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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Differentiable physics-enabled closure modeling for Burgers’ turbulence

Abstract Data-driven turbulence modeling is experiencing a surge in interest following algorithmic and hardware developments in the data sciences. We discuss an approach using the differentiable physics paradigm that combines known physics with machine learning to develop closure models for Burgers’ turbulence. We consider the one-dimensional Burgers system as a prototypical test problem for modeling the unresolved terms in advection-dominated turbulence problems. We train a series of models that incorporate varying degrees of physical assumptions on an a posteriori loss function to test the efficacy of models across a range of system parameters, including viscosity, time, and grid resolution. We find that constraining models with inductive biases in the form of partial differential equations that contain known physics or existing closure approaches produces highly data-efficient, accurate, and generalizable models, outperforming state-of-the-art baselines. Addition of structure in the form of physics information also brings a level of interpretability to the models, potentially offering a stepping stone to the future of closure modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Machine learning of hidden variables in multiscale fluid simulation

Solving fluid dynamics equations often requires the use of closure relations that account for missing microphysics. For example, when solving equations related to fluid dynamics for systems with a large Reynolds number, sub-grid effects become important and a turbulence closure is required, and in systems with a large Knudsen number, kinetic effects become important and a kinetic closure is required. By adding an equation governing the growth and transport of the quantity requiring the closure relation, it becomes possible to capture microphysics through the introduction of ‘hidden variables’ that are non-local in space and time. The behavior of the ‘hidden variables’ in response to the fluid conditions can be learned from a higher fidelity or ab-initio model that contains all the microphysics. In our study, a partial differential equation simulator that is end-to-end differentiable is used to train judiciously placed neural networks against ground-truth simulations. We show that this method enables an Euler equation based approach to reproduce non-linear, large Knudsen number plasma physics that can otherwise only be modeled using Boltzmann-like equation simulators such as Vlasov or particle-in-cell modeling.

42 ENGINEERING↗
DOE OSTI2019

Production Facility Prototype Blower 1000 Hour Test Results IV

Long duration operations tests of the Aerzen GM 12.4 roots style blower in a closed loop configuration provides valuable data and lessons learned for long-term operation at the Mo-99 production facility. The blower was operated in a closed loop configuration with the flow conditions anticipated in plant operation with a Mo-100 target inline. The additional thermal energy generated from beam heating of the Mo-100 disks was not included in these tests. Twelve long duration 500 to 1000 hour tests have been completed since the first test was performed in January of 2016. All twelve long duration tests have proven successful in exposing preventable issues related to oil and helium leaks. All blower tests to this date have resulted in stable blower performance and consistency. A summary of the results for the end of the ninth test to the twelfth test is included in this report. Complete details for the previous tests are shown in the reports, Production Facility Prototype Blower 1000 Hour Test Results, II, and III.

42 ENGINEERING↗
DOE OSTI2021

Production Facility Prototype Blower 1000 Hour Test Results V

Long duration operations tests of the Aerzen GM 12.4 roots style blower in a closed loop configuration provides valuable data and lessons learned for long-term operation at the Mo-99 production facility. The blower was operated in a closed loop configuration with the flow conditions anticipated in plant operation with a Mo-100 target inline. The additional thermal energy generated from beam heating of the Mo-100 disks was not included in these tests. Thirteen long duration 500 to 1000 hour tests have been completed since the first test was performed in January of 2016. All thirteen long duration tests have proven successful in exposing preventable issues related to oil and helium leaks. All blower tests to this date have resulted in stable blower performance and consistency. A summary of the results for the end of the thirteenth test is included in this report. Complete details for the previous tests are shown in the reports, Production Facility Prototype Blower 1000 Hour Test Results, II, III, and IV.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Waste Management Fundamentals for Environmental Professionals (UTrain 50448) [Slides]

At the pilot of this course, we discovered that we need to focus on how we do waste management at LANL. Environmental Professionals have a variety of jobs - most impact waste in some way. Finding a balance between comprehensive enough and too much is key. The goals of this training are for it to be good, consistent, and helpful, not just a requirement. The course modules are: Intro to Waste, Waste Regulations and Requirements, Waste Planning, Waste Generation and Tracking, Waste Characterization, Waste Packaging, Waste Accumulation and Storage, Waste Treatment, Waste Shipping, and Operation Experience and Lessons Learned.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

H2@Airports (Workshop Summary Report)

This report serves as the proceedings of the H2@Airports Workshop held virtually by the U.S. Department of Energy (DOE) in collaboration with the U.S. Department of Transportation (DOT) and Department of Defense (DOD), November 4-6, 2020. Presentations from the workshop can be found at H2@Airports Workshop: https://www.energy.gov/eere/fuelcells/h2airports-workshop. The workshop was held to assess the state of the art for electric aircraft and airport applications specifically using hydrogen fuel cells, to discuss operational requirements and lessons learned on early fuel cell aviation and airport projects, to understand current technology gaps, to identify collaborative research and development (R&D) opportunities, to highlight codes, standards, safety, and regulatory challenges, and to identify potential actions that address them. Experts and stakeholders from industry, government, and academia met to discuss the current state of the art of hydrogen and fuel cell technologies and the requirements for using these technologies in aviation applications and land-based applications at airports. This report summarizes the discussions and diverse opinions expressed at the workshop.

08 HYDROGEN↗
DOE OSTI2022

GraphAlign: Graph-Enabled Machine Learning for Seismic Event Filtering

This report summarizes results from a 2 year effort to improve the current automated seismic event processing system by leveraging machine learning models that can operated over the inherent graph data structure of a seismic sensor network. Specifically, the GraphAlign project seeks to utilize prior information on which stations are more likely to detect signals originating from particular geographic regions to inform event filtering. To date, the GraphAlign team has developed a Graphical Neural Network (GNN) model to filter out false events generated by the Global Associator (GA) algorithm. The algorithm operates directly on waveform data that has been associated to an event by building a variable sized graph of station waveforms nodes with edge relations to an event location node. This builds off of previous work where random forest models were used to do the same task using hand crafted features. The GNN model performance was analyzed using an 8 week IMS/IDC dataset, and it was demonstrated that the GNN outperforms the random forest baseline. We provide additional error analysis of which events the GNN model performs well and poorly against concluded by future directions for improvements.

58 GEOSCIENCES↗
DOE OSTI2023

Grid-Scale Electricity Storage at Lowest Possible Cost Enabled by Pumped Heat Electricity Storage (Final Report)

Grid-scale energy storage technologies that can provide greater than 10 hours of electricity at full power address a critical need for full penetration of renewables on electricity grids worldwide, minimize renewable curtailment, and maximize grid security and reliability. Pumped Heat Energy Storage (PHES) systems can store energy thermally in any location at the low costs necessary for displacing fossil fuels, reducing foreign fuel imports, and reducing emissions to maintain the energy security of the United States. The award allowed Southwest Research Institute® (SwRI®) and Malta, Inc. (Malta) to advance the PHES concept to a proof-of-concept demonstration for a kW-scale system. The project focused on system operation and integration. The main project objectives were: 1. Address first implementation challenges 2. Explore system control strategies and operation 3. Translate lessons learned to the full-scale system Through these objectives the project completes a first demonstration of this technology and reduces the technical risk associated with a full-scale system.

25 ENERGY STORAGE↗
DOE OSTI2024

Uncertainties in ICARUS

This paper explores the challenges in neutrino detection and emphasizes the importance of understanding the ICARUS neutrino detector. It delves into the use of cosmic rays to bridge the gap between experimental and theoretical data, offering insights into the behavior of different components of neutrino detectors. This procedure sheds light on the intricate aspects of cosmic ray detection in ICARUS, contributing to an increased understanding of how this detector's uncertainties operate. More can be learned about neutrino physics in future experiments through this understanding.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Interface Specifications for RAdiation Portal Technology Enhancement & Replacement (RAPTER) Modules

Radiation Portal Monitors (RPMs) were deployed throughout the port and border infrastructure of the United States (U.S.) beginning in 2003 to monitor for the possible presence of uncontrolled radiological and nuclear materials. Since that time, the U.S. Government (USG) has learned much about the operational challenges faced in the field. Principal among the shortcomings has been the lack of flexibility afforded the USG when all Internet Protocol (IP) rights and interfaces of the system are owned by the Original Equipment Manufacturer (OEM).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Electric Grid Security (EGS) FY24 Annual Report

Sandia’s Electric Grid Security program advances a national vision of a secure, resilient, and affordable electric system for all users. Our achievements reflect a strategic approach combining technology development; modeling, simulation, and data analytics; and partnered demonstrations and outreach to further the adoption of advanced grid and storage technologies. Our FY24 efforts leverage the strengths of our partnerships—spanning Sandia’s core science and technology competencies as well as external technology leaders—to develop the solutions today which enable the grid of tomorrow. Key accomplishments in this report that support our strategy span our technical program areas and include: • The advancement of energy storage technologies, including creation of a national Long Duration Energy Storage Consortium; • Applications of artificial intelligence and machine learning to enhanced grid operations and planning; • Development of solid-state power conversion technologies and a new medium-voltage research lab; • New technologies to assess wildfire vulnerabilities and mitigate potential impacts; • Advanced applications of new cybersecurity technologies with industry partners; • Contributions to understanding the impacts of electromagnetic pulses and geomagnetic disturbances on grid components; and • Digital twin development for hybrid microgrids with multiple generators, storage, and loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Passband Signal Detection at the Edge

Algorithms for radio frequency (RF) spectrum awareness need to be compatible with edge hardware to be practical for many applications. We developed a signal detection and classification model for the ZCU111 RF System-on-a-Chip (RFSoC) that operates on the fast Fourier transform of passband RF data. The system can detect and classify multiple signals of interest and display the predictions in real-time. The model consists of a modified ConvNeXt backbone and YOLOv3 head to operate on the Deep Learning Processing Unit on the RFSoC. We gathered datasets for training and testing by using a software defined radio to transmit example signals of Wi-Fi 802.11 b/g, Wi-Fi 802.11 n, FM Radio, LTE and LTE-M. By leveraging multiple inputs on the RFSoC frontend, the datasets span up to 4 GHz of bandwidth. The models showed high performance in classification accuracy, center frequency error, bandwidth error, and detection accuracy for both single and multi-signal datasets.

42 ENGINEERING↗
DOE OSTI2026

FY25 Electric Grid Security Annual Report

Sandia’s Electric Grid Security program advances a national vision of energy dominance and accessibility, while applying our national security -emphasis on ensuring of a secure, resilient, and affordable electric system for all users. Our achievements reflect a strategic approach combining technology development; modeling, simulation, and data analytics; and partnered demonstrations and outreach to further the adoption of advanced grid and storage technologies. Our FY25 efforts leverage the strengths of our partnerships—spanning Sandia’s core science and technology competencies as well as external technology leaders—to develop the solutions today which enable the grid of tomorrow. Key accomplishments in this report that support our strategy span our technical program areas and include: • New open-source analytical tools for systems -level planning and optimization, including significant advances to the QuESt analytical environment; • Further advancement of artificial intelligence and machine learning to enhanced grid operations and planning as we rise to the challenge of new large loads; • Development of solid-state power conversion technologies and a new medium-voltage research lab; • New technologies to assess wildfire vulnerabilities and mitigate potential impacts; • Advanced applications of new cybersecurity technologies with industry partners; • Contributions to understanding the impacts of electromagnetic pulses and geomagnetic disturbances on grid components; and • Digital twin development for hybrid microgrids with multiple generators, storage, and loads. This report indicates key areas of research and engagement and summarizes the impact of Sandia’s contributions through notable accomplishments, journal publications, patents, and technical conferences and presentations. It is provided with the hope that readers discover ways we can further team to create our modern grid and apply the outcomes of our efforts. The bulk of work described herein is funded by several offices within the U.S. Department of Energy (USDOE), including the Office of Electricity (OE); Cybersecurity, Energy Security, and Emergency Response (CESER); former offices such as the Office of Energy Efficiency and Renewable Energy (EERE), the Grid Deployment Office (GDO), the Office of Clean Energy Demonstrations (OCED), and other key programs at USDOE. As we continue to state in these annual reports, the contributors to our successes are too numerous to name here, though our team wishes to express our deep gratitude to the numerous program and project sponsors at the US Department of Energy, who often function equally as technical collaborators; our many partners in industry, academia, utilities, and other national labs; and fellow researchers and business partners at Sandia whose leadership and creativity have enabled the accomplishments described herein.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1980

Adaptive and learning control of large space structures

The paper describes the adaptive learning system for space operations which assumes that structural testing can be conducted during deployment and assembly. Simulation results using the solar electric propulsion array and a novel remote sensor are presented; they involve faster scan television coverage of the motions of the array from four cameras on the corners of the Space Shuttle payload bay. The description of the simulation, the filtering algorithm for processing the TV data, the parameter extraction algorithm, and the simulation results are presented.

Montgomery, R. C.↗
NASA NTRS1981

ATC contingency operations in the en-route flight regime

Air traffic control (ATC) operations were examined to learn what factors of controller performance should be given consideration in the design and development of future automation systems enhancing ATC. Contingencies were of two types: those constraining airspace usage or traffic flow (i.e., weather); and those related to system and equipment usage (i.e., radar/radio status). Examination of controller response to contingencies and workload pressures showed differing effects on controller allocations of effort among the three primary function of planning, monitoring, and informaton transfer. Automation advancements oriented towards aiding the controller in performing monitoring tasks may offer the most substantial safety benefit.

Lyman, E. G.↗