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DOE OSTI2025

A Large-Eddy Simulation Study in WRF on Wind over Broadband Waves of Different Directions and Spreading Widths

We use the Weather Research and Forecasting (WRF) Model coupled with moving waves to conduct large-eddy simulations (LESs) of wind over broadband waves with different propagating directions and spreading widths. Our results show that wind-opposing waves can double the form drag, and the wave propagating direction affects the mean wind velocity, velocity variances, and pressure stress. On the other hand, waves with wider spread tend to reduce the form drag in the streamwise direction. Results further indicate that the wave direction can impact the bulk drag coefficient by as much as 25%, while the wave directional spreading width can change it by 5%. Based on our wave-phase-resolved simulations, we demonstrate that the parameterization of sea surface roughness is significantly influenced by the direction of wave propagation relative to the wind, a factor that the commonly used Charnock relation does not account for.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Afterglow Polarization from Off-axis Gamma-Ray Burst Jets

As we further our studies on gamma-ray bursts (GRBs), via both theoretical models and observational tools, more and more options begin to open for exploration of its physical properties. As GRBs are transient events primarily dominated by synchrotron radiation, it is expected that the synchrotron photons emitted by GRBs should present some degree of polarization throughout the evolution of the burst. Whereas observing this polarization can still be challenging due to the constraints on observational tools, especially for short GRBs, it is paramount that the groundwork is laid for the day we have abundant data. In this work, we present a polarization model linked with an off-axis spreading top-hat jet synchrotron scenario in a stratified environment with a density profile n(r) ∝ r ⁻k . We present this model's expected temporal polarization evolution for a realistic set of afterglow parameters constrained within the values observed in the GRB literature for four degrees of stratification k = 0, 1, 1.5, and 2 and two magnetic field configurations with high extreme anisotropy. We apply this model and predict polarization from a set of GRBs exhibiting off-axis afterglow emission. In particular, for GRB 170817A, we use the available polarimetric upper limits to rule out the possibility of an extremely anisotropic configuration for the magnetic field.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Optimal deployment of resources for maximizing impact in spreading processes

Significance Spreading processes play an increasingly important role in marketing, opinion setting, and epidemic modeling. Most existing algorithms for optimal resource allocation in spreading processes are based on topological characteristics of the underlying network and aim to maximize impact at infinite time. Clearly, realistic and efficient real-time allocation policies should consider both network properties and details of the dynamics; additionally, control may be applied only to a restricted set of accessible nodes, and impact should be maximized in a limited time window. We introduce a probabilistic targeting framework that incorporates the dynamics and encompasses previously considered optimization formulations. It is based on a scalable dynamic message-passing approach that allows for the solution of large real-world network instances.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Deep Interactive Learning with Sharkzor

Sharkzor is a web application for machine-learning assisted image sort and summary. Deep learning algorithms are leveraged to infer, augment, and automate the user’s mental model. Initially, images uploaded by the user are spread out on a canvas. The user then interacts with the images to impute their mental model into the applications algorithmic underpinnings. Methods of interaction within Sharkzor’s user interface and user experience support three primary user tasks: triage, organize and automate. The user triages the large pile of overlapping images by moving images of interest into proximity. The user then organizes said images into meaningful groups. After interacting with the images and groups, deep learning helps to automate the user’s interactions. The loop of interaction, automation, and response by the user allows the system to quickly make sense of large amounts of data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Investigation of reactivity differences in cylinder arrays using various fill geometries with constant mass

The factors affecting criticality safety are well understood by the nuclear engineering industry. Array configurations present multiple challenges to the industry due to the competing effects that are present in array systems - most notably interaction/spacing, moderation, and reflection. However, even the fissile mass geometry has been shown to complicate array systems. This attribute is also seen in filled UF{sub 6} cylinders, thus making it important to understand the reactivity in cylinder arrays. The process of filling UF{sub 6} cylinders results in non-uniform cylinder fill geometries. Due to the non-uniform fill, it becomes necessary to model a specific UF{sub 6} mass, in cylinder arrays, in different ways to ensure understanding of the reactivity of the system. Some of the ways to model the UF{sub 6} include: spreading the UF{sub 6} mass across the cylinder, all UF{sub 6} on the bottom of the cylinder, UF{sub 6} consolidated in the middle of the cylinder, and UF{sub 6} consolidated on the outside of the cylinder. Spreading the UF{sub 6} mass across the cylinder is accomplished by adjusting the UF{sub 6} density to achieve the given UF{sub 6} mass, whereas all the other scenarios use a fixed UF{sub 6} density with varying thicknesses to achieve the given UF{sub 6} mass. A different modeling approach, which helps to capture mixture effects, is to model the UF{sub 6} mass using the nominal UF{sub 6} density along with the void space for a given mass and distribute the mixture throughout the entire cylinder. This paper compares the reactivity of a cylinder array at a constant mass value using three different modeling techniques - completely filling the cylinder using a reduced UF{sub 6} density, filling the cylinder with nominal UF{sub 6} density and void space throughout the cylinder (same amount of void space as in the last technique), and all UF{sub 6} in the bottom of the cylinder (all void space on top of UF{sub 6}). The results demonstrate that completely filling the cylinder produces the most reactive UF{sub 6} cylinder array system. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

MSR Salt Spill Accident Testing Using Eutectic NaCl-UCl 3

Assessing the potential consequences of identified accident scenarios is an essential part of the licensing process for a new nuclear reactor and is achieved by using accident progression models. A likely accident scenario that will be evaluated by developers of molten salt reactors (MSRs) is a spill of radionuclide-bearing fuel salt onto the reactor containment floor (i.e., a salt spill accident). Models to determine the consequences of a molten salt spill accident need to be parameterized and validated using experimental data, but little experimental effort has been dedicated to fill these data gaps to date. Specifically, data is needed to enable model development for individual processes (e.g., spreading, heat transfer, corrosion, radionuclide vaporization, and aerosol generation) that quantifies the sensitivities towards the initial conditions of the spill, the ambient environment, and the features of the containment. In addition, integrated experiments that simulate salt spill accidents will need to be conducted to provide insight into coupled processes and data for model validation, but these experiments will require the use of proven methods to quantify the processes under evaluation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Cloud feedback mechanisms and their representation in global climate models

Cloud feedback—the change in top-of-atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO 2 forcing simulated by global climate models (GCMs). In this paper, we review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global-mean cloud feedback in GCMs results from three main effects: (1) rising free-tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high-latitude low cloud optical depth (a negative SW effect). These cloud responses simulated by GCMs are qualitatively supported by theory, high-resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper-tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large-scale subsidence, and lower-tropospheric stability on the boundary-layer moisture budget. High-latitude low cloud optical depth increases are dominated by phase changes in mixed-phase clouds. Finally, the causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Modeling of 10 GeV-1 TeV laser-plasma accelerators using Lorentz boosted simulations

Modeling of laser-plasma wakefield accelerators in an optimal frame of reference [J.-L. Vay, Phys. Rev. Lett. 98, 130405 (2007)] allows direct and efficient full-scale modeling of deeply depleted and beam loaded laser-plasma stages of 10 GeV-1 TeV (parameters not computationally accessible otherwise). This verifies the scaling of plasma accelerators to very high energies and accurately models the laser evolution and the accelerated electron beam transverse dynamics and energy spread. Over 4, 5, and 6 orders of magnitude speedup is achieved for the modeling of 10 GeV, 100 GeV, and 1 TeV class stages, respectively. Agreement at the percentage level is demonstrated between simulations using different frames of reference for a 0.1 GeV class stage. Obtaining these speedups and levels of accuracy was permitted by solutions for handling data input (in particular, particle and laser beams injection) and output in a relativistically boosted frame of reference, as well as mitigation of a high-frequency instability that otherwise limits effectiveness.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

HeatMap

SAND2021-14230 O HeatMap generates geospatial wildfire fuel models by applying machine learning algorithms to satellite imagery and weather station data. The code then leverages wildfire behavior software FlamMap to determine fire spread. It also uses PSLF software to model grid impacts and display data analytics for grid components that have been impacted by wildfire. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Danford, Forest↗

DOE OSTI2014

SU-E-J-115: Using Markov Chain Modeling to Elucidate Patterns in Breast Cancer Metastasis Over Time and Space

Purpose: Traditionally, breast cancer metastasis is described as a process wherein cancer cells spread from the breast to multiple organ systems via hematogenous and lymphatic routes. Mapping organ specific patterns of cancer spread over time is essential to understanding metastatic progression. In order to better predict sites of metastases, here we demonstrate modeling of the patterned migration of metastasis. Methods: We reviewed the clinical history of 453 breast cancer patients from Memorial Sloan Kettering Cancer Center who were non-metastatic at diagnosis but developed metastasis over time. We used the variables of organ site of metastases as well as time to create a Markov chain model of metastasis. We illustrate the probabilities of metastasis occurring at a given anatomic site together with the probability of spread to additional sites. Results: Based on the clinical histories of 453 breast cancer patients who developed metastasis, we have learned (i) how to create the Markov transition matrix governing the probabilities of cancer progression from site to site; (ii) how to create a systemic network diagram governing disease progression modeled as a random walk on a directed graph; (iii) how to classify metastatic sites as ‘sponges’ that tend to only receive cancer cells or ‘spreaders’ that receive and release them; (iv) how to model the time-scales of disease progression as a Weibull probability distribution function; (v) how to perform Monte Carlo simulations of disease progression; and (vi) how to interpret disease progression as an entropy-increasing stochastic process. Conclusion: Based on our modeling, metastatic spread may follow predictable pathways. Mapping metastasis not simply by organ site, but by function as either a ‘spreader’ or ‘sponge’ fundamentally reframes our understanding of metastatic processes. This model serves as a novel platform from which we may integrate the evolving genomic landscape that drives cancer metastasis. PS-OC Trans-Network Project Grant Award for “Data Assimilation and ensemble statistical forecasting methods applied to the MSKCC longitudinal metastatic breast cancer cohort.”.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

PetroFit: A Python Package for Computing Petrosian Radii and Fitting Galaxy Light Profiles

PetroFit is an open-source Python package based on Astropy and Photutils that can calculate Petrosian profiles and fit galaxy images. It offers end-to-end tools for making accurate photometric measurements, estimating morphological properties, and fitting 2D models to galaxy images. Petrosian metric radii can be used for model parameter estimation and aperture photometry to provide accurate total fluxes. Correction tools are provided for improving Petrosian radii estimates affected by galaxy morphology. PetroFit also provides tools for sampling Astropy-based models (including custom profiles and multicomponent models) onto image grids and enables point-spread function convolution to account for the effects of seeing. These capabilities provide a robust means of modeling and fitting galaxy light profiles. We have made the PetroFit package publicly available on GitHub (PetroFit/petrofit) and PyPi (pip install petrofit).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Forecasting influenza activity using machine-learned mobility map

Human mobility is a primary driver of infectious disease spread. However, existing data is limited in availability, coverage, granularity, and timeliness. Data-driven forecasts of disease dynamics are crucial for decision-making by health officials and private citizens alike. In this work, we focus on a machine-learned anonymized mobility map (hereon referred to as AMM) aggregated over hundreds of millions of smartphones and evaluate its utility in forecasting epidemics. We factor AMM into a metapopulation model to retrospectively forecast influenza in the USA and Australia. We show that the AMM model performs on-par with those based on commuter surveys, which are sparsely available and expensive. We also compare it with gravity and radiation based models of mobility, and find that the radiation model’s performance is quite similar to AMM and commuter flows. Additionally, we demonstrate our model’s ability to predict disease spread even across state boundaries. Our work contributes towards developing timely infectious disease forecasting at a global scale using human mobility datasets expanding their applications in the area of infectious disease epidemiology.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Alternative SIAR models for infectious diseases and applications in the study of non-compliance

In this paper, we use modified versions of the SIAR model for epidemics to propose two ways of understanding and quantifying the effect of non-compliance to non-pharmaceutical intervention measures on the spread of an infectious disease. The SIAR model distinguishes between symptomatic infected (I) and asymptomatic infected (A) populations. One modification, which is simpler, assumes a known proportion of the population does not comply with government mandates such as quarantining and social-distancing. In a more sophisticated approach, the modified model treats non-compliant behavior as a social contagion. We theoretically explore different scenarios such as the occurrence of multiple waves of infections. Local and asymptotic analyses for both models are also provided.

Mathematics↗

NASA NTRS1990

Dynamic range considerations for EUV MAMA detectors

The multianode microchannel array (MAMA) has been chosen as the detector for two instruments on the ESA/NASA Solar Heliospheric Observatory. The response of the MAMA to the two extreme types of solar spectra, disk and corona, have been modeled with a view toward evaluating dynamic range effects present. The method of MAMA operation is discussed, with emphasis given to modeling the effect of electron cloud charge spreading to several detector anodes and amplifiers (n-fold events). Representative synthetic EUV spectra have been created. The detector response to these spectra is modeled by dissecting the input photon radiation field across the detector array into contributions to the various amplifier channels. The results of this dissection are shown for spectral regions across the entire wavelength region of interest. These results are used to identify regions in which total array photon counting rate or individual amplifier rate may exceed the design limits. This allows the design or operational modes to be tailored to eliminate the problem areas.

Illing, Rainer M. E.↗

DOE OSTI2015

The distribution of precipitation and the spread in tropical upper tropospheric temperature trends in CMIP5/AMIP simulations

Abstract Reconciling observations and simulations of tropical upper tropospheric temperature trends remains an important problem in climate science. Examining atmospheric models running over observed sea surface temperatures (SSTs), Flannaghan et al. (2014) show that this reconciliation is affected by the SST data set used and that a precipitation‐weighted SST (PSST) is valuable in explaining this result. Here we show that even for Coupled Model Intercomparison Project Phase 5 Atmospheric Model Intercomparison Project (CMIP5 AMIP) simulations forced with identical SSTs, tropical upper tropospheric temperature trends across models (and between ensemble members) show a substantial spread (standard deviation ∼10% of the average trend). About 60% of this spread between ensemble means, as well as deviations from the ensemble means, can be explained by PSST calculated from the time‐evolving precipitation in each model run. Both PSST and atmospheric temperature trends show statistical evidence for systematic differences between models. We conclude that the response of precipitation patterns to changes in SST patterns is a significant source of uncertainty for tropical temperature trends.

Fueglistaler, S.↗

NASA NTRS2021

The Long-term Transport and Radiative Impacts of the 2017 British Columbia Pyrocumulonimbus Smoke Aerosols in the Stratosphere

Interactions of meteorology with wildfires in British Columbia, Canada during August 2017 led to three major pyrocumulonimbus (pyroCb) events that resulted in the injection of large amounts of smoke aerosols and other combustion products at the local upper troposphere and lower stratosphere (UTLS). These plumes of UTLS smoke with elevated values of aerosol extinction and backscatter compared to the background state were readily tracked by multiple satellite-based instruments as they spread across the Northern Hemisphere (NH). The plumes were observed in the lower stratosphere for about 8-10 months following the fire injections, with a stratospheric aerosol e-folding time of about 5 months. To investigate the radiative impacts of these events on the Earth system, we performed a number of simulations with the Goddard Earth Observing System (GEOS) atmospheric general circulation model (AGCM). Observations from multiple remote-sensing instruments were used to calibrate the injection parameters (location, amount, composition and heights) and optical properties of the smoke aerosols in the model. The resulting simulations of three-dimensional smoke transport were evaluated for a year from the day of injections using daily observations from OMPS-LP (Ozone Mapping Profiler Suite Limb Profiler). The model simulated rate of ascent, hemispheric spread and residence time (or e-folding time) of the smoke aerosols in the stratosphere are in close agreement with OMPS-LP observations. We found that both aerosol self-lofting and the large-scale atmospheric motion play important roles in lifting the smoke plumes from near the tropopause altitudes (~12 km) to about 22-23 km into the atmosphere. Further, our estimations of the radiative impacts of the pyroCb-emitted smoke aerosols showed that the smoke caused an additional warming of the atmosphere by about 0.6-1 W/m2 (zonal mean) that persisted for about 2-3 months after the injections in regions north of 40oN. The surface experienced a comparable magnitude of cooling. The atmospheric warming is mainly located in the stratosphere, coincident with the location of the smoke plumes, leading to an increase in zonal mean shortwave (SW) heating rates of 0.02-0.04 K/day during September 2017.

pyrocumulonimbus (pyroCb) events↗

NASA NTRS2003

Non-Migrating Tides, with Zonally Symmetric Component, Generated in the Mesosphere

For comparison with measurements from the TIMED satellite and coordinated ground based observations, we discuss results from our Numerical Spectral Model (NSM) that incorporates the Doppler Spread Parameterization (Hines, 1997) for small-scale gravity waves (GWs). The NSM extends from the ground into the thermosphere and describes the major dynamical features of the atmosphere including the wave driven equatorial oscillations (QBO and SAO), and the seasonal variations of tides and planetary waves. With emphasis on the non-migrating tides, having periods of 24 and 12 hours, we discuss our modeling results that account for the classical migrating solar excitation sources only. As reported earlier, the NSM reproduces the observed seasonal variations and in particular the large equinoctial maxima in the amplitude of the migrating diurnal tide at altitudes around 90 km. Filtering of the tide by the zonal circulation and GW momentum deposition was identified as the cause. The GWs were also shown to produce a strong non-linear interaction between the diurnal and semi-diurnal tides. Confined largely to the mesosphere, the NSM produces through dynamical interactions a relatively large contribution of non-migrating tides. A striking feature is seen in the diurnal and semi-diurnal oscillations of the zonal mean (m = 0). Eastward propagating tides are also generated for zonal wave numbers m = 1 to 4. When the NSM is run without GWs, the amplitudes for the non-migrating tides, including m = 0, are generally small. Planetary wave interaction and non-linear coupling that involves the filtering of GWs and related height integration of dynamical features are discussed as possible mechanisms for generating these non-migrating tides in the NSM. As is the case for the solar migrating tides, the non-migrating tides reveal persistent seasonal variations. Under the influence of the QBO and SAO, interannual variations are produced.

Mayr, H. G.↗

NASA NTRS2005

A NON-PRE DOUBLE-PEAKED BURST FROM 4U 1636-536: EVIDENCE FOR BURNING FRONT PROPAGATION

We analyse Rossi X-ray Timing Explorer (RXTE) Proportional Counter Array (PCA) data of a double-peaked burst from the low mass X-ray binary (LMXB) 4U 1636-536 that shows no evidence for photospheric radius expansion (PRE). We find that the X-ray emitting area on the star increases with time as the burst progresses, even though the photosphere does not expand. We argue that this is a strong indication of thermonuclear flame spreading on the stellar surface during such bursts. We propose a model for such double-peaked bursts, based on thermonuclear flame spreading, that can qualitatively explain their essential features, as well as the rarity of these bursts.

Bhattacharyya, Sudip↗