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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 253 records · Page 14

Centralized Analysis of Local Data, With Dollars and Lives on the Line: Lessons From The Home Radon Experience

In this chapter we elucidate four main themes. The first is that modern data analyses, including "Big Data" analyses, often rely on data from different sources, which can present challenges in constructing statistical models that can make effective use of all of the data. The second theme is that although data analysis is usually centralized, frequently the final outcome is to provide information or allow decision-making for individuals. Third, data analyses often have multiple uses by design: the outcomes of the analysis are intended to be used by more than one person or group, for more than one purpose. Finally, issues of privacy and confidentiality can cause problems in more subtle ways than are usually considered; we will illustrate this point by discussing a case in which there is substantial and effective political opposition to simply acknowledging the geographic distribution of a health hazard. A researcher analyzes some data and learns something important. What happens next? What does it take for the results to make a difference in people's lives? In this chapter we tell a story - a true story - about a statistical analysis that should have changed government policy, but didn't. The project was a research success that did not make its way into policy, and we think it provides some useful insights into the interplay between locally-collected data, statistical analysis, and individual decision making.

99 GENERAL AND MISCELLANEOUS↗

Targeting accuracy of single-isocenter intensity-modulated radiosurgery for multiple lesions

To investigate the targeting accuracy of intensity-modulated SRS (IMRS) plans designed to simultaneously treat multiple brain metastases with a single isocenter. A home-made acrylic phantom able to support a film (EBT3) in its coronal plane was used. The phantom was CT scanned and three coplanar small targets (a central and two peripheral) were outlined in the Eclipse system. Peripheral targets were 6 cm apart from the central one. A reference IMRS plan was designed to simultaneously treat the three targets, but only a single isocenter located at the center of the central target was used. After positioning the phantom on the linac using the room lasers, a CBCT scan was acquired and the reference plan were mapped on it, by placing the planned isocenter at the intersection of the landmarks used in the film showing the linac isocenter. The mapped plan was then recalculated and delivered. The film dose distribution was derived using a cloud computing application ( (www.radiochromic.com)) that uses a triple-channel dosimetry algorithm. Comparison of dose distributions using the gamma index (5%/1 mm) were performed over a 5 × 5 cm{sup 2} region centered over each target. 2D shifts required to get the best gamma passing rates on the peripheral target regions were compared with the reported ones for the central target. The experiment was repeated ten times in different sessions. Average 2D shifts required to achieve optimal gamma passing rates (99%, 97%, 99%) were 0.7 mm (SD: 0.3 mm), 0.8 mm (SD: 0.4 mm) and 0.8 mm (SD: 0.3 mm), for the central and the two peripheral targets, respectively. No statistical differences (p > 0.05) were found for targeting accuracy between the central and the two peripheral targets. The study revealed a targeting accuracy within 1 mm for off-isocenter targets within 6 cm of the linac isocenter, when a single-isocenter IMRS plan is designed.

61 RADIATION PROTECTION AND DOSIMETRY↗

Fabrication of FCC-SiO{sub 2} colloidal crystals using the vertical convective self-assemble method

In order to determine the optimal conditions for the growth of high-quality 250 nm-SiO{sub 2} colloidal crystals by the vertical convective self-assemble method, the Design of Experiments (DoE) methodology is applied. The influence of the evaporation temperature, the volume fraction, and the pH of the colloidal suspension is studied by means of an analysis of variance (ANOVA) in a 3{sup 3} factorial design. Characteristics of the stacking lattice of the resulting colloidal crystals are determined by scanning electron microscopy and angle-resolved transmittance spectroscopy. Quantitative results from the statistical test show that the temperature is the most critical factor influencing the quality of the colloidal crystal, obtaining highly ordered structures with FCC stacking lattice at a growth temperature of 40°C.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Excess pressure and electric fields in nonideal plasma hydrodynamics

Nonideal plasmas have nontrivial space and time correlations, which simultaneously impact both the excess thermodynamic quantities as well as the collision processes. Yet, hydrodynamics models for designing and interpreting nonideal plasma experiments, such as inertial-confinement fusion experiments, typically neglect electrodynamics, although some models include electric fields indirectly through a generalized Fick's law. However, because most transport models are not computed self-consistently with the equation of state, there is double counting of the forces in the excess thermodynamic quantities and the collision terms. Here we employ the statistical mechanical hydrodynamic theory of Irving and Kirkwood [J. Chem. Phys. 18, 817 (1950)] to examine inhomogeneous, nonideal plasmas that contain electric fields. We show that it is not possible to simultaneously separate terms that correspond to electric fields and excess pressure; rather, these quantities arise from the same interparticle Coulomb forces. Additionally, new terms associated with nonlocality appear in the presence of strong inhomogeneities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Aerodynamic Data Fusion Toward the Digital Twin Paradigm

This paper considers the fusion of two aerodynamic data sets originating from differing types of physical or computer experiments. This paper specifically addresses the fusion of 1) noisy and in-complete fields from wind-tunnel measurements and 2) deterministic but biased fields from numerical simulations. These two data sources are fused in order to estimate the true field that best matches measured quantities that serve as the ground truth. For example, two sources of pressure fields about an aircraft are fused based on measured forces and moments from a wind-tunnel experiment. A fundamental challenge in this problem is that the true field is unknown and cannot be estimated with 100% certainty. A Bayesian framework is employed to infer the true fields conditioned on measured quantities of interest; essentially a statistical correction to the data is performed. The fused data may then be used to construct more accurate surrogate models suitable for early stages of aerospace design. An extension of the proper orthogonal decomposition with constraints is also introduced to solve the same problem. In this work, both methods are demonstrated on fusing the pressure distributions for flow past the RAE2822 airfoil and the Common Research Model wing at transonic conditions. Comparison of both methods reveals that the Bayesian method is more robust when data are scarce and capable of also accounting for uncertainties in the data. Furthermore, given adequate data, the proper-orthogonal-decomposition-based and Bayesian approaches lead to surprisingly similar results.

42 ENGINEERING↗

Simultaneous prediction of structural properties in epitaxially–grown GaN with quantum and conventional multi–output learning algorithms

Hundreds of GaN thin film crystal plasma–assisted molecular beam epitaxy synthesis experiment records spanning two decades were organized into a dataset correlating the growth experiment design parameters with discrete, binary determinations of crystallinity and surface morphology. Conventional data science techniques as well as both quantum and classical multi–output supervised machine learning algorithms were implemented to investigate the relationships between the operating parameter data and the structural figures of merit. Correlation coefficients, decision tree nodes, p–values, and SHAP values all support substrate temperature and gallium effusion cell conditions as being statistically significant for simultaneously influencing GaN crystallinity and surface morphology. Here, a conventional deep neural network learned best from the data, followed by a quantum–classical hybrid gradient boosting algorithm. When combined with calculations of uncertainty intervals based on VennAbers predictors, machine learning predictions of both structural properties show good agreement with results reported in published experimental literature.

36 MATERIALS SCIENCE↗

Omics-Lethal Human Viruses, MERS-CoV Experiment MM001

The purpose of this experiment was to evaluate the host response to wild-type Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV) virus infection. Sample data was obtained from primary mouse lung for mRNA, proteomics, lipidomics, and metabolomics expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Analysis of metabolomics datasets with high-performance computing and metabolite atlases

Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged for future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. Furthermore, by using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models.

59 BASIC BIOLOGICAL SCIENCES↗

Measurement of the top quark mass using events with a single reconstructed top quark in pp collisions at $$ \sqrt{s} $$ = 13 TeV

A measurement of the top quark mass is performed using a data sample enriched with single top quark events produced in the t channel. The study is based on proton- proton collision data, corresponding to an integrated luminosity of 35.9 fb -1 , recorded at √s = 13 TeV by the CMS experiment at the LHC in 2016. Candidate events are selected by requiring an isolated high-momentum lepton (muon or electron) and exactly two jets, of which one is identified as originating from a bottom quark. Multivariate discriminants are designed to separate the signal from the background. Optimized thresholds are placed on the discriminant outputs to obtain an event sample with high signal purity. The top quark mass is found to be $172.13^{+0.76}_{-0.77}$ GeV, where the uncertainty includes both the statistical and systematic components, reaching sub-GeV precision for the first time in this event topology. The masses of the top quark and antiquark are also determined separately using the lepton charge in the final state, from which the mass ratio and difference are determined to be $0.9952^{+0.0079}_{-0.0104}$ and $0.83^{+1.79}_{-1.35}$ GeV, respectively. The results are consistent with CPT invariance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement Error and Resolution in Quantitative Stable Isotope Probing: Implications for Experimental Design

Quantitative stable isotope probing (qSIP) estimates isotope tracer incorporation into DNA of individual microbes and can link microbial biodiversity and biogeochemistry in complex communities. As with any quantitative estimation technique, qSIP involves measurement error, and a fuller understanding of error, precision, and statistical power benefits qSIP experimental design and data interpretation. We used several qSIP data sets—from soil and seawater microbiomes—to evaluate how variance in isotope incorporation estimates depends on organism abundance and resolution of the density fractionation scheme. We assessed statistical power for replicated qSIP studies, plus sensitivity and specificity for unreplicated designs. As a taxon’s abundance increases, the variance of its weighted mean density declines. Nine fractions appear to be a reasonable trade-off between cost and precision for most qSIP applications. Increasing the number of density fractions beyond that reduces variance, although the magnitude of this benefit declines with additional fractions. Our analysis suggests that, if a taxon has an isotope enrichment of 10 atom% excess, there is a 60% chance that this will be detected as significantly different from zero (with alpha 0.1). With five replicates, isotope enrichment of 5 atom% could be detected with power (0.6) and alpha (0.1). Finally, we illustrate the importance of internal standards, which can help to calibrate per sample conversions of %GC to mean weighted density. These results should benefit researchers designing future SIP experiments and provide a useful reference for metagenomic SIP applications where both financial and computational limitations constrain experimental scope.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental Validation of a Module Cell Cracking Model

The What's Cracking app can predict how changes in crystalline silicon photovoltaic (PV) module materials, design, and mounting affect its susceptibility for cell fracture under uniform loading. This work has experimentally validated the app. A set of commercial crystalline silicon PV modules was obtained for this study. The modules were uniformly loaded at three different mounting points, and their subsequent cell fractures were recorded. A large sample size allowed for the development of an experimental statistical model for cell fracture. Here, the comparison of the experiment to predictions from the app is in excellent agreement. Both experimental and modeling results also elucidate how moving the module mounting points toward the center of the module increases the probability of cell fracture.

14 SOLAR ENERGY↗

Omics-Lethal Human Viruses, Interferon-Stimulated Response Experiment IFNaCL001

The purpose of this experiment was to evaluate the host interferon-stimulated cellular response to interferon alpha (IFNα) treatment. Sample data was obtained from human lung adenocarcinoma cells (Calu-3) treated with or without IFNα for mRNA and miRNA transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset download have a direct relationship to a primary sample submission corresponding to a specific interferon response to viral infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, Interferon-Stimulated Response Experiment IFNFB001

The purpose of this experiment was to evaluate the human host cellular response to interferon alpha/beta (IFNα/β) or interferon gamma (IFNγ) treatment. Sample data was obtained from primary human lung fibroblast (FB) cells inoculated with IFNα/β or IFNγ for transcriptome analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset download have a direct relationship to a primary sample submission corresponding to a specific interferon response to viral infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, Influenza A Experiment IM103

The purpose of this experiment was to evaluate the host response to wild-type Influenza A/Vietnam/1203/2004 (H5N1; "VN1203") virus infection and mock infection. Sample data was obtained for mouse lung tissue and processed for mRNA, miRNA, proteomics, lipidomics, and metabolomics expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset download each have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, MERS-CoV Experiment MFB001

The purpose of this experiment was to evaluate the human host response to wild-type MERS-CoV (icMERS-CoV) virus infection. Sample data was obtained from primary human fibroblasts and processed for mRNA, miRNA, proteomics, metabolomics, and lipidomics expression analysis. econdary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Enabling energy‐efficient manufacturing of pharmaceutical solid oral dosage forms via integrated techno‐economic analysis and advanced process modeling

Abstract The global pharmaceutical industry is a trillion‐dollar market. However, the pharmaceutical sector often lags in manufacturing innovation and automation which limits its potential to maximize energy efficiency. The integration of techno‐economic analysis (TEA) with advanced process models as part of an overarching smart manufacturing platform, can help industries create business models, which can be adapted for manufacturing to reduce energy consumption and operating costs while ensuring product quality which can further enable a more sustainable process operation. In this study, a rational design of experiment on three unit‐operations (wet granulation, drying, and milling) was performed on a batch (case 1) and continuous (case 2) pharmaceutical process to obtain experimental data. Process models for predicting product quality and energy efficiency of each of the three‐unit operations were developed. The experimental data were used to validate the models and good agreement was observed. The energy consumption of each unit operation was calculated using statistical models relating the power consumption and the process parameters. The developed process models and energy models were further integrated into a TEA framework, which quantified the energy and monetary cost of manufacturing for both batch and continuous manufacturing cases. With this integrated framework, energy costs savings of ~33% was obtained in the continuous manufacturing process (case 2) over the batch process (case 1).

Sampat, Chaitanya↗

Overview of ten-year operation of the superconducting linear accelerator at the Spallation Neutron Source

The Spallation Neutron Source (SNS) has acquired extensive operational experience of a pulsed proton superconducting linear accelerator (SCL) as a user facility. Numerous lessons have been learned in its first 10 years operation to achieve a stable and reliable operation of the SCL. In this paper, an overview of the SNS SCL design, qualification of superconducting radio frequency (SRF) cavities and ancillary subsystems, an overview of the SNS cryogenic system, the SCL operation including SCL output energy history and downtime statistics, performance stability of the SRF cavities, efforts for SRF cavity performance recovery and improvement at the SNS, and maintenance activities for cryomodules are introduced.

43 PARTICLE ACCELERATORS↗

Establishing temperature from radiance of dynamically compressed metals

Precise temperature determination is a significant challenge in extreme environments of dynamic compression studies. How can radiance measurements taken in high-pressure shock experiments constrain temperature in a meaningful and physically consistent way? Experiments maintaining sample compression against a transparent window can be tailored to present a uniform measurement area with uncertain spectral emissivity. We compare several methods to analyze radiance collected at multiple wavelengths, applying statistical methods and physical principles to improve temperature inference. With proper radiance collection and analysis, dynamic temperature uncertainties become comparable to thermomechanical ambiguities of the emitting surface.

36 MATERIALS SCIENCE↗