development of root nodules, we carried out an ambitious experiment to simultaneously measure metabolites and protein changes during nodule maturation. For these experiments we used a related symbiotic interaction between S. medicae and Medicago truncatula. M. truncatula has a simpler genome than alfalfa so we could identify plant proteins based on predictions from the DNA sequence. Nodules formed on Medicago grow linearly, with the least mature tissues at the tip. Because development of nitrogen fixation is accompanied by the production of the pigmented plant oxygen carrier protein leghemoglobin, we were able to locate and manually separate the tip, transitional, and mature nitrogen-fixing regions from each other. Advances in proteomic and metabolomic techniques allowed us to analyze these tissues from a pool of as few as 10 nodules. We observed correlated transitions of various enzymes in the plant and bacterial proteomes from those characteristic of free-living metabolism to the microaerobic metabolism of the nitrogen-fixing tissues. The metabolome could not be separated into plant and bacterial domains but was consistent with this overall transition. A subsequent paper examined proteolysis in nodule bacteria. Protein turnover in mature regions of the nodule is significant. We were able to show complexes between various proteins and important proteases, using precipitation capture techniques to isolate the proteases and sensitive proteomic analysis to reveal the associated proteins.

09 BIOMASS FUELS↗

AlgaeOrtho, a bioinformatics tool for processing ortholog inference results in algae

Introduction: Microalgae constitute a prominent feedstock for producing biofuels and biochemicals by virtue of their prolific reproduction, high bioproduct accumulation, and the ability to grow in brackish and saline water. However, naturally occurring wild type algal strains are rarely optimal for industrial use; therefore, bioengineering of algae is necessary to generate superior performing strains that can address production challenges in industrial settings, particularly the bioenergy and bioproduct sectors. One of the crucial steps in this process is deciding on a bioengineering target: namely, which gene/protein to differentially express. These targets are often orthologs which are defined as genes/proteins originating from a common ancestor in divergent species. Although bioinformatics tools for the identification of protein orthologs already exist, processing the output from such tools is nontrivial, especially for a researcher with little or no bioinformatics experience. Methods: The present study introduces AlgaeOrtho, a user-friendly tool that builds upon the SonicParanoid orthology inference tool (based on an algorithm that identifies potential protein orthologs based on amino acid sequences) and the PhycoCosm database from JGI (Joint Genome Institute) to help researchers identify orthologs of their proteins of interest in multiple diverse algal species. Results: The output of this application includes a table of the putative orthologs of their protein of interest, a heatmap showing sequence similarity (%), and an unrooted tree of the putative protein orthologs. Notably, the tool would be instrumental in identifying novel bioengineering targets in different algal strains, including targets in not-fully annotated algal species, since it does not depend on existing protein annotations. We tested AlgaeOrtho using three case studies, for which orthologs of proteins relevant to bioengineering targets, were identified from diverse algal species, demonstrating its ease of use and utility for bioengineering researchers. Discussion: This tool is unique in the protein ortholog identification space as it can visualize putative orthologs, as desired by the user, across several algal species.

09 BIOMASS FUELS↗

Research on metal solidification in zero-g state

The containerless solidification of several pure metals and metallic alloys was studied in a low gravity environment. The tests were performed in the MSFC 4.2 s drop tower using a rapid wire melting apparatus designed and built for this purpose. Pure iron and nickel, and alloys of iron-nickel, iron-carbon, nickel-aluminum and tungsten-rhenium were all melted and solidified at a gravity level of approximately 100.000/-4 g. Interpretation of the results has led to an appreciation of the factors controlling the successful execution of this drop test experiment and to a delineation of the limits of applicability of the apparatus. Preliminary metallurgical evaluations are presented of the overall shapes, lattice parameters, surface microstructure,, cross-sectional microstructures, solidification and transformation sequences, evaporative segregation, and localized solute redistribution observed in the low-gravity specimens. The effects of low gravity on metallic solidification are discussed with particular emphasis on observations of spontaneous undercooling and evaporative segregation in uncontained melts.

Papazian, J. M.↗

Considerations to achieve directionality for gamma ray lasers

A method of alignment of nuclei for a gamma ray laser and a means of achieving preferential emission of radiation along the crystal axis are discussed. The proposed method of preferential emission of radiation along the aligned needles is to have a symmetric field gradient at the nucleus and a sequence of excited levels of spin and parity 2(+) and C(+). The proposed scheme reduces the density of excited states required for lasing and reduces the linewidth due to inhomogeneous broadening. Mossbauer absorption experiments intended to test these ideas are outlined.

Jha, S.↗

Considerations to achieve directionality for gamma ray lasers

A method of alignment of nuclei for a gamma ray laser and a means of achieving preferential emission of radiation along the crystal axis are studied. Atomic alignment was achieved by materials researchers who made composite structures composed of needle-like single crystals all with the same orientation and all pointing in the same direction contained in a matrix of cobalt or nickel. The proposed method of preferential emission of radiation along the aligned needles is to have a symmetric field gradient at the nucleus and a sequence of excited levels of spin and parity 2(+) and 0(+). The proposed scheme reduces the density of excited states required for lasing and reduces the linewidth due to inhomogenous broadening. Mossbauer absorption experiments intended to test these ideas are outlined.

Jha, S.↗

Non-axisymmetric shapes of a rotating drop in an immiscible system

The nonaxisymmetric shapes of a rotating drop in an immiscible system were studied. Five basic families of shapes (axisymmetric, two-lobed, three-lobed, four-lobed, and toroidal) were observed. The sequence (axisymmetric to two-lobed to three-lobed to four-lobed to toroidal) seems to be linked to increasing spin-up velocity. For the axisymmetric case, direct comparisons of experiments with the theory of a free rotating drop were surprisingly good the equatorial area differs from theory by only 30%. Furthermore, the non-axisymmetric shapes are in good qualitative agreement with the theory, although the theory does not address the presence of an outer fluid.

Wang, T. G.↗

Apollo experience report: Guidance and control systems: Automated control system for unmanned mission AS-201

The Apollo command module heat shield and Apollo command and service module/Saturn launch vehicle structural integrity were evaluated in an unmanned test flight. An automated control system was developed to provide the mission event sequencing, the real-time ground control interface, and the backup attitude reference system for the unmanned flight. The required mission events, the design logic, the redundancy concept, and the ground-support-equipment concept are described and some development problem areas are discussed. The mission event time line and the real-time ground command list are included to provide an outline of the control system capabilities and requirements. The mission was accomplished with the automated control system, which functioned without flight anomalies.

Holloway, G. F.↗

In vitro selection of functional nucleic acids

In vitro selection allows rare functional RNA or DNA molecules to be isolated from pools of over 10(15) different sequences. This approach has been used to identify RNA and DNA ligands for numerous small molecules, and recent three-dimensional structure solutions have revealed the basis for ligand recognition in several cases. By selecting high-affinity and -specificity nucleic acid ligands for proteins, promising new therapeutic and diagnostic reagents have been identified. Selection experiments have also been carried out to identify ribozymes that catalyze a variety of chemical transformations, including RNA cleavage, ligation, and synthesis, as well as alkylation and acyl-transfer reactions and N-glycosidic and peptide bond formation. The existence of such RNA enzymes supports the notion that ribozymes could have directed a primitive metabolism before the evolution of protein synthesis. New in vitro protein selection techniques should allow for a direct comparison of the frequency of ligand binding and catalytic structures in pools of random sequence polynucleotides versus polypeptides.

Review↗

Melt spinning study

Containerless processing of materials provides an excellent opportunity to study nucleation phenomena and produce unique materials, primarily through the formation of metastable phases and deep undercoolings. Deep undercoolings can be readily achieved in falling drops of molten material. Extended solute solubilities and greatly refined microstructures can also be obtained in containerless processing experiments. The Drop Tube Facility at Marshall Space Flight Center has played an important role in enhancing that area of research. Previous experiments performed in the Drop Tube with refractory metals has shown very interesting microstructural changes associated with deep undercoolings. It is apparent also that the microstructure of the deep undercooled species may be changing due to the release of the latent heat of fusion during recalescence. For scientific purposes, it is important to be able to differentiate between the microstructures of the two types of metallic species. A review of the literature shows that although significant advances have been made with respect to the engineering aspects of rapid solidification phenomena, there is still much to be learned in terms of understanding the basic phenomena. The two major ways in which rapid solidification processing provides improved structures and hence improved properties are: (1) production of refined structures such as fine dendrites and eutectics, and (2) production of new alloy compositions, microstructures, and phases through extended solid solubility, new phase reaction sequences, and the formation of metallic-glass microstructures. The objective of this work has been to determine the optimal methodology required to extract this excess energy without affecting the thermo-physical parameters of the under-cooled melt. In normal containerless processing experiments recalescence occurs as the melt returns toward the melting point in order to solidify. A new type of experiment is sought in which the resultant microstructure of the undercooled species is frozen in without going through the melting point regime and subsequent near equilibrium solidification of the remaining liquid. This experimental approach entails the design of an appropriate melt spinning system which is compatible with Drop Tube operations and processing constraints. That work is the goal of this study.

Workman, Gary L.↗