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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

THE EFFECT OF MAGNETIC FIELDS AND AMBIPOLAR DIFFUSION ON CORE MASS FUNCTIONS

Linear analysis of the formation of protostellar cores in planar magnetic interstellar clouds yields information about length scales involved in star formation. Combining these length scales with various distributions of other environmental variables (i.e., column density and mass-to-flux ratio) and applying Monte Carlo methods allow us to produce synthetic core mass functions (CMFs) for different environmental conditions. Our analysis shows that the shape of the CMF is directly dependent on the physical conditions of the cloud. Specifically, magnetic fields act to broaden the mass function and develop a high-mass tail while ambipolar diffusion will truncate this high-mass tail. In addition, we analyze the effect of small number statistics on the shape and high-mass slope of the synthetic CMFs. We find that observed CMFs are severely statistically limited, which has a profound effect on the derived slope for the high-mass tail.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Uncertainty analysis of signal deconvolution using a measured instrument response function

A common analysis procedure minimizes the ln-likelihood that a set of experimental observables matches a parameterized model of the observation. The model includes a description of the underlying physical process as well as the instrument response function (IRF). Here, we investigate the National Ignition Facility (NIF) neutron time-of-flight (nTOF) spectrometers, the IRF is constructed from measurements and models. IRF measurements have a finite precision that can make significant contributions to the uncertainty estimate of the physical model’s parameters. Finally, we apply a Bayesian analysis to properly account for IRF uncertainties in calculating the ln-likelihood function used to find the optimum physical parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Pr{sub 1.33}Pt{sub 4}Ga{sub 10}: Superstructure and magnetism

Pr{sub 1.33}Pt{sub 4}Ga{sub 10} crystals were prepared by Ga-flux method. The superstructure of this compound was studied by single-crystal X-ray diffraction (XRD), transmission electron microscopy (TEM), and diffuse X-ray scattering. Pr{sub 1.33}Pt{sub 4}Ga{sub 10} adopts the P6{sub 3}/mmc space group with a=b=4.3227(5) Å, c=16.485(3) Å: the structure features Pr{sub 2}Ga{sub 3} layers alternating with Pt{sub 2}Ga{sub 4} layers along the c-axis. TEM studies and pair distribution function (PDF) analysis of X-ray total scattering data show that Pr{sub 2}Ga{sub 3} layers possess an ordered superstructure (of dimension a′=a√(3)) in which Pr vacancies and Ga atoms are ordered within the ab-plane but disordered along the c-direction. PDF analysis also shows temperature-dependent structural features local to the Pr{sup 3+} ion. Magnetic measurements reveal that Pr{sup 3+} ions order ferrimagnetically below 12.5(2) K. - Graphical abstract: Left: Crystal structure of Pr{sub 1.33}Pt{sub 4}Ga{sub 10} showing Pr and Ga vacancies in the Pr{sub 2}Ga{sub 3} plane. Right: Tunneling electron microscopy (TEM) image of Pr{sub 1.33}Pt{sub 4}Ga{sub 10}. These vacancies have been studied using TEM and pair distribution function analysis. Magnetic measurements reveal that Pr{sup 3+} ions order ferrimagnetically below 7.8(2) K. - Highlights: • TEM studies indicate a superstructure from Pr and Ga vacancies. • Pair distribution function analyses may point to structural relaxation of vacancies. • Pr{sub 1.33}Pt{sub 4}Ga{sub 10} behaves as a ferromagnet and exhibits a metamagnetic transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Molecular Dissection of Induced Platinum Resistance through Functional and Gene Expression Analysis in a Cell Culture Model of Bladder Cancer

Here, we report the development, functional and molecular characterization of an isogenic, paired bladder cancer cell culture model system for studying platinum drug resistance. The 5637 human bladder cancer cell line was cultured over ten months with stepwise increases in oxaliplatin concentration to generate a drug resistant 5637R sub cell line. The MTT assay was used to measure the cytotoxicity of several bladder cancer drugs. Liquid scintillation counting allowed quantification of cellular drug uptake and efflux of radiolabeled oxaliplatin and carboplatin. The impact of intracellular drug inactivation was assessed by chemical modulation of glutathione levels. Oxaliplatin- and carboplatin-DNA adduct formation and repair was measured using accelerator mass spectrometry. Resistance factors including apoptosis, growth factor signaling and others were assessed with RNAseq of both cell lines and included confirmation of selected transcripts by RT-PCR. Oxaliplatin, carboplatin, cisplatin and gemcitabine were significantly less cytotoxic to 5637R cells compared to the 5637 cells. In contrast, doxorubicin, methotrexate and vinblastine had no cell line dependent difference in cytotoxicity. Upon exposure to therapeutically relevant doses of oxaliplatin, 5637R cells had lower drug-DNA adduct levels than 5637 cells. This difference was partially accounted for by pre-DNA damage mechanisms such as drug uptake and intracellular inactivation by glutathione, as well as faster oxaliplatin-DNA adduct repair. In contrast, both cell lines had no significant differences in carboplatin cell uptake, efflux and drug-DNA adduct formation and repair, suggesting distinct resistance mechanisms for these two closely related drugs. The functional studies were augmented by RNAseq analysis, which demonstrated a significant change in expression of 83 transcripts, including 50 known genes and 22 novel transcripts. Most of the transcripts were not previously associated with bladder cancer chemoresistance. This model system and the associated phenotypic and genotypic data has the potential to identify some novel details of resistance mechanisms of clinical importance to bladder cancer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Local deuterium order in apparently disordered Laves phase deuteride YFe{sub 2}D{sub 4.2}

Deuterium short-range order in cubic Laves phase deuteride YFe{sub 2}D{sub 4.2} was studied by neutron (ToF) powder diffraction experiments and Pair Distribution Function (PDF) analysis between 290 and 400 K. The minimal allowed D-D distance of 2.1 A in a metal deuteride (Switendick rule) has been experimentally proved in the HT-disordered phase YFe{sub 2}D{sub 4.2}. It has been found that the distribution of deuterium atoms around the iron is not random, and cannot be explained only by applying the Switendick rule. The first coordination sphere of iron atoms in the high temperature (HT)-disordered phase resembles between 350 and 400 K the coordination observed in the low temperature (LT)-ordered phase. Reversed Monte Carlo modeling of the Pair Distribution Function of the HT-disordered phase prefers the coordination FeD{sub 5} and FeD{sub 4} in agreement with the LT-ordered phase. - Graphical abstract: Deuterium short-range order in cubic Laves phase deuteride YFe{sub 2}D{sub 4.2} was studied by ToF neutron powder diffraction experiments and Pair Distribution Function analysis between 290 and 400 K. It has been found that the distribution of deuterium atoms around the iron is not random, and cannot be explained only by applying the Switendick rule. The first coordination sphere of iron atoms in the HT-disordered phase resembles that of the LT-ordered phase. Highlights: > Switendick rule has been experimentally proved in YFe{sub 2}D{sub 4.2}. > The distribution of deuterium in YFe{sub 2}D{sub 4.2} cannot be explained only by Switendick rule. > The first coordination sphere of iron in the disordered phase resembles the ordered one.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An open-source high-content analysis workflow for CFTR function measurements using the forskolin-induced swelling assay

Abstract Motivation The forskolin-induced swelling (FIS) assay has become the preferential assay to predict the efficacy of approved and investigational CFTR-modulating drugs for individuals with cystic fibrosis (CF). Currently, no standardized quantification method of FIS data exists thereby hampering inter-laboratory reproducibility. Results We developed a complete open-source workflow for standardized high-content analysis of CFTR function measurements in intestinal organoids using raw microscopy images as input. The workflow includes tools for (i) file and metadata handling; (ii) image quantification and (iii) statistical analysis. Our workflow reproduced results generated by published proprietary analysis protocols and enables standardized CFTR function measurements in CF organoids. Availability and implementation All workflow components are open-source and freely available: the htmrenamer R package for file handling https://github.com/hmbotelho/htmrenamer; CellProfiler and ImageJ analysis scripts/pipelines https://github.com/hmbotelho/FIS_image_analysis; the Organoid Analyst application for statistical analysis https://github.com/hmbotelho/organoid_analyst; detailed usage instructions and a demonstration dataset https://github.com/hmbotelho/FIS_analysis. Distributed under GPL v3.0. Supplementary information Supplementary data are available at Bioinformatics online.

Hagemeijer, Marne C.↗
DOE OSTI2023

Predicting fatigue from heart rate signatures using functional logistic regression

Physical fatigue can have adverse effects on humans in extreme environments. Therefore, being able to predict fatigue using easy to measure metrics such as heart rate (HR) signatures has potential to have an impact in real-life scenarios. We apply a functional logistic regression model that uses HR signatures to predict physical fatigue, where physical fatigue is defined in a data-driven manner. Data were collected using commercially available wearable devices on 47 participants hiking the 20.7-mile Grand Canyon rim-to-rim trail in a single day. Fitted model provides good predictions and interpretable parameters for real-life application.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Regression models using shapes of functions as predictors

Functional variables are often used as predictors in regression problems. A commonly used parametric approach, called scalar-on-function regression, uses the $\mathbb L^2$ inner product to map functional predictors into scalar responses. This method can perform poorly when predictor functions contain undesired phase variability, causing phases to have disproportionately large influence on the response variable. One past solution has been to perform phase–amplitude separation (as a pre-processing step) and then use only the amplitudes in the regression model. In this paper, we propose a more integrated approach, termed elastic functional regression model (EFRM), where phase-separation is performed inside the regression model, rather than as a pre-processing step. This approach generalizes the notion of phase in functional data, and is based on the norm-preserving time warping of predictors. Due to its invariance properties, this representation provides robustness to predictor phase variability and results in improved predictions of the response variable over traditional models. We demonstrate this framework using a number of datasets involving gait signals, NMR data, and stock market prices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

An adaptive ANOVA-based PCKF for high-dimensional nonlinear inverse modeling

The probabilistic collocation-based Kalman filter (PCKF) is a recently developed approach for solving inverse problems. It resembles the ensemble Kalman filter (EnKF) in every aspect—except that it represents and propagates model uncertainty by polynomial chaos expansion (PCE) instead of an ensemble of model realizations. Previous studies have shown PCKF is a more efficient alternative to EnKF for many data assimilation problems. However, the accuracy and efficiency of PCKF depends on an appropriate truncation of the PCE series. Having more polynomial chaos basis functions in the expansion helps to capture uncertainty more accurately but increases computational cost. Selection of basis functions is particularly important for high-dimensional stochastic problems because the number of polynomial chaos basis functions required to represent model uncertainty grows dramatically as the number of input parameters (random dimensions) increases. In classic PCKF algorithms, the PCE basis functions are pre-set based on users' experience. Also, for sequential data assimilation problems, the basis functions kept in PCE expression remain unchanged in different Kalman filter loops, which could limit the accuracy and computational efficiency of classic PCKF algorithms. To address this issue, we present a new algorithm that adaptively selects PCE basis functions for different problems and automatically adjusts the number of basis functions in different Kalman filter loops. The algorithm is based on adaptive functional ANOVA (analysis of variance) decomposition, which approximates a high-dimensional function with the summation of a set of low-dimensional functions. Thus, instead of expanding the original model into PCE, we implement the PCE expansion on these low-dimensional functions, which is much less costly. We also propose a new adaptive criterion for ANOVA that is more suited for solving inverse problems. The new algorithm was tested with different examples and demonstrated great effectiveness in comparison with non-adaptive PCKF and EnKF algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

An ontology-based fault generation and fault propagation analysis approach for safety-critical computer systems at the design stage

Abstract Fault propagation analysis is a process used to determine the consequences of faults residing in a computer system. A typical computer system consists of diverse components (e.g., electronic and software components), thus, the faults contained in these components tend to possess diverse characteristics. How to describe and model such diverse faults, and further determine fault propagation through different components are challenging problems to be addressed in the fault propagation analysis. This paper proposes an ontology-based approach, which is an integrated method allowing for the generation, injection, and propagation through inference of diverse faults at an early stage of the design of a computer system. The results generated by the proposed framework can verify system robustness and identify safety and reliability risks with limited design level information. In this paper, we propose an ontological framework and its application to analyze an example safety-critical computer system. The analysis result shows that the proposed framework is capable of inferring fault propagation paths through software and hardware components and is effective in predicting the impact of faults.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termed as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Automated Vulnerability Detection for Compiled Smart Grid Software

While testing performed with proper experimental controls can provide scientifically quantifiable evidence that software does not contain unintentional vulnerabilities (bugs), it is insufficient to show that intentional vulnerabilities exist, and impractical to certify devices for the expected long lifetimes of use. For both of these needs, rigorous analysis of the software itself is essential. Automated software behavior computation applies rigorous static software analysis methods based on function extraction (FX) to compiled software to detect vulnerabilities, intentional or unintentional, and to verify critical functionality. This analysis is based on the compiled firmware, takes into account machine precision, and does not rely on heuristics or approximations early in the analysis.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Longitudinal data analysis in support of functional stability concepts for leachate management at closed municipal landfills

Highlights: • Longitudinal data analysis using a mixed-effects regression model. • Dataset consisted of a total of 1402 samples from 101 closed municipal landfills. • Target analytes and classes generally showed predictable degradation trends. • Validates historical studies focused on macro organic indicators such as BOD. • BOD can serve as “gateway” indicator for planning leachate management. - Abstract: Landfill functional stability provides a target that supports no environmental threat at the relevant point of exposure in the absence of active control systems. With respect to leachate management, this study investigates “gateway” indicators for functional stability in terms of the predictability of leachate characteristics, and thus potential threat to water quality posed by leachate emissions. Historical studies conducted on changes in municipal solid waste (MSW) leachate concentrations over time (longitudinal analysis) have concentrated on indicator compounds, primarily chemical oxygen demand (COD) and biochemical oxygen demand (BOD). However, validation of these studies using an expanded database and larger constituent sets has not been performed. This study evaluated leachate data using a mixed-effects regression model to determine the extent to which leachate constituent degradation can be predicted based on waste age or operational practices. The final dataset analyzed consisted of a total of 1402 samples from 101 MSW landfills. Results from the study indicated that all leachate constituents exhibit a decreasing trend with time in the post-closure period, with 16 of the 25 target analytes and aggregate classes exhibiting a statistically significant trend consistent with well-studied indicators such as BOD. Decreasing trends in BOD concentration after landfill closure can thus be considered representative of trends for many leachate constituents of concern.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Structural analysis, optical and dielectric function of [Ba{sub 0.9}Ca{sub 0.1}](Ti{sub 0.9}Zr{sub 0.1})O{sub 3} nanocrystals

This work presents the identification of inter-band transitions in the imaginary part of the dielectric function (ε{sub 2}) derived from the Kramers–Kronig analysis for [Ba{sub 0.9}Ca{sub 0.1}](Ti{sub 0.9}Zr{sub 0.1})O{sub 3} (BCZT) nanocrystals synthesized by the modified Pechini method. The analysis started with the chemical identification of the atoms that conform BCZT in the valence loss energy region of a high energy-resolution of electron energy loss spectroscopy. The indirect band energy (E{sub g}) was determined in the dielectric response function. This result is in agreement with the UV-Vis technique, and it obtained an optical band gap of 3.16 eV. The surface and volume plasmon peaks were observed at 13.1 eV and 26.2 eV, respectively. The X-ray diffraction pattern and the Rietveld refinement data of powders heat treated at 700 °C for 1 h suggest a tetragonal structure with a space group (P4 mm) with the average crystal size of 35 nm. The average particle size was determined by transmission electron microscopy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Formic Acid Electrooxidation on Pt or Pd Monolayer on Transition-Metal Single Crystals: A First-Principles Structure Sensitivity Analysis

Here, we present a density functional theory analysis of trends for the electrooxidation of formic acid (FAO) on a single Pt or Pd monolayer supported on the close-packed (111) facet of transition metals (Pt*/M or Pd*/M): Au, Ag, Cu, Pt, Pd, Ir, and Rh, the close-packed (0001) facet of Os, Ru, and Re, and the open (100) facet of Au, Ag, Pt, Pd, Ir, and Rh. We show that the deposition of Pt or Pd pseudomorphic monolayers on these single crystals modifies the electronic structure of the Pt or Pd monolayer. Specifically, we found a direct correlation between the d-band center of the Pt and Pd monolayer and the free energy of adsorbed CO*, the latter being a reactivity descriptor for FAO. Together with the free energy of adsorbed OH* as a second reactivity descriptor, we depict the thermochemistry of the reaction network as phase diagrams showing calculated free energies across regions of rate-determining steps. We found that FAO is structure-sensitive on most surfaces studied. Pt*/Au(111) is predicted to be the most active among all Pt*/M(111/0001) surfaces studied, despite binding CO*, the strongest among the close-packed facets. This is the case because of its superiority in activating water to OH*, thus removing CO* at lower potentials than other surfaces. On similar grounds, Pt*/Pd(100), Pd*/Re(0001), Pd*/Au(111), Pd*/Ag(111), and Pd*/Pt(111) are predicted to show higher FAO activity than the corresponding monometallic Pt and Pd surfaces.

(100) facets↗
DOE OSTI2021

Harmonic analysis of 2d CFT partition functions

We apply the theory of harmonic analysis on the fundamental domain of SL(2, Z) to partition functions of two-dimensional conformal field theories. We decompose the partition function of c free bosons on a Narain lattice into eigenfunctions of the Laplacian of worldsheet moduli space H/SL(2, Z), and of target space moduli space O(c, c; Z)\O(c, c; R)/O(c)×O(c). This decomposition manifests certain properties of Narain theories and ensemble averages thereof. We extend the application of spectral theory to partition functions of general two-dimensional conformal field theories, and explore its meaning in connection to AdS 3 gravity. An implication of harmonic analysis is that the local operator spectrum is fully determined by a certain subset of degeneracies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗