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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Computationally efficient and error aware surrogate construction for numerical solutions of subsurface flow through porous media

Limiting the injection rate to restrict the pressure below a threshold at a critical location can be an important goal of simulations that model the subsurface pressure between injection and extraction wells. The pressure is approximated by the solution of Darcy’s partial differential equation for a given permeability field. The subsurface permeability is modeled as a random field since it is known only up to statistical properties. This induces uncertainty in the computed pressure. Solving the partial differential equation for an ensemble of random permeability simulations enables estimating a probability distribution for the pressure at the critical location. These simulations are computationally expensive, and practitioners often need rapid online guidance for real-time pressure management. An ensemble of numerical partial differential equation solutions is used to construct a Gaussian process regression model that can quickly predict the pressure at the critical location as a function of the extraction rate and permeability realization. The Gaussian process surrogate analyzes the ensemble of numerical pressure solutions at the critical location as noisy observations of the true pressure solution, enabling robust inference using the conditional Gaussian process distribution. Our first novel contribution is to identify a sampling methodology for the random environment and matching kernel technology for which fitting the Gaussian process regression model scales as O ( n log n ) instead of the typical O ( n 3 ) rate in the number of samples n used to fit the surrogate. The surrogate model allows almost instantaneous predictions for the pressure at the critical location as a function of the extraction rate and permeability realization. Our second contribution is a novel algorithm to calibrate the uncertainty in the surrogate model to the discrepancy between the true pressure solution of Darcy’s equation and the numerical solution. Finally, although our method is derived for building a surrogate for the solution of Darcy’s equation with a random permeability field, the framework broadly applies to solutions of other partial differential equations with random coefficients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Criticality Scoping Calculations for a Multi-Function Dissolver Insert

As one of its missions, the Savannah River Site seeks to be a leader in the safe and productive disposition of special nuclear materials. One of the premier programs is the disposition of used nuclear fuel, primarily from research reactors, through dissolution, purification, and down blend into low enriched uranium for commercial power reactors. Prior to use, this fuel contained highly enriched uranium (HEU). In an effort to advance this expertise, this study has been performed to demonstrate the feasibility to disposition a number of special geometry HEU fuels. These fuels come from a number of different domestic and foreign research reactors which had geometries considerably different from round or square bundles of plates or rods. As such, they cannot be dispositioned in current H-Canyon dissolver inserts so a new, multi-function dissolver insert may be considered. While this is not a current mission, it is believed that this study's scoping calculations demonstrate the feasibility of the site taking such a mission. At the H-Canyon facility, a dissolver is a large stainless steel pot, loaded with a nitric acid solution into which uranium-alloy fuel is dissolved. The dissolver uses a device called an insert to feed the fuels to the acid solution in a controlled manner. Most fuel forms fit into one of the existing inserts which include one with ten {approx}5-inch diameter circular wells, one with four {approx}4.5 inch by {approx}15 inch slab wells, and one specifically designed for the Oak Ridge National Laboratory High Flux Isotope Reactor (HFIR). This study considered five bounding fuel candidates for scoping the potential new insert. The fuels include a generic annular plate fuel (APF), the Tower Shield Reactor (TSR) fuel elements, the Reactor A Haute Flux (RHF) core, Knolls Atomic Power Laboratory (KAPL) reactor fuel, and SLOWPOKE cores. These are expected to bound a range of proposed fuel candidates. Scoping studies were made to establish geometric restrictions for the new dissolver insert and to determine if these fuels could safely be dissolved. Homogenous models were used for the scoping study due to time constraints. Computational modeling was performed using KENOVI in the SCALE 6.1 code package.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Structure and Function of the Zinc Binding Protein ZrgA from Vibrio cholerae

ATP binding cassette (ABC) transporters are the primary means by which bacteria acquire trace elements from the environment. They rely on solute binding proteins (SBPs) to bind the relevant substrate and deliver it to the integral membrane permease for ATP-powered import into the cytoplasm. SBPs of cluster A-I are known to facilitate the transport of essential metals zinc, manganese, and iron, and many have been characterized to date. A group of ABC transporter operons dubbed zinc-regulated genes (zrg) have recently been shown to transport zinc with putative SBPs (zrgA) bearing no homology to the classical cluster A-I family, and a recent crystal structure of a representative protein from Pseudomonas aeruginosa shows no structural similarity to classical SBPs. Thus, the ZrgA proteins appear to represent a newly discovered family of zinc SBPs widespread among Gram-negative bacteria, including human pathogens. Here, we have determined the crystal structure of ZrgA from Vibrio cholerae and characterized its zinc binding in vitro and function in vivo. We also assessed the role of a histidine-rich sequence that appears to be a hallmark of ZrgA proteins that is particularly long in V. cholerae ZrgA. The results show that the zrgA gene is critical to the function of the operon, consistent with a function as an SBP in this system. Further, the His-rich region is not essential to the function of ZrgA, but it does provide additional zinc binding sites in vitro. The structure and zinc binding data for ZrgA reveal interesting differences between it and its homologue from P. aeruginosa, illustrating diversity within this little-studied protein family.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1987

Delay time for the onset of beam plasma discharge

The interaction of a nonrelativistic electron beam with a neutral gas in a large chamber is considered, and the time interval before ignition of beam plasma discharge (BPD) is studied. A new theoretical expression for the time delay before BPD ignition is found as a function of the critical current necessary for BPD to be established. There are two parameters in the theoretical expression, and both are derived from two different experiments. These parameters are used to write the time evolution equation for plasma density as a function of time.

Parish, J. L.↗
DOE OSTI2016

Analyzing Resiliency of the Smart Grid Communication Architectures

Smart grids are susceptible to cyber-attack as a result of new communication, control and computation techniques employed in the grid. In this paper, we characterize and analyze the resiliency of smart grid communication architecture, specifically an RF mesh based architecture, under cyber attacks. We analyze the resiliency of the communication architecture by studying the performance of high-level smart grid functions such as metering, and demand response which depend on communication. Disrupting the operation of these functions impacts the operational resiliency of the smart grid. Our analysis shows that it takes an attacker only a small fraction of meters to compromise the communication resiliency of the smart grid. We discuss the implications of our result to critical smart grid functions and to the overall security of the smart grid.

None, None↗
DOE OSTI2016

Analyzing Resiliency of the Smart Grid Communication Architectures

Smart grids are susceptible to cyber-attack as a result of new communication, control and computation techniques employed in the grid. In this paper, we characterize and analyze the resiliency of smart grid communication architecture, specifically an RF mesh based architecture, under cyber attacks. We analyze the resiliency of the communication architecture by studying the performance of high-level smart grid functions such as metering, and demand response which depend on communication. Disrupting the operation of these functions impacts the operational resiliency of the smart grid. Our analysis shows that it takes an attacker only a small fraction of meters to compromise the communication resiliency of the smart grid. We discuss the implications of our result to critical smart grid functions and to the overall security of the smart grid.

Anas AlMajali, Anas↗
NASA NTRS2012

A Proposed Study Examining Individual Differences in Temporal Profiles of Cardiovascular Responses to Head Down Tilt During Fluid Loading

Susceptibility of healthy astronauts to orthostatic hypotension and presyncope is exacerbated upon return from spaceflight. The effect of altered gravity during space flight and planetary transition on human cardiovascular function is of critical importance to maintenance of astronaut health and safety. Hypovolemia, reduced plasma volume, is suspected to play an important role in cardiovascular deconditioning following exposure to spaceflight, which may lead to increased peripheral resistance, attenuated arterial baroreflex, and changes in cardiac function. A promising countermeasure for post-flight orthostatic intolerance is fluid loading used to restore lost plasma volume by giving crew salt tablets and water prior to re-entry. The main purpose of the proposed study is to define the temporal profile of cardiac responses to simulated 0-G conditions before and following a fluid loading countermeasure. 8 men and 8 women will be tested during 4 hour exposures at 6o head down tilt (HDT). Each subject will be given two exposures to HDT on separate days, one with and one without fluid loading (one liter of 0.9% saline solution). Stand tests (orthostatic stress) will be done before and after each HDT. Cardiac measures will be obtained with both impedance cardiography and echo ultrasound

Cowings, Patricia↗
DOE OSTI2021

The Quest for Functional Oxide Cathodes for Magnesium Batteries: A Critical Perspective

The Mg battery is an energy storage technology which has garnered significant interest in recent years. Mg batteries incorporating a metal oxide cathode (MOC) are potential candidates to supersede the state-of-the-art Li-ion battery in energy density, cost, and sustainability. However, there are significant discrepancies in reported performances and reactivities of Mg battery MOCs, with detailed analyses revealing that parasitic electrolyte reactions can contribute almost entirely to the measured capacity. This Perspective describes a holistic approach. encompassing elemental, redox, and structural probes-which is vital to robustly confirm and quantify Mg intercalation in MOCs. It critically surveys recent literature for applications of this approach to reveal true state-of-the-art MOCs for Mg batteries. We also suggest testing and analysis protocols to ensure fair comparison of future reports with these state-of-the-art materials.

25 ENERGY STORAGE↗
DOE OSTI2011

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. For example systems biology-oriented genome scale modeling efforts greatly benefit from accurate annotation of protein-coding genes to develop proper functioning models. However, determining protein-coding genes for most new genomes is almost completely performed by inference, using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. With the ability to directly measure peptides arising from expressed proteins, mass spectrometry-based proteomics approaches can be used to augment and verify coding regions of a genomic sequence and importantly detect post-translational processing events. In this study we utilized “shotgun” proteomics to guide accurate primary genome annotation of the bacterial pathogen Salmonella Typhimurium 14028 to facilitate a systems-level understanding of Salmonella biology. The data provides protein-level experimental confirmation for 44% of predicted protein-coding genes, suggests revisions to 48 genes assigned incorrect translational start sites, and uncovers 13 non-annotated genes missed by gene prediction programs. We also present a comprehensive analysis of post-translational processing events in Salmonella, revealing a wide range of complex chemical modifications (70 distinct modifications) and confirming more than 130 signal peptide and N-terminal methionine cleavage events in Salmonella. This study highlights several ways in which proteomics data applied during the primary stages of annotation can improve the quality of genome annotations, especially with regards to the annotation of mature protein products.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1999

A Critical Examination of Wind-Wave Spectral Functional Form

Traditionally, data from random ocean waves are presented in spectral functions. The spectra are the result of Fourier analysis. Fourier spectral analysis has dominated data analysis for, at least, the last hundred years. It has been the standard method for is examining the global amplitude-frequency distributions. Although Fourier transform valid under extremely general conditions, there are some crucial restrictions for the Fourier spectral analysis. The system must be linear, and the data must be stationary- otherwise, the resulting spectrum will make little physical sense. The stationarity requirement is also a common required criterion for most of other available data analysis methods. Nevertheless, few, if any, natural phenomena are linear and stationary. To compound these complications is the imperfection of our probes or numerical schemes the interactions of the imperfect probes even with a perfect linear system can make the final data nonlinear. Furthermore, all the available data are usually of finite duration. Under these conditions, Fourier analysis is of limited use, For lack of alternatives, however, Fourier analysis is still used to process such data. The loose application of Fourier analysis and the insouciant adoption of the stationary and linear assumptions may lead to misleading conclusions. Ocean waves are know to be nonlinear, and the wind system generating the wave field are seldom stationary- As a result, the traditional examination of the spectral form hardly made physical sense. A new method for analyzing nonlinear and nonstationary data has been developed. The key part is the Empirical Mode Decomposition (EMD) method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF) that serve as the basis of the representation of the data, This decomposition method is adaptive, and, therefore, highly efficient. The IMFs admit well-behaved Hilbert transforms, and yield instantaneous energy and frequency as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Among the main conceptual innovations is the introduction of the instantaneous frequencies for complicated data sets, which eliminate the need of spurious harmonics to represent nonlinear and nonstationary signals. The spectral forms of the ocean waves are very different. This new method offers the first physical meaningful view of the wave spectrum. Data from laboratory and field will be presented to illustrate the differences.

Huang, Norden E.↗
NASA NTRS2018

Electrolyzer Exergy Analysis for an Environmental Control and Life Support System

An exergy based analysis of the Environmental Control and Life Support System (ECLSS) aboard the International Space Station (ISS) is conducted to assess its overall performance. Exergy is chosen as a measure of performance because it accounts for both the first and second laws of thermodynamics. The exergy efficiency of a system is first defined as the total exergy destroyed by the system relative to the total exergy input to the system. To determine the ECLSS exergy efficiency, the system is divided into constituent subsystems which in turn are divided into assemblies and components. Based on this system decomposition, exergy balances are derived for each assembly or component. Exergy balances and supporting calculations are implemented in MATLAB® code. The major subsystems of the ECLSS considered in this analysis include the Atmosphere Revitalization Subsystem (ARS), Atmosphere Control and Supply Subsystem (ACS), Temperature and Humidity Control Subsystem (THC), Water Recovery and Management Subsystem (WRM), and Waste Management Subsystem (WM). This paper focuses on the ARS and its constituent assemblies and components. Exergy efficiency of the ARS and its constituent assemblies and components is first presented. The Oxygen Generation Assembly (OGA), an assembly within the ARS, is then highlighted because the exergy destruction by the OGA is a large magnitude contributor to the overall exergy destruction of the ECLSS. The OGA produces oxygen to meet the crew's metabolic demand via water electrolysis in a proton exchange membrane (PEM) electrolyzer. The exergy destruction of the OGA's PEM electrolyzer is a function of the amount of oxygen produced, which determines the necessary current density and voltage drop across the PEM electrolyzer. In addition, oxygen production in the PEM electrolyzer requires deviation from the Nernst potential, presenting trade-offs between the exergy efficiency and critical life support functions. The results of parametric studies of PEM electrolyzer performance are presented with an emphasis on the impacts of polarization and operational conditions on exergy efficiency.

Chow, Raymond↗
DOE OSTI2023

Designer molecules of the synaptic organizer MDGA1 reveal 3D conformational control of biological function

MDGAs (MAM domain-containing glycosylphosphatidylinositol anchors) are synaptic cell surface molecules that regulate the formation of trans-synaptic bridges between neurexins (NRXNs) and neuroligins (NLGNs), which promote synaptic development. Mutations in MDGAs are implicated in various neuropsychiatric diseases. MDGAs bind NLGNs in cis on the postsynaptic membrane and physically block NLGNs from binding to NRXNs. In crystal structures, the six immunoglobulin (Ig) and single fibronectin III domains of MDGA1 reveal a striking compact, triangular shape, both alone and in complex with NLGNs. Whether this unusual domain arrangement is required for biological function or other arrangements occur with different functional outcomes is unknown. Here, we show that WT MDGA1 can adopt both compact and extended 3D conformations that bind NLGN2. Designer mutants targeting strategic molecular elbows in MDGA1 alter the distribution of 3D conformations while leaving the binding affinity between soluble ectodomains of MDGA1 and NLGN2 intact. In contrast, in a cellular context, these mutants result in unique combinations of functional consequences, including altered binding to NLGN2, decreased capacity to conceal NLGN2 from NRXN1β, and/or suppressed NLGN2-mediated inhibitory presynaptic differentiation, despite the mutations being located far from the MDGA1-NLGN2 interaction site. Thus, the 3D conformation of the entire MDGA1 ectodomain appears critical for its function, and its NLGN-binding site on Ig1-Ig2 is not independent of the rest of the molecule. As a result, global 3D conformational changes to the MDGA1 ectodomain via strategic elbows may form a molecular mechanism to regulate MDGA1 action within the synaptic cleft.

MDGAs↗
DOE OSTI2012

Model-driven multi-omic data analysis elucidates metabolic immunomodulators of macrophage activation

Macrophages are central players in the immune response, manifesting divergent phenotypes to control inflammation and innate immunity through the release of cytokines and other regulatory factor-dependent signaling pathways. In recent years, the focus on metabolism has been reemphasized as critical signaling and regulatory pathways of human pathophysiology, ranging from cancer to aging, often converge on metabolic responses. Here, we used genome-scale modeling and multi-omics (transcriptomics, proteomics, and metabolomics) analysis to assess metabolic features critical for macrophage functions. We constructed a genome-scale metabolic network for the RAW 264.7 cell line to determine metabolic modulators of macrophage activation. Metabolites well-known to be associated with immunoactivation (e.g., glucose and arginine) and immunosuppression (e.g., tryptophan and vitamin D3) were amongst the most critical effectors. Intracellular metabolic mechanisms linked to critical suppressive effectors were then assessed, identifying a suppressive role for de novo nucleotide synthesis. Finally, the underlying metabolic mechanisms of macrophage activation are identified by analyzing multi-omic data obtained from LPS-stimulated RAW cells in the context of our flux-based predictions. Our study demonstrates metabolism's role in regulating activation may be greater than previously anticipated and elucidates underlying metabolic connections between activation and metabolic effectors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELING FOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS

A difficult problem that is currently growing rapidly due to the sharp increase in the amount of high-throughput data available for many systems is that of determining useful and informative causative influence networks. These networks can be used to predict behavior given observation of a small number of components, predict behavior at a future time point, or identify components that are critical to the functioning of the system under particular conditions. In these endeavors incorporating observations of systems from a wide variety of viewpoints can be particularly beneficial, but has often been undertaken with the objective of inferring networks that are generally applicable. The focus of the current work is to integrate both general observations and measurements taken for a particular pathology, that of ischemic stroke, to provide improved ability to produce useful predictions of systems behavior. A number of hybrid approaches have recently been proposed for network generation in which the Gene Ontology is used to filter or enrich network links inferred from gene expression data through reverse engineering methods. These approaches have been shown to improve the biological plausibility of the inferred relationships determined, but still treat knowledge-based and machine-learning inferences as incommensurable inputs. In this paper, we explore how further improvements may be achieved through a full integration of network inference insights achieved through application of the Gene Ontology and reverse engineering methods with specific reference to the construction of dynamic models of transcriptional regulatory networks. We show that integrating two approaches to network construction, one based on reverse-engineering from conditional transcriptional data, one based on reverse-engineering from in situ hybridization data, and another based on functional associations derived from Gene Ontology, using probabilities can improve results of clustering as evaluated by a predictive model of transcriptional expression levels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Deconstructing the Soil Microbiome into Reduced-Complexity Functional Modules

The soil microbiome is an invaluable component of the biosphere and critical for ecosystem functions, including biogeochemical cycling, soil-atmosphere gas exchange, degradation of toxic compounds, and promotion of plant growth and stress resistance/resilience. An improved understanding of the soil microbiome will help with predicting how these processes respond to external perturbations, and with harnessing beneficial aspects of the soil microbiome for agronomic applications such as crop amendments. However, the extensive taxonomic and functional diversity inherent within the soil microbiome hinders efficient analysis of this system. Microbial biodiversity in soils is orders of magnitude greater than other commonly studied systems such as the human gut microbiome (Blum, Zechmeister-Boltenstern, and Keiblinger 2019; Berendsen, Pieterse, and Bakker 2012). Thousands of microbial taxa may be found in a single gram of soil (Roesch et al. 2007), and high rates of gene flow and mutation further promote microbial diversification (Sergaki et al. 2018). Concomitantly, functional diversity in soil is similarly extensive. Soil is a heterogeneous mixture of microenvironments with defined physical and chemical attributes (Bach et al. 2018), within which numerous microbial guilds of distinct life-strategies and metabolic capacities can be found (Perez-Garcia, Lear, and Singhal 2016; H.-S. Song et al. 2014). Furthermore, the soil microbiome harbors a significant fraction of rare and/or quiescent members (Blagodatskaya and Kuzyakov 2013) that exist below the threshold of detection of current technologies. Such rare taxa may make significant contributions to process rates (Shade and Gilbert 2015; Dawson et al. 2017), but their scarcity complicates their identification and analysis. Finally, the vast amounts of information generated through holistic analyses of soil communities represent an intense computational burden (Scholz, Lo, and Chain 2012; Prosser 2015) that precludes assessment of the complete functional and taxonomic diversity contained in this ecosystem.

Naylor, Dan T.↗
DOE OSTI2026

Continuous-Energy Verification of MCNP Calculations Using One-Group Spherical and Slab Criticality Benchmarks

This work presents a continuous-energy Monte Carlo verification study of one group spherical and slab criticality benchmarks using the MCNP ®1 code. Classical tabulations and newly generated benchmark solutions obtained by direct numerical evaluation by the author are considered. The benchmarks span weakly to strongly multiplying regimes and provide analytically defined critical radii as functions of a single parameter, c .

22 GENERAL STUDIES OF NUCLEAR REACTORS↗