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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 1,171 records · Page 65

Linear solvers for power grid optimization problems: A review of GPU-accelerated linear solvers

The linear equations that arise in interior methods for constrained optimization are sparse symmetric indefinite, and they become extremely ill-conditioned as the interior method converges. These linear systems present a challenge for existing solver frameworks based on sparse LU or LDL T decompositions. Here, we benchmark five well known direct linear solver packages on CPU- and GPU-based hardware, using matrices extracted from power grid optimization problems. The achieved solution accuracy varies greatly among the packages. None of the tested packages delivers significant GPU acceleration for our test cases. For completeness of the comparison we include results for MA57, which is one of the most efficient and reliable CPU solvers for this class of problem.

97 MATHEMATICS AND COMPUTING↗

Biologically-informed excitatory and inhibitory ratio for robust spiking neural network training

Spiking neural networks drawing inspiration from biological constraints of the brain promise an energy-efficient paradigm for artificial intelligence. However, challenges exist in identifying guiding principles to train these networks in a robust fashion. In addition, training becomes an even more difficult problem when incorporating biological constraints of excitatory and inhibitory connections. In this work, we identify several key factors, such as low initial firing rates and diverse inhibitory spiking patterns, that determine the overall ability to train in the context of spiking networks with various ratios of excitatory to inhibitory neurons. The results indicate networks with biologically-realistic excitatory:inhibitory ratios can reliably train at low activity levels and in noisy environments. Additionally, the Van Rossum distance, a measure of spike train synchrony, provides insight into the importance of inhibitory neurons to increase network robustness to noise. This work supports further biologically-informed large-scale networks and energy efficient hardware implementations.

bio-inspired computing↗

Enabling Marine Energy Integration for Ocean Observing: Functional Requirements

Marine renewable energy (i.e., wave, tidal or ocean current, thermal gradient, and salinity gradient) or MRE can revolutionize ocean observing capabilities. Five use cases representing a range of ocean observing platforms were developed based on end-user feedback. Drawing from these use cases, common needs or functional requirements were developed to help guide the integration of MRE power delivery for ocean observation structures and functions. The functional requirements were determined from descriptions of the use cases, specifications of hardware that are used or closely associated with existing ocean observation platforms, and direct feedback from ocean observation sensor/platform developers and users. Twenty types of functional requirements were identified, including those associated with power and energy use; physical system requirements; temperature and depth; electrical, acoustic, and motion interference; and reliability. Each set of functional requirements is illustrated as features of the use cases. By defining functional requirements for MRE technology integration in ocean observing platforms, and focusing on end-user requirements, barriers to developing MRE-driven ocean observation missions can be reduced.

50 EE - Wind and Water Power Program - Water (EE-4↗

Distributed Wind Monitoring Best Practices

Accessible performance and operational data have been identified as a key enabler for distributed wind energy industry advancement. While utility-scale wind turbines benefit from reliable and continuous supervisory control and data acquisition (SCADA)-based monitoring platforms, monitoring of the U.S. fleet of distributed wind (DW) turbines has been more inconsistent, unreliable, and sometime difficult to access. Without fleet monitoring data, the industry will never understand and thus work to improve turbine under-performance and reliability issues. For the DW industry to scale up, attract investors, and boost credibility, fleetwide monitoring must be robust and reliable, select data must be made accessible to stakeholders, and the data must be in a format useful to users. To help move the industry toward a more standardized, accessible stream of monitoring data, this distributed wind monitoring best practices report attempts to cover topics including key monitoring channels, hardware, communication strategies, and accessibility. Strategic engagement with DW original equipment manufacturers (OEMs), service providers, lab and university researchers, testing organization, certification bodies, end users and solar photovoltaic (PV) monitoring experts has enabled a better understanding of the current state-of-the-art of monitoring and aided in articulating this set of best practices that will guide OEMs toward harmonized monitoring strategies, aimed at a future goal of achieving accessible performance and operational data for the entire fleet of U.S. distributed wind turbines.

17 WIND ENERGY↗

Developments in the design, analysis, and fabrication of advanced technology transmission elements

Over the last decade, the presently reported proprietary development program for the reduction of helicopter drive system weight and cost and the enhancement of reliability and survivability has produced high speed roller bearings, resin-matrix composite rotor shafts and transmission housings, gear/bearing/shaft system integrations, photoelastic investigation methods for gear tooth strength, and the automatic generation of complex FEM models for gear/shaft systems. After describing the design features and performance capabilities of the hardware developed, attention is given to the prospective benefits to be derived from application of these technologies, with emphasis on the relationship between helicopter drive system performance and cost.

Drago, R. J.↗

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Szatkowski, Gerard P.↗

Probabilistic structural mechanics research for parallel processing computers

Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical.

Sues, Robert H.↗

A safety-based decision making architecture for autonomous systems

Engineering systems designed specifically for space applications often exhibit a high level of autonomy in the control and decision-making architecture. As the level of autonomy increases, more emphasis must be placed on assimilating the safety functions normally executed at the hardware level or by human supervisors into the control architecture of the system. The development of a decision-making structure which utilizes information on system safety is detailed. A quantitative measure of system safety, called the safety self-information, is defined. This measure is analogous to the reliability self-information defined by McInroy and Saridis, but includes weighting of task constraints to provide a measure of both reliability and cost. An example is presented in which the safety self-information is used as a decision criterion in a mobile robot controller. The safety self-information is shown to be consistent with the entropy-based Theory of Intelligent Machines defined by Saridis.

Musto, Joseph C.↗

Extravehicular Activity (EVA) Technology Development Status and Forecast

Beginning in Fiscal Year (FY) 2011, Extravehicular activity (EVA) technology development became a technology foundational domain under a new program Enabling Technology Development and Demonstration. The goal of the EVA technology effort is to further develop technologies that will be used to demonstrate a robust EVA system that has application for a variety of future missions including microgravity and surface EVA. Overall the objectives will be reduce system mass, reduce consumables and maintenance, increase EVA hardware robustness and life, increase crew member efficiency and autonomy, and enable rapid vehicle egress and ingress. Over the past several years, NASA realized a tremendous increase in EVA system development as part of the Exploration Technology Development Program and the Constellation Program. The evident demand for efficient and reliable EVA technologies, particularly regenerable technologies was apparent under these former programs and will continue to be needed as future mission opportunities arise. The technological need for EVA in space has been realized over the last several decades by the Gemini, Apollo, Skylab, Space Shuttle, and the International Space Station (ISS) programs. EVAs were critical to the success of these programs. Now with the ISS extension to 2028 in conjunction with a current forecasted need of at least eight EVAs per year, the EVA technology life and limited availability of the EMUs will become a critical issue eventually. The current Extravehicular Mobility Unit (EMU) has vastly served EVA demands by performing critical operations to assemble the ISS and provide repairs of satellites such as the Hubble Space Telescope. However, as the life of ISS and the vision for future mission opportunities are realized, a new EVA systems capability could be an option for the future mission applications building off of the technology development over the last several years. Besides ISS, potential mission applications include EVAs for missions to Near Earth Objects (NEO), Phobos, or future surface missions. Surface missions could include either exploration of the Moon or Mars. Providing an EVA capability for these types of missions enables in-space construction of complex vehicles or satellites, hands on exploration of new parts of our solar system, and engages the public through the inspiration of knowing that humans are exploring places that they have never been before. This paper offers insight into what is currently being developed and what the potential opportunities are in the forecast

Chullen, Cinda↗

NASA Space Technology Draft Roadmap Area 13: Ground and Launch Systems Processing

This slide presentation reviews the technology development roadmap for the area of ground and launch systems processing. The scope of this technology area includes: (1) Assembly, integration, and processing of the launch vehicle, spacecraft, and payload hardware (2) Supply chain management (3) Transportation of hardware to the launch site (4) Transportation to and operations at the launch pad (5) Launch processing infrastructure and its ability to support future operations (6) Range, personnel, and facility safety capabilities (7) Launch and landing weather (8) Environmental impact mitigations for ground and launch operations (9) Launch control center operations and infrastructure (10) Mission integration and planning (11) Mission training for both ground and flight crew personnel (12) Mission control center operations and infrastructure (13) Telemetry and command processing and archiving (14) Recovery operations for flight crews, flight hardware, and returned samples. This technology roadmap also identifies ground, launch and mission technologies that will: (1) Dramatically transform future space operations, with significant improvement in life-cycle costs (2) Improve the quality of life on earth, while exploring in co-existence with the environment (3) Increase reliability and mission availability using low/zero maintenance materials and systems, comprehensive capabilities to ascertain and forecast system health/configuration, data integration, and the use of advanced/expert software systems (4) Enhance methods to assess safety and mission risk posture, which would allow for timely and better decision making. Several key technologies are identified, with a couple of slides devoted to one of these technologies (i.e., corrosion detection and prevention). Development of these technologies can enhance life on earth and have a major impact on how we can access space, eventually making routine commercial space access and improve building and manufacturing, and weather forecasting for example for the effect of these process improvements on our daily lives.

Clements, Greg↗

Avionics Architectures for Exploration: Ongoing Efforts in Human Spaceflight

The field of Avionics is advancing far more rapidly in terrestrial applications than in spaceflight applications. Spaceflight Avionics are not keeping pace with expectations set by terrestrial experience, nor are they keeping pace with the need for increasingly complex automation and crew interfaces as we move beyond Low Earth Orbit. NASA must take advantage of the strides being made by both space-related and terrestrial industries to drive our development and sustaining costs down. This paper describes ongoing efforts by the Avionics Architectures for Exploration (AAE) project chartered by NASA's Advanced Exploration Systems (AES) Program to evaluate new avionic architectures and technologies, provide objective comparisons of them, and mature selected technologies for flight and for use by other AES projects. The AAE project team includes members from most NASA centers, and from industry. It is our intent to develop a common core avionic system that has standard capabilities and interfaces, and contains the basic elements and functionality needed for any spacecraft. This common core will be scalable and tailored to specific missions. It will incorporate hardware and software from multiple vendors, and be upgradeable in order to infuse incremental capabilities and new technologies. It will maximize the use of reconfigurable open source software (e.g., Goddard Space Flight Center's (GSFC's) Core Flight Software (CFS)). Our long-term focus is on improving functionality, reliability, and autonomy, while reducing size, weight, and power. Where possible, we will leverage terrestrial commercial capabilities to drive down development and sustaining costs. We will select promising technologies for evaluation, compare them in an objective manner, and mature them to be available for future programs. The remainder of this paper describes our approach, technical areas of emphasis, integrated test experience and results as of mid-2014, and future plans. As a part of the AES Program, we are encouraged to set aggressive goals and fall short if necessary, rather than to set our sights too low. We are also asked to emphasize providing our personnel with hands-on experience in development, integration, and testing. That we have embraced both of these philosophies will be evident in the descriptions below.

Goforth, Montgomery B.↗

Enabling Marine Energy Integration for Ocean Observing: Functional Requirements

Marine renewable energy (i.e., wave, tidal or ocean current, thermal gradient, and salinity gradient) or MRE can revolutionize ocean observing capabilities. Five use cases representing a range of ocean observing platforms were developed based on end-user feedback. Drawing from these use cases, common needs or functional requirements were developed to help guide the integration of MRE power delivery for ocean observation structures and functions. The functional requirements were determined from descriptions of the use cases, specifications of hardware that are used or closely associated with existing ocean observation platforms, and direct feedback from ocean observation sensor/platform developers and users. Twenty types of functional requirements were identified, including those associated with power and energy use; physical system requirements; temperature and depth; electrical, acoustic, and motion interference; and reliability. Each set of functional requirements is illustrated as features of the use cases. By defining functional requirements for MRE technology integration in ocean observing platforms, and focusing on end-user requirements, barriers to developing MRE-driven ocean observation missions can be reduced.

Cavagnaro, Robert J.↗

"Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test"

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. We explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

Jang, Kathy↗

Interchangeable end effector tools utilized on the PFMA

An instrumented task board, used for measuring forces applied by the Protoflight Manipulator Arm (PFMA) to the task board, was fabricated and delivered to Marshall Space Flight Center. SRS Technologies phased out the existing IBM compatible data acquisition system, used with a instrumented task board, and integrated the force measuring electronic hardware in with the Macintosh II data acquisition system. The purpose of this change was to acquire all data with the same time tag, allowing easier and more accurate data reduction in addition to real-time graphics. A three-dimensional optical position sensing system for determining the location of the PFMA's end effect or in reference to the center of the instrumented task board was also designed and delivered under. An improved task board was fabricated which included an improved instrumented beam design. The modified design of the task board improved the force/torque measurement system by increasing the sensitivity, reliability, load range and ease of maintenance. A calibration panel for the optical position system was also designed and fabricated. The calibration method developed for the position sensors enhanced the performance of the sensors as well as simplified the installation and calibration procedures required. The modifications made under this effort expanded the capabilities of the task board system. The system developed determines the arm's position relative to the task board and measures the signals to the joints resulting from the operator's control signals in addition to the task board forces. The software and hardware required to calculate and record the position of the PFMA during the performance of tasks with the instrumented task board were defined, designed and delivered to MSFC. PFMA joint input signals can be measured from a breakout box to evaluate the sensitivity or response of the arm operation to control commands. The data processing system provides the capability for post processing of time-history graphics and plots of the PFMA positions, the operator's actions, and the PFMA servo reactions in addition to realtime force and position sensor data presentation.

Cody, Joe↗

A Scalable Quantum Cryptography Network for Protected Automation Communication (Final Report)

This is the final report for a CEDS-funded project aimed at developing a new quantum technology for securing utility communication networks used to control and monitor electrical grid equipment. Securing these control networks represents a unique challenge as the performance of the security solution has a direct impact on the stability and reliability of the electrical grid. Traditional, software-based solutions - developed for information networks - are not suitable for utility control networks because they introduce latency, require burdensome maintenance and upgrades, are often incompatible with legacy equipment, and introduce operational complexity that reduces grid reliability. Consequently, many U.S. utilities do not use existing solutions and, instead, protect their critical control networks through the careful isolation and obscuration of their networked equipment. With more utilities embracing grid automation, the attack surface that utilities must defend from hackers has grown to an unmanageable size. To address this situation, Qubitekk and its partners proposed and developed a hardware-based solution that can secure critical control networks without negatively impacting grid performance. This new solution is based on quantum key distribution (QKD) techniques that guarantee secure key generation and distribution across a utility control network. Through deployment and field testing of a prototype QKD system, we have shown that this solution delivers long-term network security, is technically feasible to implement and maintain on a utility’s distribution substation network and does not negatively impact grid operations. In addition, the project has identified and solved key challenges associated with generating, transmitting, and measuring coherent photonic quantum states on a real-world fiber optic network. These additional findings are playing a critical role in advancing quantum networks for quantum computing applications. An overview of the QKD prototype development effort, field testing activities and results, and additional findings relevant to emerging quantum networks are presented in this report.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Embedded Sensors and Controls to Improve Component Performance and Reliability -- Bench-scale Testbed Design Report

Embedded instrumentation and control systems that can operate in extreme environments are challenging due to restrictions on sensors and materials. As a part of the Department of Energy's Nuclear Energy Enabling Technology cross-cutting technology development programs Advanced Sensors and Instrumentation topic, this report details the design of a bench-scale embedded instrumentation and control testbed. The design goal of the bench-scale testbed is to build a re-configurable system that can rapidly deploy and test advanced control algorithms in a hardware in the loop setup. The bench-scale testbed will be designed as a fluid pump analog that uses active magnetic bearings to support the shaft. The testbed represents an application that would improve the efficiency and performance of high temperature (700 C) pumps for liquid salt reactors that operate in an extreme environment and provide many engineering challenges that can be overcome with embedded instrumentation and control. This report will give details of the mechanical design, electromagnetic design, geometry optimization, power electronics design, and initial control system design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Spacelab 4: Primate experiment support hardware

A squirrel monkey feeder and automatic urine collection system were designed to fly on the Spacelab 4 Shuttle Mission presently scheduled for January 1986. Prototypes of the feeder and urine collection systems were fabricated and extensively tested on squirrel monkeys at the National Aeronautics and Space Administration's (NASA) Ames Research Center (ARC). The feeder design minimizes impact on the monkey's limited space in the cage and features improved reliability and biocompatibility over previous systems. The urine collection system is the first flight qualified, automatic urine collection device for squirrel monkeys. Flight systems are currently being fabricated.

Fusco, P. R.↗

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗