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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 19 records

Seismic Event Characterization Using Full Moment Tensors on the Hypersphere

Moment tensor solutions provide insights into the deformation that has occurred in the source region of a seismic event and are therefore of great value in identifying different types of seismic sources, such as when monitoring for underground nuclear tests. Despite this utility, inversion of waveforms recorded by seismometers for their full seismic moment tensor is not yet routine, and development of robust methods to classify events based on this information is in its infancy. Here, we assemble an inventory of 1405 full moment tensor solutions that include explosive, earthquake, and collapse events, and investigate the use of anisotropic probability distribution functions on the 5D hypersphere to discriminate between these sources. Using a Bayesian classifier, we obtain optimal success rates of 98.4% across all events and demonstrate that modification of the prior probabilities provides a natural way to alter the balance between not missing desirable events (such as explosions) versus misclassifying large numbers of undesired events (such as earthquakes). The approach is specifically designed to progress from traditional, bipolar event screening metrics to more generalized event identification across multiple types of seismic sources. Despite current databases containing insufficient numbers of events to definitively demonstrate at present, we also find intriguing evidence of subgroupings within individual source populations on the hypersphere, for example, between chemical and nuclear explosions, raising the potential possibility of discriminating between these event types in the future.

Geosciences↗

The effect of composition on helium bubble nucleation in complex concentrated alloys

Molecular dynamics simulations of helium implantation have been performed in the MoNbTaTi complex concentrated alloy (CCA) to determine the impact of composition on helium clustering and bubble nucleation. It was found that compositions with lower interstitial atomic volume resulted in smaller cluster sizes, higher helium-to-vacancy ratios, and larger migration barriers. As the atomic volume decreases, it is harder to accommodate additional helium in the lattice and for helium to diffuse between interstitial sites, resulting in smaller cluster sizes. In particular, increasing molybdenum directly correlated with a decreased interstitial atomic volume and increased migration barrier. Niobium exhibited the opposite trend, where more niobium in the material resulted in larger interstitial atomic volumes and cluster sizes but lower migration barriers. The atomic volume was determined to be an indicator of the susceptibility of the material to helium bubble growth and could potentially be used as a metric to screen compositions for resistance to helium damage. In this way, properties such as available interstitial volumes could be used to screen materials more rapidly given the vast compositional space of CCAs.

McCarthy, Megan Jeanne [Sandia National Laboratori↗

Metrics in Space Life Support Technology Selection

Engineering metrics are useful in space life support technology selection, but they must be carefully used. Metrics are only part of a complete system trade-off. Metrics do harm if they cause neglect of other important technical, organizational, or intuitive decision factors. Two metrics have damaged space life support, closure and Equivalent Systems Mass (ESM). Closure measures the fraction of the required system inputs that are produced by recycling system outputs. Increasing closure produces diminishing returns and becomes increasingly expensive. Increasing closure does not directly contribute to providing better life support. ESM measures the total launch mass required to provide life support. ESM includes the mass of the system hardware and of its power, cooling, pressurized volume, spares, and logistics. ESM predicts launch costs, but recently launch costs have been reduced by a factor of 20 or more. System development cost for space hardware is often much greater than launch cost. The past nearly exclusive use of ESM has led to the neglect of Life Cycle Cost (LCC), reliability, cost, and the other engineering factors. Closure and ESM have misguided space life support technology selection for more than twenty years and have adversely affected the expenditure of 100’s of millions of dollars. Metrics can be effectively used three ways in space life support technology selection: 1. A small set of key engineering metrics for preliminary screening. 2. A full set of engineering to guide technical selection. 3. Combining engineering metrics with organizational, political, and intuitive decision factors to understand technology selection. The past emphasis on closure and ESM served to support recycling life support over resupply and built on the intuitive appeal of a human ecosystem in space.

Harry W Jones↗

The Effective Use of Metrics in Space Life Support System Trade-Offs

Engineering metrics are useful in space life support technology selection, but they must be carefully used. Metrics are only part of a complete system trade-off. Metrics do harm if they cause neglect of other important technical, organizational, or intuitive decision factors. Two metrics have damaged space life support, closure and Equivalent Systems Mass (ESM). Closure measures the fraction of the required system inputs that are produced by recycling system outputs. Increasing closure produces diminishing returns and becomes increasingly expensive. Increasing closure does not directly contribute to providing better life support. ESM measures the total launch mass required to provide life support. ESM includes the mass of the system hardware and of its power, cooling, pressurized volume, spares, and logistics. ESM predicts launch costs, but recently launch costs have been reduced by a factor of 20 or more. System development cost for space hardware is often much greater than launch cost. The past nearly exclusive use of ESM has led to the neglect of Life Cycle Cost (LCC), reliability, cost, and the other engineering factors. Closure and ESM have misguided space life support technology selection for more than twenty years and have adversely affected the expenditure of 100’s of millions of dollars. Metrics can be effectively used three ways in space life support technology selection: 1. A small set of key engineering metrics for preliminary screening. 2. A full set of engineering to guide technical selection. 3. Combining engineering metrics with organizational, political, and intuitive decision factors to understand technology selection. The past emphasis on closure and ESM served to support recycling life support over resupply and built on the intuitive appeal of a human ecosystem in space.

Harry W. Jones↗

Metrics of Balance Control for Use in Screening Tests of Vestibular Function

Decrements in balance control have been documented in astronauts after space flight. Reliable measures of balance control are needed for use in postflight field tests at remote landing sites. Diffusion analysis (DA) is a statistical mechanical tool that shows the average difference of the dependent variable on varying time scales. These techniques have been shown to measure differences in open-loop and closed-loop postural control in astronauts and elderly subjects. The goal of this study was to investigate the reliability of these measures of balance control. Eleven subjects were tested using the Clinical Test of Sensory Interaction on Balance: the subject stood with feet together and arms crossed on a stable or compliant surface, with eyes open or closed and with or without head movements in the pitch or yaw plane. Subjects were instrumented with inertial motion sensors attached to their trunk segment. The DA curves for linear acceleration measures were characterized by linear fits measuring open- (Ds) and closed-loop (Dl) control, and their intersection point (X-int, Y-int). Ds and Y-int showed significant differences between the test conditions. Additionally, Ds was correlated with the root mean square (RMS) of the signal, indicating that RMS was dominated by open-loop events (< 0.5 seconds). The Y-int was found to be correlated with the average linear velocity of trunk movements. Thus DA measures could be applied to derive reliable metrics of balance stability during field tests.

Fiedler, Matthew↗

Stacking Fault Energy Based Alloy Screening for Hydrogen Compatibility

The selection of austenitic stainless steels for hydrogen service is challenging since there are few intrinsic metrics that relate alloy composition to hydrogen degradation. One such metric, explored here, is intrinsic stacking fault energy. Stacking fault energy has an influence on the character and structure of dislocations and on the formation of secondary crystalline phases created during mechanical deformation in austenitic alloys. In this work, a data-driven model for the intrinsic stacking fault energy of common austenitic stainless steel alloys is applied to compare the relative degradation of tensile performance in the presence of hydrogen. A transition in the tensile reduction of area of both 300-series and manganese stabilized stainless steels is observed at a calculated stacking fault energy of approximately 43 mJ m -2 , below which pronounced hydrogen degradation on tensile ductility is observed. The model is also applied to suggest alloying strategies for low nickel austenitic stainless steels for hydrogen service. Lastly, through this investigation, we find that calculated intrinsic stacking fault energy is a high-throughput screening metric that enables the ranking of the performance of a diverse range of austenitic stainless steel compositions, as well as the identification of new alloys, with regard to hydrogen compatibility.

08 HYDROGEN↗

ASSESSING FUEL PROPERTY EFFECTS ON CAVITATION AND EROSION PROPENSITY USING A COMPUTATIONAL FUEL SCREENING TOOL

To advance compression ignition combustion strategies, researchers have evaluated fuel property effects and their impact on achieving higher efficiencies and lower emissions levels relative to current capabilities. Within the Department of Energy's Co-Optima initiative, there has been a recent focus on understanding the influence of fuel properties on fuel injection performance. To help identify candidate fuels that can meet desired injector performance metrics, a computational fuel screening tool is under development that can link fuel properties with the tendency of a given fuel to cavitate and lead to cavitation-induced erosion. In the initial development of this tool, five liquid fuel properties were selected to represent candidate fuels, namely density, viscosity, vapor pressure, surface tension, and heat of vaporization. A design of experiments methodology was employed to generate a set of pseudo fuel cases, which can represent the main effects and interactions among the fuel properties and be related to cavitation erosion predictions. Large eddy simulations were performed using a mixture modeling approach to predict the cavitation and erosion propensity of these pseudo-fuels in terms of the mean fuel vapor mole fraction and stored impact energy from repeated cloud collapse events. The low order regression models generated from this study revealed the importance of liquid fuel density on cavitation formation, whereas liquid viscosity was found to have a strong negative correlation with erosion severity. The surrogate models were then used in the fuel screening tool to rank the cavitation and erosion tendency of four candidate single-component fuels: methyl decanoate, isooctane, ethanol and n-dodecane. While the fuel screening tool was not able to quantitatively predict the cavitation and erosion response metrics, the tool was able to accurately rank the relative cavitation and erosion propensity of the four fuels. Overall, ethanol and iso-octane were observed to produce the highest levels of cavitation and erosion, respectively.

cavitation-induced erosion↗

A public website for the automated assessment and validation of SARS-CoV-2 diagnostic PCR assays

Abstract Summary Polymerase chain reaction-based assays are the current gold standard for detecting and diagnosing SARS-CoV-2. However, as SARS-CoV-2 mutates, we need to constantly assess whether existing PCR-based assays will continue to detect all known viral strains. To enable the continuous monitoring of SARS-CoV-2 assays, we have developed a web-based assay validation algorithm that checks existing PCR-based assays against the ever-expanding genome databases for SARS-CoV-2 using both thermodynamic and edit-distance metrics. The assay-screening results are displayed as a heatmap, showing the number of mismatches between each detection and each SARS-CoV-2 genome sequence. Using a mismatch threshold to define detection failure, assay performance is summarized with the true-positive rate (recall) to simplify assay comparisons. Availability and implementation The assay evaluation website and supporting software are Open Source and freely available at https://covid19.edgebioinformatics.org/#/assayValidation, https://github.com/jgans/thermonucleotide BLAST and https://github.com/LANL-Bioinformatics/assay_validation. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

Distance and organization in multifunction displays

One approach to organizing information in a multifunction display (MFD) is to place related screens of information closer to each other. This study identified three metrics that could be used to operationalize the concept of distance in an MFD. The proposed distance metrics - navigational (the number of choice points lying between two screens), organizational (the hierarchical structure of the data base), and cognitive (the user's perception of relationships among screens) - were empirically examined by using a simulated, hierarchically arranged, menu-driven MFD in an aviation context. Subjects engaged in two tasks that required them to access different target screens from various starting screens in a 290-screen MFD. The tasks differed in the navigational mechanisms subjects were allowed to use to navigate around the MFD and the relationships between the starting and target screens. The results suggest that the three distance metrics are meaningful within the context of a multifunction display.

Seidler, Karen S.↗

acCRISPR: an activity-correction method for improving the accuracy of CRISPR screens

Abstract High throughput CRISPR screens are revolutionizing the way scientists unravel the genetic underpinnings of engineered and evolved phenotypes. One of the critical challenges in accurately assessing screening outcomes is accounting for the variability in sgRNA cutting efficiency. Poorly active guides targeting genes essential to screening conditions obscure the growth defects that are expected from disrupting them. Here, we develop acCRISPR, an end-to-end pipeline that identifies essential genes in pooled CRISPR screens using sgRNA read counts obtained from next-generation sequencing. acCRISPR uses experimentally determined cutting efficiencies for each guide in the library to provide an activity correction to the screening outcomes via calculation of an optimization metric, thus determining the fitness effect of disrupted genes. CRISPR-Cas9 and -Cas12a screens were carried out in the non-conventional oleaginous yeast Yarrowia lipolytica and acCRISPR was used to determine a high-confidence set of essential genes for growth under glucose, a common carbon source used for the industrial production of oleochemicals. acCRISPR was also used in screens quantifying relative cellular fitness under high salt conditions to identify genes that were related to salt tolerance. Collectively, this work presents an experimental-computational framework for CRISPR-based functional genomics studies that may be expanded to other non-conventional organisms of interest.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of alloying on intrinsic ductility in WTaCrV high entropy alloys

Tungsten (W) exhibits desirable properties for extreme applications, such as the divertor in magnetic fusion reactors, but its practicality remains limited due to poor formability and insufficient irradiation resistance. In this work, we study the intrinsic ductility of body-centered cubic WTaCrV based high entropy alloys (HEAs), which are known to exhibit excellent irradiation resistance. The ductility evaluations are carried out using a criterion based on the competition between the critical stress intensity factors for emission (K Ie ) and cleavage (K Ic ) in the {110} slip planes and {110} crack planes, which are evaluated within the linear elastic fracture mechanics framework and computed using density functional theory. The results suggest that increasing the alloying concentrations of V and reducing the concentrations of W can significantly improve the ductility in these HEAs. The elastic anisotropy for these HEAs is analyzed using the Zener anisotropy ratio and its correlation with the concentration of W in the alloys is studied. Results indicate that these alloys tend to be fairly isotropic independently from the concentration of W in them. The computed data for the elastic constants of these HEAs is also compared against available experimental data. The results are in good agreement, validating the robustness and accuracy of the computational methods. Multiple phenomenological ductility metrics were also computed and analyzed against the analytical model. Some metrics, mainly the surrogate D parameter, show a good correlation with the Rice model. The potential of these empirical metrics to serve as surrogate screening models for optimizing the compositional space is also discussed.

Anisotropy↗

Seismic moment tensor classification using elliptical distribution functions on the hypersphere

Discrimination of underground explosions from naturally occurring earthquakes and other anthropogenic sources is one of the fundamental challenges of nuclear explosion monitoring. In an operational setting, the number of events that can be thoroughly investigated by analysts is limited by available resources. The capability to rapidly screen out events that can be robustly identified as not being explosions is, therefore, of great potential benefit. Nevertheless, possible mis-classification of explosions as earthquakes currently limits the use of screening methods for verification of test-ban treaties. Moment tensors provide a physics-based classification tool for the characterization of different seismic sources and have enabled the advent of new techniques for discriminating between earthquakes and explosions. Following normalization and projection of their six-degree vectors onto the hypersphere, existing screening approaches use spherically symmetric metrics to determine whether any new moment tensor may have been an explosion. Here, we show that populations of moment tensors for both earthquakes and explosions are anisotropically distributed on the hypersphere. Distributions possessing elliptical symmetry, such as the scaled von Mises–Fisher distribution, therefore provide a better description of these populations than the existing spherically symmetric models. We describe a method that uses these elliptical distributions in combination with a Bayesian classifier to achieve successful classification rates of 99 per cent for explosions and 98 per cent for earthquakes using existing catalogues of events from the western United States. The 1983 May 5 Crowdie underground nuclear test and 2018 July 20 DAG-1 deep-borehole chemical explosion are the only two explosions out of 140 that are incorrectly classified. Application of the method to the 2006–2017 nuclear tests in the Democratic People’s Republic of Korea yields 100 per cent identification rates and we provide a simple routine MTid for general usage. The approach provides a means to rapidly assess the likelihood of an event being an explosion and can be built into monitoring workflows that rely on simultaneously assessing multiple different discrimination metrics.

58 GEOSCIENCES↗

Evaluation of Cathode Materials with Lithium-Metal Anodes: Baseline Performance and Protocol Standardization of Coin Cells

The collaborative evaluation of electrode materials across multiple research entities requires standardized electrochemical testing protocols to produce reliable, one-to-one comparisons between different systems of interest. Similar to the work done by Long et al. on protocol standardization for coin-cell testing with graphite anodes [J. Electrochem. Soc., 163, A2999, (2016)], here we introduce two standardized testing protocols designed to quickly evaluate important electrochemical properties of cathode materials using lithium-metal anodes. The two protocols measure kinetic and thermodynamic capacity losses, rate- and voltage-dependent cycling capacities, instabilities at high voltage and high cycling rate, and overpotentials at various states of charge. We then apply these protocols to four commercially available cathode materials to establish benchmark performance metrics that can be used to screen and evaluate new cathode materials.

25 ENERGY STORAGE↗

Solubility Behavior of CO 2 in Ionic Liquids Based on Ionic Polarity Index Analyses

Ionic liquids (ILs) can serve as effective CO 2 solvents with an appropriate selection of different anions and cations. However, due to the large library of potential IL compositions, rapid screening methods are needed for characterizing and ranking the expected properties. We have recently proposed the ionic polarity index (IPI) parameter, effectively connecting volume-based approaches and electrostatic potential analyses, providing a single metric that can potentially be used to rapidly screen for desirable IL properties. In this work, the corresponding anion and cation IPIs are used to generate correlations with respect to the CO 2 volumetric solubility in ILs. The relationships are generally applicable to groups of ILs within a homologous ion series, and this can be particularly valuable for pre-screening different ion pairings for maximizing gas solvation performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

COTS Ceramic Chip Capacitors: An Evaluation of the Parts and Assurance Methodologies

Commercial-Off-The-Shelf (COTS) multilayer ceramic chip capacitors (MLCCs) are continually evolving to reduce physical size and increase volumetric efficiency. Designers of high reliability aerospace and military systems are attracted to these attributes of COTS MLCCs and would like to take advantage of them while maintaining the high standards for long-term reliable operation they are accustomed io when selecting military qualified established reliability (MIL-ER) MLCCs. However, MIL-ER MLCCs are not available in the full range of small chip sizes with high capacitance as found in today's COTS MLCCs. The objectives for this evaluation were to assess the long-term performance of small case size COTS MLCCs and to identify effective, lower-cost product assurance methodologies. Fifteen (15) lots of COTS X7R dielectric MLCCs from four (4) different manufacturers and two (2) MIL-ER BX dielectric MLCCs from two (2) of the same manufacturers were evaluated. Both 0805 and 0402 chip sizes were included. Several voltage ratings were tested ranging from a high of 50 volts to a low of 6.3 volts. The evaluation consisted of a comprehensive screening and qualification test program based upon MIL-PRF-55681 (i.e., voltage conditioning, thermal shock, moisture resistance, 2000-hour life test, etc.). In addition, several lot characterization tests were performed including Destructive Physical Analysis (DPA), Highly Accelerated Life Test (HALT) and Dielectric Voltage Breakdown Strength. The data analysis included a comparison of the 2000-hour life test results (used as a metric for long-term performance) relative to the screening and characterization test results. Results of this analysis indicate that the long-term life performance of COTS MLCCs is variable -- some lots perform well, some lots perform poorly. DPA and HALT were found to be promising lot characterization tests to identify substandard COTS MLCC lots prior to conducting more expensive screening and qualification tests. The results indicate that lot- specific screening and qualification are still recommended for high reliability applications. One significant and concerning observation is that MIL- type voltage conditioning (100 hours at twice rated voltage, 125 C) was not an effective screen in removing infant mortality parts for the particular lots of COTS MLCCs evaluated.

Brusse, Jay A.↗

CoRE MOF DB: A curated experimental metal-organic framework database with machine-learned properties for integrated material-process screening

Here, we present an updated version of the Computation-Ready, Experimental (CoRE) Metal-Organic Framework (MOF) database, which includes a curated set of computation-ready MOF crystal structures designed for high-throughput computational materials discovery. Data collection and curation procedures were improved from the previous version to enable more frequent updates in the future. Machine-learning-predicted properties, such as stability metrics and heat capacities, are included in the dataset to streamline screening activities. An updated version of MOFid was developed to provide detailed information on metal nodes, organic linkers, and topologies of an MOF structure. DDEC6 partial atomic charges of MOFs were assigned based on a machine-learning model. Gibbs ensemble Monte Carlo simulations were used to classify the hydrophobicity of MOFs. The finalized dataset was subsequently used to perform integrated material-process screening for various carbon-capture conditions using high-fidelity temperature-swing adsorption (TSA) simulations. Our workflow identified multiple MOF candidates that are predicted to outperform CALF-20 for these applications.

CoRE MOF database↗