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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 379 records · Page 21

Property Variations in Modern REBCO Coated Conductors from Multiple Manufacturers

The complex, multilayer structure of REBCO Coated Conductor (CC) poses significant challenges in the fabrication of high magnetic field devices where large stresses may initiate various forms of damage. Our goal is to peer below the cartoon representations of CC so that, amongst other things, we might better understand whether a CC from one manufacturer is interchangeable with that from another. This involves knowledge of a broad range of electromagnetic, geometric, microstructural, and J c (θ,B,T) properties, and their variations that collectively pose challenges for the fault tolerance of REBCO CC devices. Accordingly, comparative measurements of J c , visualization of flux penetration with Magneto-Optical Imaging (MOI), tape geometry from Scanning Electron Microscopy (SEM) of polished cross-sections, and extensive optical microscopy was performed on recently purchased samples from multiple manufacturers. Our analyses reveal many deviations from or characteristics absent from manufacturers’ specifications, while a comparison of different manufacturers’ mechanically and laser slit tapes shows a diverse array of slitting characteristics amongst the manufacturers and variation in properties those made to the same specification. Laser slit tapes from several manufacturers reveal ablated edges with damaged regions extending up to 50 μm, comparable to the damaged region found in the mechanically slit CC of this study. Overall, the aim of this study is to flesh out appropriate ways to understand the real conductor below the manufacturers’ cartoons to avoid surprises in our REBCO CC coil development program. The goal of this work was to perform a broad array of characterizations of the type needed for validation of purpose for making high field magnets: to our surprise we found a wide range of properties which greatly impact the mechanical strength and electromagnetic performance of solenoids composed of these conductors and reinforced the need for a broad characterization program for each conductor prior to its implementation.

Bradford, G.↗

Accelerated Aging Experiments for Capacitor Health Monitoring and Prognostics

This paper discusses experimental setups for health monitoring and prognostics of electrolytic capacitors under nominal operation and accelerated aging conditions. Electrolytic capacitors have higher failure rates than other components in electronic systems like power drives, power converters etc. Our current work focuses on developing first-principles-based degradation models for electrolytic capacitors under varying electrical and thermal stress conditions. Prognostics and health management for electronic systems aims to predict the onset of faults, study causes for system degradation, and accurately compute remaining useful life. Accelerated life test methods are often used in prognostics research as a way to model multiple causes and assess the effects of the degradation process through time. It also allows for the identification and study of different failure mechanisms and their relationships under different operating conditions. Experiments are designed for aging of the capacitors such that the degradation pattern induced by the aging can be monitored and analyzed. Experimental setups and data collection methods are presented to demonstrate this approach.

Prognostics of Electronics↗

Analyzing Prospects for Quantum Advantage in Topological Data Analysis

Lloyd [Nat. Commun. , 10138 (2016)] were first to demonstrate the promise of quantum algorithms for computing Betti numbers, a way to characterize topological features of data sets. Here, we propose, analyze, and optimize an improved quantum algorithm for topological data analysis (TDA) with reduced scaling, including a method for preparing Dicke states based on inequality testing, a more efficient amplitude estimation algorithm using Kaiser windows, and an optimal implementation of eigenvalue projectors based on Chebyshev polynomials. We compile our approach to a fault-tolerant gate set and estimate constant factors in the Toffoli complexity. Our analysis reveals that superquadratic quantum speedups are only possible for this problem when targeting a multiplicative error approximation and the Betti number grows asymptotically. Further, we propose a dequantization of the quantum TDA algorithm that shows that having exponentially large dimension and Betti number are necessary, but insufficient conditions, for superpolynomial advantage. We then introduce and analyze specific problem examples which have parameters in the regime where superpolynomial advantages may be achieved, and argue that quantum circuits with tens of billions of Toffoli gates can solve seemingly classically intractable instances. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗

Scalable Circuit Cutting and Scheduling in a Resource-constrained and Distributed Quantum System

Despite quantum computing's rapid development, current systems remain limited in practical applications due to their limited qubit count and quality. Various technologies, such as superconducting, trapped ions, and neutral atom quantum computing technologies are progressing towards a fault tolerant era, however they all face a diverse set of challenges in scalability and control. Recent efforts have focused on multi-node quantum systems that connect multiple smaller quantum devices to execute larger circuits. Future demonstrations hope to use quantum channels to couple systems, however current demonstrations can leverage classical communication with circuit cutting techniques. This involves cutting large circuits into smaller subcircuits and reconstructing them post-execution. However, existing cutting methods are hindered by lengthy search times as the number of qubits and gates increases. Additionally, they often fail to effectively utilize the resources of various worker configurations in a multi-node system. To address these challenges, we introduce FitCut, a novel approach that transforms quantum circuits into weighted graphs and utilizes a community-based, bottom-up approach to cut circuits according to resource constraints, e.g., qubit counts, on each worker. FitCut also includes a scheduling algorithm that optimizes resource utilization across workers. Implemented with Qiskit and evaluated extensively, FitCut significantly outperforms the Qiskit Circuit Knitting Toolbox, reducing time costs by factors ranging from 3 to 2000 and improving resource utilization rates by up to 3.88 times on the worker side, achieving a system-wide improvement of 2.86 times.

Kan, Shuwen [Fordham University]↗

Analysis of a Memory Device Failure

The recent failure of a vintage memory device presented a unique challenge to failure analysts. Normally device layouts, fabrication parameters and other technical information were available to assist the analyst in the analysis. However, this device was out of production for many years and the manufacturer was no longer in business, so the information was not available. To further complicate this analysis, the package leads were all but removed making additional electrical testing difficult. Under these conditions, new and innovative methods were used to analyze the failure. The external visual exam, radiography, PIND, and leak testing were performed with nominal results. Since electrical testing was precluded by the short lead lengths, the device was delidded to expose the internal structures for microscopic examination. No failure mechanism was identified. The available electrical data suggested an ESD or low level EOS type mechanism which left no visible surface damage. Due to parallel electrical paths, electrical probing on the chip failed to locate the failure site. Two non-destructive Scanning Electron Microscopy techniques, CIVA (Charge Induced Voltage Alteration) and EBIC (Electron Beam Induced Current), and a liquid crystal decoration technique which detects localized heating were employed to aid in the analysis. CIVA and EBIC isolated two faults in the input circuitry, and the liquid crystal technique further localized two hot spots in regions on two input gates. Removal of the glassivation and metallization revealed multiple failure sites located in the gate oxide of two input transistors suggesting machine (testing) induced damage.

Nicolas, David P.↗

Compact, Reliable EEPROM Controller

A compact, reliable controller for an electrically erasable, programmable read-only memory (EEPROM) has been developed specifically for a space-flight application. The design may be adaptable to other applications in which there are requirements for reliability in general and, in particular, for prevention of inadvertent writing of data in EEPROM cells. Inadvertent writes pose risks of loss of reliability in the original space-flight application and could pose such risks in other applications. Prior EEPROM controllers are large and complex and do not provide all reasonable protections (in many cases, few or no protections) against inadvertent writes. In contrast, the present controller provides several layers of protection against inadvertent writes. The controller also incorporates a write-time monitor, enabling determination of trends in the performance of an EEPROM through all phases of testing. The controller has been designed as an integral subsystem of a system that includes not only the controller and the controlled EEPROM aboard a spacecraft but also computers in a ground control station, relatively simple onboard support circuitry, and an onboard communication subsystem that utilizes the MIL-STD-1553B protocol. (MIL-STD-1553B is a military standard that encompasses a method of communication and electrical-interface requirements for digital electronic subsystems connected to a data bus. MIL-STD- 1553B is commonly used in defense and space applications.) The intent was to both maximize reliability while minimizing the size and complexity of onboard circuitry. In operation, control of the EEPROM is effected via the ground computers, the MIL-STD-1553B communication subsystem, and the onboard support circuitry, all of which, in combination, provide the multiple layers of protection against inadvertent writes. There is no controller software, unlike in many prior EEPROM controllers; software can be a major contributor to unreliability, particularly in fault situations such as the loss of power or brownouts. Protection is also provided by a powermonitoring circuit.

Katz, Richard↗

Mission Radiation Environment Modeling and Analysis: Avionics Trade Study for GCD Rad-Neuro Project

The two main objectives of this trade study are characterizing the mission radiation environment for multiple Design Reference Missions (DRM) and analysis of radiation effects on avionics with the goal of producing radiation tolerant Neuromorphic Computing processor chips with innovative radiation-induced fault mitigation. The NASA process for defining radiation requirements for flight avionics is applied to this domain. The effects of trapped protons and electrons in the Van Allen radiation belts predominates in Low-Earth-Orbit (LEO) and the solar wind, solar flares and Galactic Cosmic Rays (GCRs) are the dominant radiation challenge in the open space between the planets of our solar system. The nature and energy of the particles that cause circuit upset and failure is very different in the two regimes. Two results are produced from the radiation models: determining the Total Integrated Dose (TID) experienced by avionics for a given DRM and predicting the Single Event Effects (SEE) rates for avionics during high rate exposure. These tools are applied to existing semiconductors and can be used for predicting the radiation performance of future semiconductors based on early radiation testing of new devices.

Space Radiation↗

Autonomous Satellite Command and Control through the World Wide Web: Phase 3

NASA's New Millenium Program (NMP) has identified a variety of revolutionary technologies that will support orders of magnitude improvements in the capabilities of spacecraft missions. This program's Autonomy team has focused on science and engineering automation technologies. In doing so, it has established a clear development roadmap specifying the experiments and demonstrations required to mature these technologies. The primary developmental thrusts of this roadmap are in the areas of remote agents, PI/operator interface, planning/scheduling fault management, and smart execution architectures. Phases 1 and 2 of the ASSET Project (previously known as the WebSat project) have focused on establishing World Wide Web-based commanding and telemetry services as an advanced means of interfacing a spacecraft system with the PI and operators. Current automated capabilities include Web-based command submission, limited contact scheduling, command list generation and transfer to the ground station, spacecraft support for demonstrations experiments, data transfer from the ground station back to the ASSET system, data archiving, and Web-based telemetry distribution. Phase 2 was finished in December 1996. During January-December 1997 work was commenced on Phase 3 of the ASSET Project. Phase 3 is the subject of this report. This phase permitted SSDL and its project partners to expand the ASSET system in a variety of ways. These added capabilities included the advancement of ground station capabilities, the adaptation of spacecraft on-board software, and the expansion of capabilities of the ASSET management algorithms. Specific goals of Phase 3 were: (1) Extend Web-based goal-level commanding for both the payload PI and the spacecraft engineer; (2) Support prioritized handling of multiple PIs as well as associated payload experimenters; (3) Expand the number and types of experiments supported by the ASSET system and its associated spacecraft; (4) Implement more advanced resource management, modeling and fault management capabilities that integrate the space and ground segments of the space system hardware; (5) Implement a beacon monitoring test; (6) Implement an experimental blackboard controller for space system management; (7) Further define typical ground station developments required for Internet-based remote control and for full system automation of the PI-to-spacecraft link. Each of those goals is examined in the next section. Significant sections of this report were also published as a conference paper.

Cantwell, Brian↗

Adapting Secure MultiParty Computation to Support Machine Learning in Radio Frequency Sensor Networks

In this project we developed and validated algorithms for privacy-preserving linear regression using a new variant of Secure Multiparty Computation (MPC) we call "Hybrid MPC" (hMPC). Our variant is intended to support low-power, unreliable networks of sensors with low-communication, fault-tolerant algorithms. In hMPC we do not share training data, even via secret sharing. Thus, agents are responsible for protecting their own local data. Only the machine learning (ML) model is protected with information-theoretic security guarantees against honest-but-curious agents. There are three primary advantages to this approach: (1) after setup, hMPC supports a communication-efficient matrix multiplication primitive, (2) organizations prevented by policy or technology from sharing any of their data can participate as agents in hMPC, and (3) large numbers of low-power agents can participate in hMPC. We have also created an open-source software library named "Cicada" to support hMPC applications with fault-tolerance. The fault-tolerance is important in our applications because the agents are vulnerable to failure or capture. We have demonstrated this capability at Sandia's Autonomy New Mexico laboratory through a simple machine-learning exercise with Raspberry Pi devices capturing and classifying images while flying on four drones.

42 ENGINEERING↗

Breaking down barriers in cooperative fault management: Temporal and functional information displays

At the highest level, the fundamental question addressed by this research is how to aid human operators engaged in dynamic fault management. In dynamic fault management there is some underlying dynamic process (an engineered or physiological process referred to as the monitored process - MP) whose state changes over time and whose behavior must be monitored and controlled. In these types of applications (dynamic, real-time systems), a vast array of sensor data is available to provide information on the state of the MP. Faults disturb the MP and diagnosis must be performed in parallel with responses to maintain process integrity and to correct the underlying problem. These situations frequently involve time pressure, multiple interacting goals, high consequences of failure, and multiple interleaved tasks.

Potter, Scott S.↗

Extended Investigation into Fault-Tolerant Integrated Motor Drive for a Quadrotor Urban Air Mobility (UAM) Aircraft

Electric propulsor machines and their associated power electronics have been identified in past studies as low-reliability components in emerging Urban Air Mobility (UAM) Vertical Takeoff and Landing (VTOL) vehicles that raise their predicted catastrophic failure rates. This research effort extends previously presented work investigating the use of fault-tolerant (FT) motor drives in quadrotor aircraft as a promising approach to significantly increase their mean-time-to-failure (MTTF). In particular, fault-tolerant modular motor drives (FT-MMDs) are identified as strong candidates for closing the electric propulsor reliability gap. These FT-MMDs divide a machine drive into multiple redundant modules, each consisting of three phase stator windings and power electronics units, enabling continued machine operation after a module failure. Achieving the highest possible isolation between modules (physical, magnetic, thermal, electrical) is critically important in FT-MMDs to prevent the propagation of any failure between modules. Key additional requirements for achieving the highest possible reliability characteristics with FT-MMDs are high repair rates and aggressive suppression of all single-point failures.

quadrotor↗

Assessment of the Electrical Substation-Grid Testbed with Inside/Outside Devices and Distributed Ledger Technology

The electrical substation-grid testbed was created to integrate the GOOSE and/or DNP (Distributed Network Protocol) messages with time synchronized sources and Distributed Ledger Technology (DLT). The objective was to study the impact of faults and cyber-events at an electrical substation with inside (protective relays) and outside (power meters) substation devices. The electrical substation-grid testbed was based on the design of a 34.5/ 12.47 kV electrical substation (sectionalized bus configuration) with two power transformers, connected to radial power lines and load feeders. The electrical substation-grid testbed was installed at 252 lab space (Advanced Power System Protection), Grid Research Integration and Deployment Center (GRID-C), Oak Ridge National Laboratory. This testbed was created for Task 5, DarkNet project. The electrical substation-grid testbed was created to simulate fault and/or cyber events that could potentially result in damage to the electrical infrastructure. In addition, tests were run that are usually not allowed to be performed in an operational electrical power grid, because these test scenarios could trip breakers and/or generate fault situations that could potentially damage equipment. The number of tests performed in the electrical substation-grid testbed were executed in a better way than in a real electrical substation and/or power grid, because multiple tests could be run in a short period of time, and complex permits, and safety/ schedule restrictions like in a real electrical substation environment were not needed. The electrical substation-grid testbed was created using real measurement, communication, and protection devices that are used by electrical utilities, to have same conditions that we could observe in a real power grid or electrical substation. The electrical substation-grid testbed was based on using a real time simulator and expansion box with amplifiers that were wired to electrical substation-grid devices. This hardware-in-the-loop (HIL) was provided by protective relays, power meters, ethernet switches, remote terminal units, synchronized timing network clock, DLT devices, workstations, and servers. This report includes the design, installation, and assessment of the electrical substation-grid testbed that was similar to an operational electrical substation, integrating the power system protection, communication, and control systems. The results for the electrical substation-grid testbed were based on:• verifying the analog signals for protective relays and power meters, • observing the synchronized time source frame at devices, • authenticating the GOOSE (IEC 61850) and DNP messages from power meters and protective relays, and • verifying the trip conditions of protective relays at fault tests with the power system fault event detection, using DLT devices. For future work, the electrical substation-grid testbed with protective relays and power meters, using DLT and synchronized time source from DarkNet, will be used to study the impact of cyber-events at inside and outside substation devices. Advanced algorithms for detecting cyber-events produced by non-desired protective relay settings will be studied, to improve the detection and reliability of protection, control, and communication systems at power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Performance and power modeling and prediction using MuMMI and 10 machine learning methods

Energy-efficient scientific applications require insight into how high performance computing system features impact the applications' power and performance. This insight can result from the development of performance and power models. Here, in this article, we use the modeling and prediction tool MuMMI (Multiple Metrics Modeling Infrastructure) and 10 machine learning methods to model and predict performance and power consumption and compare their prediction error rates. We use an algorithm-based fault-tolerant linear algebra code and a multilevel checkpointing fault-tolerant heat distribution code to conduct our modeling and prediction study on the Cray XC40 Theta and IBM BG/Q Mira at Argonne National Laboratory and the Intel Haswell cluster Shepard at Sandia National Laboratories. Our experimental results show that the prediction error rates in performance and power using MuMMI are less than 10% for most cases. By utilizing the models for runtime, node power, CPU power, and memory power, we identify the most significant performance counters for potential application optimizations, and we predict theoretical outcomes of the optimizations. Based on two collected datasets, we analyze and compare the prediction accuracy in performance and power consumption using MuMMI and 10 machine learning methods.

97 MATHEMATICS AND COMPUTING↗

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗

Research in computer science

Synopses are given for NASA supported work in computer science at the University of Virginia. Some areas of research include: error seeding as a testing method; knowledge representation for engineering design; analysis of faults in a multi-version software experiment; implementation of a parallel programming environment; two computer graphics systems for visualization of pressure distribution and convective density particles; task decomposition for multiple robot arms; vectorized incomplete conjugate gradient; and iterative methods for solving linear equations on the Flex/32.

Ortega, J. M.↗

Signal and data processing of small targets 1989; Proceedings of the Meeting, Orlando, FL, Mar. 27-29, 1989

The present conference on digital signal processing, association and filtering techniques, and multiple-sensor/multiple-tracking techniques, discusses single-frame velocity estimation, efficient target extraction for laser radar imagery, precision target tracking for small extended objects, IR clutter partitioning for matched filter design, the maximum-likelihood approach to gamma circumvention, position estimation for optical point targets using staring detector arrays, and a multiple-scan signal processing technique for area-moving target indication. Also discussed are a proportional integral estimator, the prediction of track purity in tracking performance evaluations, synchronization and fault-tolerance in a distributed tracker, the benefits of soft sensors and probabilistic fusion, and testing track initiation algorithms fusing two-dimensional tracks.

Drummond, Oliver E.↗

Patterns of brittle deformation under extension on Venus

The development of fractures at regular length scales is a widespread feature of Venusian tectonics. Models of lithospheric deformation under extension based on non-Newtonian viscous flow and brittle-plastic flow develop localized failure at preferred wavelengths that depend on lithospheric thickness and stratification. The characteristic wavelengths seen in rift zones and tessera can therefore provide constraints on crustal and thermal structure. Analytic solutions were obtained for growth rates in infinitesimal perturbations imposed on a one-dimensional, layered rheology. Brittle layers were approximated by perfectly-plastic, uniform strength, overlying ductile layers exhibiting thermally-activated power-law creep. This study investigates the formation of faults under finite amounts of extension, employing a finite-element approach. Our model incorporates non-linear viscous rheology and a Coulomb failure envelope. An initial perturbation in crustal thickness gives rise to necking instabilities. A small amount of velocity weakening serves to localize deformation into planar regions of high strain rate. Such planes are analogous to normal faults seen in terrestrial rift zones. These 'faults' evolve to low angle under finite extension. Fault spacing, orientation and location, and the depth to the brittle-ductile transition, depend in a complex way on lateral variations in crustal thickness. In general, we find that multiple wavelengths of deformation can arise from the interaction of crustal and mantle lithosphere.

Neumann, G. A.↗

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

Ali, Moonis↗