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At least 1,423 records · Page 79

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Johnston, William E.↗

Oak Ridge Reservation Meteorological Overview Report, Oak Ridge, TN

This report is purposed to provide a summary of the local climate and data from meteorological (Met) towers and wind profilers at the East Tennessee Technology Park (ETTP), the Y-12 National Security Complex Site (Y-12), the Oak Ridge National Laboratory (ORNL), as well as other federal, state, or local agencies as necessary to support the natural phenomena hazards (NPH) analysis 10-year update required by Department of Energy (DOE)- STD-1020-2016, Natural Phenomena Hazards Analysis and Design Criteria for DOE Facilities. The data from this report will be used to support high wind analyses, precipitation analysis, flood analysis, lightning analysis, and other severe weather phenomena for the ETTP, the ORNL, and Y-12.

54 ENVIRONMENTAL SCIENCES↗

Attribution of gamma-ray background collected by a mobile detector system to its surroundings using panoramic video

Mobile radiation detector systems are important tools for detecting radiological and nuclear sources outside of regulatory control, but due to their mobility, they are subject to complex and varying backgrounds in most realistic operational scenarios. Recent work has found correlations between non-radiological contextual information and gamma-ray spectral features that can be used to decrease false alarm rates, however a more complete understanding of background source terms has been elusive. A measurement campaign developed a full radiological characterization of a controlled facility that roughly corresponded to two city blocks. As part of the campaign, the Radiological Multi-sensor Analysis Platform (RadMAP) collected extensive multi-sensor data. In this work, RadMAP’s panoramic video data were used to visually identify several different materials and quantify the detector response to each material. A linear model was fit between the material responses and radiological features, and the results demonstrate reasonable agreement with ground truth flux measurements for each material. This paper will describe the data collection, processing, and analysis of the gamma-ray and video data from RadMAP. The paper will conclude with perspectives on the applicability of such a method to less controlled environments both with respect to achieving better understanding the sources of variability of background radiation in urban environments and whether such methods could be leveraged in operational scenarios.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

LandScan Global 30 Arcsecond Annual Global Gridded Population Datasets from 2000 to 2022

Abstract Oak Ridge National Laboratory (ORNL) annually develops the LandScan Global (LSG) dataset, a 30 arcsecond global gridded population dataset representing global ambient human population distribution. This multivariable dasymetric model disaggregates census counts within administrative boundaries using ancillary data. Each country’s distribution reflects cultural and socioeconomic patterns; manual validations yield a unique global dataset for assessing populations at risk. For over two decades, LSG has been a standard for estimating populations at risk, aiding U.S. federal government, academia and humanitarian organizations. During disasters such as the 2004 Indian Ocean tsunami and the 2010 Haiti earthquake and geopolitical crises such as the Syrian civil war and the 2022 Russian invasion of Ukraine, LSG supported scientific and operational communities in emergency response and recovery. In 2022, LSG datasets from 2000 onward were made publicly available through ORNL’s LandScan Portal. This data descriptor details our methodology and the application of geospatial science and machine learning to geographic and demographic data, highlighting uses in urban resiliency, emergency management, disaster response, and human health and security.

Science & Technology - Other Topics↗

Authentication of smart grid communications using quantum key distribution

Smart grid solutions enable utilities and customers to better monitor and control energy use via information and communications technology. Information technology is intended to improve the future electric grid’s reliability, efficiency, and sustainability by implementing advanced monitoring and control systems. However, leveraging modern communications systems also makes the grid vulnerable to cyberattacks. Here we report the first use of quantum key distribution (QKD) keys in the authentication of smart grid communications. In particular, we make such demonstration on a deployed electric utility fiber network. The developed method was prototyped in a software package to manage and utilize cryptographic keys to authenticate machine-to-machine communications used for supervisory control and data acquisition (SCADA). This demonstration showcases the feasibility of using QKD to improve the security of critical infrastructure, including future distributed energy resources (DERs), such as energy storage.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Autonomous Wireless Technology Detection in Seamless IoT Applications

The ever-increasing use of Internet of Things (IoT) devices results in the implementation of multiple wireless technologies that would not only cater their data rate requirements but also support various applications. To optimize the energy efficiency and security of the wireless transmission, it is imperative to identify the wireless technologies in various IoT implementations. Many of the existing approaches are based on measuring only the receiving signal strength indicator (RSSI). However, such approaches may not work well because of transmit power control and complex channel variations among different wireless technologies. In this article, we propose an autonomous wireless detection scheme that considers multiple distinguishable physical (PHY)-layer settings for real-time identification of wireless technologies for real-time applications. Specifically, the proposed scheme relies on the PHY-layer measurements of the targeted spectrum. Transmission settings, such as bandwidth, carrier frequency, and RSSI are estimated from the raw in-phase and quadrature-phase (I/Q) measurements. In addition, a symbol-level extraction scheme is implemented to extract unique features of modulation settings. These aforementioned features are applied to a machine learning process to identify the received wireless technologies. Compared with raw I/Q measurements, the extracted features are much simplified and, thus, the machine learning classifier can be designed with a simple structure for fast processing on IoT nodes. Finally, the proposed schemes are primarily evaluated theoretically, followed by implementing them on a USRP software-defined radio (SDR)-based hardware testbed. The evaluation results demonstrate high accuracy in the real-time detection of different wireless technologies for seamless IoT applications.

42 ENGINEERING↗

Tools, Techniques, and Methodologies: A Survey of Digital Forensics for SCADA Systems

Security aspects of SCADA environments and the systems within are increasingly a center of interest to researchers and security professionals. As the rise of sophisticated and nation-state malware targeting such systems flourishes, traditional digital forensics tools struggle to transfer the same capabilities to systems lacking typical volatile memory primitives, monitoring software, and the compatible operating-system primitives necessary for conducting forensic investigations. Even worse, SCADA systems are typically not designed and implemented with security in mind, nor were they purpose-built to monitor and record system data at the granularity associated with traditional IT systems. Rather, these systems are often built to control field devices and drive industrial processes. More succinctly, SCADA systems were not designed with a primary goal of interacting with the digital world. Consequently, forensics investigators well-versed in the world of digital forensics and incident response face an array of challenges that prevent them from conducting effective forensic investigation in environments with vast amounts of critical infrastructure. In order to bring SCADA systems within the reach of the armies of digital forensics professionals and tooling already available, both researchers and practitioners need a guide to the current state-of-the-art techniques, a road-map to the challenges lying on the path forward, and insight into the future directions R&D must move towards. To that end, this paper presents a survey into the literature on digital forensics applied to SCADA systems. We cover not only the challenges to applying digital forensics to SCADA like most other reviews, but also the range of proposed frameworks, methodologies, and actual implementations in literature.

Asmar Awad, Rima↗

Monitoring Operational States of a Nuclear Reactor Using Seismoacoustic Signatures and Machine Learning

Monitoring nuclear reactors is an important safety and security task with growing requirements. We explore the possibility of using seismic and acoustic data for inferring the power level of an operating reactor. Continuous data recorded at a single seismoacoustic station that is located about 50 m away from a research reactor was visualized and analyzed. The data show a clear correlation between seismoacoustic features and reactor main operational states. We designed a workflow that includes two machine learning (ML) models to classify the reactor operational states (OFF, transition, and ON) and estimate reactor power levels (10%, 30%, 50%, 70%, and 90%). We applied and compared five ML algorithms for the reactor OFF-transition-ON and four approaches for the power level classification. We also compared the performance of ML models trained with seismic-only, acoustic-only, and both types of data. Five-fold cross validations were implemented to assure a thorough evaluation of the model performances. Additionally, the results show the extreme boosting gradient algorithm worked best for the first model, whereas random forests performed best for the second model. Combining seismic and acoustic data leads to better performance than using a single type of data. Seismic data contributed more than acoustic data for both models. We reached an accuracy of 0.98 for reactor OFF and ON. The accuracies for the transition state and power levels are less optimal with a minimum accuracy of 0.66. However, our results suggest seismic and acoustic data contain useful information about the transition state as well as power levels. Seismic and acoustic data could be integrated with other observations to improve monitoring performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

BioWatch SMS Supervisor Guide

The BioWatch Sample Management System is software developed by Los Alamos National Laboratory to support the Department of Homeland Security BioWatch program. Field Operations Supervisors use the software to record, track, and manage data for the BioWatch sample collection process. This includes installing the software, creating and updating databases, assigning user IDs and passwords, editing and customizing reports, correcting data errors, recovering lost data, and troubleshooting. The BioWatch SMS Field Operations Supervisor Guide provides procedures for each task a Field Operations Supervisor performs. The reference information in this guide includes appendices of error messages and solutions, terms used interchangeably, and safety warnings along with a glossary, an index, and a list of suggested reference documents.

99 GENERAL AND MISCELLANEOUS↗

Coding a Weather Model: DOE-FIU Science & Technology Workforce Development Program.

DOE Fellow, Andres Cremisini, completed a 10-week internship with Sandia National Laboratories (SNL) in Albuquerque, New Mexico. Under the management of Kristopher Klingler and the mentorship of Jon Bradley, he was tasked with conceiving and coding a realistic weather model for use in physical security applications. The objective was to make a weather model that could use real data to accurately predict wind and precipitation conditions at any location of interest on the globe at any user-determined time. The intern received guidance on software design, the C++ programming language and clear communication of project goals and ongoing progress. In addition, Mr. Cremisini was given license to structure the program however he best saw fit, an experience that will benefit ongoing research endeavors.

54 ENVIRONMENTAL SCIENCES↗

2014 Annual Site Environmental Report for Sandia National Laboratories, New Mexico

Sandia National Laboratories is a multiprogram laboratory managed and operated by Sandia Corporation (Sandia), a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000. This Annual Site Environmental Report summarizes data and the compliance status of Sandia’s sustainability, environmental protection, and monitoring programs at Sandia National Laboratories, New Mexico, during calendar year 2014. Major environmental programs include air quality, water quality, groundwater protection, terrestrial surveillance, waste management, pollution prevention, environmental restoration, oil and chemical spill prevention, and implementation of the National Environmental Policy Act. Environmental monitoring and surveillance programs are required by DOE O 231.1B, Change 1, Environment, Safety, and Health Reporting .

54 ENVIRONMENTAL SCIENCES↗

Rock Valley Dense Gravity Acquisition

Characterizing the shallow structure of the Rock Valley region of the Nevada National Security Site is a critical component of the Rock Valley Direct Comparison project. Geophysical data of the region is needed for operational decisions, to constrain geologic models used for simulation, and to facilitate the analysis of future explosive source data. Local measurements of gravity are a key piece of geophysical information that helps to resolve the underlying geologic composition, fault structure, and density characteristics, yet, in the Rock Valley region these measurements are sparse on the scale of the testbed. In this report, we present the details of a recent gravity data acquisition survey designed to collect a dense dataset in the region of interest that complements the existing gravity work but greatly enhances our resolution. This dataset will be integrated with a complementary Los Alamos National Laboratory gravity collection and combined with the existing seismic data in a joint inversion. These measurements were conducted over two weeks with a portable gravimeter and high-resolution GPS and include repeat measurements at a USGS base station as well as reoccupation of gravity sites in the regional dataset. This collection of over 100 new dense gravity measurements will facilitate refinement of the existing Geologic Framework Model and directly complement newly acquired dense seismic data, ultimately improving the project’s ability to investigate the direct comparison of shallow earthquake and explosive sources.

58 GEOSCIENCES↗

Facial Named Entity Recognition by Attention-Based Graph Convolutional Neural Network

In the realm of facial recognition and analysis, the ability to accurately cluster large datasets of facial images stands as a cornerstone for various applications, ranging from security surveillance to user biometric identification. This project evolves a novel approach to facial data clustering by embedding facial images into a high-dimensional vector space using an advanced embedding model trained on separate data and assumes a graph-like structure on the high-dimensional vectors. We find our method works significantly better than common shallow methods.

97 MATHEMATICS AND COMPUTING↗

The collapse of the wien tail in the coldest brown dwarf? Hubble Space Telescope near-infrared photometry of WISE J085510.83-071442.5

We present Hubble Space Telescope (HST) near-infrared photometry of the coldest known brown dwarf, WISE J085510.83−071442.5 (WISE 0855−0714). WISE 0855−0714 was observed with the Wide Field Camera 3 (WFC3) on board HST using the F105W, F125W, and F160W filters, which approximate the Y, J, and H near-infrared bands. WISE 0855−0714 is undetected at F105W with a corresponding 2σ magnitude limit of ∼26.9. We marginally detect WISE 0855−0714 in the F125W images (S/N ∼ 4), with a measured magnitude of 26.41 ± 0.27, more than a magnitude fainter than the J-band magnitude reported by Faherty et al. WISE J0855−0714 is clearly detected in the F160W band, with a magnitude of 23.86 ± 0.03, the first secure detection of WISE 0855−0714 in the near-infrared. Based on these data, we find that WISE 0855−0714 has extremely red F105W−F125W and F125W−F160W colors relative to other known Y dwarfs. We find that when compared to the models of Saumon et al. and Morley et al., the F105W−F125W and F125W−F160W colors of WISE 0855−0714 cannot be accounted for simultaneously. These colors likely indicate that we are seeing the collapse of flux on the Wien tail for this extremely cold object.

79 ASTRONOMY AND ASTROPHYSICS↗

Bridging the Gap from Networking Technologies to Applications: Workshop Report

The objective of the Next Generation Internet (NGI) Federal program is threefold, encompassing development of networking technologies, high-performance network testbeds, and revolutionary applications. There have been notable advances in emerging network technologies and several nationwide testbeds have been established, but the integration of emerging technologies into applications is lagging. To help bridge this gap between developers of NGI networking technologies and developers of NGI applications, the NASA Research and Education Network (NREN) project hosted a two-day workshop at NASA Ames Research Center in August 1999. This paper presents a summary of the results of this workshop and also describes some of the challenges NREN is facing while incorporating new technologies into HPCC and other NASA applications. The workshop focused on three technologies - Quality of Service (QoS), advanced multicast, and security-and five major NGI application areas - telemedicine, digital earth, digital video, distributed data-intensive applications, and computational infrastructure applications. Network technology experts, application developers, and NGI testbed representatives came together at the workshop to promote cross-fertilization between the groups. Presentations on the first day, including an overview of the three technologies, application case studies and testbed status reports, laid the foundation for discussions on the second day. The objective of these latter discussions, held within smaller breakout groups, was to establish a coherent picture of the current status of the various pieces of each of the three technologies, to create a roadmap outlining future technology development, and to offer technological guidance to application developers. In this paper we first present a brief overview of the NGI applications that were represented at the workshop, focusing on the identification of technological advances that have successfully been incorporated in each application and technological challenges that remain. Next we present the technology roadmaps that were created at the workshop, summarizing the status of various mechanisms that are currently under development and forecasting when various advances are likely to occur within the next one-to-three-year time span. Then we identify issues that were raised at the workshop that might hinder technology development or that might impede integration into NGI applications. We also report some specific guidelines that were offered at the workshop to enable application developers to integrate and effectively use emerging NGI technology building blocks. Finally, we describe NREN activities to incorporate emerging technologies into NASA applications. These activities include support for other NASA High-Performance Computing and Communications Program areas such as IPG (Information Power Grid), support for NASA science enterprises such as Earth science and Mars program prototyping activities, support for satellite/terrestrial networking applications such as the TransAtlantic and TransPacific demonstrations and the Interplanetary Internet, support for NASA telemedicine applications such as the Virtual Collaborative Clinic, and participation in NGI advanced technology testbed initiatives such as the QBone and the NTON/Supernet. For each activity we highlight the primary technological challenge that is associated with it.

Johnson, Marjory J.↗

The Next Generation of Space Telemetry and Telecommand Standards

New standards for space/ground communications protocols are suggested for the following areas: a) file transfer based on the Internet, b) transport based on the Internet TCP/UDP, c) security derived from the ISO NLSP, a new space network, and a new space data link.

spacecraft communications telemetry standards tele↗

In-Time Non-Participant Casualty Risk Assessment to Support Onboard Decision Making for Autonomous Unmanned Aircraft

Numerous operational paradigms, technologies, and missions are emerging as newcomers to the National Airspace System (NAS) develop small Unmanned Aircraft Systems (sUAS), personal air vehicles and other Urban Air Mobility (UAM) concepts. As the list of applications expands, maintaining the safety of the current airspace system remains one of the core concerns preventing widespread commercial implementation of these concepts. Further, the risks associated with unmanned aircraft operations themselves have to be recognized and mitigated in a timely manner. Safety-critical risks include, but are not limited to, flight outside of approved airspace, unsafe proximity to people or property, critical system failures, loss-of control, and cyber-security related risks. Instead of reacting to accidents, a set of predictive and data-driven risk monitoring, assessment, and mitigation capabilities are envisioned to help capture and eliminate hazards as these systems become operational. NASA’s System-wide Safety project is performing R&D on such a safety assurance concept. As part of this concept, this paper describes an architecture that continuously monitors a diverse set of onboard and ground-based sources to estimate and predict non-participant casualty risk during flight. Timely identification of the changing nature of this risk can inform decision making processes to mitigate current and impending situations.

Ancel, Ersin↗

Occupational Radiation Exposure Report for Calendar Year 2023

The U.S. Department of Energy Occupational Radiation Exposure Report for Calendar 2023 presents the results of analyses of occupational radiation exposures at the U.S. Department of Energy (DOE), including the National Nuclear Security Administration (NNSA) operations, during calendar year 2023. This report includes occupational radiation exposure data for over 80,000 DOE Federal employees, contractors, and subcontractors as well as members of the public who have worked in or entered controlled areas monitored for exposure to radiation. DOE publishes this annual report to provide DOE Management, Program Offices, workers, health physicists, and other stakeholders an evaluation of DOE-wide performance regarding compliance with Title 10 of the Code of Federal Regulations (CFR) Part 835, Occupational Radiation Protection (10 CFR 835) radiation exposure limits and adherence to as low as reasonably achievable principles. This report provides a discussion regarding radiation protection and exposure reporting requirements. It also includes calendar year (CY) 2023 information and analyses regarding aggregate, individual, site, DOE Program, transient individuals’ dose, as well as a historical review of DOE exposure data. DOE continues to be diligent in protecting its workers and the public from exposure to radiation from DOE operations as illustrated by the results contained in this report.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗