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DOE OSTI2020

Beowulf v2.5.3 User Guide: Revision 5

This document is a user guide for the Beowulf (rebranding of Watchmen) tool. It describes how operators can access and utilize the application's functionality. Beowulf is a research software application developed by Pacific Northwest National Laboratory (PNNL) that incorporates the scientific and operational expertise for reviewing data from treaty monitoring radionuclide stations. These stations are part of a worldwide network to monitor for nuclear explosions, and the data they produce are critical to make the determination of whether a sample is from a nuclear explosion or some other source (i.e., nuclear reactor or medical isotope production facility). Stations deliver their measurements and system status to the International Monitoring System (IMS), which forwards it via email to all subscribers. Beowulf is capable of processing data from several radioxenon station types and development is in progress on a solution for particulate stations. Screening of data in Beowulf may be done by a number of different users such as radionuclide analysts, evaluators, and data quality experts. This guide is provided to assist those users in navigating the application. The term Beowulf is used generically throughout this document to refer to any of the various components in the software application. The user interface that is viewed with a web browser is the primary focus of this user guide. Other components include a database to store measurements and state of health (SOH) data; and the data loader that monitors incoming emails, parses the data, populates the database, does the initial analysis, and routes data for review.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Applying the FAIR Principles to computational workflows

Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity and reproducibility that also democratize access to platforms and processing know-how. As digital objects to be shared, discovered, and reused, computational workflows benefit from the FAIR principles, which stand for Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative’s FAIR Workflows Working Group (WCI-FW), a global and open community of researchers and developers working with computational workflows across disciplines and domains, has systematically addressed the application of both FAIR data and software principles to computational workflows. We present recommendations with commentary that reflects our discussions and justifies our choices and adaptations. These are offered to workflow users and authors, workflow management system developers, and providers of workflow services as guidelines for adoption and fodder for discussion. The FAIR recommendations for workflows that we propose in this paper will maximize their value as research assets and facilitate their adoption by the wider community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Securing Federated Learning Against Active Reconstruction Attacks

Federated Learning (FL) has amassed notable attention for its ability to preserve user privacy while emphasizing the retainment of model training efficiency. Due to this potential, FL has been integrated in many domains, such as healthcare, finance, law, and industrial engineering, where data cannot be easily exchanged due to sensitive information and strict privacy laws. However, current research has indicated that FL protocols are easily compromised by active data reconstruction attacks employed by actively dishonest servers. The malicious modification of global model parameters allows an actively dishonest server to obtain a direct copy of users’ private data via gradient inversion. Here, this class of attacks is highly underexplored and continues to be a major challenge due to the intense threat model. In this paper, we propose OASIS as a scalable and modality-agnostic defense based on data augmentation that counteracts active data reconstruction attacks while preserving model performance. To generalize our defense, we uncover the intuition behind gradient inversion that enables these attacks and theoretically establish the conditions by which the defense can be considered robust regardless of attack design. From this, we formulate our defense with data augmentation that illustrates its ability to undermine the attack principle. We evaluate OASIS on five real-world datasets–two image-based (ImageNet and CIFAR100) and three text-based (Wikitext, Stack Overflow, and Shakespeare)–which span diverse uses cases such as vision tasks and language modeling. Comprehensive evaluations on these datasets exhibit the efficacy of OASIS and highlight its feasibility as a solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

US Department of Energy, Office of Science, High-Performance Computing Facility: 2023 Operational Assessment Oak Ridge Leadership Computing Facility

The Oak Ridge Leadership Computing Facility (OLCF) was established to accelerate scientific discovery by providing world-leading computational performance and advanced data infrastructure. As a US Department of Energy (DOE) Office of Science user facility, the OLCF has managed the successful deployment and operation of a succession of leadership-class resources dedicated to open science. In addition to these resources, the OLCF staff continually strive to develop innovative processes and technologies, improve security, and empower users through effective allocation management and comprehensive user support and training. These efforts support the advancement of science by the OLCF users and benefit high-performance computing (HPC) facilities around the world. In calendar year (CY) 2023, the OLCF supported 1,676 users and 598 projects and exceeded all targets for user satisfaction. The facility received an average satisfaction score of 4.52 out of 5 on the annual user survey, and 94% of respondents reported a high satisfaction rate with the OLCF overall. Of the 3,619 user tickets submitted in CY 2023, OLCF staff resolved 97% within 3 business days. The facility opened Frontier to full scientific operations this year. Two projects conducted on Frontier received the Association for Computing Machinery (ACM) Gordon Bell Prize and the Gordon Bell Special Prize for Climate Modeling, and a third earned a nomination as a Gordon Bell Prize finalist. The facility’s previous flagship machine, Summit, gained new life and was extended through 2024 in part to help provide resources to the Integrated Research Infrastructure (IRI) projects and the National Artificial Intelligence Research Resource (NAIRR) pilot program. The facility instantiated an Advanced Computing Ecosystem testbed in part to support IRI workflows. OLCF made interactivity easier and more accessible to users than ever through tools like Jupyter notebooks and workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Case Study of Tunable White LED Lighting with Networked Lighting Controls (Emory University Cognitive Empowerment Program)

Emory University and Georgia Institute of Technology (Georgia Tech) partnered to create the Charlie and Harriet Schaffer Cognitive Empowerment Program (CEP) facility in northeast Atlanta. Together with the funders they are building a program to help individuals experiencing mild cognitive impairment (MCI) to maintain their physical and cognitive health, and independence as long as possible. In addition to applying effective strategies and therapies, the two research groups are investigating the responses of the MCI members to treatments that involve acoustical conditions, exercise and movement, and lighting changes that may support retention or relearning of skills. Care partners and family members receive support and instruction to improve home and work life, promoting joy, purpose, and wellness in the family groups. The lighting system uses tunable-white LEDs, employing luminaires with both warm and cool-color emitters that can be dimmed separately to produce any white correlated color temperature (CCT) between 2700 K and 6500 K. All luminaires were dimmable to achieve subdued or lively surroundings for different treatments, time-of-day, and mood. A central networked digital control system was employed to allow tuning of multiple spaces together (for example, bright, cool morning light could be programmed for extra stimulation, or lighting in all spaces at the end of the day could be reduced in both light output and CCT to promote relaxation and not interfere with the melatonin cycle of occupants). Almost all spaces were equipped with individual room control of dimming and color temperature with touch screens to allow users to tune the lighting as desired, but each room’s controls could also be specially programmed through the server in case the research staff were investigating lighting settings on learning, for example. The server incorporates a timeclock, and it is able to send signals to switch off all lighting after occupancy hours, or enable occupancy sensors to control the lighting. The bulk of the construction work was completed in January 2020. It was clear from an initial walk-through that although the lighting system produced the expected high light level with low-glare qualities of light, that there were issues and inconsistencies to be resolved. These were noted in an initial punchlist visit and expected to be resolved when the tech representatives from the agency visited with the electrical contractor in the following few weeks. What followed was 2.5 years of identifying unexpected lighting performance in terms of light output, color, scheduling, and occupancy. This report documents the issues encountered in the effort to get the lighting and controls systems to operate as intended. It concludes with guidance for design professionals and manufacturers to help avoid problematic complexity in future projects.

42 ENGINEERING↗
DOE OSTI2020

Resource for the Development of Biomedical Accelerator Mass Spectrometry (AMS) Final Report

The NIH Research Resource for Biomedical AMS was originally funded at Lawrence Livermore National Laboratory in 1999 to develop and apply the technology of accelerator mass spectrometry (AMS) in broad- based biomedical research. The Resource’s niche is to fill needs for ultra high sensitivity quantitation when isotope-labeled agents are used. The Research Resource’s Technology Research and Development (TR&D) efforts will focus on the needs of the biomedical research community in the context of seven Driving Biomedical Projects (DBPs) that will drive the Center’s technical capabilities through three core TR&Ds. We will expand our present capabilities by developing a fully integrated HPLC AMS to increase our capabilities for metabolic measurements, we will develop methods to understand cellular processes and we will develop and validate methods for the application of AMS in human studies, which is a growing area of demand by collaborators and service users. In addition, we will continue to support new and ongoing collaborative and service projects that require the capabilities of the Resource. The Center will continue to train researchers in the use of the AMS capabilities being developed, and the results of all efforts will be widely disseminated to advance progress in biomedical research. Towards these goals, our specific aims are to:1.) Increase the value and information content of AMS measurements by combining molecular speciation with quantitation of defined macromolecular isolates. Specifically, develop and validate methods for macromolecule labeling, characterization and quantitation.2.) Develop and validate methods and strategies to enable AMS to become more broadly used in human studies. Specifically, demonstrate robust methods for conducting pharmacokinetic/pharmacodynamics studies in humans and model systems.3.) Increase the accessibility of AMS to the Biomedical research community and the throughput of AMS through direct coupling to separatory instruments.4.) Provide high throughput 14C BioAMS analysis for collaborative and service clients.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

LDRD 2022 Annual Report: Laboratory Directed Research and Development Program Activities

Each year, Brookhaven National Laboratory (BNL) is required to provide a report of its completed Laboratory Directed Research and Development Program (LDRD) projects to the Department of Energy (DOE) Office of Scientific and Technical Information in accordance with DOE Order 413.2C Chg1 (MinChg) dated August 2, 2018. This report provides a detailed look at the scientific and technical activities for each of the LDRD projects funded by BNL in FY 2022, in fulfillment of that requirement. In FY 2022, the BNL LDRD Program funded 70 projects, 30 of which were new starts, at a total cost of $17.2M. The investments that BNL makes in its LDRD program support the Laboratory’s strategic goals. BNL has identified seven scientific initiatives that define the Laboratory’s scientific future and that will enable it to realize its overall vision. This requires simultaneous excellence in all aspects of BNL’s work – from science and operations, to external partnerships with the local, state, and national communities, and beyond. This is enabled by safe, efficient, and secure operations; by an unwavering commitment to a diverse, equitable, and inclusive environment, including workforce development, both with staff and reaching out to the community; and by a strong focus on renewed infrastructure. The seven scientific initiatives are: 1) Nuclear Physics: uncover the structure of visible matter by constructing and operating the Electron-Ion Collider at BNL to maintain international leadership in nuclear physics for decades; 2) Clean Energy and Climate: support a net-zero U.S. economy through fundamental research in basic energy and climate sciences to revolutionize grid-scale storage, renewable integration, and the study of atmospheric processes with a new facility to improve climate predictability; 3) Quantum Information Science and Technology: discover new quantum materials to enhance quantum computers and develop an entanglement sharing quantum network as a prototype for the first quantum internet; 4) Discovery Science Driven by the Human-AI Facility Integration: revolutionize the operation of experiments across the sciences at user facilities and in core programs; 5) High Energy Physics: understand the origin of space and time with the ATLAS high luminosity upgrade at CERN and the future Long Baseline Neutrino Facility/Deep Underground Neutrino Experiment; 6) Isotope Production: accelerate and expand isotope production to ensure the security of the Nation’s supply; 7) Accelerator Science and Technology: harness the cross-cutting accelerator science expertise at BNL to develop new facilities, improve and expand its user facilities, and promote the use of accelerators in industry. The funded projects support BNL’s seven scientific initiatives and priority programs as well as new areas of research and competencies at the Laboratory that are consistent with the Laboratory’s vision and mission. In total, these LDRD investments supported 43 postdoctoral researchers in whole or in part and resulted in 138 publications and 7 awards. This Program Activities Report represents the future of BNL science; it is an impressive body of exploratory work that investigates many scientific and technical directions in support of the DOE and BNL missions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Flexible Plant Operation and Generation Technical Program Plan for FY2023

This report presents the Technical Program Plan for Fiscal Years 2023-2027 (FY2023 to FY2027) for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability Program—Flexible Plant Operation and Generation Research Pathway. The objective of this pathway is to carry out the research needed to help nuclear power plants diversify revenue generation for the life of these plants. The purpose of these research and development activities is two fold: (1) to reduce the technical and economic risks of implementing FPOG applications and (2) to provide guidance on relevant safety and environmental operating license reviews, amendments, and renewals. This pathway provides a clear understanding of the benefits of nuclear energy beyond electricity markets. A detailed description of the research and development activities that have been completed and that are planned for FY2023—FY2027 are presented in this report. These activities include completing the development of analysis tools to perform technical and economic assessments of realistic market opportunities for producing secondary energy products near nuclear power plants. They also include developing and demonstrating engineering systems and control concepts to dispatch thermal and electrical power to an industrial user. Additionally, this plan includes developing guidance for addressing potential regulatory and licensing requirements. In addition, the formation, purpose, and activities of a group referred to as the Hydrogen Regulatory Research and Review Group is discussed. An overview is also provided on the potential benefits of the Infrastructure Investment and Jobs Act (IIJA) Bill that will support the commencement of Regional Clean Hydrogen Hubs, and the Inflation Reduction Act (IRA) that provides compelling production tax credits for nuclear electricity and clean hydrogen using nuclear energy.

08 HYDROGEN↗
DOE OSTI2022

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Using Facebook to Recruit Urban Participants for Smartphone-Based Travel Surveys

Social media has become an integral part of everyday life for many individuals, serving as a platform to express opinions, share memories and lifestyles, follow news, and adapt to social trends and norms. The wealth of user information and analytics on these platforms has facilitated the development and sale of tailored products and services, benefiting advertisers and researchers seeking survey participants. Social media advertising has demonstrated its effectiveness in reaching hard-to-reach populations. However, transport researchers have yet to capitalise on this potential fully. This paper presents our experience using social media to recruit participants for two smartphone travel surveys conducted in Australia. We demonstrate that social media recruitment and smartphone-based travel surveys are highly effective, adaptable, and can be rapidly deployed in response to research opportunities, such as during the early phase of the COVID-19 pandemic when traditional methods may be less suitable. This approach also holds great potential for travel surveys targeting the general population. This paper shares several lessons from this experiment, including our administrative approach and detailed technical instructions to utilise open-source software tools for conducting smartphone travel surveys like ours. This approach significantly reduces study costs compared to most commercial solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Demonstrating SolarPILOT’s Python API Through Heliostat Optimal Aimpoint Strategy Use Case

SolarPILOT is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s1 System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This paper presents a new, full-featured, Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT’s capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instance with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layouts; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying solar field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating solar field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux distribution; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot’s functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize power tower CSP research. This enables CSP researchers to perform analysis that was previously not possible through SolarPILOT’s existing interfaces. This paper discusses the capabilities of CoPylot and presents a use case wherein we demonstrate optimal solar field aiming strategies.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

ggtaxplot v 0.0.1

ggtaxplot is an R package designed to process and visualize taxonomic data through a taxonomic river plot. This package is ideal for researchers and data scientists who need to visualize taxonomic data. ggtaxplot function processes data and generates a taxonomic river plot, allowing users to visualize the distribution of taxa across different samples.

Coclet, Clement [Lawrence Berkeley National Labora↗
DOE OSTI2020

CRISpy-Pop: A Web Tool for Designing CRISPR/Cas9-Driven Genetic Modifications in Diverse Populations

CRISPR/Cas9 is a powerful tool for editing genomes, but design decisions are generally made with respect to a single reference genome. With population genomic data becoming available for an increasing number of model organisms, researchers are interested in manipulating multiple strains and lines. CRISpy-pop is a web application that generates and filters guide RNA sequences for CRISPR/Cas9 genome editing for diverse yeast and bacterial strains. The current implementation designs and predicts the activity of guide RNAs against more than 1000 Saccharomyces cerevisiae genomes, including 167 strains frequently used in bioenergy research. Zymomonas mobilis, an increasingly popular bacterial bioenergy research model, is also supported. CRISpy-pop is available as a web application (https://CRISpy-pop.glbrc.org/) with an intuitive graphical user interface. CRISpy-pop also cross-references the human genome to allow users to avoid the selection of sgRNAs with potential biosafety concerns. Additionally, CRISpy-pop predicts the strain coverage of each guide RNA within the supported strain sets, which aids in functional population genetic studies. Lastly, we validate how CRISpy-pop can accurately predict the activity of guide RNAs across strains using population genomic data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

CROCUS Air Quality Data at Northeastern Illinois University Rooftop

This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). The AQT (Vaisala AQT530) instrument provides observations on meteorological conditions, including particulate matter (PM2.5, PM10), gas species concentrations (NO, NO2, O3, CO), and environment temperature and moisture. These measurements are critical for understanding air quality. These measurements are useful for understanding changes in aerosol properties, air quality research, and comparing to model experiments especially in urban environments.Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Performance Evaluation of Three RTU Energy Efficiency Technologies

This project was part of an effort by CLEAResult and ComEd to evaluate the energy saving potential of emerging technologies in the Chicago area. This project focused on evaluating emerging technologies related to rooftop units (RTUs). An RTU with a single-stage compressor and a constant-speed fan with an induction motor was selected as the baseline for technology comparison. Three retrofit strategies were investigated. The first two involved replacing the single-stage compressor of an RTU by either a two-stage or variable-speed compressor and adding a variable frequency drive (VFD) to the constant speed fan. The use of a multi-/variable-stage compressor improves the part-load efficiency of the compressor which will ultimately result in annual energy savings as well as peak demand shaving in some cases where the design capacity of the RTU is larger than the maximum cooling load of the building space that it is serving. The third technology was the use of a high rotor pole switched reluctance motor (SRM) as a replacement for the constant-speed supply fan. The SRM was applied in single-speed, two-stage and variable-speed compressor RTUs. SRM motors run via reluctance torque. Their stator poles are driven by direct current (DC) power and require an inverter as well as active control when using alternating current (AC) power. This inherent property results in high efficiency over a range of operating conditions. It also exhibits higher efficiency compared to variable frequency drives (VFDs) since its switching frequency is much slower (SCE, 2018).The three technologies investigated are summarized below: 1) Replacing the single-speed compressor with a two-stage compressor and adding a VFD to the supply fan. 2)Replacing the single-speed compressor with a variable-speed compressor and adding a VFD to the supply fan. 3) Replacing the constant-speed induction motor of the supply fan with a high rotor pole SRM. DOE’s building simulation platform EnergyPlus and its graphical user interface OpenStudio were used to evaluate the energy-saving potential of upgrading RTUs, by leveraging experimental data from previous research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Best Practices for NERSC Training

The National Energy Research Supercomputing Center (NERSC) at Lawrence Berkeley National Laboratory (LBNL) organizes approximately 20 training events per year for its 8,000 users from 800 projects, who have varying levels of High Performance Computing (HPC) knowledge and familiarity with NERSC's HPC resources. Due to the novel circumstances of the pandemic, NERSC began transforming our traditional smaller-scale, on-site training events to larger-scale, fully virtual sessions in March 2020. We treated this as an opportunity to try new approaches and improve our training best practices. This paper describes the key practices we have developed since the start of this transformation, including considerations for organizing events; collaboration with other HPC centers and the DOE ECP Program to increase reach and impact of events; targeted emails to users to increase attendance; efficient management of user accounts for computational resource access; strategies for preventing Zoombombing; streamlining the publication of professional-quality, closed-captioned videos on the NERSC YouTube channel for accessibility; effective communication channels for Q&A; tailoring training contents to NERSC user needs via close collaboration with vendors and presenters; standardized training procedures and publishing of training materials; and considerations for planning HPC training topics. Additionally, most of these practices will be continued after the pandemic as effective norms for training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Ultrasonic Transducer Irradiation Test Results

Ultrasonic technologies offer the potential for high accuracy and resolution in-pile measurement of a range of parameters, including geometry changes, temperature, crack initiation and growth, gas pressure and composition, and microstructural changes. Many Department of Energy-Office of Nuclear Energy (DOE-NE) programs are exploring the use of ultrasonic technologies to provide enhanced sensors for in-pile instrumentation during irradiation testing. For example, the ability of small diameter ultrasonic thermometers (UTs) to provide a temperature profile in candidate metallic and oxide fuel would provide much needed data for validating new fuel performance models. These efforts are limited by the lack of identified ultrasonic transducer materials capable of long term performance under irradiation test conditions. To address this need, the Pennsylvania State University (PSU) was awarded an Advanced Test Reactor National Scientific User Facility (ATR NSUF) project to evaluate the performance of promising magnetostrictive and piezoelectric transducers in the Massachusetts Institute of Technology Research Reactor (MITR) up to a fast fluence of at least 1021 n/cm2 . A multi-National Laboratory collaboration funded by the Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program also provided initial support for this effort. This irradiation, which started in February 2014, is an instrumented lead test and real-time transducer performance data are collected along with temperature and neutron and gamma flux data. The irradiation is ongoing and will continue to approximately mid-2015. To date, very encouraging results have been attained as several transducers continue to operate under irradiation.

Daw, Joshua↗
DOE OSTI2025

NGEE Arctic Tram: Radiation and Environmental Measurements over Low- and High-Centered Polygon Vegetation Communities, Barrow, Alaska, 2014-2017

These data were generated from an observational platform (Tram), an automated cart carrying a suite of radiation and remote sensing instruments running on 68 meters of elevated track 1 to 1.5 meters above the surface of the vegetation communities of low- and high-centered polygon ground. The Tram is in the footprint of the NGEE Arctic/AmeriFlux eddy covariance flux tower (US-NGB) at the Barrow Environmental Observatory, Barrow, Alaska, and operated before, during, and after the growing seasons of 2014-2017. Dataset includes one user guide (*.pdf) with final and raw *.csv data files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗