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

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At least 523 records · Page 29

Nuclear Science Training for Secondary School Teachers at Argonne National Laboratory - 2019

In continued support of International Atomic Energy Agency (IAEA) project RAS/0/079, with its stated goal to educate 1 million students on the topic of nuclear science by 2021, Argonne National Laboratory (Argonne) hosted its second two-week nuclear science and technology training course for secondary school teachers in October 2019. A modified course format was adopted based on experience from the first course held at Argonne in 2018, along with similar project workshops held across the world. The results of the course, in terms of both technical knowledge retention and teaching capabilities, demonstrated the benefits of the revised approach.

Grabaskas, David↗

Solar Ready Vets: Training, Credentialing and Career Pathways

The Solar Ready Vets team is expanding and accelerating veterans access to solar training and career pathways across the industry. Join The Solar Foundation and NABCEP to learn about solar career development resources and initiatives for veterans.

14 SOLAR ENERGY↗

Forewarning of Bridge Failure Without Algorithm Training

Forewarning of bridge failure without algorithm training uses Griffith's criterion for failure with crack growth induced by structural defamations under load in combination with a statistical criterion for forewarning under cyclic loading.

Abercrombie, Robert↗

How to Read the Snowmass White Papers on Power Dynamics in Physics, Informal Socialization in Physics Training, and Policing and Gatekeeping in STEM

The Community Engagement Frontier presents this set of three white papers, as part of Snowmass 2021. These papers address critical issues -- Power Dynamics in Physics, Informal Socialization in Physics Training, and Policing and Gatekeeping in STEM -- that make significant impacts on the experiences of the people who work in and learn particle physics. In this introductory document, we present crosscutting concepts that appear in each paper, and some advice on how to manage readers' responses to the contents. We expect that you will learn something new here. We hope that whatever you encounter, you will be energized to increase justice in this discipline we all love.

Hodari, Apriel K.↗

Emulating Variable Uranium Enrichments With Radiation Signature Training Devices (RSTD)

Radiological signature training devices (RSTDs) are sealed sources (or assemblies of sources) that emulate the radiation signature of larger masses of special nuclear material for passive detection while maintaining a minimal logistical footprint in security, radiological safety, criticality safety, and transportation requirements. Previous work focused on emulation of large quantities of highly enriched uranium for search and field identification with radioisotope identification detectors and mobile systems. New work has expanded into investigating use of the RSTDs with laboratory safeguards tools, such as MGAU and FRAM, and emulating uranium spectra of multiple enrichments over more energy regions (particularly the x-ray region).

Blessinger, Christopher S.↗

Microgrid Training Session 5: Alternative Solutions to Microgrids

This presentation is the second session of a microgrid training series for the Air Force. Microgrids have advantages over other solutions; however, microgrids have their own costs in terms of finance and operations. This session will help attendees identify alternative solutions to specific issues.

Air Force↗

Surrogate isotope-containing materials for emergency response training and Methods of formation and dispersal

Surrogate materials are in the form of solid particles that include surrogate isotopes, namely, short-lived isotopes selected and formed to serve as surrogates for the radioactive materials of a nuclear fallout without including isotopes that are, or that decay to, biologically or environmentally deleterious and persistent isotopes. The surrogate material may be formed using high-purity reactant material and irradiation and separation techniques that enable tailoring of the isotopes and ratios thereof included in the surrogate material, and the surrogate material may be dispersed, e.g., in a training environment, in solid form.

Carney, Kevin P.↗

Power supply circuit with multiple stages for converting high voltage to low voltage and power train having the same

A power supply circuit for converting a first voltage to a second voltage where the first voltage is greater than the second voltage, and a power train having the same, are provided. The power supply circuit may have multiple stages and each stage of the power supply circuit may include a first circuit block configured to provide a start-up power to a second circuit block; a second circuit block configured to generate a Pulse-Width-Modulation (PWM) signal that controls a pulse duration of a transistor; a third circuit block configured to activate or deactivate the transistor based on the PWM signal; a fourth circuit block configured to reset a magnetic flux in a transformer to a zero state when the transistor is deactivated; and a fifth circuit block configured to maintain an output of a stage below a predetermined value by adjusting a voltage across the transformer.

Singh, Brij N.↗

Optimized asynchronous training of neural networks using a distributed parameter server with eager updates

A method of training a neural network includes, at a local computing node, receiving remote parameters from a set of one or more remote computing nodes, initiating execution of a forward pass in a local neural network in the local computing node to determine a final output based on the remote parameters, initiating execution of a backward pass in the local neural network to determine updated parameters for the local neural network, and prior to completion of the backward pass, transmitting a subset of the updated parameters to the set of remote computing nodes.

Hamidouche, Khaled↗

Heliostat Consortium: Update on Resource, Training, and Education Development and Women+ in Concentrating Solar

One of the major barriers to Concentrating Solar Power (CSP) industry growth in the U.S. is the lack of accessibility of expert knowledge, a lack of a stable workforce pipeline, and little public awareness of the technology area. Improved Resource, Training, and Education (RTE) is needed to address these gaps, to draw workers into the field from diverse technology areas and backgrounds, and to reduce the learning curves of newcomers into the industry. As part of the RTE topic under the NREL-led Heliostat Consortium (HelioCon), a public online resource database has been created to support information sharing across the heliostat and CSP community. Here, information will be presented on the existing and planned database resources, including introductory information about CSP and heliostats, a reference library of texts and publications, educational videos, a CSP power tower plant database and case studies, a contact list of component suppliers and developers, and a list of available software/metrology tools. Women+ in Concentrating Solar is a newly created organization to promote the education, professional development, and advancement of underrepresented genders in the Concentrating Solar Power (CSP) community in a way that includes diverse backgrounds, attitudes, and perspectives. The main objectives of the groups are to provide the following opportunities for underrepresented genders: 1) organize events to provide networking opportunities and community building, 2) boost partnerships and scientific collaboration, 3) create resources to facilitate knowledge and experience sharing, 4) provide mentorship programs to support those new to the industry, 5) bring visibility to underrepresented genders and attract more to the field, and 6) promote Diversity, Equity, and Inclusion (DEI) and engage minorities and underrepresented groups. Initial activities being pursued by the group include creating an expert database to support event organizers in recruiting speakers with representation of all gender identities, hosting online networking and webinar events, organizing conference events including seminars and networking/social events, and establishing a mentorship program to connect members in the CSP community across the globe. The group is open to all genders and has grown to over 60 members in its first few months.

concentrating solar↗

Virtual and Augmented Realities to Support Development, Training, Deployment, and Operations of Remote Systems - 20516

Throughout the U.S. Department of Energy complex, there is a need to deploy new, unique equipment and systems for cleanup activities, waste processing, infrastructure repair, and decommissioning and demolition in radioactive and hazardous environments. The new equipment often consists of custom systems created by integrating and modifying commercial technologies. In addition, the systems are deployed in unique environments due to limited access, waste properties, and the presence of previously installed equipment or infrastructure that has been left in place. The deployment of custom systems that are 'turnkey' ready for first-time installation and application has its risks. Use of test platforms and mockups for cold (i.e., non-radioactive) testing is one method to mitigate that risk: however, full-scale test mockups for operations such as waste retrieval and tank inspection can be expensive and must be modified to incorporate the uniqueness of each application. An alternative to full-scale mockups is to use three-dimensional (3D) virtual environments and virtual reality (VR) technology to develop interactive virtual test beds. These can be used throughout the down-selection, development, system integration, operational planning, operator training, and mission execution phases of a task. Virtual test beds are readily reconfigured, can be used for multiple tasks, support multiple users in parallel, and can accommodate enhancements and changes not originally planned or conceived in the initial design. Virtual test beds also provide a platform for developing and testing augmented reality (AR) tools for improving operator efficiency. A VR experience has been generated for waste retrieval from a Hanford waste tank to present the potential applications of a virtual test bed. Features of the VR experience are presented, potential applications of VR and AR for remote applications are discussed, and development areas for improving future application are considered. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Decoherence Noise on the Superconducting Qubits Training Program

Quantum computing is a growing field with promising applications in a variety of fields such as healthcare, energy consumption, and cryptography. Quantum computing leverages the principles of quantum mechanics - superposition and entanglement. Yet, in the Noisy Intermediate Scale Quantum (NISQ) Era - quantum systems face the major challenge of decoherence due to noise. This era is characterized by low amounts of qubits and high gate error. Decoherence leads to the loss of the quantum information stored in the qubit. Noise occurs with any quantum system that is exposed to the environment. It should also be noted that quantum information can be stored in the cavity - Fermilab specializes in coupling transmons to ultrahigh-Q SRF cavities. The Superconducting Qubits Training Program (SQTP) provides a visualization for beginners in quantum computing. The open quantum system simulated is a superconducting qubit (two-level atom) coupled to a microwave cavity whose excitations are photons. The Rotating Wave Approximation of the Jaynes-Cumming Hamiltonian is used. SQTP utilizes open-source Python-based libraries scQubits, NumPy, and QuTiP alongside the Master Lindblad equation. In this project, we study the different decay behaviors of qubits and cavities with collapse operators.

Lopez, Sara↗

Cybersecurity Education, Training, and WFD

Availability of skilled workforce in sufficient number is one of the most often cited barriers to improving cybersecurity. INL's research has determined that this is not a cybersecurity problem but rather a strategic business imperative; in response INL created the Cyber Competency Health and Maturity Progression Model (Cyber-CHAMP) to help organizations learn the realities of their cyber workforce and their development needs. The presentation starts with an overview of Cyber-CHAMP as a unifying theme for workforce development and then provides brief introductions to selected DHS (ICS cybersecurity hands-on training), DOE (CyberStrike, OT Defender Fellowship, Liberty Eclipse), and INL (Cybercore Summer Camp, University Collaboration Laboratory) programs. Cyber-Informed Engineering discussion concludes the presentation, with an update on activities conducted by the CIE Education Working Group to further the second pillar of the National CIE Strategy, Education.

42 ENGINEERING↗

Generation IV International Forum – Knowledge Management and Knowledge Preservation: An initiative from the Education and Training Working Group

Dr. Patricia Paviet is the Chair of the Generation IV International Forum – Education and Training Working Group. As such, she is overseeing and directing several initiative: The GIF webinar series and the Pitch your Gen IV Research competition. This group has launched a new initiative on knowledge management and knowledge preservation of advanced reactor systems and how lessons learned are passed on in an international context. The paper is a summary of the various GIF member countries’ strategies to preserve and transfer the knowledge of advanced reactors.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Dynamic Low-Rank Training with Spectral Regularization: Achieving Robustness in Compressed Representations

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94\% compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗