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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Applying Machine Learning to the Classification of DC-DC Converters. NA-22 Final Report

Tools are now available that enable measurement electromagnetic radiation (EMR) from active electronics in an item. This radiation may be intended WIFI or cellular network links, for example or unintended such as the switching noise generated by DC-to-DC converters. It would be extremely valuable to have the capability to discriminate between the low-voltage DC-to-DC converters or other digital noise prevalent in most modern electronics, versus the high-voltage DC-to-DC converters used in utility firesets. Previous work performed under a Sandia Laboratory Directed Research and Development (LDRD) project on Charge State Detection using a deep neural network has been continued in this effort. A state-of-the-art supervised machine learning algorithm has not only been extended to discriminate between low and high voltage converters but has been validated in determining a converters make and model.

42 ENGINEERING↗
DOE OSTI2023

CRITICAL FUNCTION ASSURANCE: Understanding Critical Function and Critical Function Delivery is Foundational for Meaningful ICS Security Improvement and Policy Efforts

Modern life is enabled by a complex and interdependent web of critical functions, including energy, communications, transportation, food, and water. Automation has significantly reduced or replaced human interactions in the delivery of these functions, resulting in a web of goods and services that are made available 24/7 only through unique and intentional deployments of microprocessors, software, and firmware technologies. The prospect of cyber-enabled sabotage of these processes disrupts traditional risk determination models. Critical Function Assurance (CFA) is a foundational approach to identifying, prioritizing, and mitigating the risk that is inherent in the delivery of critical functions that depend on digital technology. It provides rapid focus to what matters most and illuminates elements and areas of risk that otherwise are often overlooked. This focus enables effective application of available security resources and optimizes security strategy and policy efforts. This paper introduces CFA to decision makers and risk executives (including CEOs, COOs, CFOs, and CISOs) whose organizations support and deliver the critical functions that underpin national defense, societal health and safety, and a vibrant economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Graph Theory and IC Component Design Analysis

Graph analysis in large integrated circuit (IC) designs is an essential tool for verifying design logic and timing via dynamic timing analysis (DTA). IC designs resemble graphs with each logic gate as a vertex and the conductive connections between gates as edges. Using DTA digital statistical correlations, graph condensation, and graph partitioning, it is possible to identify high-entropy component centers and paths within an IC design. Identification of high-entropy component centers (HECC) enables focused DTA, effectively lowering the computational complexity of DTA on large integrated circuit graphs. In this paper, a devised methodology termed IC layout subgraph component center identification (CCI) is used to identify described. CCI lowers DTA computationally complexity by condensing IC graphs into reduced subgraphs in which dominant logic functions are verified.

42 ENGINEERING↗
DOE OSTI2021

Grid-Scale Ternary-Pumped Thermal Electricity Storage for Flexible Operation of Nuclear Power Generation under High Penetration of Renewable Energy Sources

In this work, the integration of a grid-scale ternary-Pumped Thermal Electricity Storage (t-PTES) with a nuclear power generation to enhance operation flexibility is assessed using physics-based models and digital real time simulation. A part of the electricity from the nuclear power generation is delivered to the grid, and the balance is used to power a heat pump that can be augmented by an auxiliary resistive load element to increase the charging rate of the thermal storage. This increases the thermal potential between hot and cold thermal stores (usually solid materials or molten salts inside large storage tanks). The thermal energy is transformed back into electricity by reversing the heat pump cycle. Different transient scenarios including startup, shutdown, and power change for grid-connected operation are simulated to determine the behavior of the hybrid nuclear-t-PTES system operating under variable loads that constitute a departure from conventional, baseload nuclear plant operation schemes. Ternary refers to the three modes operation: (i) heat pump (including heating coil), (ii) heat engine, and (iii) simultaneous operation of heat pump (including heating coil) and heat engine during changeover from pumping to generation or vice-versa. The controllability of t-PTES in the short timescales as a dynamic load is used to demonstrate operational flexibility of hybrid nuclear plants for flexible operation through advanced load management. The integration of t-PTES into nuclear power systems enhances the system flexibility and is an enabler for high penetration of renewable energy resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Severe turbulence and maneuvering from airline flight records

Digital flight records from reported clear-air turbulence incidents are used to determine winds, to determine maneuver G loads, and to analyze control problems. Severe turbulence is found downwind of mountains and thunderstorms associated with vortices in atmospheric waves. It is also found in strong updrafts above thunderstorm buildups that are not detected by onboard weather radar. An important finding is that there are large maneuvering loads in over half of the reported clear-air turbulence incidents. Maneuvering loads are determined through an analysis of the short-term variations in elevator deflection and aircraft pitch angle. For altitude control in mountain waves the results indicate that small pitch angle changes with proper timing are sufficient to counter the vertical winds. For airspeed control in strong mountain waves, however, there is neither the available thrust nor the quickness in engine response necessary to counter the large and rapid variations in horizontal wind.

Wingrove, R. C.↗
NASA NTRS1991

Liquid jet breakup and atomization in rocket chambers under dense spray conditions

Two advanced diagnostic techniques were established and employed in this project. The first technique involves the use of a real-time x ray radiography system along with a high-speed CCD Xybion camera and an advanced digital image processor to investigate the breakup processes of the liquid core. The focus of this part of the project is to determine the inner structure of the liquid jet and via thin sheets of laser light, with the scatters light being photographed by a Xybion electronic camera synchronized to the laser pulse. This technique, which is capable of recording the breakup event occurring within 25 nano-seconds, enables us to freeze the motions of the jet and liquid droplets. The focus of this part of the project is to determine the outer structure of the liquid jet and to discover the configuration of the surface waves, the spray pattern, and the droplet size distribution in the non-dilute region. Results obtained by these two advanced diagnostic techniques will provide the much needed database for model development and accurate prediction of engine performance. The present work also represents a breakthrough in the area of advanced diagnostics of dense sprays.

Kuo, Kenneth K.↗
NASA NTRS1990

Digital angular position sensor using wavelength division multiplexing

Future aircraft will use fly-by-light control systems with fiber-linked optical sensors for such measurands as temperature, pressure, and linear and angular position. A digital optical sensor is described which was developed to transmit the angular position of such slowly rotating parts as a throttle of fuel flow control valve on an aircraft. The sensor employs a reflective code plate with ten channels providing a resolution of 0.35 degrees. Two light-emitting diodes with overlapping spectra are used as light sources. A single microoptic multiplexer-demultiplexer composed of a GRIN rod lens and a miniature grating is used to disperse the spectrum and recombine the spectral components from each channel after reflection by the code plate. The results of preliminary environmental tests of this unit are discussed. The sensor has been operated for brief periods of time between -60 C and +125 without adverse effects. Preliminary vibration tests indicate that the unit will work properly at the maximum vibration levels expected in a jet-engine environment.

Fritsch, Klaus↗
NASA NTRS2002

An Examination of Drag Reduction Mechanisms in Marine Animals, with Potential Applications to Uninhabited Aerial Vehicles

Previous engineering research and development has documented the plausibility of applying biomimetic approaches to aerospace engineering. Past cooperation between the Virginia Institute of Marine Science (VIMS) and NASA focused on the drag reduction qualities of the microscale dermal denticles of shark skin. This technology has subsequently been applied to submarines and aircraft. The present study aims to identify and document the three-dimensional geometry of additional macroscale morphologies that potentially confer drag reducing hydrodynamic qualities upon marine animals and which could be applied to enhance the range and endurance of Uninhabited Aerial Vehicles (UAVs). Such morphologies have evolved over eons to maximize organismal energetic efficiency by reducing the energetic input required to maintain cruising speeds in the viscous marine environment. These drag reduction qualities are manifested in several groups of active marine animals commonly encountered by ongoing VIMS research programs: namely sharks, bony fishes such as tunas, and sea turtles. Through spatial data acquired by molding and digital imagery analysis of marine specimens provided by VIMS, NASA aims to construct scale models of these features and to test these potential drag reduction morphologies for application to aircraft design. This report addresses the efforts of VIMS and NASA personnel on this project between January and November 2001.

Musick, John A.↗
NASA NTRSDate not supplied

DLES Unreal Simulation Tool (DUST)

NASA’s future Artemis missions to the Moon seek to explore areas around the Lunar South Pole. Though humans have previously set foot on the lunar surface, the proposed region provides unique and challenging environments that require insight and investigation prior to arrival. Several teams throughout the agency are performing this site and mission planning, design, and analysis to support areas like the Human Landing System (HLS), surface mobility, habitation elements, and scientific exploration. The NASA Exploration Systems Simulation (NExSyS) team at Johnson Space Center is developing a graphical environment of the Lunar South Pole region. Lunar terrain information collected from the Lunar Reconnaissance Orbiter (LRO) is compiled and made available through Johnson Space Center’s Digital Lunar Exploration Sites (DLES) data sets. The DLES data is used to build this graphic environment. The process of ingesting and accurately modeling this information in a meaningful way for analysis creates its own challenges such as generating a performant model from the source data and the application of curvature. Additionally, the area around the Lunar South Pole experiences different lighting conditions than those observed from the Apollo missions. The need to use the lunar environmental data products provided by DLES combined with the capability to calculate date specific ephemerides in real-time has given rise to the development of the DLES Unreal Simulation Tool (DUST). DUST incorporates augmented terrain from the DLES product into a desktop application that allows exploration of the Lunar South Pole region and its complex lighting conditions. DUST leverages advanced capabilities in the recently released Unreal Engine 5 renderer by Epic Games such as double precision for positioning of planetary bodies and surface elements, multiple infinite light sources to represent the Sun and eventually Earthshine, high resolution shadow maps for dynamic shadow accuracy, real-time software ray-tracing for multi-surface bounce lighting to render sunlight reflected off surface elements and terrain features, and performance optimized level of detail shifting as the eyepoint changes in a scene. This paper details the DUST application, the technologies of the engine platform that enable scientific and engineering analysis, the unique techniques and processes developed to consume the DLES data sets, and how the tool is being used to support the Artemis program.

Lunar Visualization↗
DOE OSTI2020

Analysis of tow architecture variability in biaxially braided composite tubes

Spatial deviations in composite braid unit cell dimensions limit mechanical performance and are challenging to model. Full-field measurements of the irregular tow placement in biaxially braided composite tubes were obtained by digital image correlation. Analysis of the reconstructed tow paths showed long-range defects along the hoop direction with short-range defects dominating the biased tow direction. A route toward numerical simulation of the composite response is established by developing a 3D model of the composite using the measured tow trajectories. Finally, a comparison to previously-published triaxial braid results indicates axial tows work to constrain unit cells dimensions along the hoop direction.

3-Dimensional reinforcement↗
NASA NTRS2001

Miniaturized Autonomous Extravehicular Robotic Camera (Mini AERCam)

The NASA Johnson Space Center (JSC) Engineering Directorate is developing the Autonomous Extravehicular Robotic Camera (AERCam), a low-volume, low-mass free-flying camera system . AERCam project team personnel recently initiated development of a miniaturized version of AERCam known as Mini AERCam. The Mini AERCam target design is a spherical "nanosatellite" free-flyer 7.5 inches in diameter and weighing 1 0 pounds. Mini AERCam is building on the success of the AERCam Sprint STS-87 flight experiment by adding new on-board sensing and processing capabilities while simultaneously reducing volume by 80%. Achieving enhanced capability in a smaller package depends on applying miniaturization technology across virtually all subsystems. Technology innovations being incorporated include micro electromechanical system (MEMS) gyros, "camera-on-a-chip" CMOS imagers, rechargeable xenon gas propulsion system , rechargeable lithium ion battery, custom avionics based on the PowerPC 740 microprocessor, GPS relative navigation, digital radio frequency communications and tracking, micropatch antennas, digital instrumentation, and dense mechanical packaging. The Mini AERCam free-flyer will initially be integrated into an approximate flight-like configuration for demonstration on an airbearing table. A pilot-in-the-loop and hardware-in-the-loop simulation to simulate on-orbit navigation and dynamics will complement the airbearing table demonstration. The Mini AERCam lab demonstration is intended to form the basis for future development of an AERCam flight system that provides beneficial on-orbit views unobtainable from fixed cameras, cameras on robotic manipulators, or cameras carried by EVA crewmembers.

Fredrickson, Steven E.↗
DOE OSTI2026

Accelerating kinetic plasma simulations with machine-learning-generated initial conditions

Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.

Artificial neural networks↗
DOE OSTI2024

Nonlinear encoding in diffractive information processing using linear optical materials

Nonlinear encoding of optical information can be achieved using various forms of data representation. Here, we analyze the performances of different nonlinear information encoding strategies that can be employed in diffractive optical processors based on linear materials and shed light on their utility and performance gaps compared to the state-of-the-art digital deep neural networks. For a comprehensive evaluation, we used different datasets to compare the statistical inference performance of simpler-to-implement nonlinear encoding strategies that involve, e.g., phase encoding, against data repetition-based nonlinear encoding strategies. We show that data repetition within a diffractive volume (e.g., through an optical cavity or cascaded introduction of the input data) causes the loss of the universal linear transformation capability of a diffractive optical processor. Therefore, data repetition-based diffractive blocks cannot provide optical analogs to fully connected or convolutional layers commonly employed in digital neural networks. However, they can still be effectively trained for specific inference tasks and achieve enhanced accuracy, benefiting from the nonlinear encoding of the input information. Our results also reveal that phase encoding of input information without data repetition provides a simpler nonlinear encoding strategy with comparable statistical inference accuracy to data repetition-based diffractive processors. Our analyses and conclusions would be of broad interest to explore the push-pull relationship between linear material-based diffractive optical systems and nonlinear encoding strategies in visual information processors.

42 ENGINEERING↗
DOE OSTI2023

Conceptual Machine Learning Strategy for Maintenance of Molten Salt Heat Exchanger

This report addresses the requirements of Milestone M3.2 Define maintenance scenarios and benchmarks. Development of digital twins (DT) for molten salt reactor (MSR) components is crucial for reducing operating and maintenance costs (O&M) and ensuring commercial viability of these reactors. Our focus is on development of DT for MSR primary system heat exchanger (HX), a critical component, the fault in which can reduce operating efficiency and force reactor shutdown. We are investigating feasibility of a conceptual DT of HX consisting of internal distributed temperature sensing with fiber optics and machine learning (ML) algorithms to detect and localize faults.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Core–Multishell-Structured Digital-Gradient Cathode Materials with Enhanced Mechanical and Electrochemical Durability

Ni-rich cathode materials provide high energy density, but their structural and surface instability limits their cyclability and thermal stability. As one of the approaches to mitigate this problem, cathode materials comprising Ni-rich high-capacity core wrapped in Mn-rich multiple shells are produced successfully. In contrast to the conventional batch-type process for concentration-gradient materials, a digital-gradient cascade coprecipitation process described here achieves the improvements in productivity and quality consistency needed to move toward large-scale manufacturing. The core-multishell cathode materials produced in this manner not only have longer cycle life and improved rate performance compared to homogeneous Ni-rich cathode materials having the same overall composition, but also show remarkably enhanced thermal stability and low impedance growth characteristics. In a novel attempt to determine the correlation between the mechanical properties of the core-multishell cathode particles and their electrochemical cyclabilities, their breaking force and elasticity were successfully measured using a statistical approach, which indicates that a cathode particle with stable surface composition as well as high breaking force has improved capacity retention and durability. These results guide the realization of long life and high thermal stability in Ni-rich cathode materials through heterogeneous particle engineering.

25 ENERGY STORAGE↗
NASA NTRS2005

Real-time Enhanced Vision System

Flying in poor visibility conditions, such as rain, snow, fog or haze, is inherently dangerous. However these conditions can occur at nearly any location, so inevitably pilots must successfully navigate through them. At NASA Langley Research Center (LaRC), under support of the Aviation Safety and Security Program Office and the Systems Engineering Directorate, we are developing an Enhanced Vision System (EVS) that combines image enhancement and synthetic vision elements to assist pilots flying through adverse weather conditions. This system uses a combination of forward-looking infrared and visible sensors for data acquisition. A core function of the system is to enhance and fuse the sensor data in order to increase the information content and quality of the captured imagery. These operations must be performed in real-time for the pilot to use while flying. For image enhancement, we are using the LaRC patented Retinex algorithm since it performs exceptionally well for improving low-contrast range imagery typically seen during poor visibility conditions. In general, real-time operation of the Retinex requires specialized hardware. To date, we have successfully implemented a single-sensor real-time version of the Retinex on several different Digital Signal Processor (DSP) platforms. In this paper we give an overview of the EVS and its performance requirements for real-time enhancement and fusion and we discuss our current real-time Retinex implementations on DSPs.

Hines, Glenn D.↗
DOE OSTI2023

Laboratory Instrument Software Controlled Spread Spectrum Time Domain Reflectometry for Electrical Cable Testing

This research discusses development of a software-controlled laboratory instrument based spread spectrum time domain reflectometry system (SSTDR). This constitutes one task within PNNL’s Light Water Sustainability Program (LWRS) whose mission includes advancing nondestructive examination (NDE) techniques for off-line and on-line in-situ cable condition monitoring. In 2022, PNNL evaluated SSTDR for detection and characterization of a number of cable anomalies (Glass et al. 2022). The review included comparison of SSTDR to Frequency Domain Reflectometry (FDR) techniques which have enjoyed encouraging feedback and are starting to be used in nuclear power plants for periodic cable condition monitoring of cable systems as part of the plant’s overall cable aging management program. The FDR test introduces a broad-band chirp onto the cable at the cable end then listens for any reflection from a change of impedance along the cable caused by a damaged conductor or insulation, splices, contact with moisture, or other cable anomalies. The signal is captured in the frequency domain then transformed back to the time domain using an inverse Fourier transform (IFT). Based on the velocity of propagation, the impedance response signal is plotted against distance along the cable. Peak locations along the X-axis indicate the distance along the cable where a portion of the signal has been reflected back to the instrument as a result of a cable anomaly. The FDR test is considered the gold standard of reflectometry however it does require the cable to be de-energized to perform the test. The LIVEWIRE commercial SSTDR produces a similar plot to the FDR however all processing is in the time domain. A pseudo-random noise code (PN code) is input onto the cable conductor and the instrument listens for any reflected response from cable anomalies. The SSTDR processes the signal as an autocorrelation comparing the input PN code to any reflected signal detected. The autocorrelation analysis for thermal aging, water and water ingress detection, ground fault and phase-to-phase fault detection at various locations along the cable and with the cable attached and detached from a motor load, and on both energized and un-energized conditions were performed. These results were contrasted to Frequency Domain Reflectometry (FDR) measurements of the un-energized cable. Results were encouraging but indicated more work was warranted – particularly with the SSTDR, it seemed that the insulation damage would likely be better evaluated with multiple bandwidth cable tests particularly including larger bandwidths than were possible with the current commercial instrument. The commercial instrument’s bandwidth was set at 6, 12, 24, and 48MHz but note that SSTDR and FDR definitions of bandwidth trend similarly but are not the same. The FDR response could be more broadly adjusted, and the bandwidth of 100 to 500 MHz produced the best responses. FDR responses to anomalies were clearer than SSTDR responses and indications were that a broader bandwidth SSTDR may lead to improved SSTDR detection capability. This project used a laboratory instrument based SSTDR (primarily using an Arbitrary Waveform Generator (AWG) and a digital oscilloscope plus Python in-house software) that allowed software adjustment of the SSTDR bandwidth, window functions applied to the exciting Pseudo-random Noise (PN) code plus and other aspects of the SSTDR signal processing. Hereafter, this will be referred to as the PNNL SSTDR. Evaluating specific performance of the PNNL SSTDR is left to a separate report. This report documents hardware and software development to produce the SSTDR cable test system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Probabilistic learning and updating of a digital twin for composite material systems

This paper presents an approach for characterizing and estimating statistical dependence between a large number of observables in a composite material system. Conditional regression is carried out using the estimated joint density function, permitting a systematic exploration of interdependence between fine scale and coarse observables that can be used for both prognosis and design of complex material systems. An example demonstrates the integration of experimental data with a computational database. The statistical approach is based on the probabilistic learning on manifolds recently developed by the authors. This approach leverages intrinsic structure detected through diffusion on graphs with projected stochastic differential equations to generate samples constrained to that structure.

42 ENGINEERING↗