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DOE OSTI2019

Technology Integration 2018 Annual Progress Report

The FY 2018 Technology Integration Annual Progress Report covers 28 multi-year projects funded by the Vehicle Technologies Office. The report includes information on 21 competitively awarded projects, ranging from training on alternative fuels and vehicles for first responders, to safety training and design for maintenance facilities housing gaseous fuel vehicles, to electric vehicle community partner programs. It also includes seven projects conducted by several of VTO’s national laboratory partners, Argonne National Laboratory, Oak Ridge National Laboratory and the National Renewable Energy Laboratory. These projects range from a Technical Assistance project for business, industry, government and individuals, to the EcoCar 3 Student Competition, and the Fuel Economy Information Project.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

NCSP – AWE Collaboration [Slides]

Several points of collaboration between NCSP and AWE are noted, including the CIDAAS IS589 installation plan, CIDAAS testing, nuclear verification and detector physics, nuclear material control and nuclear security, and hands on criticality safety training.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Sandtank-ML: An Educational Tool at the Interface of Hydrology and Machine Learning

Hydrologists and water managers increasingly face challenges associated with extreme climatic events. At the same time, historic datasets for modeling contemporary and future hydrologic conditions are increasingly inadequate. Machine learning is one promising technological tool for navigating the challenges of understanding and managing contemporary hydrological systems. However, in addition to the technical challenges associated with effectively leveraging ML for understanding subsurface hydrological processes, practitioner skepticism and hesitancy surrounding ML presents a significant barrier to adoption of ML technologies among practitioners. In this paper, we discuss an educational application we have developed—Sandtank-ML—to be used as a training and educational tool aimed at building user confidence and supporting adoption of ML technologies among water managers. We argue that supporting the adoption of ML methods and technologies for subsurface hydrological investigations and management requires not only the development of robust technologic tools and approaches, but educational strategies and tools capable of building confidence among diverse users.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2002

Developments in Understanding Stability as Applied to Magnetic Levitated Launch Assist

Magnetic levitation is a promising technology, with the potential of constituting the first stage of a third generation space transportation system. Today, the Space Shuttle burns on the order of one million pounds of solid rocket propellant to bring the orbiter and external tank to nearly Mach 1 (1,000 kph). Imagine the reductions in launch vehicle weight, complexity and risk if an aerospace vehicle could be accelerated to the same speed utilizing about $1,000 of off-board electrical energy stored in flywheels. After over two decades of development, maglev trains travel on full-scale demonstration tracks in Germany and Japan reaching speeds approaching 500 kph. Encouraging as this may appear, the energy and power required to accelerate a 1 million pound launch vehicle to 1,000 kph would radically redefine the state-of-the-art in electrical energy storage and delivery. Reaching such a goal will require levitation with sufficient stability to withstand an operating environment fundamentally different from that of a high-speed train. Recently NASA let contracts for the construction of three maglev demonstration tracks. This construction and several associated trade studies represent a first-order investigation into the feasibility of maglev launch assist. This report provides a review of these efforts, other government sponsored maglev projects and additional technical literature pertinent to maglev stability. This review brings to light details and dimensions of the maglev stability problem which are not found in previous NASA-sponsored trade studies and which must be addressed in order to realize magnetic levitation as a launch assist technology.

Gering, James A.↗

DOE OSTI2015

The conduct of the united states department of energy nuclear criticality safety program hands-on training and education courses - 14621

The United States Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP), funded and managed by the National Nuclear Security Administration (NNSA), offers courses to educate nuclear criticality safety (NCS) engineers, process supervisors, and others, and to provide experimental, hands-on training addressing important characteristics of neutron multiplying systems. This training satisfies the American National Standard Institute/American Nuclear Society (ANSI/ANS)-8.26-2007 requirement for participating in hands-on experiments with fissionable materials and provides awareness and understanding of DOE Orders, Guides and Rules, ANS standards, and hazard identification techniques, as well as control design, implementation, and maintenance in criticality safety evaluations. Since the pilot course was developed in 2011, a variety of courses have been developed for NCS practitioners and process supervisors. Attendees have come from several US and international sites. Through NCSP international collaborations and relationships, students from the Atomic Weapons Establishment (AWE) in the United Kingdom, Atomic Energy of Canada, and the Institute for Radiation Protection and Nuclear Safety in France have participated in these courses in the US. Manager courses are available for process supervisors and operations managers with NCS responsibilities in their daily jobs. Manager courses are taught at Sandia National Laboratory (SNL) and the National Criticality Experiments Research Center (NCERC); they offer a combination of hands-on experiments and classroom discussions. A two-week course is also offered for NCS practitioners, with a week of classroom instruction at Los Alamos National Laboratory (LANL) focused on generation of NCS evaluations, and a week of hands-on training utilizing the critical assemblies at either SNL or NCERC. Cleared students can attend the hands-on training at either SNL or NCERC, and uncleared students can attend at SNL. Courses continue to evolve and continuously improve as important elements of NCS evaluations (e.g., human factors, non-destructive assay (NDA) techniques, process criticality accident lessons-learned, and hand calculation methods) are integrated with criticality safety evaluation exercises. Courses include tours of process operations at SNL, NCERC, and LANL, and interaction with instructors experienced in conducting critical experiments and working in NCS. The NNSA NCSP provides management, funding, and technical direction for these courses and makes them available with no tuition cost to NCS practitioners. This paper provides a status report to the NCS community on the conduct of these courses and how they will likely evolve in the future. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Evaluation of Technical and Utility Programmatic Challenges With Residential Forced-Air Integrated Space/Water Heat Systems

This multi-unit field demonstration of combined space and water heating (combi) systems was conducted to help document combi system installation and performance issues that needed to be addressed through research. The objective of the project was to put commercialized forced-air tankless combi units into the field through local contractors that were trained by manufacturers and GTI staff under the auspices of utility-implemented ETPs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Evaluation of Technical and Utility Programmatic Challenges With Residential Forced-Air Integrated Space/Water Heat Systems

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Usefulness of Cone-Beam Computed Tomography and Automatic Vessel Detection Software in Emergency Transarterial Embolization

BackgroundThis study was designed to evaluate the utility of dual phase cone beam computed tomography (DP-CBCT) and automatic vessel detection (AVD) software to guide transarterial embolization (TAE) of angiographically challenging arterial bleedings in emergency settings.MethodsTwenty patients with an arterial bleeding at computed tomography angiography and an inconclusive identification of the bleeding vessel at the initial 2D angiographic series were included. Accuracy of DP-CBCT and AVD software were defined as the ability to detect the bleeding site and the culprit arterial bleeder, respectively. Technical success was defined as the correct positioning of the microcatheter using AVD software. Clinical success was defined as the successful embolization. Total volume of iodinated contrast medium and overall procedure time were registered.ResultsThe bleeding site was not detected by initial angiogram in 20 % of cases, while impossibility to identify the bleeding vessel was the reason for inclusion in the remaining cases. The bleeding site was detected by DP-CBCT in 19 of 20 (95 %) patients; in one case CBCT-CT fusion was required. AVD software identified the culprit arterial branch in 18 of 20 (90 %) cases. In two cases, vessel tracking required manual marking of the candidate arterial bleeder. Technical success was 95 %. Successful embolization was achieved in all patients. Mean contrast volume injected for each patient was 77.5 ml, and mean overall procedural time was 50 min.ConclusionsC-arm CBCT and AVD software during TAE of angiographically challenging arterial bleedings is feasible and may facilitate successful embolization. Staff training in CBCT imaging and software manipulation is necessary.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2025

A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring

We introduce a novel digital twin (DT) framework for the predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the DT framework can be used to enhance automotive safety and efficiency, and how the technical challenges can be overcome using a three-step approach. First, to manage the data complexity over a long operation span, we employ data reduction techniques to concisely represent physical tires using historical performance and usage data. Relying on these data, for fast real-time prediction, we train a transformer-based model offline on our concise dataset to predict future tire health over time, represented as remaining casing potential (RCP). Based on our architecture, our model quantifies both epistemic and aleatoric uncertainties, providing reliable confidence intervals around predicted RCP. Second, to incorporate real-time data, we update the predictive model in the DT framework, ensuring its accuracy throughout its lifespan with the aid of hybrid modeling and the use of the discrepancy function. Third, to assist decision-making in predictive maintenance, we implement a tire state decision algorithm, which strategically determines the optimal timing for tire replacement based on RCP forecasted by our transformer model. This approach ensures that our DT accurately predicts system health, continually refines its digital representation, and supports predictive maintenance decisions. Furthermore, our framework effectively embodies a physical system, leveraging big data and machine learning (ML) for predictive maintenance, model updates, and decision-making.

advanced computing infrastructure↗

DOE OSTI2024

DOE Support for the 8th International Conference on Attosecond Science (Final Technical Report)

The 8th International Conference on Attosecond Science and Technology (ATTO VIII) was held on the campus of the University of Central Florida in Orlando, FL from July 10-16, 2022. The main objectives of the conference were (i) to outline the state of the art of attosecond research; (ii) to jump-start national and international collaborations that had been hindered by the pandemic; (iii) to promote recruiting and training of postdocs and tenure-track candidates; and (iv) to consolidate the global and diverse identity of the attosecond community.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Real-time Distribution Simulation and Application Development for Power Systems Education

To help bridge the gap between traditional power system engineering instruction and emerging industry needs, a new set of classroom and research tools are needed. Real-time simulation tools emulating power system control room software present an opportunity to introduce students to the array of operational considerations, technical challenges, and decision-making associated with power system operations. The GridAPPS-D platform is proposed to support coursework and academic research as it provides an open-source platform for simulation, application development, and software integration. The GridAPPS-D platform, simulation capabilities, development environment, and interactive training are discussed in the context of lessons-learned from implementation for undergraduate and graduate students in the US and India. A series of potential GridAPPS-D supported academic capabilities are introduced.

Active distribution networks, open educational res↗

DOE OSTI2013

Nuclear Fabrication Consortium

This report summarizes the activities undertaken by EWI while under contract from the Department of Energy (DOE) Office of Nuclear Energy (NE) for the management and operation of the Nuclear Fabrication Consortium (NFC). The NFC was established by EWI to independently develop, evaluate, and deploy fabrication approaches and data that support the re-establishment of the U.S. nuclear industry: ensuring that the supply chain will be competitive on a global stage, enabling more cost-effective and reliable nuclear power in a carbon constrained environment. The NFC provided a forum for member original equipment manufactures (OEM), fabricators, manufacturers, and materials suppliers to effectively engage with each other and rebuild the capacity of this supply chain by : Identifying and removing impediments to the implementation of new construction and fabrication techniques and approaches for nuclear equipment, including system components and nuclear plants. Providing and facilitating detailed scientific-based studies on new approaches and technologies that will have positive impacts on the cost of building of nuclear plants. Analyzing and disseminating information about future nuclear fabrication technologies and how they could impact the North American and the International Nuclear Marketplace. Facilitating dialog and initiate alignment among fabricators, owners, trade associations, and government agencies. Supporting industry in helping to create a larger qualified nuclear supplier network. Acting as an unbiased technology resource to evaluate, develop, and demonstrate new manufacturing technologies. Creating welder and inspector training programs to help enable the necessary workforce for the upcoming construction work. Serving as a focal point for technology, policy, and politically interested parties to share ideas and concepts associated with fabrication across the nuclear industry. The report the objectives and summaries of the Nuclear Fabrication Consortium projects. Full technical reports for each of the projects have been submitted as well.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2011

Technophiles to Newbies: The Challenge of Supporting Distributed Teams to Maintain Engagement in Virtual Worlds

The purpose of this paper is to look for links in a virtual trainee's interest and self-efficacy in a simulated event as it relates to their previous self-reported technical skill level. Ultimately, the idea would be to provide the right amount of support at the right place at the right time to set the conditions for maximum transfer of the skill sets to the work place. An anecdotal recap of a recent experiment of a medium-scale training event produced in a virtual world will provide examples for discussion. In July 2010, a virtual training event was produced for the Air Force Research Lab's Games for Team Training (GaMeTT) at the Patriot Exercise at Volk Field in Wisconsin. There were 29 EMEDS participants who completed the simulated OCO event using the OLIVE gaming engine. Approximately 25 avatars were present at any given time; including role players, observers, coordinators and participants.

Griffith, Karen↗

NASA NTRS2025

Private Astronaut Post-Mission Debrief Interviews Study

BACKGROUND The commercialization of space will increasingly include individuals that are not rigorously-selected, highly-trained professional astronauts. Private astronaut missions (PAMs), such as Axiom-1 in 2022, will continue to travel to the International Space Station in the coming years, but the risk of integrating private astronauts with NASA astronauts has not been clearly quantified nor mitigated. An earlier internal NASA operations assessment, which consisted of a comprehensive literature review and interviews of current NASA experts, found that PAMs are likely to increase the risk to NASA astronauts during integrated missions (Landon, Whiting, Russell, Schorn, Passmore, & Roma, 2022). There are ongoing efforts at NASA to mitigate concerns from a medical, psychological, and technical perspective. NASA experts are working closely with PAM providers to offer recommendations and best practices beyond the limits of requirements to ensure crew health and safety. However, efforts are siloed between groups to some extent, and with the rate of PAMs likely to increase, a more comprehensive and integrated process is needed to reduce the burden on NASA resources. AIMS The purpose of this project is to understand private astronauts’ motivations for journeying to space, their pre-mission preparation period, and their experiences in space. Data will be collected via private astronaut post-mission debrief interviews. This data will inform training needs and in-mission support needed for missions that include private astronauts; the preparation NASA astronauts and mission support personnel will need to work with these integrated crews; and gaps in knowledge to guide research and countermeasure development. Our study aims to (1) Characterize risks posed by commercialization and private astronaut crew integration in spaceflight operations, as it relates to Team, Human Systems Integration Architecture (HSIA), and Behavioral Medicine (BMed) Risks, (2) Recommend potential countermeasures and identify gaps in current research. Countermeasures may be related to crew selection and composition, training, crew support systems (e.g., medical/psychological support, support from Mission Control, on-board resources), and habitability and human factors design. METHOD The BHP Lab will conduct 30-minute interviews with up to eight (8) private astronaut mission (PAM) astronauts (e.g., Axiom) and spaceflight participants (e.g., SFPs or “free flyers” on Polaris Dawn) per year from 2024-2030 to discuss knowledge gaps and needs related to selection and assessment, crew composition, training, crew support systems (e.g., medical/psychological support, support from Mission Control, onboard resources), and habitability and human factors design, which may influence the risk to NASA astronauts. Interviews will then be coded using thematic analysis and interpreted with the assistance of lexical analysis software (e.g., LIWC). As of the end of 2024, we have collected data from one PAM crew. At the conclusion of data collection in 2030, a final report will be prepared integrating all data collected by 2031. SUMMARY Post-return interviews of private astronauts are being conducted to understand their experiences and inform training and countermeasures to ensure the safety of all who journey to the ISS.

Private Astronaut Missions↗

DOE OSTI2016

Research Projects for Interrogations of Biological Systems: Training for the Development of Novel Radiotracers

This grant was situated at the University of Missouri to train Ph.D. scientists in radiochemistry and synthetic chemistry in conjunction with Faculty from the Interdisciplinary Plant Group, Division of Biological Sciences, the MU Research Reactor Center, Molecular Biology and the Radiopharmaceutical Sciences Institute. This project was collaborative with Brookhaven National Laboratory (Richard Ferrieri, PI). Projects for the Ph.D. candidates included novel probe development for peptides, nucleosides, small molecules or radiometals, the direct use of radiometals as probes, or nuclear techniques for analysis. The projects for the postdoctoral fellow involved synthetic chemistry for the preparation of precursors for novel tracers that will be radiolabeled with 18 F or other appropriate radionuclides. The skill sets of our team members allowed us to prepare probes with positron or single photon emitters, as well as ones that are dual-labeled (fluorescent and radiolabeled). We focused our technical advances to those that will be broadly applicable to any research field.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

NASA NTRSDate not supplied

The NASA Space Life Sciences Training Program (SLSTP)

The NASA Space Life Sciences Training Program (SLSTP) provides undergraduate students entering their junior or senior years with professional experience in space life science disciplines. This challenging ten-week summer program is hosted by NASA Ames Research Center. The primary goal of the program is to train the next generation of scientists and engineers, enabling NASA to meet future research and development challenges in the space life sciences. SLSTP Research Associates (RAs) work closely with NASA scientists and engineers on cutting-edge research and technology development. In addition to providing hands-on research experience and the ability to present their findings in a professional forum, SLSTP RAs attend technical lectures given by experts on a wide range of topics, tour NASA and other research facilities, participate in leadership and team building exercises, and develop a group project. Historically the SLSTP program has been held at Ames Research Center in Mountain View, California. However, due to the pandemic, both the 2020 and 2021 programs were restructured to be conducted virtually, enabling the program to continue despite the challenging times. For this presentation, we will highlight program processes, student recruitment, accomplishments, goals, and feedback from alumni and mentors since 2013. To date, 92 RAs from 64 different academic institutions in 29 states, 21 staffers, and 37 mentors have participated in the program. The SLSTP is funded by NASA’s Space Biology Program, which is part of the Biological and Physical Sciences Division of NASA. The SLSTP is managed by the Space Biology Project within the Science Directorate at Ames Research Center.

Training Space Biosciences Student↗

DOE OSTI2025

Labels as a feature: Network homophily for systematically annotating human GPCR drug-target interactions

Machine learning has revolutionized drug discovery by enabling the exploration of vast, uncharted chemical spaces essential for discovering novel patentable drugs. Despite the critical role of human G protein-coupled receptors in FDA-approved drugs, exhaustive in-distribution drug-target interaction testing across all pairs of human G protein-coupled receptors and known drugs is rare due to significant economic and technical challenges. This often leaves off-target effects unexplored, which poses a considerable risk to drug safety. In contrast to the traditional focus on out-of-distribution exploration (drug discovery), we introduce a neighborhood-to-prediction model termed Chemical Space Neural Networks that leverages network homophily and training-free graph neural networks with labels as features. We show that Chemical Space Neural Networks’ ability to make accurate predictions strongly correlates with network homophily. Thus, labels as features strongly increase a machine learning model’s capacity to enhance in-distribution prediction accuracy, which we show by integrating labeled data during inference. We validate these advancements in a high-throughput yeast biosensing system (3773 drug-target interactions, 539 compounds, 7 human G protein-coupled receptors) to discover novel drug-target interactions for FDA-approved drugs and to expand the general understanding of how to build reliable predictors to guide experimental verification.

Hansson, Frederik G↗