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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ON-OFF neuromorphic ISING machines using Fowler-Nordheim annealers

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using a Fowler-Nordheim quantum mechanical tunneling based threshold-annealing process. The core component of NeuroSA consists of a pair of asynchronous ON-OFF neurons, which effectively map classical simulated annealing dynamics onto a network of integrate-and-fire neurons. The threshold of each ON-OFF neuron pair is adaptively adjusted by an FN annealer and the resulting spiking dynamics replicates the optimal escape mechanism and convergence of SA, particularly at low-temperatures. To validate the effectiveness of our neuromorphic Ising machine, we systematically solved benchmark combinatorial optimization problems such as MAX-CUT and Max Independent Set. Across multiple runs, NeuroSA consistently generates distribution of solutions that are concentrated around the state-of-the-art results (within 99%) or surpass the current state-of-the-art solutions for Max Independent Set benchmarks. Furthermore, NeuroSA is able to achieve these superior distributions without any graph-specific hyperparameter tuning. For practical illustration, we present results from an implementation of NeuroSA on the SpiNNaker2 platform, highlighting the feasibility of mapping our proposed architecture onto a standard neuromorphic accelerator platform.

42 ENGINEERING↗
DOE OSTI2024

Characterizing Interaction Uncertainty in Human-Machine Teams

With the increasing use and adoption of artificial intelligence (AI), the reliability of modern data systems will be driven by a tighter teaming between human experts and intelligent machine teammates. As in the case of human-human teams, the success of human-machine teams will also rely on clear communication about mutual goals and actions. In this paper, we combine related literature from cognitive psychology, human-machine teaming, uncertainty in data analysis, and multi-agent systems to propose a new form of uncertainty: interaction uncertainty for characterizing bidirectional communication in human-machine teams. We map the causes and effects of interaction uncertainty and outline potential ways to mitigate uncertainty for mutual trust in a high-consequence real-world scenario.

uncertainty, data analytics, interaction, trust, h↗
DOE OSTI2024

NSTXU Diagnostic Disruption Dynamic Loading Represented by Response Spectra

This article presents the results of transient dynamic simulations of loads due to disruption eddy currents on the NSTXU vacuum vessel. Dynamic loading at diagnostic mounting locations is expressed as response spectra derived from the time history results of the dynamic structural simulations of a variety of disruption scenarios. The disruption simulations draw on a history of the project assessments of worst case disruptions for specific components. Major efforts to assess disruption loading have included the vacuum vessel which is the major structural support for the machine, as well as the passive plates (PPs), high harmonic fast wave (HHFW) antenna, and centerstack casing. Each one of these efforts included transient electromagnetic simulations producing time-dependent eddy current Lorentz loads (and in some cases halo loads) which then were applied to time-dependent structural dynamic analyses intended to obtain the proper dynamic amplification factors. In some instances, the EM model and structural model were identical allowing direct transfer of EM forces to the structural model. In other cases, the EM and structural model were not identical and the vector potential (VP) transfer method was used. The results files from these analyses were available (or re-run) to post process in ANSYS Classic time history postprocessor. In conclusion, the ANSYS command is used to create response spectra from time history data at desired points on the vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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

2024 Photovoltaic Inverter Reliability Workshop Summary Report & Proceedings

The National Renewable Energy Laboratory (NREL) organized the 2024 Photovoltaic Inverter Reliability Workshop on April 11-12, 2024, hosted at NREL's South Table Mountain campus in Golden, Colorado. The workshop was organized around seven key topics, including the present state of inverter reliability; solutions for reliability challenges; life cycle cost and ownership issues; testing, standards, performance, and reliability metrics; data reporting, analytics, and sharing; and the future of PV inverter reliability research. Participants included inverter manufacturers, national laboratory researchers, academics, independent testing laboratories, and more. Over the course of the two-day workshop, attendees arrived at several key priorities and conclusions. This report summarizes these conclusions and then collects presentations from the workshop into a record of the workshop's proceedings.

14 SOLAR ENERGY↗
DOE OSTI2025

Lilith: An Enduring Plutonium Critical Assembly [Slides]

A design of an enduring Pu critical assembly has been produced. This is very important to DOE/NNSA missions. This assembly would result in advances/improvements in nuclear data validation, analytical methods validation, dosimetry, reactor kinetics, materials, and more.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Enhanced Preparation for Intelligent Cybermanufacturing Systems (EPICS)

Opportunities exist for realizing transformative advances in productivity and reductions in energy footprint through ubiquitous sensing in manufacturing environments. Enhanced Preparation for Intelligent Cybermanufacturing Systems (EPICS) is a 21-month (4 academic semesters, plus one summer) experience for graduate students that focuses on scaling the knowledge, understanding and leadership skills in the cyber manufacturing area. Masters students (8/year, 32 total) complete 2-year projects on industrially-driven project topics, rotating to internships in summer semester to work on scoping and implementation at project partners. Students complete academic training in embedded systems, process modeling, data science, and cloud-based systems design. Their projects are targeted toward sensor retrofit, process monitoring, root cause analysis, and sensor fusion.

Advanced Manufacturing↗
NASA NTRS1971

Improved scaling laws for stage inert mass of space propulsion systems. Volume 2: System modeling and weight data

Technical models and analytical approaches used to develop the weight data for vehicle system concepts using advanced technology are reported. Weight data are supplied for the following major system elements: engine, pressurization, propellant containers, structural shells and secondary structure, and environmental protection shields for the meteoroid and thermal design requirements. Scaling laws, improved and a simplified set, are developed from the system weight data. The laws consider the implications of the major design parameters and mission requirements on the stage inert mass.

Source record↗
NASA NTRS1972

Silica reinforcement and char reactions in the Apollo heat shield.

Reactions of the silica reinforcement fiber and ablation char of the Apollo heat shield have been investigated by laboratory tests in an arc image furnace (at temperature levels up to 5000 R, pressures up to 0.7 atm, and heat flux similar to reentry) and by an actual reentry test. Microchemical analyses and X-ray diffraction studies have been made to determine the presence of SiC formation in the char. Experimental data and analytical predictions of thermal and density profiles have been compared for the ablation of virgin heat shield and precharred materials to determine the effects of SiC formation on ablation performance. In all analyses, general agreement was found between chemical composition and the thermal predictions for laboratory tests and reentry materials. In all ablated materials, SiC was formed in the front surface of the char. The highest SiC content found was 58% by weight and found in a high-pressure environment. The SiC formed was found to act as a heat sink in the ablation process and can lower the front surface temperature by 300 R.

Cagliostro, D. E.↗
NASA NTRS1972

High Pressure Reverse Flow APS Engine

A design and test demonstration effort was undertaken to evaluate the concept of the reverse flow engine for the APS engine application. The 1500 lb (6672 N) thrust engine was designed to operate on gaseous hydrogen and gaseous oxygen propellants at a mixture ratio of 4 and to achieve the objective performance of 435 sec (4266 Nsec/kg) specific impulse. Superimposed durability requirements called for a million-cycle capability with 50 hours duration. The program was undertaken as a series of tasks including the initial preliminary design, design of critical test components and finally, the design and demonstration of an altitude engine which could be used interchangeably to examine operating parameters as well as to demonstrate the capability of the concept. The program results are reported with data to indicate that all of the program objectives were met or exceeded within the course of testing on the program. The analysis effort undertaken is also reported in detail and supplemented with test data in some cases where prior definitions could not be made. The results are contained of these analyses as well as the test results conducted throughout the course of the program. Finally, the test data and analytical results were combined to allow recommendations for a flight weight design. This preliminary design effort is also detailed.

Senneff, J. M.↗
NASA NTRS1973

A representation of Jacchia's thermospheric models in spherical harmonics

The Jacchia models are represented in terms of spherical harmonic functions. This representation has the advantages of ease of comparison with theoretical and other observational models and data, mathematical analyticity and relative simplicity. The symmetry properties of the models are emphasized by this representation and some physical characteristics like the increase of the amplitude of the diurnal density variation with decreasing solar activity become more apparent.

Blum, P.↗