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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,243 records · Page 69

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DOE OSTI2016

Microscopic Fuel Particles Produced by Self-Assembly of Actinide Nanoclusters on Carbon Nanomaterials

Many consider further development of nuclear power to be essential for sustained development of society; however, the fuel forms currently used are expensive to recycle. In this project, we sought to create the knowledge and knowhow that are needed to produce nanocomposite materials by directly depositing uranium nanoclusters on networks of carbon- based nanomaterials. The objectives of the proposed work were to (1) determine the control of uranium nanocluster surface chemistry on nanocomposite formation, (2) determine the control of carbon nanomaterial surface chemistry on nanocomposite formation, and (3) develop protocols for synthesizing uranium-carbon nanomaterials. After examining a wide variety of synthetic methods, we show that synthesizing graphene-supported UO 2 nanocrystals in polar ethylene glycol compounds by polyol reduction under boiling reflux can enable the use of an inexpensive graphene precursor graphene oxide in the production of uranium-carbon nanocomposites in a one-pot process. We further show that triethylene glycol is the most suitable solvent for producing nanometer-sized UO 2 crystals compared to monoethylene glycol, diethylene glycol, and polyethylene glycol. Graphene-supported UO 2 nanocrystals synthesized with triethylene glycol show evidence of heteroepitaxy, which can be beneficial for facilitating heat transfer in nuclear fuel particles. Furthermore, we show that graphene-supported UO 2 nanocrystals synthesized by polyol reduction can be readily stored in alcohols, preventing oxidation from the prevalent oxygen in air. Together, these methods provide a facile approach for preparing and storing graphene-supported UO nanocrystals for further investigation and development under ambient conditions.

36 MATERIALS SCIENCE↗

NASA NTRS1987

Digital Autonomous Terminal Access Communication (DATAC) system

In order to accommodate the increasing number of computerized subsystems aboard today's more fuel efficient aircraft, the Boeing Co. has developed the DATAC (Digital Autonomous Terminal Access Control) bus to minimize the need for point-to-point wiring to interconnect these various systems, thereby reducing total aircraft weight and maintaining an economical flight configuration. The DATAC bus is essentially a local area network providing interconnections for any of the flight management and control systems aboard the aircraft. The task of developing a Bus Monitor Unit was broken down into four subtasks: (1) providing a hardware interface between the DATAC bus and the Z8000-based microcomputer system to be used as the bus monitor; (2) establishing a communication link between the Z8000 system and a CP/M-based computer system; (3) generation of data reduction and display software to output data to the console device; and (4) development of a DATAC Terminal Simulator to facilitate testing of the hardware and software which transfer data between the DATAC's bus and the operator's console in a near real time environment. These tasks are briefly discussed.

Novacki, Stanley M., III↗

NASA NTRS1993

Mathematical modelling of the human cardiovascular system in the presence of stenosis

This paper reports a theoretical study on the distribution of blood flow in the human cardiovascular system when one or more blood vessels are affected by stenosis. The analysis employs a mathematical model of the entire system based on the finite element method. The arterial-venous network is represented by a large number of interconnected segments in the model. Values for the model parameters are based upon the published data on the physiological and rheological properties of blood. Computational results show how blood flow through various parts of the cardiovascular system is affected by stenosis in different blood vessels. No significant changes in the flow parameters of the cardiovascular system were found to occur when the reduction in the lumen diameter of the stenosed vessels was less than 65%.

NASA Program Data Analysis↗

DOE OSTI2017

3D polymer hydrogel for high-performance atomic iron-rich catalysts for oxygen reduction in acidic media

Current platinum group metal (PGM)-free carbon nanocomposite catalysts for the oxygen reduction reaction (ORR) in acidic electrolyte often suffer from rapid degradation associated with carbon corrosion due to the use of large amount of amorphoous carbon black supports. Here, we developed a new concept of using freestanding 3D hydrogel to design support-free Fe-N-C catalysts. A 3D polyaniline (PANI)-based hydrogel was used for preparing a new type of single atomic iron site-rich catalyst, which has exhibited exceptionally enhanced activity and stability compared to conventional Fe-N-C catalysts supported on amorphous carbon blacks. The achieved performance metric on the hydrogel PANI-Fe catalysts is one of the best ever reported PGM-free catalysts, reaching a half-wave potential up to 0.83 V vs. RHE and only leaving 30 mV gap with Pt/C catalysts (60 μgPt/cm2) in challenging acidic media. Remarkable ORR stability was accomplished as well on the same catalyst evidenced by using harsh potential cycling tests. The well dispersion of atomic iron into partially graphitized carbon, featured with dominance of micropores and porous network structures, is capable of accommodating increased number of active sites, strengthening local bonding among iron, nitrogen and carbon, and facilitating mass transfer. The 3D polymer hydrogel approach would be a new pathway to advance PGM-free catalysts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Evaluating On-Node GPU Interconnects for Deep Learning Workloads

Scaling deep learning workloads across multiple GPUs on a single node has become increasingly important in data analytics. A key question is how well a PCIe-based GPU interconnect can perform relative to a custom high-performance interconnect such as NVIDIA's NVLink. This paper evaluates two such on-node interconnects for eight NVIDIA Pascal P100 GPUs: (a) the NVIDIA DGX-1's NVLink 1.0 `hybrid cube mesh'; and (b) the Cirrascale GX8's two-level PCIe tree using dual SR3615 switch risers. To show the effects of a range of neural network workloads, we define a parameterized version of the popular ResNet. We define a workload intensity metric that characterizes the expected computation/communication ratio; we also locate AlexNet and GoogLeNet within that space. As expected, the DGX-1 typically has superior performance. However, when equalizing GPU SM frequencies, the GX8 is very competitive on all ResNet workloads. With 8 GPUs, the GX8 can outperform the DGX-1 on all-to-all reductions by 10% for medium-sized payloads; and in rare cases, the GX8 slightly outperforms on ResNet.

Tallent, Nathan R.↗

DOE OSTI2013

Rice Rab11 is required for JA-mediated defense signaling

Highlights: •OsRab11 interacts with OsOPR8. •OsOPR8 is localized in the cytosol and peroxisome. •OsRab11 enhances the NADPH consumption by OsOPR8. •Transgenic Arabidopsis overexpressing OsRab11 represents a pathogen-resistant phenotype. -- Abstract: Rab proteins play an essential role in regulating vesicular transport in eukaryotic cells. Previously, we characterized OsRab11, which in concert with OsGAP1 and OsGDI3 regulates vesicular trafficking from the trans-Golgi network (TGN) to the plasma membrane or vacuole. To further elucidate the physiological function of OsRab11 in plants, we performed yeast two-hybrid screens using OsRab11 as bait. OsOPR8 was isolated and shown to interact with OsRab11. A co-immunoprecipitation assay confirmed this interaction. The green fluorescent protein-OsOPR8 fusion product was targeted to the cytoplasm and peroxisomes of protoplasts from Arabidopsis thaliana. OsOPR8 exhibited NADPH-dependent reduction activity when 2-cyclohexen-1-one (CyHE) and 12-oxo-phytodienoic acid (OPDA) were supplied as possible substrates. Interestingly, NADPH oxidation by OsOPR8 was increased when wild-type OsRab11 or the constitutively active form of OsRab11 (Q78L) were included in the reaction mix, but not when the dominant negative form of OsRab11 (S28N) was included. OsRab11 was expressed broadly in plants and both OsRab11 and OsOPR8 were induced by jasmonic acid (JA) and elicitor treatments. Overexpressed OsRab11 transgenic plants showed resistance to pathogens through induced expression of JA-responsive genes. In conclusion, OsRab11 may be required for JA-mediated defense signaling by activating the reducing activity of OsOPR8.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

What Makes Fluoroethylene Carbonate Different?

Rechargeable lithium-ion batteries containing silicon-based negative electrodes have the potential to revolutionize electrical energy storage, but carbonate solvents (such as ethylene carbonate) that are commonly used in graphite Li-ion batteries, yield unsatisfactory performance when used with such Li alloying electrodes. It has been found by trial-and-error that additions of the closely related carbonate additive, fluoroethylene carbonate (FEC) to conventional electrolytes, yields a robust solid electrolyte interphase (SEI) on the LixSiy alloy surface. Several mechanisms for this protective action have been considered in the literature and modeled theoretically; however, at present these mechanisms remain speculative. In this study, we use radiolysis, laser photoionization, electron paramagnetic resonance, and transient absorption spectroscopy to establish the redox chemistry of FEC. While the oxidation chemistry is similar to that of other carbonates, the reduction chemistry is strikingly different. Specifically, one-electron reduction of FEC causes the fission of two (instead of one) C-O bonds, resulting in concerted defluorination and decarboxylation. This reaction yields the vinoxyl radical that can abstract an H atom from FEC, initiating both the chain reaction causing FEC decomposition and radical polymerization involving the reaction products. The resulting polymer can further defluorinate yielding the interior radicals that migrate and recombine to produce a highly cross-linked network. We suggest that the outer SEI resulting from FEC addition has elastomeric properties, which account for its cohesion during expansion and contraction of silicon particles in the course of Li alloying/dealloying cycling.

electron paramagnetic resonance↗

DOE OSTI2024

Task-oriented machine learning surrogates for tipping points of agent-based models

We present a machine learning framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale approach, for the construction of different types of effective reduced order models from detailed agent-based simulators and the systematic multiscale numerical analysis of their emergent dynamics. The specific tasks of interest here include the detection of tipping points, and the uncertainty quantification of rare events near them. Our illustrative examples are an event-driven, stochastic financial market model describing the mimetic behavior of traders, and a compartmental stochastic epidemic model on an Erdös-Rényi network. We contrast the pros and cons of the different types of surrogate models and the effort involved in learning them. Importantly, the proposed framework reveals that, around the tipping points, the emergent dynamics of both benchmark examples can be effectively described by a one-dimensional stochastic differential equation, thus revealing the intrinsic dimensionality of the normal form of the specific type of the tipping point. This allows a significant reduction in the computational cost of the tasks of interest.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

An orthogonal metabolic framework for one-carbon utilization

Metabolic engineering often entails concurrent engineering of substrate utilization, central metabolism, and product synthesis pathways to maximize the conversion of a carbon substrate into desired product(s). Here, we report an alternative approach using synthetic pathways for C1 bioconversion that are orthogonal to the host metabolic network, thus minimizing interdependency on native metabolism and enabling more efficient biocatalysts. Here, the engineered pathways are based on formyl-CoA elongation (FORCE) reactions catalyzed by the enzyme 2-hydroxyacyl-CoA lyase (HACL) and generate multi-carbon products directly from C1 elongation units in the form of formyl-CoA. Herein, we use thermodynamic and stoichiometric analyses to evaluate different FORCE pathway variants, including aldose elongation, α-reduction, and aldehyde elongation. Promising variants were further prototyped using cell-free systems (purified enzymes and cell extracts) as well as resting and growing cultures of non-methylotrophic bacterium Escherichia coli. We demonstrate that C1 substrates formate, formaldehyde, and methanol can be used as inputs for FORCE pathways and that FORCE reactions can serve as a platform for varied product synthesis including glycolate, ethylene glycol, ethanol, and glycerate. Furthermore, the orthogonal FORCE pathways have the potential to be integrated with host metabolism for synthetic methylotrophy by the production of native growth substrates as demonstrated in a two-strain culture system.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Topological structure of complex predictions

Abstract Current complex prediction models are the result of fitting deep neural networks, graph convolutional networks or transducers to a set of training data. A key challenge with these models is that they are highly parameterized, which makes describing and interpreting the prediction strategies difficult. We use topological data analysis to transform these complex prediction models into a simplified topological view of the prediction landscape. The result is a map of the predictions that enables inspection of the model results with more specificity than dimensionality-reduction methods such as tSNE and UMAP. The methods scale up to large datasets across different domains. We present a case study of a transformer-based model previously designed to predict expression levels of a piece of DNA in thousands of genomic tracks. When the model is used to study mutations in the BRCA1 gene, our topological analysis shows that it is sensitive to the location of a mutation and the exon structure of BRCA1 in ways that cannot be found with tools based on dimensionality reduction. Moreover, the topological framework offers multiple ways to inspect results, including an error estimate that is more accurate than model uncertainty. Further studies show how these ideas produce useful results in graph-based learning and image classification.

Computer Science↗

DOE OSTI2016

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with evolutionarily ancient functions (e.g. the ribosomal proteins), in contrast to those with more recently evolved functions (e.g., cell-cell communication). This suggests that despite striking morphological differences, some fundamental embryonic-developmental processes are still controlled by ancient regulatory systems.

Biochemistry & Molecular Biology↗

NASA NTRSDate not supplied

Analysis of Traffic Flow in Structured Urban Airspace Networks with MFD-based Feedback Control

This research delves into applying the Macroscopic Fundamental Diagram (MFD) concept to structured airspace networks for comprehensive aggregate modeling and introduces a feedback-based departure function aimed at optimizing traffic flow. Previous studies have rarely examined structured airspace networks featuring non-stationary vehicles through the MFD perspective. We devised a scenario grounded in practical applications, featuring a multi-lane network with explicit lane-changing behavior. The MFD effectively captured the open-loop response, displaying a low-scatter, unimodal curve on the flow versus occupancy plot. Drawing inspiration from the ground transportation ramp-metering strategies, a proportional-integral-based controller was developed. Extensive simulation outcomes suggest that feedback control, informed by MFD, holds significant potential for managing traffic flow in Urban Air Mobility (UAM) environments; a reduction of 80% in the peak number of vehicles in a holding pattern was observed for a slight reduction in throughput in this study.

MFD↗

NASA NTRSDate not supplied

Analysis of Traffic Flow in Structured Urban Airspace Networks with MFD-based Feedback Control

MFD↗

DOE OSTI2020

Examining the Net Revenue and Downstream Flow Impact Trade-Offs for a Network of Cascading, Small-Scale Hydropower Facilities: Preprint

In this work, we used a price-taker model to investigate the trade-offs between net revenue and downstream flow impacts for a network of small, cascading hydro facilities. The network consisted of 36 facilities, each with a small amount of local storage (between 2 and 45 minutes). Generator sizes ranged between 0.5 and 1 MW, nominal, and the total capacity of the network was 33.5 MW. We used a multi-integer linear programing model to maximize the net revenue of the combined network subject to operating and environmental constraints. Net revenue optimizations relied on historic price data, and dry, typical, and wet years were studied to help ensure robustness. Energy and ancillary service sales were included in the net revenue calculations, and both unit commitment and dispatch simulations were performed. We found that limiting the downstream flows to ±50% of the river’s natural flows had a negligible impact on net revenues (<1% reduction), irrespective of hydrologic conditions, and even when downstream flows were limited to ±5%, net revenues were only impacted by 4%. These outcomes are significant because they demonstrate how an array of small-scale hydropower facilities can be operated to have minimal impact on natural stream flows—addressing a critical environmental concern.

downstream flow↗

DOE OSTI2014

Superoxide reduction by a superoxide reductase lacking the highly conserved lysine residue

Superoxide reductases (SORs) are the most recently identified superoxide detoxification systems, being found in microorganisms from the three domains of life. These enzymes are characterized by a catalytic mononuclear iron site, with one cysteine and four histidine ligands of the ferrous active form. A lysine residue in the –EKHVP– motif, located close to the active site, has been considered to be essential for the enzyme function, by contributing to the positive surface patch that attracts the superoxide anion and by controlling the chemistry of the catalytic mechanism through a hydrogen bond network. However, we show here that this residue is substituted by non-equivalent amino acids in several putative SORs from Archaea and unicellular Eukarya. In this work, we focus on mechanistic and spectroscopic studies of one of these less common enzymes, the SOR from the hyperthermophilic crenarchaeon Ignicoccus hospitalis . We employ pulse radiolysis fast kinetics and spectroscopic approaches to study the wild-type enzyme (₋E₂₃T₂₄HVP₋), and two mutants, T24K and E23A, the later mimicking enzymes lacking both the lysine and glutamate (a ferric ion ligand) of the motif. The efficiency of the wild type protein and mutants in reducing superoxide is comparable to other SORs, revealing the robustness of these enzymes to single mutations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2014

Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

SU-E-I-36: A KWIC and Dirty Look at Dose Savings and Perfusion Metrics in Simulated CT Neuro Perfusion Exams

Purpose: CT neuro perfusion scans are one of the highest dose exams. Methods to reduce dose include decreasing the number of projections acquired per gantry rotation, however conventional reconstruction of such scans leads to sampling artifacts. In this study we investigated a projection view-sharing reconstruction algorithm used in dynamic MRI – “K-space Weighted Image Contrast” (KWIC) – applied to simulated perfusion exams and evaluated dose savings and impacts on perfusion metrics. Methods: A FORBILD head phantom containing simulated time-varying objects was developed and a set of parallel-beam CT projection data was created. The simulated scans were 60 seconds long, 1152 projections per turn, with a rotation time of one second. No noise was simulated. 5mm, 10mm, and 50mm objects were modeled in the brain. A baseline, “full dose” simulation used all projections and reduced dose cases were simulated by downsampling the number of projections per turn from 1152 to 576 (50% dose), 288 (25% dose), and 144 (12.5% dose). KWIC was further evaluated at 72 projections per rotation (6.25%). One image per second was reconstructed using filtered backprojection (FBP) and KWIC. KWIC reconstructions utilized view cores of 36, 72, 144, and 288 views and 16, 8, 4, and 2 subapertures respectively. From the reconstructed images, time-to-peak (TTP), cerebral blood flow (CBF) and the FWHM of the perfusion curve were calculated and compared against reference values from the full-dose FBP data. Results: TTP, CBF, and the FWHM were unaffected by dose reduction (to 12.5%) and reconstruction method, however image quality was improved when using KWIC. Conclusion: This pilot study suggests that KWIC preserves image quality and perfusion metrics when under-sampling projections and that the unique contrast weighting of KWIC could provided substantial dose-savings for perfusion CT scans. Evaluation of KWIC in clinical CT data will be performed in the near future. R01 EB014922, NCI Grant U01 CA181156 (Quantitative Imaging Network), and Tobacco Related Disease Research Project grant 22RT-0131.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Atomic-scale structure of ZrO 2 : Formation of metastable polymorphs

Metastable phases can exist within local minima in the potential energy landscape when they are kinetically “trapped” by various processing routes, such as thermal treatment, grain size reduction, chemical doping, interfacial stress, or irradiation. Despite the importance of metastable materials for many technological applications, little is known about the underlying structural mechanisms of the stabilization process and atomic-scale nature of the resulting defective metastable phase. Investigating ion-irradiated and nanocrystalline zirconia with neutron total scattering experiments, we show that metastable tetragonal ZrO 2 consists of an underlying structure of ferroelastic, orthorhombic nanoscale domains stabilized by a network of domain walls. The apparent long-range tetragonal structure that can be recovered to ambient conditions is only the configurational ensemble average of the underlying orthorhombic domains. This structural heterogeneity with a distinct short-range order is more broadly applicable to other nonequilibrium materials and provides insight into the synthesis and recovery of functional metastable phases with unique physical and chemical properties.

74 ATOMIC AND MOLECULAR PHYSICS↗