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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Geometric registration and rectification of spaceborne SAR imagery

This paper describes the development of automated location and geometric rectification techniques for digitally processed synthetic aperture radar (SAR) imagery. A software package has been developed that is capable of determining the absolute location of an image pixel to within 60 m using only the spacecraft ephemeris data and the characteristics of the SAR data collection and processing system. Based on this location capability algorithms have been developed that geometrically rectify the imagery, register it to a common coordinate system and mosaic multiple frames to form extended digital SAR maps. These algorithms have been optimized using parallel processing techniques to minimize the operating time. Test results are given using Seasat SAR data.

Curlander, J. C.↗
NASA NTRS1999

Advanced Interactive Display Formats for Terminal Area Traffic Control

This research project deals with an on-line dynamic method for automated viewing parameter management in perspective displays. Perspective images are optimized such that a human observer will perceive relevant spatial geometrical features with minimal errors. In order to compute the errors at which observers reconstruct spatial features from perspective images, a visual spatial-perception model was formulated. The model was employed as the basis of an optimization scheme aimed at seeking the optimal projection parameter setting. These ideas are implemented in the context of an air traffic control (ATC) application. A concept, referred to as an active display system, was developed. This system uses heuristic rules to identify relevant geometrical features of the three-dimensional air traffic situation. Agile, on-line optimization was achieved by a specially developed and custom-tailored genetic algorithm (GA), which was to deal with the multi-modal characteristics of the objective function and exploit its time-evolving nature.

Grunwald, Arthur J.↗
NASA NTRS1999

Advanced Interactive Display Formats for Terminal Area Traffic Control

This research project deals with an on-line dynamic method for automated viewing parameter management in perspective displays. Perspective images are optimized such that a human observer will perceive relevant spatial geometrical features with minimal errors. In order to compute the errors at which observers reconstruct spatial features from perspective images, a visual spatial-perception model was formulated. The model was employed as the basis of an optimization scheme aimed at seeking the optimal projection parameter setting. These ideas are implemented in the context of an air traffic control (ATC) application. A concept, referred to as an active display system, was developed. This system uses heuristic rules to identify relevant geometrical features of the three-dimensional air traffic situation. Agile, on-line optimization was achieved by a specially developed and custom-tailored genetic algorithm (GA), which was to deal with the multi-modal characteristics of the objective function and exploit its time-evolving nature.

Grunwald, Arthur J.↗
NASA NTRS2019

Human Performance Contributions to Safety in Commercial Aviation

Every day in aviation, pilots, air traffic controllers, and other front-line personnel perform countless correct judgments and actions in a variety of operational environments. These judgments and actions are often the difference between an accident and a non-event. Ironically, data on these behaviors are rarely collected or analyzed. Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence how decision makers characterize problems and identify solutions. Large volumes of data are collected on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that result in routine successful outcomes, safety management and system design decisions are based on a small sample of nonrepresentative safety data. This assessment aimed to find and document “safety successes” made possible by human operators. With many Aeronautics Research Mission Directorate (ARMD) Programs and Projects focusing on increased automation and autonomy and decreased human involvement, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant risk — a risk that has not been recognized to date. Without understanding how humans contribute to safety, any estimate of predicted safety of autonomous capabilities is incomplete and inherently suspect. Furthermore, understanding the ways in which humans contribute to safety can promote strategic interactions among safety technologies, functions, procedures and the people using them. Without this understanding, the full benefits of an integrated, optimized human/technology or autonomous system will not be realized. Historically, safety has been consistently defined in terms of the occurrence of accidents or recognized risks (i.e., in terms of things that go wrong). These adverse outcomes are explained by identifying their causes, and safety is restored by eliminating or mitigating these causes. An alternative to this approach is to focus on what goes right and identify how to replicate that process. Focusing on the rare cases of failures attributed to “human error” provides little information about why human performance routinely prevents adverse events. Hollnagel has proposed that things go right because people continuously adjust their work to match their operating conditions. These adjustments become increasingly important as systems continue to grow in complexity. Thus, the definition of safety should reflect not only “avoiding things that go wrong” but “ensuring that things go right.” The basis for safety management requires developing an understanding of everyday activities. However, few mechanisms to monitor everyday work exist in the aviation domain, which limits opportunities to learn how designs function in reality. This concept of safety thinking and safety management is reflected in the emerging field of resilience engineering. According to Hollnagel, a system is resilient if it can sustain required operations under expected and unexpected conditions by adjusting its functioning prior to, during, or following changes, disturbances, and opportunities. To explore “positive” behaviors that contribute to resilient performance in commercial aviation, the assessment team examined a range of existing sources of data about pilot and air traffic control (ATC) tower controller performance, including subjective interviews with domain experts and objective aircraft flight data records. These data were used to identify strategies that support resilient performance, methods for exploring and refining those strategies in existing data, and proposed methods for capturing and analyzing new data.

Null, Cynthia H.↗
NASA NTRSDate not supplied

Design of a Manufacturing Demonstration Unit for a Composite Lunar Landing Gear Strut

The goal of the current work was to develop an analytical framework for design of composite struts using various levels of model fidelity. An additional goal of this work was to perform an initial assessment of using automated fiber placement (AFP) and other advanced manufacturing methods to explore their feasibility for the fabrication of struts for lunar landers, strut-braced wings, and other aerospace components. In particular, designs were considered for fabrication at the Integrated Structural Assembly of Advanced Composites (ISAAC) facility at Langley Research Center (LaRC). The designs presented in this paper do not represent the exact geometry and material systems currently in use by the Artemis landing system, but they are considered to be representative. The designs produced during this study will be used to develop manufacturing demonstration units (MDU) that can be fabricated at ISAAC and tested in lab facilities at LaRC

carbon-epoxy↗
NASA NTRS2007

Analytical Approach for Estimating Preliminary Mass of ARES I Crew Launch Vehicle Upper Stage Structural Components

In January 2004, President Bush gave the National Aeronautics and Space Administration (NASA) a vision for Space Exploration by setting our sight on a bold new path to go back to the Moon, then to Mars and beyond. In response to this vision, NASA started the Constellation Program, which is a new exploration launch vehicle program. The primary mission for the Constellation Program is to carry out a series of human expeditions ranging from Low Earth Orbit to the surface of Mars and beyond for the purposes of conducting human exploration of space, as specified by the Vision for Space Exploration (VSE). The intent is that the information and technology developed by this program will provide the foundation for broader exploration activities as our operational experience grows. The ARES I Crew Launch Vehicle (CLV) has been designated as the launch vehicle that will be developed as a "first step" to facilitate the aforementioned human expeditions. The CLV Project is broken into four major elements: First Stage, Upper Stage Engine, Upper Stage (US), and the Crew Exploration Vehicle (CEV). NASA's Marshall Space Flight Center (MSFC) is responsible for the design of the CLV and has the prime responsibility to design the upper stage of the vehicle. The US is the second propulsive stage of the CLV and provides CEV insertion into low Earth orbit (LEO) after separation from the First Stage of the Crew Launch Vehicle. The fully integrated Upper Stage is a mix of modified existing heritage hardware (J-2X Engine) and new development (primary structure, subsystems, and avionics). The Upper Stage assembly is a structurally stabilized cylindrical structure, which is powered by a single J-2X engine which is developed as a separate Element of the CLV. The primary structure includes the load bearing liquid hydrogen (LH2) and liquid oxygen (LOX) propellant tanks, a Forward Skirt, the Intertank structure, the Aft Skirt and the Thrust Structure. A Systems Tunnel, which carries fluid and electrical power functions to other Elements of the CLV, is included as secondary structure. The MSFC has an overall responsibility for the integrated US element as well as structural design an thermal control of the fuel tanks, intertank, interstage, avionics, main propulsion system, Reaction Control System (RCS) for both the Upper Stage and the First Stage. MSFC's Spacecraft and Vehicle Department, Structural and Analysis Design Division is developing a set of predicted mass of these elements. This paper details the methodology, criterion and tools used for the preliminary mass predictions of the upper stage structural assembly components. In general, weight of the cylindrical barrel sections are estimated using the commercial code Hypersizer, whereas, weight of the domes are developed using classical solutions. HyperSizer is software that performs automated structural analysis and sizing optimization based on aerospace methods for strength, stability, and stiffness. Analysis methods range from closed form, traditional hand calculations repeated every day in industry to more advanced panel buckling algorithms. Margin-of-safety reporting for every potential failure provides the engineer with a powerful insight into the structural problem. Optimization capabilities include finding minimum weight panel or beam concepts, material selections, cross sectional dimensions, thicknesses, and lay-ups from a library of 40 different stiffened and sandwich designs and a database of composite, metallic, honeycomb, and foam materials. Multiple different concepts (orthogrid, isogrid, and skin stiffener) were run for multiple loading combinations of ascent design load with and with out tank pressure as well as proof pressure condition. Subsequently, selected optimized concept obtained from Hypersizer runs was translated into a computer aid design (CAD) model to account for the wall thickness tolerance, weld land etc for developing the most probable weight of the components. The flow diram summarizes the analysis steps used in developing these predicted mass.

Aggarwal, Pravin↗
NASA NTRS2007

NASA Tech Briefs, July 2007

Topics covered include: Miniature Intelligent Sensor Module; "Smart" Sensor Module; Portable Apparatus for Electrochemical Sensing of Ethylene; Increasing Linear Dynamic Range of a CMOS Image Sensor; Flight Qualified Micro Sun Sensor; Norbornene-Based Polymer Electrolytes for Lithium Cells; Making Single-Source Precursors of Ternary Semiconductors; Water-Free Proton-Conducting Membranes for Fuel Cells; Mo/Ti Diffusion Bonding for Making Thermoelectric Devices; Photodetectors on Coronagraph Mask for Pointing Control; High-Energy-Density, Low-Temperature Li/CFx Primary Cells; G4-FETs as Universal and Programmable Logic Gates; Fabrication of Buried Nanochannels From Nanowire Patterns; Diamond Smoothing Tools; Infrared Imaging System for Studying Brain Function; Rarefying Spectra of Whispering-Gallery-Mode Resonators; Large-Area Permanent-Magnet ECR Plasma Source; Slot-Antenna/Permanent-Magnet Device for Generating Plasma; Fiber-Optic Strain Gauge With High Resolution And Update Rate; Broadband Achromatic Telecentric Lens; Temperature-Corrected Model of Turbulence in Hot Jet Flows; Enhanced Elliptic Grid Generation; Automated Knowledge Discovery From Simulators; Electro-Optical Modulator Bias Control Using Bipolar Pulses; Generative Representations for Automated Design of Robots; Mars-Approach Navigation Using In Situ Orbiters; Efficient Optimization of Low-Thrust Spacecraft Trajectories; Cylindrical Asymmetrical Capacitors for Use in Outer Space; Protecting Against Faults in JPL Spacecraft; Algorithm Optimally Allocates Actuation of a Spacecraft; and Radar Interferometer for Topographic Mapping of Glaciers and Ice Sheets.

Source record↗
NASA NTRSDate not supplied

TPSAS-NF1676L-13606-DND

For over two decades, researchers at NASA Langley Research Center have been combining principles of engineering and psychology to explore the cognitive experiences of system operators. Conceptualizing the application of this interdisciplinary combination in the context of operators? extracurricular activities has resulted in the creation of numerous mental training spin-off technologies. Methods derived from feedback control concepts have been employed to assess the brains responses when managing automation and principles of conditioning have been embodied in devices designed to reinforce effective modes of psychophysiological activity. These methods and devices will be discussed and how they are being applied to ameliorate attention and stress disorders in clinical practice and impediments to optimal performance in sports will be demonstrated.

Alan T Pope↗
NASA NTRSDate not supplied

Initial Design Guidelines for Onboard Automation of Flight Path Management

Achieving the National Academy of Science’s vision of advanced aerial mobility will depend on significant developments in automation to achieve safe and efficient operations. Flight path management (FPM), a major category of automation functionality needed to achieve this vision, will provide dynamic management of an aircraft’s flight path, ensuring that it remains feasible to fly to mission completion, deconflicted from hazards, coordinated with other traffic, flexible to accommodate future disturbances, and optimized to meet business objectives. While efforts are underway to advance FPM technology for the Urban Air Mobility application, initial design guidelines are presented for FPM automation capabilities to achieve each of these objectives based on 15+ years of prior FPM automation research and development. Methods to efficiently account for uncertainty in the prediction of trajectories are described, as are additional considerations for prioritizing safety in the design of FPM automation capabilities and interactions between aircraft. Recommendations are supported by extensive experience gained via previous work with the FPM reference automation system, Autonomous Operations Planner, developed by NASA. By employing capable FPM automation supported by cooperative operational flight rules and information sharing, future aircraft operators will benefit from an increased ability to plan and execute safe and efficient flights and to achieve mission success in a dynamic airspace.

Flight Path Management, FPM, AOP, UAM, deconflicti↗
NASA NTRSDate not supplied

Initial Design Guidelines for Onboard Automation of Flight Path Management

Achieving the National Academy of Science’s vision of advanced aerial mobility will depend on significant developments in automation to achieve safe and efficient operations. Flight path management (FPM), a major category of automation functionality needed to achieve this vision, will provide dynamic management of an aircraft’s flight path, ensuring that it remains feasible to fly to mission completion, deconflicted from hazards, coordinated with other traffic, flexible to accommodate future disturbances, and optimized to meet business objectives. While efforts are underway to advance FPM technology for the Urban Air Mobility application, initial design guidelines are presented for FPM automation capabilities to achieve each of these objectives based on 15+ years of prior FPM automation research and development. Methods to efficiently account for uncertainty in the prediction of trajectories are described, as are additional considerations for prioritizing safety in the design of FPM automation capabilities and interactions between aircraft. Recommendations are supported by extensive experience gained via previous work with the FPM reference automation system, Autonomous Operations Planner, developed by NASA. By employing capable FPM automation supported by cooperative operational flight rules and information sharing, future aircraft operators will benefit from an increased ability to plan and execute safe and efficient flights and to achieve mission success in a dynamic airspace.

Flight Path Management↗
DOE OSTI2023

Development of an Unmanned Mobile Current Turbine Platform: Preprint

The design and development of a prototype unmanned mobile floating platform, equipped with a custom low-flow marine current turbine for autonomously seeking and harnessing tidal/coastal currents is described. The platform is an unmanned surface vehicle in the form of a catamaran with two electric outboard motors and capabilities for autonomous navigation. An undershot water wheel, aided by a custom flow concentrator, has been selected as the basic design for the marine current turbine, which is mounted on the stern of the unmanned surface vehicle platform. The concept of operation is that the platform would navigate to a designated marine current resource, autonomously anchor at the location, align itself in the current and deploy the current turbine using a custom cable-lift deployment mechanism. As the turbine harnesses the local current, an onboard power-take-off device converts the harnessed mechanical energy to electricity which is stored in onboard batteries. Considerations of deployment in tidal and coastal waters required obtaining the necessary environmental permits for conducting in-water testing; developing required mitigation measures in protecting local wildlife and their habitats; and identifying potential in-water test sites and surveying them for their suitability in terms of the current resource, bottom type, water depth, and local boat traffic. The design and development of the turbine and the results of initial in-water testing are discussed. The potential for scaling up the system for extended capacity is presented.

ENGINEERING,TIDAL AND WAVE POWER↗
DOE OSTI2024

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

AI-Powered Knowledge Graphs for Neuromorphic and Energy-Efficient Computing

The surge in scientific literature obscures breakthroughs and hinders the discovery of new research paths. We propose an artificial intelligence (AI) powered framework using large language models (LLMs) and knowledge graphs (KGs) to automate parts of scientific discovery, focusing on energy-efficient AI circuits. Our hybrid approach combines LLMs, structured data, and ontology-based reasoning to construct a comprehensive knowledge graph that integrates insights across computational neuroscience, spiking neuron models, learning rules, architectural motifs, and neuromorphic device technologies. This multi-domain representation enables the generation of hypotheses that connect biological function with implementable, energy-efficient hardware architectures. Using KG embeddings and graph neural networks, the framework generates hypotheses for novel circuits, validates them through optimization on exascale HPC systems, and with tools like SuperNeuro and Fugu, the most promising designs will be prototyped in hardware. This open-source system aims to accelerate discoveries and bridging neuroscience with hardware innovation, drive collaboration, and unlock new opportunities in low-power AI computing.

Gautam, Ashish [ORNL]↗
DOE OSTI2024

Pedestrian-Involved Traffic Signal Optimization Using Decentralized Graph-based Multi-Agent Reinforcement Learning

Incorporating pedestrian movements in traffic signal timing optimization is essential for ensuring smooth and safe urban transportation systems. To develop an effective signal timing plan, it is crucial to comprehend how various pedestrian accommodation strategies impact both vehicle and pedestrian flow. This study explores the application of the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) method for signal timing optimization. It considers both pedestrian and vehicle traffic state and assesses the effects of fixed and adaptive pedestrian request response on traffic and signal timing. The evaluation of DGMARL encompasses vehicles Eco_PI which is fuel consumption impact related to vehicle stops and stop delay, and pedestrian waiting time to ensure overall system efficiency. The proposed approach was evaluated using a Digital Twin microscopic traffic simulation model of MLK Smart Corridor in Chattanooga, Tennessee. The evaluation outcomes of vehicles Eco_PI, pedestrian waiting time and serving time are compared with the actuated and DGMARL signal timing with fixed pedestrian recall and minimum recall to determine the most suitable approaches for various traffic conditions. The results indicated that, on average, the strategy of Signal timing optimization with adaptive pedestrian request response improved the Eco_PI by 32.43%, and Signal timing optimization with both automated pedestrian traffic demand and adaptive pedestrian request response improved the Eco_PI by 31.62% compared to the actuated and DGMARL signal timing with fixed pedestrian recall and minimum recall.

K Kumarasamy, Vijayalakshmi↗
NASA NTRS2013

Robust Multivariable Optimization and Performance Simulation for ASIC Design

Application-specific-integrated-circuit (ASIC) design for space applications involves multiple challenges of maximizing performance, minimizing power, and ensuring reliable operation in extreme environments. This is a complex multidimensional optimization problem, which must be solved early in the development cycle of a system due to the time required for testing and qualification severely limiting opportunities to modify and iterate. Manual design techniques, which generally involve simulation at one or a small number of corners with a very limited set of simultaneously variable parameters in order to make the problem tractable, are inefficient and not guaranteed to achieve the best possible results within the performance envelope defined by the process and environmental requirements. What is required is a means to automate design parameter variation, allow the designer to specify operational constraints and performance goals, and to analyze the results in a way that facilitates identifying the tradeoffs defining the performance envelope over the full set of process and environmental corner cases. The system developed by the Mixed Signal ASIC Group (MSAG) at the Goddard Space Flight Center is implemented as a framework of software modules, templates, and function libraries. It integrates CAD tools and a mathematical computing environment, and can be customized for new circuit designs with only a modest amount of effort as most common tasks are already encapsulated. Customization is required for simulation test benches to determine performance metrics and for cost function computation.

DuMonthier, Jeffrey↗
NASA NTRSDate not supplied

Automation of the Uncertainty Quantification Process Based on Probability Boxes with DAKOTA

To date, while the use of CFD is prevalent, very few efforts have been undertaken that truly attempt to document all (or even most) of the sources of uncertainty in the simulations. Instead, the current state-of-the-art relies heavily on the experience of the CFD practitioner to estimate the uncertainty associated with their simulations through simple sensitivity studies or subject matter expertise. This practice will have to be replaced with a formal uncertainty quantification (UQ) process if CFD is to play an expanded role in the design research and engineering community, test and evaluation community, and ultimately certification for flight. This is especially true for hypersonic air-breathing propulsion systems due to the environment, scale, and duration limitations of ground test facilities. Accounting for uncertainties in a formal manner is a tedious process. Moreover, the typical CFD practitioner is not likely to be familiar with formal UQ methods. Hence, a major obstacle that has prevented the adoption of UQ methods for engineering design and development work is the lack of a tool set to automate most (if not all) of the UQ workflow. Towards this end, the SANDIA package DAKOTA (which has been developed to drive both UQ and optimization processes) will be tightly wrapped around the VULCAN-CFD code to automate the uncertainty quantification process. The automated process will be applied to an isolator turbulence model validation exercise that has previously been documented using a manual approach to the UQ process. Hence, the focus of this paper will be documenting the level to which automation can hide the UQ process details from the CFD practitioner rather than the UQ method itself.

CFD↗
DOE OSTI2023

A critical review of existing and emerging technologies and systems to optimize solid waste management for feedstocks and energy conversion

Solid waste generation and its accumulation is increasing at an alarming pace due to population growth and urbanization posing severe risks to health, safety, and natural ecosystems. Herein this review strategically addresses the challenges and solutions to increasing the sustainability footprint of solid waste management (SWM) systems by revealing multipronged approaches that reduce solid waste and handling costs while generating revenue and reducing greenhouse gas and related emissions. For example, the United States sends ~150 million tons of waste to landfills, which is composed of over 75% organic and recyclable materials having a potential to be diverted to alternative scenarios. The emergence of an automated upstream and downstream sorting process for solid waste to increase material diversion from landfills is a promising approach for creating sustainable SWM. The utilization of artificial-intelligence-enabled smart and automated systems at the home and industrial scales, comprehensive public re-education including awareness of the adverse effects of landfilled waste on the ecosystem, and more eco-friendly product development are required to significantly reduce landfills and their negative footprint.

09 BIOMASS FUELS↗