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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Predicting Frigid Mixed-Phase Clouds for Pristine Coastal Antarctica

Supercooled water is common in the clouds near coastal Antarctica and occasionally occurs at temperatures at or below -30°C. Yet the ice physics in most regional and global numerical models will glaciate out these clouds. This presents a challenge for the simulation of highly supercooled clouds that were observed at McMurdo, Antarctica during the Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) project during 2015–2017. The polar optimized version of the Weather Research and Forecasting model (Polar WRF) with the recently developed two-moment P3 microphysics scheme was used to simulate observed supercooled liquid water cases during March and November 2016. Nudging of the simulations to observed rawinsonde profiles and Antarctic automatic weather station observations provided increased realism and much greater cloud water amounts. Furthermore, sensitivity tests that adjust the ice physics for extremely low ice nucleating particle (INP) concentrations decrease cloud ice and increases the cloud liquid water closer to observed amounts. In these tests, a liquid layer near cloud top is simulated, in agreement with observations. Accurate representation of INP concentrations appears to be critical for the simulation of coastal Antarctic clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Stochastic nucleation processes and substrate abundance explain time-dependent freezing in supercooled droplets

Atmospheric immersion freezing (IF), a heterogeneous ice nucleation process where an ice nucleating particle (INP) is immersed in supercooled water, is a dominant ice formation pathway impacting the hydrological cycle and climate. Implementation of IF derived from field and laboratory data in cloud and climate models is difficult due to the high variability in spatio-temporal scales, INP composition, and morphological complexity. We demonstrate that IF can be consistently described by a stochastic nucleation process accounting for uncertainties in the INP surface area. This approach accounts for time-dependent freezing, a wide range of surface areas and challenges phenomenological descriptions typically used to interpret IF. The results have an immediate impact on the current description, interpretation, and experiments of IF and its implementation in models. The findings are in accord with nucleation theory, and thus should hold for any supercooled liquid material that nucleates in contact with a substrate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Active learning path-dependent properties using a cloud-based materials acceleration platform

Solid state materials are central to many modern technologies in which a given material may be exposed to a variety of environments. The material properties often vary with the sequence of environments in an irreversible manner, resulting in a quintessential path-dependency in experimental observables. While sequential learning techniques have been effectively deployed for accelerating learning of state properties of materials, they often use a consistent environment path in all experiments. To elevate such techniques for making optimal decisions in experimental investigations of path-dependent properties, we introduce an iterated expected information gain acquisition function that optimizes over entire experimental trajectories. This approach is implemented within a cloud-based Materials Acceleration Platform architecture utilizing an event-driven stateful broker coupled with remote HELAO (Hierarchical Experimental Laboratory Automation and Orchestration) instances and an AI science manager. The platform's efficacy was demonstrated through a case study optimizing multi-step spectro-electrochemical experiments to identify optically stable potential windows in (Co–Ni–Sb)O z metal oxides. The system successfully integrated AI-driven experiment design, remote laboratory automation, and cloud-based data infrastructure, validating the platform's capability for managing complex, adaptive, path-dependent workflows in materials discovery.

Guevarra, Dan [California Institute of Technology ↗
DOE OSTI2014

The Fabric for Frontier Experiments Project at Fermilab

The FabrIc for Frontier Experiments (FIFE) project is a new, far-reaching initiative within the Fermilab Scientific Computing Division to drive the future of computing services for experiments at FNAL and elsewhere. It is a collaborative effort between computing professionals and experiment scientists to produce an end-to-end, fully integrated set of services for computing on the grid and clouds, managing data, accessing databases, and collaborating within experiments. FIFE includes 1) easy to use job submission services for processing physics tasks on the Open Science Grid and elsewhere, 2) an extensive data management system for managing local and remote caches, cataloging, querying, moving, and tracking the use of data, 3) custom and generic database applications for calibrations, beam information, and other purposes, 4) collaboration tools including an electronic log book, speakers bureau database, and experiment membership database. All of these aspects will be discussed in detail. FIFE sets the direction of computing at Fermilab experiments now and in the future, and therefore is a major driver in the design of computing services worldwide.

Kirby, Michael↗
DOE OSTI2015

RADIO CONTINUUM EMISSION FROM THE MAGNETAR SGR J1745-2900: INTERACTION WITH GAS ORBITING Sgr A*

We present radio continuum light curves of the magnetar SGR J1745−2900 and Sgr A* obtained with multi-frequency, multi-epoch Very Large Array observations between 2012 and 2014. During this period, a powerful X-ray outburst from SGR J1745−2900 occurred on 2013 April 24. Enhanced radio emission is delayed with respect to the X-ray peak by about seven months. In addition, the flux density of the emission from the magnetar fluctuates by a factor of 2–4 at frequencies between 21 and 41 GHz and its spectral index varies erratically. Here, we argue that the excess fluctuating emission from the magnetar arises from the interaction of a shock generated from the X-ray outburst with the orbiting ionized gas at the Galactic center. In this picture, variable synchrotron emission is produced by ram pressure variations due to inhomogeneities in the dense ionized medium of the Sgr A West bar. The pulsar with its high transverse velocity is moving through a highly blueshifted ionized medium. This implies that the magnetar is at a projected distance of ∼0.1 pc from Sgr A* and that the orbiting ionized gas is partially or largely responsible for a large rotation measure detected toward the magnetar. Despite the variability of Sgr A* expected to be induced by the passage of the G2 cloud, monitoring data show a constant flux density and spectral index during this period.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Two-stage atlas subset selection in multi-atlas based image segmentation

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors have developed a novel two-stage atlas subset selection scheme for multi-atlas based segmentation. It achieves good segmentation accuracy with significantly reduced computation cost, making it a suitable configuration in the presence of extensive heterogeneous atlases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

2014 HPC Annual Report

Our commitment is to support you through delivery of an IT environment that provides mission value by transforming the way you use, protect, and access information. We approach this through technical innovation, risk management, and relationships with our workforce, Laboratories leadership, and policy makers nationwide. This second edition of our HPC Annual Report continues our commitment to communicate the details and impact of Sandia’s large-scale computing resources that support the programs associated with our diverse mission areas. A key tenet to our approach is to work with our mission partners to understand and anticipate their requirements and formulate an investment strategy that is aligned with those Laboratories priorities. In doing this, our investments include not only expanding the resources available for scientific computing and modeling and simulation, but also acquiring large-scale systems for data analytics, cloud computing, and Emulytics. We are also investigating new computer architectures in our advanced systems test bed to guide future platform designs and prepare for changes in our code development models. Our initial investments in large-scale institutional platforms that are optimized for Informatics and Emulytics work are serving a diverse customer base. We anticipate continued growth and expansion of these resources in the coming years as the use of these analytic techniques expands across our mission space. If your program could benefit from an investment in innovative systems, please work through your Program Management Unit ’s Mission Computing Council representatives to engage our teams.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE)

This report describes the development and testing of a novel system, the Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE), for Monitoring, Reporting and Verification (MRV) of CO 2 at Geological Carbon Storage (GCS) sites. The system consists of a pair of laser based transceivers, a number of retroreflectors, and a set of cloud based data processing, storage and dissemination tools, which enable 2-D mapping of the CO 2 in near real time. A system was built, tested locally in New Haven, Indiana, and then deployed to the Zero Emissions Research and Technology (ZERT) facility in Bozeman, MT. Testing at ZERT demonstrated the ability of the GreenLITE system to identify and map small underground leaks, in the presence of other biological sources and with widely varying background concentrations. The system was then ruggedized and tested at the Harris test site in New Haven, IN, during winter time while exposed to temperatures as low as -15 °CºC. Additional testing was conducted using simulated concentration enhancements to validate the 2-D retrieval accuracy. This test resulted in a high confidence in the reconstruction ability to identify sources to tens of meters resolution in this configuration. Finally, the system was deployed for a period of approximately 6 months to an active industrial site, Illinois Basin – Decatur Project (IBDP), where >1M metric tons of CO 2 had been injected into an underground sandstone basin. The main objective of this final deployment was to demonstrate autonomous operation over a wide range of environmental conditions with very little human interaction, and to demonstrate the feasibility of the system for long term deployment in a GCS environment.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2017

Model simulations of aerosol effects on clouds and precipitation in comparison with ARM data

Observation-based studies have shown that the aerosol cloud lifetime effect or the increase of cloud liquid water path (LWP) with increased aerosol loading may have been overestimated in climate models. Here, we simulate shallow warm clouds on 05/27/2011 at the Southern Great Plains (SGP) measurement site established by Department of Energy's Atmospheric Radiation Measurement (ARM) Program using a single column version of a global climate model (Community Atmosphere Model or CAM) and a cloud resolving model (CRM). The LWP simulated by CAM increases substantially with aerosol loading while that in the CRM does not. The increase of LWP in CAM is caused by a large decrease of the autoconversion rate when cloud droplet number increases. In the CRM, the autoconversion rate is also reduced, but this is offset or even outweighed by the increased evaporation of cloud droplets near cloud top, resulting in an overall decrease in LWP. Our results suggest that climate models need to include the dependence of cloud top growth and the evaporation/condensation process on cloud droplet number concentrations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

COMBLE Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility recently concluded its Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE), with its campaign emphasis on marine boundary-layer clouds and mixed-phase clouds during cold-air outbreaks. The COMBLE campaign featured the deployment of the first ARM Mobile Facility (AMF1) to northern Scandinavia (Andenes, Norway), including its standard complement of ARM cloud radars. In keeping with user demands stemming from the previous AMF Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, a post-campaign radar mentor effort was initiated for COMBLE. This activity was intended to improve the usability of the ARM cloud radar data sets in response to overall demands for calibrated, corrected data sets for downstream studies and retrieval applications. In addition to the terrain complexities previously important to CACTI data sets (e.g., clutter designation and/or removal), COMBLE presented new challenges to existing ARM radar mentor capabilities. These included the extension of existing methodologies (e.g., relative calibration adjustment [RCA] target techniques) to frozen environments and the potential issues with their applicability when considering mixed-phase precipitation conditions. As in the previous CACTI documentation (Hardin et al. 2020), the overall calibration and conditioning process in ARM nomenclature is referred to as generating a “b1” datastream. For the radars, these “b1” standards refer to a datastream that has been calibrated (and cross-calibrated), with effort to deliver the highest-quality (well-characterized) data possible. The “b1” radar mentor reporting (this current document) is intended to detail (i) the status/quality of the original “a1” (raw) data sets during the COMBLE AMF campaign, (ii) the corrections and calibrations that are applied to generate the b1 datastreams available on ARM’s Data Discovery, and (iii) the details of the applied methods, e.g., how radar offset/calibration numbers were determined.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessment and Coordination of EVSE Cybersecurity Standards

Cybersecurity certification programs for Electric Vehicle Supply Equipment (EVSE) are fragmented due to no single certification covering all aspects of the device and additionally the existence of multiple programs and under different levels of regulation. These devices are also confronted by the intricate assembly of product software, firmware, and hardware. Devices contain both logical and physical interfaces. These multifaceted devices have vulnerabilities at many levels and interconnect with other potentially vulnerable systems including the electric vehicle, the cloud where data and payment information are stored, and the electric grid and electric grid equipment including utilities. Of the EVSE certification programs that are found, none are directly for the cybersecurity of EVSE. Many standards are for safety, specifically battery safety, some are cybersecurity standards for other types of equipment and can be modeled for EVSE. In specific, ISA/IEC 62443 is found to be significantly in line with EVSE security needs and will be used in future testing to certify EVSE and help guide the project to demonstrate where gaps exist, where strengths lie in the standard and how this can be used to lead the certification efforts in harmonizing EVSE cybersecurity standards. In addition, there are multiple efforts that are currently seeking to build EVSE standards or revise existing standards to address gaps. This effort is seeking to establish a cybersecurity program for EVSE that will inform customers and help increase the level of security across products and state EVSE procurements to achieve consistency across different jurisdictions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Dependence of Mass–Dimensional Relationships on Median Mass Diameter

Retrievals of ice cloud properties require accurate estimates of ice particle mass. Empirical mass–dimensional ( m – D ) relationships in the form m = a D b are widely used and usually universally applied across the complete range of particle sizes. For the first time, the dependence of a and b coefficients in m–D relationships on median mass diameter ( D mm ) is studied. Using combined cloud microphysical data collected during the Olympic Mountains Experiment and coincident observations from Airborne Precipitation Radar Third Generation, D mm -dependent ( a , b ) coefficients are derived and represented as surfaces of equally plausible solutions determined by some tolerance in the chi-squared difference χ 2 that minimizes the difference between observed and retrieved radar reflectivity. Robust dependences of a and b on D mm are shown with both parameters significantly decreasing with D mm , leading to smaller effective densities for larger D mm ranges. A universally applied constant m–D relationship overestimates the mass of large aggregates when D mm is between 3–6 mm and temperatures are between −15–0 °C. Multiple m–D relations should be applied for different D mm ranges in retrievals and simulations to account for the variability of particle sizes that are responsible for the mass and thus for the variability of particle shapes and densities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Raindrop Size Spectrum in Deep Convective Regions of the Americas

This study compared drop size distribution (DSD) measurements on the surfaces, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter D m , and normalized droplet concentration N w ) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader N w distributions in Córdoba. The raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h -1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In the light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of N w in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Computational Strategies for Scalable Genomics Analysis

The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data technologies have been explored to scale up/out current bioinformatics solutions to mine the big genomics data. In this review, we survey some of these exciting developments in the applications of parallel distributed computing and special hardware to genomics. We comment on the pros and cons of each strategy in the context of ease of development, robustness, scalability, and efficiency. Although this review is written for an audience from the genomics and bioinformatics fields, it may also be informative for the audience of computer science with interests in genomics applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Dispersion of magnetic fields in molecular clouds. IV. Analysis of interferometry data

We expand on the dispersion analysis of polarimetry maps toward applications to interferometry data. We show how the filtering of low spatial frequencies can be accounted for within the idealized Gaussian turbulence model, initially introduced for single-dish data analysis, to recover reliable estimates for correlation lengths of magnetized turbulence, as well as magnetic field strengths (plane-of-the-sky component) using the Davis–Chandrasekhar–Fermi method. We apply our updated technique to TADPOL/CARMA data obtained on W3(OH), W3 Main, and DR21(OH). For W3(OH), our analysis yields a turbulence correlation length δ≃19 mpc, a ratio of turbulent-to-total magnetic energy 〈B{sub t}{sup 2}〉/〈B{sup 2}〉≃0.58, and a magnetic field strength B{sub 0}∼1.1 mG; for W3 Main δ≃22 mpc, 〈B{sub t}{sup 2}〉/〈B{sup 2}〉≃0.74, and B{sub 0}∼0.7 mG; while for DR21(OH) δ≃12 mpc, 〈B{sub t}{sup 2}〉/〈B{sup 2}〉≃0.70, and B{sub 0}∼1.2 mG.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Breakthrough Listen Search for Intelligent Life: Searching for Technosignatures in Observations of TESS Targets of Interest

Exoplanetary systems are prime targets for the Search for Extraterrestrial Intelligence (SETI). With the recent uptick in the identification of candidate and confirmed exoplanets through the work of missions like the Transiting Exoplanet Survey Satellite (TESS), we are beginning to understand that Earth-like planets are common. In this work, we extend the Breakthrough Listen (BL) search for extraterrestrial intelligence to include targeted searches of stars identified by TESS as potential exoplanet hosts. We report on 113 30 minute cadence observations collected for 28 targets selected from the TESS Input Catalog from among those identified as containing signatures of transiting planets. The targets were searched for narrowband signals from 1 to 11 GHz using the turboSETI pipeline architecture modified for compatibility with the Google Cloud environment. Data were searched for drift rates of ±4 Hz s{sup −1} above a minimum signal-to-noise threshold of 10, following the parameters of previous searches conducted by Price et al. and Enriquez et al. The observations presented in this work establish some of the deepest limits to date over such a wide band (1–11 GHz) for life beyond Earth. We determine that fewer than 12.72% of the observed targets possess transmitters operating at these frequencies with an equivalent isotropic radiated power greater than our derived threshold of 4.9×10{sup 14} W.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗