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DOE OSTI2022

The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)

Abstract. Classical numerical models for the global atmosphere, as used for numerical weather forecasting or climate research, have been developed for conventional central processing unit (CPU) architectures. This hinders the employment of such models on current top-performing supercomputers, which achieve their computing power with hybrid architectures, mostly using graphics processing units (GPUs). Thus also scientific applications of such models are restricted to the lesser computer power of CPUs. Here we present the development of a GPU-enabled version of the ICON atmosphere model (ICON-A), motivated by a research project on the quasi-biennial oscillation (QBO), a global-scale wind oscillation in the equatorial stratosphere that depends on a broad spectrum of atmospheric waves, which originates from tropical deep convection. Resolving the relevant scales, from a few kilometers to the size of the globe, is a formidable computational problem, which can only be realized now on top-performing supercomputers. This motivated porting ICON-A, in the specific configuration needed for the research project, in a first step to the GPU architecture of the Piz Daint computer at the Swiss National Supercomputing Centre and in a second step to the JUWELS Booster computer at the Forschungszentrum Jülich. On Piz Daint, the ported code achieves a single-node GPU vs. CPU speedup factor of 6.4 and allows for global experiments at a horizontal resolution of 5 km on 1024 computing nodes with 1 GPU per node with a turnover of 48 simulated days per day. On JUWELS Booster, the more modern hardware in combination with an upgraded code base allows for simulations at the same resolution on 128 computing nodes with 4 GPUs per node and a turnover of 133 simulated days per day. Additionally, the code still remains functional on CPUs, as is demonstrated by additional experiments on the Levante compute system at the German Climate Computing Center. While the application shows good weak scaling over the tested 16-fold increase in grid size and node count, making also higher resolved global simulations possible, the strong scaling on GPUs is relatively poor, which limits the options to increase turnover with more nodes. Initial experiments demonstrate that the ICON-A model can simulate downward-propagating QBO jets, which are driven by wave–mean flow interaction.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

ReclaimingSTEM: A healing-centered counterspace model for inclusive science communication and policy training

The dominant U.S. cultural norms shape science, technology, engineering, and math (STEM), and in turn, these norms shape science communication, further perpetuating oppressive systems. Despite being a core scientific skill, science communication research and practice lack inclusive training spaces that center marginalized identities. We address this need with a healing-centered counterspace grounded in the key principles of inclusive science communication: ReclaimingSTEM. ReclaimingSTEM is a science communication and science policy training space that centers the experiences, needs, and wants of people from marginalized communities. ReclaimingSTEM problematizes and expands the definitions of “what counts” as science communication. We organize ReclaimingSTEM with intentionality, emphasizing inclusion at every part of the process. Since initiating in 2018, five ReclaimingSTEM workshops have been held in multiple locations, both in-person and virtually, reaching more than 700 participants from all over the globe. In this paper, we share our model for ReclaimingSTEM, reflections of workshop participants and speakers, barriers faced during organizing, and recommendations for creating truly inclusive practices in science communication spaces.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Emergency department visits in California associated with wildfire PM 2.5 : differing risk across individuals and communities

The threats to human health from wildfires and wildfire smoke (WFS) in the United States (US) are increasing due to continued climate change. A growing body of literature has documented important adverse health effects of WFS exposure, but there is insufficient evidence regarding how risk related to WFS exposure varies across individual or community level characteristics. To address this evidence gap, we utilized a large nationwide database of healthcare utilization claims for emergency department (ED) visits in California across multiple wildfire seasons (May through November, 2012–2019) and quantified the health impacts of fine particulate matter <2.5 μm (PM 2.5 ) air pollution attributable to WFS, overall and among subgroups of the population. We aggregated daily counts of ED visits to the level of the Zip Code Tabulation Area (ZCTA) and used a time-stratified case-crossover design and distributed lag non-linear models to estimate the association between WFS and relative risk of ED visits. We further assessed how the association with WFS varied across subgroups defined by age, race, social vulnerability, and residential air conditioning (AC) prevalence. Over a 7 day period, PM 2.5 from WFS was associated with elevated risk of ED visits for all causes (1.04% (0.32%, 1.71%)), non-accidental causes (2.93% (2.16%, 3.70%)), and respiratory disease (15.17% (12.86%, 17.52%)), but not with ED visits for cardiovascular diseases (1.06% (–1.88%, 4.08%)). Analysis across subgroups revealed potential differences in susceptibility by age, race, and AC prevalence, but not across subgroups defined by ZCTA-level Social Vulnerability Index scores. These results suggest that PM 2.5 from WFS is associated with higher rates of all cause, non-accidental, and respiratory ED visits with important heterogeneity across certain subgroups. Notably, lower availability of residential AC was associated with higher health risks related to wildfire activity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Dark energy survey year 3 results: likelihood-free, simulation-based w CDM inference with neural compression of weak-lensing map statistics

We present simulation-based cosmological wcold dark matter (wCDM) inference using dark energy survey year 3 weak-lensing maps, via neural data compression of weak-lensing map summary statistics: power spectra, peak counts, and direct map-level compression/inference with convolutional neural networks (CNN). Using simulation-based inference, also known as likelihood-free or implicit inference, we use forward-modelled mock data to estimate posterior probability distributions of unknown parameters. This approach allows all statistical assumptions and uncertainties to be propagated through the forward-modelled mock data; these include sky masks, non-Gaussian shape noise, shape measurement bias, source galaxy clustering, photometric redshift uncertainty, intrinsic galaxy alignments, non-Gaussian density fields, neutrinos, and non-linear summary statistics. We include a series of tests to validate our inference results. This paper also describes the Gower Street simulation suite: 791 full-sky pkdgrav3 dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock dark energy survey lensing data sets. For wCDM inference, for which we allow –1 < w < –$\frac{1}{3}$⁠, our most constraining result uses power spectra combined with map-level (CNN) inference. Using gravitational lensing data only, this map-level combination gives Ω m = 0.283$^{+0.020}_{–0.027}$⁠, S 8 = 0.804$^{+0.025}_{–0.017⁠}$, and w < –0.80 (with a 68 per cent credible interval); compared to the power spectrum inference, this is more than a factor of two improvement in dark energy parameter (Ω⁠ DE , w⁠) precision.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Neutron multiplicity counting: Confidence intervals for reconstruction parameters

From nuclear materials accountability to homeland security, the need for improved nuclear material detection, assay, and authentication has grown over the past decades. Starting in the 1940s, neutron multiplicity counting techniques have enabled quantitative evaluation of masses and multiplications of fissile materials. In this paper, we propose a new method to compute uncertainties on these parameters using a model-based sequential Bayesian processor, resulting in credible regions in the fissile material mass and multiplication space. These uncertainties will enable us to evaluate quantitatively proposed improvements to the theoretical fission chain model. Additionally, because the processor can calculate uncertainties in real time, it is a useful tool in applications such as portal monitoring: monitoring can stop as soon as a preset confidence of non-threat is reached.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

Star-forming Filament Models

New models of star-forming filamentary clouds are presented in order to quantify their properties and to predict their evolution. These 2D axisymmetric models describe filaments that have no core, one low-mass core, and one cluster-forming core. They are based on Plummer-like cylinders and spheroids that are bounded by a constant-density surface of finite extent. In contrast to 1D Plummer-like models, they have specific values of length and mass, they approximate observed column density maps, and their distributions of column density ( N -pdfs) are pole-free. Each model can estimate the star-forming potential of a core-filament system by identifying the zone of gas dense enough to form low-mass stars and by counting the number of enclosed thermal Jeans masses. This analysis suggests that the Musca central filament may be near the start of its star-forming life, with enough dense gas to make its first ∼3 protostars, while the Coronet filament is near the midpoint of its star formation, with enough dense gas to add ∼8 protostars to its ∼20 known stars. In contrast, L43 appears to be near the end of its star-forming life, since it lacks enough dense gas to add any new protostars to the two young stellar objectsalready known.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1980

X-ray studies of quasars and active galaxies with the Einstein Observatory

Preliminary results of the first six months of an X-ray survey of active galaxies and quasars performed with the imaging proportional counter on board the Einstein Observatory are presented. Consideration is given to detections of Seyfert galaxies, N galaxies, BL Lac objects and quasars, and properties of selected representative objects are discussed in detail. The statistical properties, including class averages and correlation coefficients, of the various X-ray active galaxies are calculated in an attempt to determine the relation of X-ray properties to the similarities and differences between the various classes of galaxies. Evidence is obtained for a continuity of high-energy behavior among all active galaxies, and it is noted that they all exhibit flux variability, often on a short time scale. The soft X-ray emission can be explained in terms of the synchrotron self-Compton model, or alternatively by thermal emission from hot gas. A significant correlation is obtained between the X-ray and optical fluxes for all objects considered, indicating that optical quasar counts may be used to infer the contribution of quasars to the diffuse X-ray background.

Ku, W. H.-M.↗

NASA NTRS1993

Supporting research and technology activities in the preparation of a three-dimensional map of the infrared sky

The final report for the period 15 Mar. 1986 to 31 Mar. 1993 for the Cooperative Agreement is presented. The purpose of this Cooperative Agreement was to collaborate with NASA civil servant and contractor personnel, and other Institute personnel in a project to use all available cataloged astronomical infrared data to construct a detailed three dimensional model of the infrared sky. Areas of research included: IRAS colors of normal stars and the infrared excesses in Be stars; galactic structure; how to use the observed IRAS source counts as a function of position to deduce the physical structure of the galaxy; IRAS properties of metal-poor stars; IRAS database studies; and solar space exploration including projects such as the Space Station Gas-Grain Simulator and the Mars Rover/Sample Return Mission.

Tarter, Jill C.↗

NASA NTRS1993

Structure in gamma ray burst time profiles: Correlations with other observables

One of the current debates raging in the world of gamma-ray burst physics is whether the sources of these enigmatic bursts arise from a single or from multiple distributions. Several authors contend that the histograms of GRB observables imply the latter. The two most-likely candidate components are galactic and cosmological. For example, some researchers claim that a dip in the V/V max distribution is a result of such a two-component source distribution. Others have used a parameter called the 'burst variability' calculated by dividing the maximum count rate on the 64-msec timescale by that from the 1024-msec timescale to show that a correlation of this parameter with bursts brightness implies a two-component model. This method has met vigorous criticism. We have developed two parameters that measure the variability or structure in the time profiles of BATSE gamma-ray bursts. Both parameters ('structure' and 'spike height') are based on the statistics of 'runs up' and 'runs down.' In short, the structure parameter is the observed number of runs (at several lengths) minus the number expected in a chance distribution. The 'spike height' is the sum of all run heights minus the expected sum. These two are straight-forward to calculate, robust, and measure the variability over the complete profile--not just at the peak. We have applied this algorithm to the profiles of 156 GRB's. In this paper we present graphs of the two parameters as functions of the following: (1) burst duration, (2) burst hardness ratio, (3) V/V max, (4) source galactic longitude, and (5) source galactic latitude. We seek correlations as well as groupings in the data that might indicate a multi-component source distribution.

Lestrade, John Patrick↗

NASA NTRSDate not supplied

Spectral Mass-Gauging of Propellant Tanks

An overview of our recent results on the development of Spectral Mass-Gauging (SMG) technology for model-free gauging of propellants in microgravity applications will be presented. The technology is based on application a rigorous result from spectral theory – the Weyl’s Law – which relates the counting function of natural modes in a resonator with its volume. Development of the SMG includes theory of acoustic response of propellant tank, hardware and procedure characterization and optimization, development of data pre-processing approaches and software for automatic mode identification and counting. Main accomplishments in each field of the technology development will be presented. SMG has been tested recently in 1-g on a flight tank filled with water or LN2. We will present results of the tests and discuss their implications for the technology development. The presentation will conclude with a summary of the next steps in the technology maturation.

Mass-gauging↗

DOE OSTI2019

Expanded Use of ISOCS Characterization Techniques for WIPP Certification at the Idaho Clean-up Project - 19623

The Advanced Mixed Waste Treatment Project (AMWTP) has been retrieving, treating, characterizing, and shipping legacy Transuranic (TRU) waste for disposal since 2003 as part of the overall Idaho Cleanup Project (ICP) in support of the US Department of Energy. As the ICP has progressed, over 700 containers have been identified that cannot be successfully assayed using the current suite of non-destructive assay (NDA) instruments. To meet this challenge, Fluor Idaho, LLC, and Mirion Technologies (formerly Canberra Industries) have teamed to deploy the In-Situ Object Counting System (ISOCS) to supplement the current NDA capabilities. ISOCS has long been used in various radioactive waste management applications, but never has the ISOCS ability to perform intrinsic efficiency modeling of discrete waste containers been employed to characterize and certify TRU waste for disposal at the Waste Isolation Pilot Plant (WIPP), near Carlsbad, New Mexico. Since the primary disposal facility for this waste is the WIPP, the characterization processes for determining the quantity of radioactive material entrained in the waste are subject to WIPP Waste Acceptance Criteria (WAC) quality requirements and associated performance criteria. Until now, the Carlsbad Field Office (CBFO) WIPP-certified NDA equipment has utilized pre-defined efficiency calibrations for fixed geometries. However, due to the radioactive material content, activity levels, waste stream matrix, and/or the geometries of various size drums, boxes and other-odd-shaped containers or container integrity issues, it may not be suitable to characterize these containers with any of the existing WIPP-certified NDA equipment located at the AMWTP. Therefore, advanced technologies are needed to complete characterization of these problematic waste containers. The July 5, 2016 release of the WIPP WAC, DOE/WIPP-02-3122, Revision 8.0, Appendix A, 'Radioassay Requirements for Transuranic Waste,' was expanded to include several newer concepts such as American Society for Testing and Materials (ASTM) approved methods for efficiency-based calibrations and the use of mathematical computer modeling techniques for calibration. This change prompted AMWTP to pursue obtaining WIPP certification authority for expanded ISOCS techniques to deal with the remaining challenging waste containers and the development and implementation of Mirion's Figures of Merit (FOM) evaluations. These vital FOM evaluations enhance the ISOCS's modeling capabilities by optimizing the dynamic efficiency calibration for each object and reducing the assay's Total Measurement Uncertainty (TMU) budget. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Electronic health record analysis via deep poisson factor models

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activation of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2017

Spatiotemporal modeling of ecological and sociological predictors of West Nile virus in Suffolk County, NY, mosquitoes

Abstract Suffolk County, New York, is a locus for West Nile virus ( WNV ) infection in the American northeast that includes the majority of Long Island to the east of New York City. The county has a system of light and gravid traps used for mosquito collection and disease monitoring. In order to identify predictors of WNV incidence in mosquitoes and predict future occurrence of WNV , we have developed a spatiotemporal Bayesian model, beginning with over 40 ecological, meteorological, and built‐environment covariates. A mixed‐effects model including spatially and temporally correlated errors was fit to WNV surveillance data from 2008 to 2014 using the R package “R‐INLA,” which allows for Bayesian modeling using the stochastic partial differential equation ( SPDE ) approach. The integrated nested Laplace approximation ( INLA ) SPDE allows for simultaneous fitting of a temporal parameter and a spatial covariance, while incorporating a variety of likelihood functions and running in R statistical software on a home computer. We found that land cover classified as open water and woody wetlands had a negative association with WNV incidence in mosquitoes, and the count of septic systems was associated with an increase in WNV . Mean temperature at two‐week lag was associated with a strong positive impact, while mean precipitation at no lag and one‐week lag was associated with positive and negative impacts on WNV , respectively. Incorporation of spatiotemporal factors resulted in a marked increase in model goodness‐of‐fit. The predictive power of the model was evaluated on 2015 surveillance results, where the best model achieved a sensitivity of 80.9% and a specificity of 77.0%. The spatial covariate was mapped across the county, identifying a gradient of WNV prevalence increasing from east to west. The Bayesian spatiotemporal model improves upon previous approaches, and we recommend the INLA SPDE methodology as an efficient way to develop robust models from surveillance data to develop and enhance monitoring and control programs. Our study confirms previously found associations between weather conditions and WNV and suggests that wetland cover has a mitigating effect on WNV infection in mosquitoes, while high septic system density is associated with an increase in WNV infection.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Near-Body Mesh Adaption for Transitional Flows Using OVERFLOW

Accurate modeling of boundary-layer transition is an important aspect of developing greener air transport technologies. In that regard, transition models based on auxiliary transport equations offer a robust approach that is easily integrated into the Reynolds-averaged Navier-Stokes (RANS) solvers. Recent workshops under NATO and AIAA have identified the verification of transport-equations-based transition modeling as a critical aspect of reducing the scatter between the predictions of different CFD codes. Follow-on work has highlighted the need for highly dense grids to achieve an asymptotic convergence of transition related flow metrics. The present work examines the role of automatic near-body mesh adaptation capability in the NASA OVERFLOW CFD solver to enable verification studies in an efficient manner, and for establishing best practices for designing grids for the RANS-based transition models. A sensor function relevant to the Langtry-Menter \gamma-Re_{\theta t}\ transition model has been identified and used for error-based mesh adaptation for canonical configurations comprising a flat plate, and the S809 and NLR-7301 airfoils. The efficacy of the mesh adaptation approach is assessed for flow conditions involving multiple transition scenarios such as natural transition, separation-induced transition, and shock-induced transition. The results from this exploratory study indicate that the meshes adapted using the proposed sensor provide solutions that approach the references solutions obtained with uniformly refined hand-crafted meshes, in terms of the chosen metrics, and yield modest yet significant savings in grid count. We also highlight areas for improvement in the grid adaptation methodology within OVERFLOW.

CFD↗

DOE OSTI2017

One-point fluctuation analysis of the high-energy neutrino sky

We perform the first one-point fluctuation analysis of the high-energy neutrino sky. This method reveals itself to be especially suited to contemporary neutrino data, as it allows to study the properties of the astrophysical components of the high-energy flux detected by the IceCube telescope, even with low statistics and in the absence of point source detection. Besides the veto-passing atmospheric foregrounds, we adopt a simple model of the high-energy neutrino background by assuming two main extra-galactic components: star-forming galaxies and blazars. By leveraging multi-wavelength data from Herschel and Fermi , we predict the spectral and anisotropic probability distributions for their expected neutrino counts in IceCube. We find that star-forming galaxies are likely to remain a diffuse background due to the poor angular resolution of IceCube, and we determine an upper limit on the number of shower events that can reasonably be associated to blazars. We also find that upper limits on the contribution of blazars to the measured flux are unfavourably affected by the skewness of the blazar flux distribution. One-point event clustering and likelihood analyses of the IceCube HESE data suggest that this method has the potential to dramatically improve over more conventional model-based analyses, especially for the next generation of neutrino telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Discrete models of fluids: spatial averaging, closure and model reduction

We consider semidiscrete ODE models of single-phase fluids and two-fluid mixtures. In the presence of multiple fine-scale heterogeneities, the size of these ODE systems can be very large. Spatial averaging is then a useful tool for reducing computational complexity of the problem. The averages satisfy exact balance equations of mass, momentum, and energy. These equations do not form a satisfactory continuum model because evaluation of stress and heat flux requires solving the underlying ODEs. To produce continuum equations that can be simulated without resolving microscale dynamics, we recently proposed a closure method based on the use of regularized deconvolution. Here we continue the investigation of deconvolution closure with the long term objective of developing consistent computational upscaling for multiphase particle methods. The structure of the fine-scale particle solvers is reminiscent of molecular dynamics. For this reason we use nonlinear averaging introduced for atomistic systems by Noll, Hardy, and Murdoch-Bedeaux. We also consider a simpler linear averaging originally developed in large eddy simulation of turbulence. We present several simple but representative examples of spatially averaged ODEs, where the closure error can be analyzed. Based on this analysis we suggest a general strategy for reducing the relative error of approximate closure. For problems with periodic highly oscillatory material parameters we propose a spectral boosting technique that augments the standard deconvolution and helps to correctly account for dispersion effects. We also conduct several numerical experiments, one of which is a complete mesoscale simulation of a stratified two-fluid flow in a channel. In this simulation, the operation count per coarse time step scales sublinearly with the number of particles.

Multiscale modeling, discrete models, fluid flow↗

NASA NTRS1984

The Resonant Count Diagram and Solar g Mode Oscillations

Evidence is provided to support the hypothesis that, because of the particular frequency separations of the solar g modes, resonant three-wave interactions stimulate only a selected few g modes. A resonant count diagram was obtained by plotting the total number of possible resonant three-wave interactions or a given beat frequency against the inverse of the beat frequency (the beat period), within a given frequency tolerance. The 1 = 1, 2, 3, 4 g modes calculated by Christensen-Dalsgaard, Gough and Morgan (1979) for a standard model of the Sun were used. The diagram has a significant peak at 160 minutes as well as other peaks at longer periods. The g modes that Delache and Scherrer (1983) tentatively identified from the Crimea-Stanford data were also plotted. These modes were found to correspond with the other peaks in the diagram. This coincidence between the observed g modes and the peaks in the resonant count diagram suggest that the observed g modes do owe their observability to resonant three-wave interactions.

Guenther, D. B.↗

NASA NTRS2011

Corrigendum to "Microstructural Characterization of Metal Foams: An Examination of the Applicability of the Theoretical Models for Modeling Foams"

Establishing the geometry of foam cells is useful in developing microstructure-based acoustic and structural models. Since experimental data on the geometry of the foam cells are limited, most modeling efforts use an idealized three-dimensional, space-filling Kelvin tetrakaidecahedron. The validity of this assumption is investigated in the present paper. Several FeCrAlY foams with relative densities varying between 3 and 15% and cells per mm (c.p.mm.) varying between 0.2 and 3.9 c.p.mm. were microstructurally evaluated. The number of edges per face for each foam specimen was counted by approximating the cell faces by regular polygons, where the number of cell faces measured varied between 207 and 745. The present observations revealed that 50-57% of the cell faces were pentagonal while 24-28% were quadrilateral and 15-22% were hexagonal. The present measurements are shown to be in excellent agreement with literature data. It is demonstrated that the Kelvin model, as well as other proposed theoretical models, cannot accurately describe the FeCrAlY foam cell structure. Instead, it is suggested that the ideal foam cell geometry consists of 11 faces with 3 quadrilateral, 6 pentagonal faces and 2 hexagonal faces consistent with the 3-6-2 Matzke cell

Raj. Sai V.↗