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NASA NTRS2004

Satellite Geopotential Anomaly Constraints for the Crust of the Greenland-Iceland Region

Satellite magnetometer observations of the Greenland-Iceland region compare quite well with lower altitude data. The satellite magnetic data suggest magnetically enhanced crust was emplaced by the Iceland Plume. Crustal thicknesses, which may be more than 30 km for the Greenland-Scotland Ridge, were obtained from inversion of the compensating terrain gravity effects that were estimated by spectral correlation analysis of the free-air gravity anomalies and terrain gravity effects. Regional magnetic anomaly maxima overlie possible thickened crust from eastern Iceland to the Greenland Coast. The Iceland-Faroe Ridge may involve thinner crust than the Greenland-Iceland portion of the Greenland-Scotland Ridge. The gravity derived crustal model exceeds a 0.7 correlation with available seismic estimates. In thermally active areas our gravity Moho estimates are systematically deeper than the seismic estimates suggesting local density reductions of the underlying lower crust/upper mantle. In south central Greenland, on the other hand, the gravity Moho estimates are shallower than seismic estimates to suggest a local enhancement of the lower crust/upper mantle density. The dichotomous crust of the Greenland-Iceland and Iceland-Faroe Ridges suggests unequal crustal development by the Iceland Plume and the Mid-Atlantic Ridge, where more crustal material may have been contributed to the North Atlantic Plate than the Eurasian Plate. A new thermal modeling scheme based on Poisson's relation between point pole gravity and thermal potentials allows estimation of magnetic crustal thicknesses. Subsequent magnetic anomaly inversion for susceptibility contrasts infers crustal development of the Greenland-Scotland Ridge by temporally variable pulses in plume strength.

vonFrese, R. R.↗

NASA NTRS2008

Analysis of Thermal and Reaction Times for Hydrogen Reduction of Lunar Regolith

System analysis of oxygen production by hydrogen reduction of lunar regolith has shown the importance of the relative time scales for regolith heating and chemical reaction to overall performance. These values determine the sizing and power requirements of the system and also impact the number and operational phasing of reaction chambers. In this paper, a Nusselt number correlation analysis is performed to determine the heat transfer rates and regolith heat up times in a fluidized bed reactor heated by a central heating element (e.g., a resistively heated rod, or a solar concentrator heat pipe). A coupled chemical and transport model has also been developed for the chemical reduction of regolith by a continuous flow of hydrogen. The regolith conversion occurs on the surfaces of and within the regolith particles. Several important quantities are identified as a result of the above analyses. Reactor scale parameters include the void fraction (i.e., the fraction of the reactor volume not occupied by the regolith particles) and the residence time of hydrogen in the reactor. Particle scale quantities include the particle Reynolds number, the Archimedes number, and the time needed for hydrogen to diffuse into the pores of the regolith particles. The analysis is used to determine the heat up and reaction times and its application to NASA s oxygen production system modeling tool is noted.

Hegde, U.↗

NASA NTRS2009

Analysis of Thermal and Reaction Times for Hydrogen Reduction of Lunar Regolith

Hegde, U.↗

NASA NTRS2019

The X-Ray Halo Scaling Relations of Supermassive Black Holes

We carry out a comprehensive Bayesian correlation analysis between hot halos and direct masses of supermassive black holes (SMBHs), by retrieving the X-ray plasma properties (temperature, luminosity, density, pressure, and masses) over galactic to cluster scales for 85 diverse systems. We find new key scalings, with the tightest relation being −, followed by −. The tighter scatter (down to 0.2 dex) and stronger correlation coefficient of all the X-ray halo scalings compared with the optical counterparts (as the −) suggest that plasma halos play a more central role than stars in tracing and growing SMBHs (especially those that are ultramassive). Moreover, correlates better with the gas mass than dark matter mass. We show the important role of the environment, morphology, and relic galaxies/coronae, as well as the main departures from virialization/self-similarity via the optical/X-ray fundamental planes. We test the three major channels for SMBH growth: hot/Bondi-like models have inconsistent anticorrelation with X-ray halos and too low feeding; cosmological simulations find SMBH mergers as subdominant over most of cosmic time and too rare to induce a central-limit-theorem effect; the scalings are consistent with chaotic cold accretion, the rain of matter condensing out of the turbulent X-ray halos that sustains a long-term self-regulated feedback loop. The new correlations are major observational constraints for models of SMBH feeding/feedback in galaxies, groups, and clusters (e.g., to test cosmological hydrodynamical simulations), and enable the study of SMBHs not only through X-rays, but also via the Sunyaev–Zel'dovich effect (Compton parameter), lensing (total masses), and cosmology (gas fractions).

Supermassive black holes↗

NASA NTRS2018

Methodologies for Verification and Validation of Space Launch System (SLS) Structural Dynamic Models

Responses to challenges associated with verification and validation (V&V) of Space Launch System (SLS) structural dynamics models are presented in this paper. Four methodologies addressing specific requirements for V&V are discussed. (1) Residual Mode Augmentation (RMA), which has gained acceptance by various principals in the NASA community, defines efficient and accurate FEM modal sensitivity models that are useful in test-analysis correlation and reconciliation and parametric uncertainty studies. (2) Modified Guyan Reduction (MGR) and Harmonic Reduction (HR, introduced in 1976), developed to remedy difficulties encountered with the widely used Classical Guyan Reduction (CGR) method, are presented. MGR and HR are particularly relevant for estimation of "body dominant" target modes of shell-type SLS assemblies that have numerous "body", "breathing" and local component constituents. Realities associated with configuration features and "imperfections" cause "body" and "breathing" mode characteristics to mix resulting in a lack of clarity in the understanding and correlation of FEM- and test-derived modal data. (3) Mode Consolidation (MC) is a newly introduced procedure designed to effectively "de-feature" FEM and experimental modes of detailed structural shell assemblies for unambiguous estimation of "body" dominant target modes. Finally, (4) Experimental Mode Verification (EMV) is a procedure that addresses ambiguities associated with experimental modal analysis of complex structural systems. Specifically, EMV directly separates well-defined modal data from spurious and poorly excited modal data employing newly introduced graphical and coherence metrics.

Coppolino, Robert N.↗

DOE OSTI2012

Fixation and partitioning of heavy metals in slag after incineration of sewage sludge

Highlights: Black-Right-Pointing-Pointer The contents and partitioning of HMs in slag of sludge incineration were examined. Black-Right-Pointing-Pointer The fixation rate decreases with residential time and finally keeps a constant. Black-Right-Pointing-Pointer Water mass fraction of 55% is optimal for the sediment for Ni, Mn, Zn, Cu and Cr. Black-Right-Pointing-Pointer Water mass fraction of 75% is optimal for the sediment for Pb. Black-Right-Pointing-Pointer We found higher temperature versus lower non-residual fraction except that of Pb. - Abstract: Fixation of heavy metals in the slag produced during incineration of sewage sludge will reduce emission of the metals to the atmosphere and make the incineration process more environmentally friendly. The effects of incineration conditions (incineration temperature 500-1100 Degree-Sign C, furnace residence time 0-60 min, mass fraction of water in the sludge 0-75%) on the fixation rates and species partitioning of Cd, Pb, Cr, Cu, Zn, Mn and Ni in slag were investigated. When the incineration temperature was increased from 500 to 1100 Degree-Sign C, the fixation rate of Cd decreased from 87% to 49%, while the fixation rates of Cu and Mn were stable. The maximum fixation rates for Pb and Zn and for Ni and Cr were reached at 900 and 1100 Degree-Sign C, respectively. The fixation rates of Cu, Ni, Cd, Cr and Zn decreased as the residence time increased. With a 20 min residence time, the fixation rates of Pb and Mn were low. The maximum fixation rates of Ni, Mn, Zn, Cu and Cr were achieved when the mass fraction of water in the sludge was 55%. The fixation rate of Cd decreased as the water mass fraction increased, while the fixation rate of Pb increased. Partitioning analysis of the metals contained in the slag showed that increasing the incineration temperature and residence time promoted complete oxidation of the metals. This reduced the non-residual fractions of the metals, which would lower the bioavailability of the metals. The mass fraction of water in the sludge had little effect on the partitioning of the metals. Correlation analysis indicated that the fixation rates of heavy metals in the sludge and the forms of heavy metals in the incinerator slag could be controlled by optimization of the incineration conditions. These results show how the bioavailability of the metals can be reduced for environmentally friendly disposal of the incinerator slag.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRSDate not supplied

Probability Bounds Analysis Applied to Multi-Purpose Crew Vehicle Nonlinearity

The Multi-Purpose Crew Vehicle (MPCV) Program Orion vehicle finite element model (FEM) was updated based on a modal test performed by Lockheed Martin. Due to nonlinearity observed in the test results, linear low force level (LL) and high force level (HL) FEMs were developed for use during various Space Launch System (SLS) flight regimes depending on expected forcing levels. Uncertainty models were derived for the combined MPCV and MPCV Stage Adaptor LL and HL Hurty/Craig-Bampton (HCB) components based on the MPCV structural test article Configuration 4 modal test-analysis correlation results. Subsequently, system-level uncertainty quantification analyses were performed using both models for various SLS flight configurations to determine the impact of the nonlinearity on important system metrics. The system metrics included both transfer functions associated with attitude control and dynamic loads associated with aerodynamic buffeting during ascent. In each case, an independent Monte Carlo (MC) analysis was performed, and no attempt was made to combine the results. The Hybrid Parametric Variation (HPV) method was used to develop the LL and HL MPCV HCB uncertainty models. The HPV method provides both parametric and non-parametric components of uncertainty. The non-parametric uncertainty accounts for the difference in model-form between the linearized analytical model and the corresponding linearized component test results in the form of mode shapes and frequencies at that force level. This linear model-form uncertainty is implemented in the HPV method using random matrix theory. However, the HPV uncertainty models developed for the linear LL and HL MPCV components do not account for the nonlinearity in the MPCV. With respect to the linearized models, this nonlinearity is also an uncertainty in model form, but in this case, it must be treated independently as an epistemic uncertainty. It represents a lack of knowledge, in contrast to an aleatory uncertainty due to the randomness of a variable. In the case of an epistemic variable, the true value is unknown, only the interval within which it lies is known. Epistemic uncertainty can be reduced with increased knowledge, while in general, aleatory uncertainty cannot. This work combines the epistemic uncertainty due to the MPCV nonlinearity with the parametric and non-parametric uncertainty within the HPV method using a second order propagation approach. The LL and HL test data is augmented with surrogate test data derived from a nonlinear MPCV representation. The impact of the MPCV nonlinearity on system response statistics is determined using a series of cumulative distribution functions in the form of a horsetail plot, or p-box. This results in an interval of probabilities for a specific response value, or an interval of response values at a specific probability.

Daniel C Kammer↗

DOE OSTI2026

Kaon leptonic and semileptonic decays with $N_f=2+1+1$ HISQ fermions

Precision tests of the Standard Model (SM) currently show a deficit in first-row Cabibbo-Kobayashi-Maskawa (CKM) unitarity. In this talk, we discuss progress towards a correlated analysis of the lattice-QCD inputs needed to test this relation with kaon data using highly improved staggered quarks (HISQ) on the MILC $N_{f}=2+1+1$ configurations. We present the status of a new analysis of light-meson decay constant data where chiral-continuum fits are guided by staggered chiral perturbation theory (SChPT). The goal of SChPT is twofold: it allows us to use data not only at physical pion mass but also at unphysical masses. Moreover, it provides values of ChPT low energy constants (LECs) as well as their correlations. We also present a reanalysis of our previous kaon semileptonic form factor calculation, aiming to estimate correlations between the form factor and light-meson decay constants. We discuss the new methodology, new data included, and present some preliminary results.

Merino, Ramón [Granada U.] (ORCID:000900039150393X↗

NASA NTRS1985

The corotating variation of the north-south anisotropy of cosmic rays

Correlation analysis on the relation of the north-south (N-S) anisotropy of cosmic rays, observed by the Nagoya multidirectional meson telescope, with the interplanetary magnetic field (IMP) as well the solar wind velocity within solar Carrington rotation for the period 1971 to 1976 is discussed. It is found that the N-S anisotropy of cosmic rays correlates quite well with the Bx component of the IMF. The correlation coefficient is nearly equal to 0.8.

Xue, S.↗

NASA NTRS2018

Test and Analysis of Full-Scale 27.5-Foot-Diameter Stiffened Metallic Launch Vehicle Cylinders

The Shell Buckling Knockdown Factor Project (SBKF) was established with the goal of developing improved (i.e., less-conservative, more robust) shell buckling knockdown factors (KDFs) for modern launch-vehicle structures. To this end, SBKF has engaged in several activities to support the development, validation, and implementation of the new design factors, including subscale and full-scale structural testing. Tests on eight different subscale, 8-foot-diameter, integrally stiffened aluminum-lithium 2195 (Al-Li 2195) cylinders were conducted in order to obtain the majority of the required validation data. In addition, two full-scale, 27.5-foot-diameter, Al-Li 2195, integrally stiffened cylinders were tested to provide additional validation data and to determine structural scaling trends. Presented herein are the details of a recent analysis model development and test and analysis correlation effort on the full-scale test articles. The effects of selected modeling assumptions and approaches are discussed, and results from a modeling sensitivity study are presented. It was found that simplified finite element models, that assume nominal test article geometry and material properties, can predict the overall response characteristics well. However, several discrepancies in the test and analysis results were observed. A sensitivity study was performed to determine the effects of several modeling assumptions and address the observed discrepancies. The results from the study indicated that the evolution of local skin pocket buckling and the presence of residual stresses due to the manufacturing process can have a significant influence on the predicted buckling response of the cylinders considered.

Lovejoy, Andrew E.↗

NASA NTRS1975

Design Data Collection with Skylab Microwave Radiometer-Scatterometer S-193, Volume 1

The author has identified the following significant results. Observations with S-193 have provided radar design information for systems to be flown on spacecraft, but only at 13.9 GHz and for land areas over the United States and Brazil plus a few other areas of the world for which this kind of analysis was not made. Observations only extended out to about 50 deg angle of incidence. The value of a sensor with such a gross resolution for most overland resource and status monitoring systems seems marginal, with the possible exception of monitoring soil moisture and major vegetation variations. The complementary nature of the scatterometer and radiometer systems was demonstrated by the correlation analysis. Although radiometers must have spatial resolutions dictated by antenna size, radars can use synthetic aperture techniques to achieve much finer resolutions. Multiplicity of modes in the S-193 sensors complicated both the system development and its employment. An attempt was made in the design of the S-193 to arrange optimum integration times for each angle and type of measurement. This unnecessarily complicated the design of the instrument, since the gains in precision achieved in this way were marginal. Either a software-controllable integration time or a set of only two or three integration times would have been better.

Moore, R. K.↗

DOE OSTI2012

Inferring Correlation Networks from Genomic Survey Data

High-throughput sequencing based techniques, such as 16S rRNA gene profiling, have the potential to elucidate the complex inner workings of natural microbial communities - be they from the world's oceans or the human gut. A key step in exploring such data is the identification of dependencies between members of these communities, which is commonly achieved by correlation analysis. However, it has been known since the days of Karl Pearson that the analysis of the type of data generated by such techniques (referred to as compositional data) can produce unreliable results since the observed data take the form of relative fractions of genes or species, rather than their absolute abundances. Using simulated and real data from the Human Microbiome Project, we show that such compositional effects can be widespread and severe: in some real data sets many of the correlations among taxa can be artifactual, and true correlations may even appear with opposite sign. Additionally, we show that community diversity is the key factor that modulates the acuteness of such compositional effects, and develop a new approach, called SparCC (available at https://bitbucket.org/yonatanf/sparcc), which is capable of estimating correlation values from compositional data. To illustrate a potential application of SparCC, we infer a rich ecological network connecting hundreds of interacting species across 18 sites on the human body. Using the SparCC network as a reference, we estimated that the standard approach yields 3 spurious species-species interactions for each true interaction and misses 60% of the true interactions in the human microbiome data, and, as predicted, most of the erroneous links are found in the samples with the lowest diversity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Tools and Models for Integrating Multiple Cellular Networks

In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novel algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed CRIT for correlation analysis in systems biology [5]. For Aim 3, we have further investigated the scaling relationship that the number of Transcription Factors (TFs) in a genome is proportional to the square of the total number of genes. We have extended the analysis from transcription factors to various classes of functional categories, and from individual categories to joint distribution [6]. By introducing a new analytical framework, we have generalized the original toolbox model to take into account of metabolic network with arbitrary network topology [7].

09 BIOMASS FUELS↗

NASA NTRS1989

Use of near infrared correlation spectroscopy for quantitation of surface iron, absorbed water and stored electronic energy in a suite of Mars soil analog materials

A number of questions concerning the surface mineralogy and the history of water on Mars remain unresolved using the Viking analyses and Earth-based telescopic data. Identification and quantitation of iron-bearing clays on Mars would elucidate these outstanding issues. Near infrared correlation analysis, a method typically applied to qualitative and quantitative analysis of individual constituents of multicomponent mixtures, is adapted here to selection of distinctive features of a small, highly homologous series of Fe/Ca-exchanged montmorillonites and several kalinites. Independently determined measures of surface iron, relative humidity and stored electronic energy were used as constituent data for linear regression of the constituent vs. reflectance data throughout the spectral region 0.68 to 2.5 micrometers. High correlations were found in appropriate regions for all three constituents, though that with stored energy is still considered tenuous. Quantitation was improved using 1st and 2nd derivative spectra. High resolution data over a broad spectral range would be required to quantitatively identify iron-bearing clays by remotely sensed reflectance.

Coyne, Lelia M.↗

DOE OSTI2018

Deep Data Analytics in Structural and Functional Imaging of Nanoscale Materials

Recent advances in scanning probe microscopy and scanning transmission electron microscopy have opened unprecedented opportunities in probing the materials structural parameters and electronic properties in real space on a picometre-scale. At the same time, the ability of modern day microscopes to quickly produce large, high-resolution datasets has created a challenge for rapid physics-guided analysis of data that typically contain several hundreds to several thousand atomic or molecular units per image. Here it is demonstrated how the advanced statistical analysis and machine learning techniques can be used for extracting relevant physical and chemical information from microscope data on multiple functional materials. Specifically, the following three case studies are discussed (i) application of a combination of convolutional neural network and Markov model for analyzing positional and orientational order in molecular self-assembly; (ii) a combination of sliding window fast Fourier transform, Pearson correlation matrix and canonical correlation analysis methods to study the relationships between lattice distortions and electron scattering patterns in graphene; (iii) application of a non-negative matrix factorization with physics-based constraints and Moran’s analysis of spatial associations to extracting electronic responses linked to different types of structural domains from multi-modal imaging datasets on iron-based superconductors. The approaches demonstrated here are universal in nature and can be applied to a variety of microscopic measurements on different materials.

Ziatdinov, Maxim↗

DOE OSTI2022

Information content of the differences in the charge radii of mirror nuclei

Differences in the charge radii of mirror nuclei have been recently suggested to contain information on the slope of the symmetry energy L. To test this hypothesis, we perform statistical correlation analysis using quantified energy density functionals that are consistent with our previous knowledge on global nuclear observables such as binding energies and charge radii. We conclude that the difference in charge radii between a mirror pair, $ΔR$$^{mir}_{ch}$, is an inferior isovector indicator compared to other observables, such at the neutron skin or electric dipole polarizability α D . In particular, this quantity correlates poorly with both the neutron skin and L. Here, we demonstrate that $ΔR$$^{mir}_{ch}$ is influenced by pairing correlations in the presence of low-lying proton continuum in the proton-rich mirror-partner nucleus. Considering the large theoretical uncertainties on $ΔR$$^{mir}_{ch}$, we conclude that the precise data on mirror charge radii cannot provide a stringent constraint on L.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Finding the missing baryons with fast radio bursts and Sunyaev-Zeldovich maps

Almost a third of the cosmic baryons are “missing” at low redshifts, as they reside in the invisible warm-hot intergalactic medium (WHIM). The thermal Sunyaev-Zeldovich (tSZ) effect, which measures the line-of-sight integral of the plasma pressure, can potentially detect this WHIM, although its expected signal is hidden below the noise. Extragalactic dispersion measures (DMs)—obtained through observations of fast radio bursts (FRBs)—are excellent tracers of the WHIM, as they measure the column density of plasma, regardless of its temperature. Here we propose cross correlating DMs and tSZ maps as a new way to find and characterize the missing baryons in the WHIM. Our method relies on the precise (~ arcminute) angular localization of FRBs to assign each burst a DM and a y parameter. We forecast that the signal from the WHIM should be confidently detected in a cross-correlation analysis of ~10 4 FRBs, expected to be gathered in a year of operation of the upcoming CHIME and HIRAX radio arrays, confirming the recent tentative detections of filamentary WHIM. Using this technique, future CMB probes (which might lower the tSZ noise) could determine both the temperature of the WHIM and its evolution to within tens of percent. Overall, DM-tSZ cross correlations hold great promise for studying the baryons in the local Universe.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2001

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

Shen, Samuel S. P.↗