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139 records · Page 8

Ongoing Work: A Prototype Dataset for Low-flying Autonomous Medical UAS Operations

This paper presents ongoing work to create a dataset for low-flying autonomous medical UAS operations, focused on human stance recognition. This is an exploration of the viability of airborne classification for the Drone as a First Responder (DFR) concept in which a UAS arrives at the scene of an incident before emergency response personnel can get there and provides some level of situational awareness for the personnel arriving to the scene. Future incarnations could also see the UAS administer some level of care to injured parties at the scene. The data set, focused on detecting human stance, being developed here is the result of 30 test flights at NASA Langley Research Center in early 2024. In addition to flights where the participant (an anthropomorphic testing device or human) is alone in the viewing area holding a particular stance, two emergency scenes have been fabricated and collected through video - ``bike crash'' and ``difficult camping''. These test flights include four human participants. The contribution of this work upon completion will be a publicly available data set for the development of classification engines focused on human stance, and in the future, even triage.

Uncrewed Aerial Systems↗

Making Heliophysics Research More Open and Accessible at the Community Coordinated Modeling Center (CCMC)

The Space Weather and Heliophysics modeling community seeks to improve our understanding of space weather events and their impact on human activities. The Community Coordinated Modeling Center’s (CCMC, https://ccmc.gsfc.nasa.gov) mission is to support the community by providing a convenient collaborative platform that brings together space weather models, model simulation data, curated datasets of solar events, and associated value-added services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, triage designated R2O models, as well as collaborate on a continuously updated archive of model run results. This presentation reports on CCMC’s ongoing efforts in making Heliophysics models and data more accessible, open, and reproducible. We will also explore interoperability within the ecosystem of CCMC services and how this ecosystem interoperates with external partner services and data streams.

space weather↗

Lowering Barriers to Science and Space Weather Research at the Community Coordinated Modeling Center (CCMC)

The Space Weather and Heliophysics research and modeling community has been pushing the limits of our ability to understand and predict space weather events. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) supports the community by providing a convenient collaborative platform hosting space weather models, model simulation data, curated datasets of solar events, and associated value-added services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, triage designated R2O models, as well as collaborate on a continuously updated archive of model run results. We will focus on CCMC’s ongoing commitment to the principles and guidelines of the Open Science initiative. Particularly, we will discuss our work towards making our services more transparent and our library of model simulations more accessible, open, and reproducible. We will introduce our recent tools for data discovery and correlative analysis designed to further increase the value of the user-generated data and metadata. We will also present our recent work on making heliophysical models more accessible and open to the community, particularly through simplified user experience and expert domain support. We will report on our progress in establishing an inter-center infrastructure with the ESA Virtual Space Weather Modelling Centre (VSWMC), designed to cross organizational boundaries and provide streamlined access to a joint palette of the models.

space weather↗

NARAC Modeling During the Response to the Fukushima Dai-ichi Nuclear Power Plant Emergency

This paper summarizes the activities of the National Atmospheric Release Advisory Center (NARAC) during the Fukushima Dai-ichi nuclear power plant crisis. NARAC provided a wide range of products and analyses as part of its support including: (1) Daily Japanese weather forecasts and hypothetical release (generic source term) dispersion predictions to provide situational awareness and inform planning for U.S. measurement data collection and field operations; (2) Estimates of potential dose in Japan for hypothetical scenarios developed by the Nuclear Regulatory Commission (NRC) to inform federal government considerations of possible actions that might be needed to protect U.S. citizens in Japan; (3) Estimates of possible plume arrival times and dose for U.S. locations; and (4) Plume model refinement and source estimation based on meteorological analyses and available field data. The Department of Energy/National Nuclear Security Administration (DOE/NNSA) deployed personnel to Japan and stood up 'home team' assets across the DOE complex to aid in assessing the consequences of the releases from the Fukushima Dai-ichi Nuclear Power Plant. The DOE Nuclear Incident Team (NIT) coordinated response activities, while DOE personnel provided predictive modeling, air and ground monitoring, sample collection, laboratory analysis, and data assessment and interpretation. DOE deployed the Aerial Measuring System (AMS), Radiological Assistance Program (RAP) personnel, and the Consequence Management Response Team (CMRT) to Japan. DOE/NNSA home team assets included the Consequence Management Home Team (CMHT); National Atmospheric Release Advisory Center (NARAC); Radiation Emergency Assistance Center/Training Site (REAC/TS); and Radiological Triage. NARAC was activated by the DOE/NNSA on March 11, shortly after the Tohoku earthquake and tsunami occurred. The center remained on active operations through late May when DOE ended its deployment to Japan. Over 32 NARAC staff members, supplemented by other LLNL scientists, invested over 5000 person-hours of time and generated over 300 analyses and predictions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Top Ten Interaction Challenges in Extreme-Scale Visual Analytics

The chapter presents ten selected user interfaces and interaction challenges in extreme-scale visual analytics. The study of visual analytics is often referred to as 'the science of analytical reasoning facilitated by interactive visual interfaces' in the literature. The discussion focuses on the issues of applying visual analytics technologies to extreme-scale scientific and non-scientific data ranging from petabyte to exabyte in sizes. The ten challenges are: in situ interactive analysis, user-driven data reduction, scalability and multi-level hierarchy, representation of evidence and uncertainty, heterogeneous data fusion, data summarization and triage for interactive query, analytics of temporally evolving features, the human bottleneck, design and engineering development, and the Renaissance of conventional wisdom. The discussion addresses concerns that arise from different areas of hardware, software, computation, algorithms, and human factors. The chapter also evaluates the likelihood of success in meeting these challenges in the near future.

99 GENERAL AND MISCELLANEOUS↗

Data-Intensive Visual Analysis for Cyber Security

Protecting communications networks against attacks where the aim is to steal information, disrupt order, or harm critical infrastructure can require the collection and analysis of staggering amounts of data. The ability to detect and respond to threats quickly is a paramount concern across sectors, and especially for critical government, utility and financial networks. Yet detecting emerging or incipient threats in immense volumes of network traffic requires new computational and analytic approaches. Network security increasingly requires cooperation between human analysts able to spot suspicious events through means such as data visualization and automated systems that process streaming network data in near real-time to triage events so that human analysts are best able to focus their work.

Pike, William A.↗

Advances in Grid Computing for the FabrIc for Frontier Experiments Project at Fermialb

The FabrIc for Frontier Experiments (FIFE) project is a major initiative within the Fermilab Scientic Computing Division charged with leading the computing model for Fermilab experiments. Work within the FIFE project creates close collaboration between experimenters and computing professionals to serve high-energy physics experiments of diering size, scope, and physics area. The FIFE project has worked to develop common tools for job submission, certicate management, software and reference data distribution through CVMFS repositories, robust data transfer, job monitoring, and databases for project tracking. Since the projects inception the experiments under the FIFE umbrella have signicantly matured, and present an increasingly complex list of requirements to service providers. To meet these requirements, the FIFE project has been involved in transitioning the Fermilab General Purpose Grid cluster to support a partitionable slot model, expanding the resources available to experiments via the Open Science Grid, assisting with commissioning dedicated high-throughput computing resources for individual experiments, supporting the eorts of the HEP Cloud projects to provision a variety of back end resources, including public clouds and high performance computers, and developing rapid onboarding procedures for new experiments and collaborations. The larger demands also require enhanced job monitoring tools, which the project has developed using such tools as ElasticSearch and Grafana. in helping experiments manage their large-scale production work ows. This group in turn requires a structured service to facilitate smooth management of experiment requests, which FIFE provides in the form of the Production Operations Management Service (POMS). POMS is designed to track and manage requests from the FIFE experiments to run particular work ows, and support troubleshooting and triage in case of problems. Recently a new certicate management infrastructure called Distributed Computing Access with Federated Identities (DCAFI) has been put in place that has eliminated our dependence on a Fermilab-specic third-party Certicate Authority service and better accommodates FIFE collaborators without a Fermilab Kerberos account. DCAFI integrates the existing InCommon federated identity infrastructure, CILogon Basic CA, and a MyProxy service using a new general purpose open source tool. We will discuss the general FIFE onboarding strategy, progress in expanding FIFE experiments presence on the Open Science Grid, new tools for job monitoring, the POMS service, and the DCAFI project.

Herner, K.↗

Toward a Multimodal-Deep Learning Retrieval System for Monitoring Nuclear Proliferation Activities

As the amount of available data increases, the human ability to locate, process, and analyze it is strained and eventually overwhelmed. To address this challenge for nonproliferation analysts, the authors have been creating a large-scale multimodal retrieval system to help analysts triage and search open source science, technology, and news data for indicators of nuclear proliferation capabilities and activities. The system relies on a set of deep neural networks (DNNs) trained to evaluate conceptual similarities across data modalities, such as text, image, and video. These DNNs can be used to search and prioritize data, according to a nuclear fuel cycle (NFC) process template, that are conceptually closest to the seed query items regardless of data modality. The DNNs have been trained to map conceptually related words, sentences, and images to nearby points in a multimodal feature space, enabling intra- and intermodal retrieval via nearest-neighbor calculations to seed query points. The authors evaluate the system’s ability to retrieve NFC-related data that have been purposely hidden in collections of unrelated background data. They demonstrate quantitative and qualitative results for text-to-image, image-to-image, and image-to-video retrievals. This paper discusses data challenges confronting nonproliferation analysts, describes the DNNs designed to retrieve multimodal data that are proximal in the semantic space, and demonstrates their effectiveness by applying the DNNs to nonproliferation-specific multimodal data sets.

97 MATHEMATICS AND COMPUTING↗

Stable Element Doping of Sol-gel Toward Simulating Environmental Matrix in Surrogate Explosive Nuclear Debris

Training nuclear forensic analysis personnel in post-detonation scenarios is of critical importance to nuclear threat response capabilities. Thus, realistic nuclear debris simulants which resemble the size, color, elemental composition, and radionuclide content of actual nuclear fallout from a recent detonation would be valuable for training nuclear first responders in realistic scenarios. As nuclear fallout types vary significantly in each of these parameters based on detonation environment (rural, urban, maritime etc.) and collection location, the ability to tailor each of these parameters accurately in simulated debris would be of immense benefit to the post-detonation analysis community for training both in-field collections and triage and the validation of laboratory level nuclear forensic techniques. Sol-gel synthesis techniques can provide the tunability of size, shape and composition required for producing surrogate nuclear debris of a wide variety. The sol-gel process consists of forming a metal oxide material, often silica, through polymerization of a metal-alkoxy precursor. In this work, we characterize the ability to load the sol-gel particles with secondary elemental components such as iron, aluminum, and calcium toward approximating the elemental composition of debris from various detonation environments and demonstrate the ability to produce particles with controllable size, shape, and color. We also demonstrate quantitative radionuclide encapsulation toward reproducing the radionuclide content of actual fallout from a recent detonation. Finally, we then employ these techniques in producing simulated aerodynamic debris samples with realistic elemental matrix composition and radionuclide content simulating a recent uranium-fueled detonation taking place in a rural desert environment and compare it to historic fallout from the Nevada Nuclear Security Site.

36 MATERIALS SCIENCE↗

Stable Element Doping of Sol-gel Toward Simulating Environmental Matrix in Surrogate Explosive Nuclear Debris

Training nuclear forensic analysis personnel in post-detonation scenarios is of critical importance to nuclear threat response capabilities. Thus, realistic nuclear debris simulants which resemble the size, color, elemental composition, and radionuclide content of actual nuclear fallout from a recent detonation would be valuable for training nuclear first responders in realistic scenarios. As nuclear fallout types vary significantly in each of these parameters based on detonation environment (rural, urban, maritime etc.) and collection location, the ability to tailor each of these parameters accurately in simulated debris would be of immense benefit to the post-detonation analysis community for training both in-field collections and triage and the validation of laboratory level nuclear forensic techniques. Sol-gel synthesis techniques can provide the tunability of size, shape and composition required for producing surrogate nuclear debris of a wide variety. The sol-gel process consists of forming a metal oxide material, often silica, through polymerization of a metal-alkoxy precursor. In this work, we characterize the ability to load the sol-gel particles with secondary elemental components such as iron, aluminum, and calcium toward approximating the elemental composition of debris from various detonation environments and demonstrate the ability to produce particles with controllable size, shape, and color. We also demonstrate quantitative radionuclide encapsulation toward reproducing the radionuclide content of actual fallout from a recent detonation. Finally, we then employ these techniques in producing simulated aerodynamic debris samples with realistic elemental matrix composition and radionuclide content simulating a recent uranium-fueled detonation taking place in a rural desert environment and compare it to historic fallout from the Nevada Nuclear Security Site.

36 MATERIALS SCIENCE↗

When Every Drum is a Win - Tackling a Thirty-Five Thousand Drum Legacy - 20064

Cameco Corporation's (Cameco) Port Hope Conversion Facility (PHCF) was previously owned by the federal Crown Corporation, Eldorado Nuclear, which held a significant inventory of legacy waste material at the time Cameco was formed in 1988. As a result, Cameco was granted an allocation of 150,000 cubic metres of space in the Long-Term Waste Management Facility (LTWMF) located in the Municipality of Port Hope (MPH), which opened to the receipt of Cameco material in June 2018. Cameco is currently undertaking a major site cleanup and renewal of its Port Hope Conversion Facility (PHCF) which is known as the Vision in Motion (VIM) project. Over its operating history, Eldorado accumulated an inventory of over 35,000 drums of accumulated waste that was primarily stored at two offside warehouse locations. In 2017 and 2018, the project focused on repackaging two well characterized legacy wastes (magnesium fluoride slag and depleted uranium titanium oxide) from one of the two offsite locations. At the conclusion of this work, approximately 15,000 drums of these wastes had been repackaged and disposed of at the LTWMF. There remained approximately 1000 drums from this location that either could not be repackaged safely or were different waste types and required further verification and/or processing. The buildings at this location were scheduled for demolition in early 2019, which triggered the development of a process for triaging legacy drums in August 2018, which allowed for preparation and shipment of approximately half of these drums to the LTWMF by March 2019, with the remainder moved to the second offsite warehouse location in February 2019 for further characterization which is ongoing. This paper will discuss key lessons learned as the drummed legacy waste disposal inventory has been reduced to approximately half of the initial inventory. This will include the development of an alternate packaging process; prioritization of characterization activities and selection of techniques where minimal inventory information is available; determination of next step(s) for each drum as it is assessed; key safety considerations; and how to make inroads into an overwhelming task while under public and regulatory scrutiny. In a relatively short period of time, significant progress has been made to organize and gather information about the legacy waste, update the inventory records and determine the most appropriate pathways (i.e. LTWMF disposal, disposal at another appropriate facility, site storage until future processing and/or disposal). Since 2017 the volume of the decades-old legacy waste inventory has decreased significantly. With the majority of the known materials safely disposed of at the LTWMF, every drum removed from the endless rows of 20,000 pyramidally-stacked waste drums with limited history that is safely characterized, prepared and shipped is considered a win. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Anatomy of a Turtle Confiscation: What to Expect When You're Not Expecting and Recommendations for Improving Outcomes

Turtles are being subjected to unprecedented collection for the illegal wildlife trade, but only a portion of the trade is detected. When confiscations do happen, wildlife agencies must decide what to do with those animals—euthanize them, place them in permanent captivity, or release them back into the wild. Here, we present a case study of a confiscation of .200 eastern box turtles (Terrapene carolina carolina) and our efforts to repatriate them back to the wild. Twentyfive percent of turtles died in captivity, and at least another 33% died during the soft-release phase. Approximately half of the confiscated turtles survived until they were released from their soft-release pen 9 months post-confiscation. For each phase, from the time turtles were seized until released, we describe our objectives, the challenges we encountered, and our recommendations for improving future turtle confiscations. Given the extended stressful conditions that confiscated turtles often experience before being seized, it is important to recalibrate our expectations regarding future confiscation outcomes.

60 APPLIED LIFE SCIENCES↗