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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Materials and Fuels Complex (FY22 – FY26 Five-Year Investment Strategy)

The Department of Energy Office of Nuclear Energy (DOE-NE) vision is to “Advance nuclear energy science and technology to meet U.S. energy, environmental, and economic needs.” The Materials and Fuels Complex (MFC) serves as the foundation of a nuclear RD&D enabling test bed at Idaho National Laboratory (INL) and is an integral part of a National Reactor Innovation Center (NRIC) strategy. MFC facilities focus on developing and maintaining RD&D capabilities that can increase research throughput, reduce barriers to deployment, and facilitate commercialization of new ideas and technologies for clean and secure sources of energy.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Effect of Citrate on the Solubility of Uranium (VI) in WIPP Brine

The Waste Isolation Pilot Plant (WIPP) is the only active deep geological repository in the United States for the disposal of defense-related transuranic (TRU) waste, located in the northern part of the Delaware Basin in southeastern New Mexico, approximately 26 miles east of Carlsbad. The repository is situated 2,150 feet (about 610 meters) underground within the Salado Formation, a thick layer of stable salt deposits. This unique geological formation provides a secure and long-term environment for isolating TRU waste, ensuring its safe containment for thousands of years.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Study the Protection Improvements for a Weak Grid Area With High IBRs

NLR is collaborating with Florida Power & Light (FPL) and GE to investigate power system stability and protection reliability challenges in a weak-grid region with high penetration of inverter-based resources (IBRs). This presentation will primarily focus on the protection aspects of the study. We will share key insights from this real-world project, including best practices for developing high-fidelity fault study models, establishing a controller-hardware-in-the-loop (CHIL) platform for testing physical relays, identifying system-level protection challenges, and designing enhanced protection schemes to address those issues. Through this discussion, the audience will gain practical understanding of protection studies in IBR-dominated systems, the emerging challenges associated with reduced fault current and altered transient behavior, and effective mitigation strategies. In particular, we will highlight the critical importance of IBR compliance with IEEE 2800-2022 to ensure dependable and secure protection relay operation in modern transmission systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1976

Implementation of an experimental fault-tolerant memory system

The experimental fault-tolerant memory system described in this paper has been designed to enable the modular addition of spares, to validate the theoretical fault-secure and self-testing properties of the translator/corrector, to provide a basis for experiments using the new testing and correction processes for recovery, and to determine the practicality of such systems. The hardware design and implementation are described, together with methods of fault insertion. The hardware/software interface, including a restricted single error correction/double error detection (SEC/DED) code, is specified. Procedures are carefully described which, (1) test for specified physical faults, (2) ensure that single error corrections are not miscorrections due to triple faults, and (3) enable recovery from double errors.

Carter, W. C.↗
NASA NTRS1990

Management of the Space Physics Analysis Network (SPAN)

Here, the purpose is to define the operational management structure and to delineate the responsibilities of key Space Physics Analysis Network (SPAN) individuals. The management structure must take into account the large NASA and ESA science research community by giving them a major voice in the operation of the system. Appropriate NASA and ESA interfaces must be provided so that there will be adequate communications facilities available when needed. Responsibilities are delineated for the Advisory Committee, the Steering Committee, the Project Scientist, the Project Manager, the SPAN Security Manager, the Internetwork Manager, the Network Operations Manager, the Remote Site Manager, and others.

Green, James L.↗
NASA NTRS2017

Object and Facial Recognition in Augmented and Virtual Reality: Investigation into Software, Hardware and Potential Uses

As augmented and virtual reality grows in popularity, and more researchers focus on its development, other fields of technology have grown in the hopes of integrating with the up-and-coming hardware currently on the market. Namely, there has been a focus on how to make an intuitive, hands-free human-computer interaction (HCI) utilizing AR and VR that allows users to control their technology with little to no physical interaction with hardware. Computer vision, which is utilized in devices such as the Microsoft Kinect, webcams and other similar hardware has shown potential in assisting with the development of a HCI system that requires next to no human interaction with computing hardware and software. Object and facial recognition are two subsets of computer vision, both of which can be applied to HCI systems in the fields of medicine, security, industrial development and other similar areas.

object recognition↗
DOE OSTI2024

Efficient Anomaly Detection Driven By Different Machine Learning Architectures And Models

The rapid growth and ubiquitous adoption of the internet and cyber-physical systems (CPS) have fundamentally transformed modern communication, work, and human-system interactions. While networks now form the backbone of critical digital ecosystems, enabling seamless data transmission across diverse, interconnected systems, this increased connectivity also expands the attack surface, making real-time detection of network intrusions and anomalies a pressing challenge. Detecting unusual activities within network infrastructure requires advanced data traffic analysis to differentiate between legitimate and malicious interactions. Traditional approaches to network anomaly detectionâ??such as rule-based and signature-based systemsâ??often depend on predefined patterns to identify known anomalies, limiting their effectiveness against emerging, stealthy, or previously unseen threats. These conventional methods suffer from high false alarm rates and fail to adapt to the ever-evolving nature of network traffic, particularly in large-scale, decentralized environments where data volume, velocity, and variety are constantly increasing. This dissertation presents artificial intelligence (AI)-driven approaches to anomaly detection that leverage graphics processing unit (GPU)-enabled high-performance computing (HPC) platforms for processing massive network traffic data and monitoring the components of cyber-physical systems (CPS) for potentially hazardous conditions. The research advances several key contributions: (1) Designing efficient machine learning techniques for CPS condition monitoring and anomaly detection; (2) enabling federated learning (FL) frameworks that enable distributed detection while preserving data privacy and system resilience; (3) exploring graph-based methodologies combining graph neural networks (GNN) and graph machine learning (ML) approaches for the Internet of Things (IoT) and automotive network security, and (4) performing distributed edge computing optimizations that integrate FL with scalable technologies for reduced communication overhead. Through extensive experiments, these methodologies demonstrate that complex anomaly detection and condition monitoring tasks can be achieved while balancing computational efficiency and detection accuracy through fine-grained network information processing. The frameworks developed in this research establish a robust foundation for network anomaly detection, providing scalable, adaptive, and privacy-preserving solutions for safeguarding CPS and IoT networks in an increasingly interconnected digital landscape. The practical implications of these research findings are significant, as they can inform the development of next-generation network security systems and contribute to the protection of critical infrastructure against sophisticated cyber attacks.

Marfo, William↗
DOE OSTI2022

The Missing Satellite Problem outside of the Local Group. II. Statistical Properties of Satellites of Milky Way–like Galaxies

We present a new observation of satellite galaxies around seven Milky Way (MW)–like galaxies located outside of the Local Group (LG) using Subaru/Hyper Suprime-Cam imaging data to statistically address the missing satellite problem. We select satellite galaxy candidates using magnitude, surface brightness, Sérsic index, axial ratio, FWHM, and surface brightness fluctuation cuts, followed by visual screening of false positives such as optical ghosts of bright stars. We identify 51 secure dwarf satellite galaxies within the virial radius of nine host galaxies, two of which are drawn from the pilot observation presented in Paper I. We find that the average luminosity function of the satellite galaxies is consistent with that of the MW satellites, although the luminosity function of each host galaxy varies significantly. We observe an indication that more massive hosts tend to have a larger number of satellites. Physical properties of the satellites such as the size–luminosity relation are also consistent with the MW satellites. However, the spatial distribution is different; we find that the satellite galaxies outside of the LG show no sign of concentration or alignment, while that of the MW satellites is more concentrated around the host and exhibits a significant alignment. As we focus on relatively massive satellites with M V < –10, we do not expect that the observational incompleteness can be responsible here. This trend might represent a peculiarity of the MW satellites, and further work is needed to understand its origin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Quantum adversarial learning for kernel methods

We show that hybrid quantum classifiers based on quantum kernel methods and support vector machines are vulnerable against adversarial attacks, namely small engineered perturbations of the input data can deceive the classifier into predicting the wrong result. Nonetheless, we also show that simple defense strategies based on data augmentation with a few crafted perturbations can make the classifier robust against new attacks. Our results find applications in security-critical learning problems and in mitigating the effect of some forms of quantum noise, since the attacker can also be understood as part of the surrounding environment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Lawrence Livermore National Laboratory (LLNL) Laboratory Directed Research and Development (LDRD) Annual Report (FY 2023)

As Lawrence Livermore National Laboratory’s most significant resource for supporting internally directed research and development, the LDRD Program provides investments in cutting-edge science and technology that allow the Laboratory to attract and retain the world’s most talented scientists and engineers and enables them to expand the frontiers of knowledge and anticipate emerging national security challenges. In this annual report, we summarize how Lawrence Livermore National Laboratory (LLNL) uses LDRD investments to advance our knowledge in strategic science and technology domains, develop our world-class workforce, and foster innovation in key programmatic areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Performance Portable Graphics Processing Unit Acceleration of a High-Order Finite Element Multiphysics Application

The Lawrence Livermore National Laboratory (LLNL) will soon have in place the El Capitan exascale supercomputer, based on advanced micro devices (AMD) graphics processing units (GPUs). As part of a multiyear effort under the National Nuclear Security Administration (NNSA) Advanced Simulation and Computing (ASC) program, we have been developing marbl, a next generation, performance portable multiphysics application based on high-order finite elements. In previous years, we successfully ported the Arbitrary Lagrangian–Eulerian (ALE), multimaterial, compressible flow capabilities of marbl to nvidia GPUs as described in Vargas et al. Here, in this paper, we describe our ongoing effort in extending marbl's GPU capabilities with additional physics, including multigroup radiation diffusion and thermonuclear burn for high energy density physics (HEDP) and fusion modeling. We also describe how our portability abstraction approach based on the raja Portability Suite and the mfem finite element discretization library has enabled us to achieve high performance on AMD based GPUs with minimal effort in hardware-specific porting. Throughout this work, we highlight numerical and algorithmic developments that were required to achieve GPU performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Health Analysis and Research for Public Events (HARPE) Tool (Final CRADA Report)

Based on its experience in building assessment tools, Argonne National Laboratory (Argonne) has demonstrated expertise in developing comparative methodologies and question sets that provide both a physical and cyber-based risk assessment for the commercial facilities sector. A high-level risk assessment tool can be beneficial for venues and organizations that fall under a wide array of facility characterizations, ultimately accommodating the evolving landscape of threats specific to these facilities. The Health Analysis and Research for Public Events (HARPE) Tool is an assessment that seeks to help facility managers assess and mitigate aspects of safety, security, and emergency management within their venues. With the pandemic featuring prominently in today’s landscape, we have adapted and extended the scope of the HARPE tool so that it offers users the ability to integrate assessments of their preparation for, response to, and recovery from threats faced at the venue arising from the COVID-19 pandemic. Traditional threats and hazards remain prevalent in today’s landscape, and the best defense is a proactive approach to preventing and mitigating these threats. At the very core of prevention and mitigation is the first step of conducting a risk assessment—this is the gap that HARPE fills. While it is obvious that the response to COVID-19 is health and sanitation driven, leaders within the commercial facilities sector must also know where to best extend their efforts in mitigating future threats arising from the pandemic. Public events and mass gatherings are directly impacted by COVID-19; however, with the help of HARPE, leaders can focus their attention on core impact areas related to the safety and security of returning to a new normal, as they assess their risks using the Argonne-developed tool. HARPE provides an important solution to the COVID-19 situation by assisting venue managers and health officials in identifying their risks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Analyzing Insider Risk Threat to the Internet of Things (IoT)

Recent technological advancement has created a growing convergence of innovation. From machine learning to ubiquitous computing to wireless networks and automation, the world is seeing new technology increasingly capable of connecting with each other. Devices and systems use open communications networks to interact, process information, and react. This is called the Internet of Things (IoT) and is comprised of physical devices that exchange data over networks, creating revolutionary possibilities. The most common way most people interact with an IoT is through ‘smart home’ products like Amazon’s Alexa, which use microphones, speakers, and phones to control a variety of devices, from lights and thermostats, to cameras, to appliances and vacuum cleaners. But the open nature of IoT networks—necessary for their ability to communicate and operate—also introduces privacy and security concerns. At a personal level, this might mean a hack into a home to steal private information, but when applied in broader industries like healthcare, transportation, manufacturing, or the military, this vulnerability can have serious consequences. As IoT usage and interconnectivity increases, so too does the susceptibility to malicious actors. And the entire system is only as secure as its least secure member. This creates particular risk and vulnerability to radiological material industries, as a competent insider adversary could utilize the IoT to potentially steal or access classified or sensitive information about employees, sites, or systems; or simply sabotage security or maintenance from a more remote—and less secure—device. The IoT relies on a secure network across the entire system, especially in transport which may lack the security of more permanent locations; if one device fails, it can create a ripple effect and an insider threat may seek to exploit that connectivity. While IoT benefits drive increased innovation and usage, there are also vulnerabilities an insider threat could exploit; this risk of an IoT to radiological material must be addressed in any mitigation effort.

Kinney, Justin↗
DOE OSTI2021

Irradiation-Driven Restructuring of UO 2 Thin Films: Amorphization and Crystallization

Combustion synthesis in uranyl nitrate–acetylacetone–2-methoxyethanol solutions was used to deposit thin UO 2 films on aluminum substrates to investigate the irradiation-induced restructuring processes. Thermal analysis revealed that the combustion reactions in these solutions are initiated at ~160 °C. The heat released during the process and the subsequent brief annealing at 400 °C allow the deposition of polycrystalline films with 5–10 nm UO 2 grains. The use of multiple deposition cycles enables tuning of the film thicknesses in the 35–260 nm range. Irradiation with Ar 2+ ions (1.7 MeV energy and a fluence of up to 1 × 10 17 ions/cm 2 ) is utilized to generate a uniform distribution of atomic displacements within the films. X-ray fluorescence (XRF) and alpha-particle emission spectroscopy showed that the films were stable under irradiation and did not undergo sputtering degradation. X-ray photoelectron spectroscopy (XPS) showed that the stoichiometry and uranium ionic concentrations remain stable during irradiation. The high-resolution electron microscopy imaging and electron diffraction analysis demonstrated that at the early stages of irradiation (below 1 × 10 16 ion/cm 2 ) UO 2 films show complete amorphization and beam-induced densification (sintering), resulting in a pore-free disordered film. Prolonged irradiation (5 × 10 16 ion/cm 2 ) is shown to trigger a crystallization process at the surface of the films that moves toward the UO 2 /Al interface, converting the entire amorphous material into a highly crystalline film. This work reports on an entirely different radiation-induced restructuring of the nanoscale UO 2 compared to the coarse-grained counterpart. The preparation of thin UO 2 films deposited on Al substrates fills an area of national need within the stockpile stewardship program of the National Nuclear Security Administration and fundamental research with actinides. Here, the method reported in this work produces pure, robust, and uniform thin-film actinide targets for nuclear science measurements

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement Fusion Target Design

Reliable, secure access to energy is a major focus for national security efforts. One potential route to such energy is through fusion reactions in inertial confinement fusion (ICF) experiments. Such experiments are carried out at facilities such as the National Ignition Facility (NIF) in Livermore, California, where high powered lasers are used to compress a DT fuel-containing target to the necessary high temperature, high pressure conditions. These experiments are limited in number, which creates a heavy dependence on high fidelity predictive physics simulations and analysis performed “pre shot,” or before the experiment occurs. Many of these simulations in higher dimensions (2D and 3D) are computationally expensive, so finding optimal simulation-based designs presents its own challenges. In this work, we present our multi-fidelity Bayesian optimization with Gaussian processes (GPs) for ICF double shell targets, where a 1D surrogate model is used to help find a 2D surrogate model, enabling us to find optimal targets in the higher fidelity (2D), while saving computational cost.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

National Criticality Experiments Research Center, NCERC NEWS (Apr. - Jun. 2021) [Slides]

National Center for Nuclear Security (NCNS) samples were irradiated on Godiva. Fission chamber testing for NCNS was conducted on Flat-Top. This operation involved multiple core configuration changes, which doubled as important training opportunities for NEN-2 Crew Member Trainees. These experiments support nuclear forensics research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗