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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cosmic shear cosmology beyond two-point statistics: a combined peak count and correlation function analysis of DES-Y1

ABSTRACT We constrain cosmological parameters from a joint cosmic shear analysis of peak-counts and the two-point shear correlation functions, as measured from the Dark Energy Survey (DES-Y1). We find the structure growth parameter $S_8\equiv \sigma _8\sqrt{\Omega _{\rm m}/0.3} = 0.766^{+0.033}_{-0.038}$ which, at 4.8 per cent precision, provides one of the tightest constraints on S8 from the DES-Y1 weak lensing data. In our simulation-based method we determine the expected DES-Y1 peak-count signal for a range of cosmologies sampled in four w cold dark matter parameters (Ωm, σ8, h, w0). We also determine the joint covariance matrix with over 1000 realizations at our fiducial cosmology. With mock DES-Y1 data we calibrate the impact of photometric redshift and shear calibration uncertainty on the peak-count, marginalizing over these uncertainties in our cosmological analysis. Using dedicated training samples we show that our measurements are unaffected by mass resolution limits in the simulation, and that our constraints are robust against uncertainty in the effect of baryon feedback. Accurate modelling for the impact of intrinsic alignments on the tomographic peak-count remains a challenge, currently limiting our exploitation of cross-correlated peak counts between high and low redshift bins. We demonstrate that once calibrated, a fully tomographic joint peak-count and correlation functions analysis has the potential to reach a 3 per cent precision on S8 for DES-Y1. Our methodology can be adopted to model any statistic that is sensitive to the non-Gaussian information encoded in the shear field. In order to accelerate the development of these beyond-two-point cosmic shear studies, our simulations are made available to the community upon request.

Harnois-Déraps, Joachim↗
DOE OSTI2015

Subspace-based Inverse Uncertainty Quantification for Nuclear Data Assessment

Safety analysis and design optimization depend on the accurate prediction of various reactor attributes. Predictions can be enhanced by reducing the uncertainty associated with the attributes of interest. An inverse problem can be defined and solved to assess the sources of uncertainty, and experimental effort can be subsequently directed to further improve the uncertainty associated with these sources. In this work a subspace-based algorithm for inverse sensitivity/uncertainty quantification (IS/UQ) has been developed to enable analysts account for all sources of nuclear data uncertainties in support of target accuracy assessment-type analysis. An approximate analytical solution of the optimization problem is used to guide the search for the dominant uncertainty subspace. By limiting the search to a subspace, the degrees of freedom available for the optimization search are significantly reduced. A quarter PWR fuel assembly is modeled and the accuracy of the multiplication factor and the fission reaction rate are used as reactor attributes whose uncertainties are to be reduced. Numerical experiments are used to demonstrate the computational efficiency of the proposed algorithm. Our ongoing work is focusing on extending the proposed algorithm to account for various forms of feedback, e.g., thermal-hydraulics and depletion effects.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2011

On the Causes and Dynamics of the Early Twentieth Century North American Pluvial

The early twentieth century North American pluvial (1905-1917) was one of the most extreme wet periods of the last five hundred years and directly led to overly generous water allotments in the water-limited American West. Here we examine the causes and dynamics of the pluvial event using a combination of observation-based data sets and general circulation model (GCM) experiments. The character of the moisture surpluses during the pluvial differed by region, alternately driven by increased precipitation (the Southwest), low evaporation from cool temperatures (the Central Plains), or a combination of the two (the Pacific Northwest). Cool temperature anomalies covered much of the west and persisted through most months, part of a globally extensive period of cooler land and sea surface temperatures (SST). Circulation during boreal winter favored increased moisture import and precipitation in the southwest, while other regions and seasons were characterized by near normal or reduced precipitation. Anomalies in the mean circulation, precipitation, and SST fields are partially consistent with the relatively weak El Nino forcing during the pluvial, and also reflect the impact of positive departures in the Arctic Oscillation that occurred in ten of the thirteen pluvial winters. Differences between the reanalysis dataset, an independent statistical drought model, and GCM simulations highlight some of the remaining uncertainties in understanding the full extent of SST forcing of North American hydroclimatic variability.

Cook, Benjamin I.↗
NASA NTRS1995

Comment on 'The Global Resurfacing of Venus' by R. G. Strom, G.G. Schaber, and D.D. Dawson

The distribution of impact craters on Venus has been the subject of a great deal of analysis since the return of Magellan data. Phillips el al. (1992) performed Monte Carlo two-dimensional (2-D) modeling of the areal distribution of craters, and the results of that exercise allowed a restricted, but still quite large, range of possible planetary resurfacing histories, including the possibility that the crater, were emplaced on a geologically inactive planet. However, the nonrandom distribution of embayed and deformed craters (Phillips el al., 1992), the hypsometric distribution of craters (Herrick and Phillips, 1994), the varied degradation states of craters (Izenberg et al., 1994), their nonrandom distribution with different geologic terrain types (Namiki and Solomon, 1994; Price et al, 1994), and three-dimensional resurfacing modeling (Bullock el al., 1993) all seem to argue against that particular possibility. In contrast, Strom el al. (1994) have collected a refined and more comprehensive data set of impact features, and they input these data into more sophisticated 2-D Monte Carlo modeling and statistical analyses of the areal distribution of craters, the hypsometric distribution of craters, and the number of embayed craters. They concluded that 'Venus experienced a global resurfacing event about 300 m.y. ago followed by a dramatic reduction of volcanism and tectonism. This global resurfacing event ended abruptly (less than 10 m.y.). The present crater population has accumulated since then and remains largely intact . . . only about 4%-6% of the planet has been volcanically resurfaced since the global event . . .' If these conclusions are well-founded, this work certainly represents a significant advancement in restricting tile number of plausible resurfacing histories for the planet. If Strom et al. (1994) are correct, it would also mean that all of the other aforementioned works are in error to various degrees, or at least represent overzealous interpretation of the data. However, we have identified apparent flaws in the observations, modeling, and interpretations presented by Strom el al. (1994) that lead us to question whether their conclusions are warranted. We limit our comments to three areas of their analysis: (1) observations pertaining to the number and area of disrupted and pristine craters and crater-related features, (2) modeling of the areal and elevation distribution of craters, and (3) interpretations of resurfacing models.

Herrick, Robert R.↗
DOE OSTI2026

Model Parameter Development for Complex Materials: Species-Specific Diffusion Barriers in 316 Stainless Steel from Systematic DFT Calculations

Vacancy-mediated diffusion barriers in 316 stainless steel have been systematically calculated using density functional theory to provide essential parameters for mesoscale microstructure evolution models. A statistical sampling approach employing 210 nudged elastic band calculations across multiple special quasi-random structures captures the effects of local chemical environments in this concentrated alloy. The computational methodology addresses challenges specific to chemically disordered systems, including proper magnetic treatment throughout multi-step calculations and validation against experimental structural properties. The calculated activation barriers reveal clear species-dependent diffusion behavior with the hierarchy Ni >> Fe ˜ Cr >> Mo. Nickel exhibits the highest barriers (0.74–1.31 eV, mean 1.045 eV), confirming its role as the slowest-diffusing major component. Iron and chromium show similar moderate barriers averaging 0.587 eV and 0.522 eV, respectively. Remarkably, molybdenum demonstrates exceptionally low barriers (0.12–0.28 eV, mean 0.194 eV), suggesting much higher mobility than previously recognized and potentially significant implications for precipitation kinetics and microstructure evolution. The barrier ranges remain consistent across different 316 SS compositions, supporting parameter transferability for modeling applications. The overall mean barrier of 0.64 eV provides a practical approximation for phase field simulations, while species-specific values enable detailed treatments of diffusion-controlled processes. This systematic approach establishes a validated framework for generating diffusion parameters in other concentrated alloys where experimental data are limited, while providing the first systematic set of species-specific barriers for predictive modeling of 316 stainless steel microstructure evolution.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Periodicity in extinction and the problem of catastrophism in the history of life

The hypothesis that extinction events have recurred periodically over the last quarter billion years is greatly strengthened by new data on the stratigraphic ranges of marine animal genera. In the interval from the Permian to Recent, these data encompass some 13,000 generic extinctions, providing a more sensitive indicator of species-level extinctions than previously used familial data. Extinction time series computed from the generic data display nine strong peaks that are nearly uniformly spaced at 26 Ma intervals over the last 270 Ma. Most of these peaks correspond to extinction events recognized in more detailed, if limited, biostratigraphic studies. These new data weaken or negate most arguments against periodicity, which have involved criticisms of the taxonomic data base, sampling intervals, chronometric time scales, and statistical methods used in previous analyses. The criticisms are reviewed in some detail and various new calculations and simulations, including one assessing the effects of paraphyletic taxa, are presented. Although the new data strengthen the case for periodicity, they offer little new insight into the deriving mechanism behind the pattern. However, they do suggest that many of the periodic events may not have been catastrophic, occurring instead over several stratigraphic stages or substages.

NASA Discipline Number 52-40↗
DOE OSTI2017

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions is examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and datasets were examined. A penalized logistic regression model fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at different time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. The methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.

Bramer, L. M.↗
DOE OSTI2013

Variogram Identification Aided by a Structural Framework for Improved Geometric Modeling of Faulted Reservoirs: Jeffara Basin, Southeastern Tunisia

This article describes a proposed work-sequence to generate accurate reservoir-architecture models, describing the geometry of bounding surfaces (i.e., fault locations and extents), of a structurally complex geologic setting in the Jeffara Basin (South East Tunisia) by means of geostatistical modeling. This uses the variogram as the main tool to measure the spatial variability of the studied geologic medium before making any estimation or simulation. However, it is not always easy to fit complex experimental variograms to theoretical models. Thus, our primary purpose was to establish a relationship between the geology and the components of the variograms to fit a mathematically consistent and geologically interpretable variogram model for improved predictions of surface geometries. We used a three-step approach based on available well data and seismic information. First, we determined the structural framework: a seismo-tectonic data analysis was carried out, and we showed that the study area is cut mainly by NW-SE-trending normal faults, which were classified according to geometric criteria (strike, throw magnitude, dip, and dip direction). We showed that these normal faults are at the origin of a large-scale trend structure (surfaces tilted toward the north-east). At a smaller scale, the normal faults create a distinct compartmentalization of the reservoirs. Then, a model of the reservoir system architecture was built by geostatistical methods. An efficient methodology was developed, to estimate the bounding faulted surfaces of the reservoir units. Emphasis was placed on (i) elaborating a methodology for variogram interpretation and modeling, whereby the importance of each variogram component is assessed in terms of probably geologic factor controlling the behavior of each structure; (ii) integrating the relevant fault characteristics, which were deduced from the previous fault classification analysis, as constraints in the kriging estimation of bounding surfaces to best reflect the geologic structure of the study area. Finally, the estimated bounding surfaces together with seismic data and variogram interpretations were used to obtain further insights into the tectonic evolution of the study area that has induced the current reservoirs configuration.

58 GEOSCIENCES↗
DOE OSTI2019

Mapping Aedes aegypti (Diptera: Culicidae) and Aedes albopictus Vector Mosquito Distribution in Brownsville, TX

Abstract Aedes mosquitoes are vectors of several emerging diseases and are spreading worldwide. We investigated the spatiotemporal dynamics of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) mosquito trap captures in Brownsville, TX, using high-resolution land cover, socioeconomic, and meteorological data. We modeled mosquito trap counts using a Bayesian hierarchical mixed-effects model with spatially correlated residuals. The models indicated an inverse relationship between temperature and mosquito trap counts for both species, which may be due to the hot and arid climate of southern Texas. The temporal trend in mosquito populations indicated Ae. aegypti populations peaking in the late spring and Ae. albopictus reaching a maximum in winter. Our results indicated that seasonal weather variation, vegetation height, human population, and land cover determine which of the two Aedes species will predominate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Computational Workflow of Elucidating Viral Impact on Mediating Microbial Response to In-situ Experimental Warming: Bridging microbial modeling to carbon and mineral modeling

Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

An architecture for a brain-image database

The widespread availability of methods for noninvasive assessment of brain structure has enabled researchers to investigate neuroimaging correlates of normal aging, cerebrovascular disease, and other processes; we designate such studies as image-based clinical trials (IBCTs). We propose an architecture for a brain-image database, which integrates image processing and statistical operators, and thus supports the implementation and analysis of IBCTs. The implementation of this architecture is described and results from the analysis of image and clinical data from two IBCTs are presented. We expect that systems such as this will play a central role in the management and analysis of complex research data sets.

NASA Discipline Neuroscience↗
NASA NTRS1994

Radiative interactions in multi-dimensional chemically reacting flows using Monte Carlo simulations

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical narrow band model with an exponential-tailed inverse intensity distribution. The amount and transfer of the emitted radiative energy in a finite volume element within a medium are considered in an exact manner. The spectral correlation between transmittances of two different segments of the same path in a medium makes the statistical relationship different from the conventional relationship, which only provides the non-correlated results for nongray methods is discussed. Validation of the Monte Carlo formulations is conducted by comparing results of this method of other solutions. In order to further establish the validity of the MCM, a relatively simple problem of radiative interactions in laminar parallel plate flows is considered. One-dimensional correlated Monte Carlo formulations are applied to investigate radiative heat transfer. The nongray Monte Carlo solutions are also obtained for the same problem and they also essentially match the available analytical solutions. the exact correlated and non-correlated Monte Carlo formulations are very complicated for multi-dimensional systems. However, by introducing the assumption of an infinitesimal volume element, the approximate correlated and non-correlated formulations are obtained which are much simpler than the exact formulations. Consideration of different problems and comparison of different solutions reveal that the approximate and exact correlated solutions agree very well, and so do the approximate and exact non-correlated solutions. However, the two non-correlated solutions have no physical meaning because they significantly differ from the correlated solutions. An accurate prediction of radiative heat transfer in any nongray and multi-dimensional system is possible by using the approximate correlated formulations. Radiative interactions are investigated in chemically reacting compressible flows of premixed hydrogen and air in an expanding nozzle. The governing equations are based on the fully elliptic Navier-Stokes equations. Chemical reaction mechanisms were described by a finite rate chemistry model. The correlated Monte Carlo method developed earlier was employed to simulate multi-dimensional radiative heat transfer. Results obtained demonstrate that radiative effects on the flowfield are minimal but radiative effects on the wall heat transfer are significant. Extensive parametric studies are conducted to investigate the effects of equivalence ratio, wall temperature, inlet flow temperature, and nozzle size on the radiative and conductive wall fluxes.

Liu, Jiwen↗
DOE OSTI2015

Uncertainty quantification and propagation in nuclear density functional theory

Nuclear density functional theory (DFT) is one of the main theoretical tools used to study the properties of heavy and superheavy elements, or to describe the structure of nuclei far from stability. While on-going eff orts seek to better root nuclear DFT in the theory of nuclear forces, energy functionals remain semi-phenomenological constructions that depend on a set of parameters adjusted to experimental data in fi nite nuclei. In this study, we review recent eff orts to quantify the related uncertainties, and propagate them to model predictions. In particular, we cover the topics of parameter estimation for inverse problems, statistical analysis of model uncertainties and Bayesian inference methods. Illustrative examples are taken from the literature.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Numerical and experimental characterization of twin transmission across grain boundaries along the forward and lateral directions

Pervasive deformation twinning and transmission events across grain boundaries (GBs) affect the strength and failure of hexagonal close-packed (HCP) magnesium. A three-dimensional twin can transmit along the twinning shear direction, (forward), and along the direction perpendicular to both the twinning plane normal and the shear direction, (lateral). For the first time, phase-field calculations and electron backscatter diffraction (EBSD)-based statistical analysis are combined to investigate the effect of the twinned grain boundary characteristics on twin transmission (TT) along the forward and lateral directions. This combined analysis reveals that TT propensity decreases with increasing misorientation angle across the GB for both forward and lateral directions. Also, the TT is more favorable along the lateral than along the forward direction. Twin transmission seems harder across GBs with a misorientation axis closer to the twin -direction than the other directions ( and ). Further, the PF calculations reveal that, at the onset of a transmission process, the crystallography tends to be preserved in the case of lateral transmission, whereas, in the forward transmission case, the transmitted twin punches straight through the GBs and its morphology prevails. Additionally, the EBSD analysis finds that pure forward and lateral transmissions do not occur often, yet reveals a preference for lateral propagation consistent with PF simulations. Further, the local twin transmission configurations observed in the actual material do not correspond to pure tilt or twist GBs, which are most commonly considered as model cases.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Environment-assisted non-Markovian speedup dynamics control

For the damped Jaynes–Cummings model in the weak system–environment coupling regime, a scheme to manipulate the non-Markovian dynamics has been previously proposed in the controllable environment. We here mainly focus on the two-Lorentzian model and the band-gap model, which are composed by adding a new Lorentzian spectrum to the original single-Lorentzian spectrum. By manipulating the parameters of the new added Lorentzian spectrum, i.e., changing the weights of the two Lorentzians, and tuning the spectral width of the new second Lorentzian, the dynamical crossover from Markovian to non-Markovian is achieved in the weak system–environment coupling regime. In addition, according to the controllable non-Markovian dynamics behavior, the roles of the parameters of the environment on the speedup evolution of the system are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Extracting model-independent nuclear level densities away from stability

The nuclear level density (NLD) is a fundamental measure of the complex structure of atomic nuclei at relatively high energies. Here, in this study, we present the first model-independent measurement of the absolute partial NLD for a short-lived nucleus. For this purpose we adapt the recently introduced “shape method” for β-decay experiments, providing the shape of the γ-ray strength function for exotic nuclei. In this work, we show that combining the shape method with the β-Oslo technique allows for the extraction of the NLD of the populated states without the need for theoretical input. This development opens the way for the extraction of experimental NLDs far from stability with major implications in astrophysical and other applications. We benchmark our approach using data for the stable 76 Ge nucleus, finding excellent agreement with previous experimental results. In addition, we present new experimental data and determine the absolute partial level density for the short-lived 88 Kr nucleus. Our results suggest a fivefold increase in the NLD for the case of 88 Kr, compared to the recommended values from semimicroscopic Hartree-Fock Bogoliubov calculations recommended by the RIPL3 nuclear data library. However, our results are in good agreement with other semimicroscopic level density models. We demonstrate the impact of our method on the 87 Kr(n, γ) neutron capture rate and show that our experimental uncertainties for NLDs fulfill the requirements needed for astrophysical calculations predicting r-process abundances.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Spin cutoff factor and level density for Ni 59 from an analysis of compound nuclear reactions

The spin cutoff parameter for 59 Ni has been studied from different types of experimental data, including neutron angular distributions from the 56 Fe(α,n) 59 Ni reaction, spin of discrete levels, the level density from the proton evaporation spectrum of the 54 Fe( 6 Li,p) 59 Ni reaction and neutron resonance spacing. Experimental data points were compared with calculations using models widely used in literature. It was found that the available empirical models overestimate data points in the energy region below the neutron separation energy, while microscopic calculations which take into account pairing correlations within Hartree-Fock +Bardeen-Cooper-Schrieffer approach are consistent with data. As a result, it confirmed earlier findings that pairing correlations play an important role and need to be taken into account when the spin cutoff parameter is calculated below the neutron separation energy.

(a,n) reaction↗
NASA NTRS2020

Using Two-Stream Theory to Capture Fluctuations of Satellite-Perceived TOA SW Radiances Reflected from Clouds Over Ocean

Shortwave (SW) fluxes estimated from broadband radiometry rely on empirically gathered and hemispherically resolved fields of outgoing top-of-atmosphere (TOA) radiances. This study aims to provide more accurate and precise fields of TOA SW radiances reflected from clouds over ocean by introducing a novel semiphysical model predicting radiances per narrow sun-observer geometry. This model was statistically trained using CERES-measured radiances paired with MODIS-retrieved cloud parameters as well as reanalysis-based geophysical parameters. By using radiative transfer approximations as a framework to ingest the above parameters, the new approach incorporates cloud-top effective radius and above-cloud water vapor in addition to traditionally used cloud optical depth, cloud fraction, cloud phase, and surface wind speed. A two-stream cloud albedo – serving to statistically incorporate cloud optical thickness and cloud-top effective radius – and Cox–Munk ocean reflectance were used to describe an albedo over each CERES footprint. Effective-radius-dependent asymmetry parameters were obtained empirically and separately for each viewing-illumination geometry. A simple equation of radiative transfer, with this albedo and attenuating above-cloud water vapor as inputs, was used in its log-linear form to allow for statistical optimization. We identified the two-stream functional form that minimized radiance residuals calculated against CERES observations and outperformed the state-of-the-art approach for most observer geometries outside the sun-glint and solar zenith angles between 20 and 70∘, reducing the median SD of radiance residuals per solar geometry by up to 13.2 % for liquid clouds, 1.9 % for ice clouds, and 35.8 % for footprints containing both cloud phases. Geometries affected by sun glint (constituting between 10 % and 1 % of the discretized upward hemisphere for solar zenith angles of 20 and 70∘, respectively), however, often showed weaker performance when handled with the new approach and had increased residuals by as much as 60 % compared to the state-of-the-art approach. Overall, uncertainties were reduced for liquid-phase and mixed-phase footprints by 5.76 % and 10.81 %, respectively, while uncertainties for ice-phase footprints increased by 0.34 %. Tested for a variety of scenes, we further demonstrated the plausibility of scene-wise predicted radiance fields. This new approach may prove useful when employed in angular distribution models and may result in improved flux estimates, in particular dealing with clouds characterized by small or large droplet/crystal sizes.

Two- stream theory↗

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