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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

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↗
NASA NTRS2003

Abstract of talk for Silicon Valley Linux Users Group

The use of Linux for research at NASA Ames is discussed.Topics include:work with the Atmospheric Physics branch on software for a spectrometer to be used in the CRYSTAL-FACE mission this summer; work on in the Neuroengineering Lab with code IC including an introduction to the extension of the human senses project,advantages with using linux for real-time biological data processing,algorithms utilized on a linux system, goals of the project,slides of people with Neuroscan caps on, and progress that has been made and how linux has helped.

Clanton, Sam↗
NASA NTRS2020

Barefoot Rover: a Sensor-Infused Rover Wheel Demonstrating In-Situ Engineering and Science Extractions using Machine Learning

In this work, we demonstrate an instrumented wheel concept which utilizes a 2D pressure grid, an electrochemical impedance spectroscopy (EIS) sensor and machine learning (ML) to extract meaningful metrics from the interaction between the wheel and surface terrain. These include continuous slip/skid estimation, balance, and sharpness for engineering applications. Estimates of surface hydration, texture, terrain patterns, and regolith physical properties such as cohesion and angle of internal friction are additionally calculated for science applications. Traditional systems rely on post-processing of visual images and vehicle telemetry to estimate these metrics. Through in-situ sensing, these metrics can be calculated in near real time and made available to onboard science and engineering autonomy applications. This work aims to provide a deployable system for future planetary exploration missions to increase science and engineering capabilities through increased knowledge of the terrain.

Marchetti, Yuliya↗
NASA NTRSDate not supplied

Human-Autonomy Teaming Research in Support of m:N Operations

Since 2019, the NASA and industry partners have been involved in research focused on a novel paradigm for operations of remotely piloted aircraft. This paradigm involves multiple people sharing a fleet of multiple vehicles between them. Referred to as m:N (pronounced “em-to-en”), this configuration describes a ratio where m is the number of operators and N is the number of vehicles. Through force and asset multiplication, the m:N concept seeks to enable a scalable and resilient operation of remotely crewed vehicles. The primary means of obtaining such a robust operation is through allowing a flexible crew of variable size to dynamically attend to the needs of assets in while performing real-time operator workload management. It is in that sense that assets are shared between operators: as needed (such as in events of elevated workload) an operator in an m:N context can “handoff” the responsibility for some amount of assets, nh < N, to be absorbed by the m – 1 crew members on staff. At some time later, these nh assets could be returned to their original owner or they may be further distributed to other crew if called for by the mission. During this panel, I will elaborate on the research activity undertaken by the Human-Autonomy Teaming (HAT) Laboratory at NASA Ames Research Center over the previous three years. The studies conducted by the HAT Lab range from interviews with subject matter experts, a cognitive walkthrough, a task analysis, and two simulation experiments to-date. During experimentation, pilots made use of an advanced Ground Control Station developed by the HAT Lab and industry partners to simulate m:N operations in two large, metropolitan areas of Southern California: Los Angeles and San Diego. Further experimentation planned over the next few years. Results from our research to-date indicates that pilots of a moderately sized fleet of about a dozen remotely crewed aircraft adequately maintained safety performance and situation awareness of their aircraft, even when presented with unexpected situations of heightened workload.

multi-vehicle control↗
NASA NTRS2009

Selective functionalization of carbon nanotube tips allowing fabrication of new classes of nanoscale sensing and manipulation tools

Embodiments in accordance with the present invention relate to techniques for the growth and attachment of single wall carbon nanotubes (SWNT), facilitating their use as robust and well-characterized tools for AFM imaging and other applications. In accordance with one embodiment, SWNTs attached to an AFM tip can function as a structural scaffold for nanoscale device fabrication on a scanning probe. Such a probe can trigger, with nanometer precision, specific biochemical reactions or conformational changes in biological systems. The consequences of such triggering can be observed in real time by single-molecule fluorescence, electrical, and/or AFM sensing. Specific embodiments in accordance with the present invention utilize sensing and manipulation of individual molecules with carbon nanotubes, coupled with single-molecule fluorescence imaging, to allow observation of spectroscopic signals in response to mechanically induced molecular changes. Biological macromolecules such as proteins or DNA can be attached to nanotubes to create highly specific single-molecule probes for investigations of intermolecular dynamics, for assembling hybrid biological and nanoscale materials, or for developing molecular electronics. In one example, electrical wiring of single redox enzymes to carbon nanotube scanning probes allows observation and electrochemical control over single enzymatic reactions by monitoring fluorescence from a redox-active cofactor or the formation of fluorescent products. Enzymes ''nanowired'' to the tips of carbon nanotubes in accordance with embodiments of the present invention, may enable extremely sensitive probing of biological stimulus-response with high spatial resolution, including product-induced signal transduction.

Wade, Lawrence A.↗
NASA NTRS2016

Application of an ADS-B Sense and Avoid Algorithm

The National Aeronautics and Space Administration Armstrong Flight Research Center in Edwards, California is leading a program aimed towards integrating unmanned aircraft system into the national airspace system (UAS in the NAS). The overarching goal of the program is to reduce technical barriers associated with related safety issues as well as addressing challenges that will allow UAS routine access to the national airspace. This research paper focuses on three novel ideas: (1) A design of an integrated UAS equipped with Automatic Dependent Surveillance-Broadcast that constructs a more accurate state-based airspace model; (2) The use of Stratway Algorithm in a real-time environment; and (3) The verification and validation of sense and avoid performance and usability test results which provide a pilot's perspective on how our system will benefit the UAS in the NAS program for both piloted and unmanned aircraft.

ADS-B↗
DOE OSTI2026

Distributed optical fibre sensing in physical oceanography: emergence and future prospects

Distributed optical fibre sensing (DOFS) is a technology that enables continuous, real-time measurements of a range of environmental parameters along the length of a fibre optic cable. In this article, we review the recently emerged applications of DOFS techniques in physical oceanography and offer a perspective on the technology's potential for future growth within the field. The introduction of DOFS to physical oceanography is contextualised with a brief history of the technology, which spun off primarily from the use of seafloor-laid optical fibres for telecommunications purposes. The key components and underpinning physics of a DOFS system are outlined and, on their basis, the suite of variables that are observable with DOFS are discussed. The implementation factors of DOFS, which include trade-offs between measurement accuracy and spatio-temporal resolutions and ranges, are also examined. The physical oceanographic applications of DOFS to date are then illustrated with case examples of four distinct DOFS techniques: distributed temperature sensing (DTS), which can provide ocean temperature observations; distributed static strain sensing (DSS) and distributed acoustic sensing (DAS), which are sensitive to temperature, cable strain and strain-associated variables, such as pressure and ocean velocity; and ultra-long-range observations of ocean currents with optical interferometry. The forthcoming prospects of DOFS in physical oceanography are considered, and are proposed to include new fibre optic-based approaches to sense ocean salinity and measure through the water column. We conclude with reflections on the future role of DOFS within the Global Ocean Observing System, and highlight the opportunities provided by the existing world-wide network of seafloor-laid optical fibres.

Naveira Garabato, Alberto C. [Univ. of Southampton↗
NASA NTRS1996

A convertor and user interface to import CAD files into worldtoolkit virtual reality systems

Virtual Reality (VR) is a rapidly developing human-to-computer interface technology. VR can be considered as a three-dimensional computer-generated Virtual World (VW) which can sense particular aspects of a user's behavior, allow the user to manipulate the objects interactively, and render the VW at real-time accordingly. The user is totally immersed in the virtual world and feel the sense of transforming into that VW. NASA/MSFC Computer Application Virtual Environments (CAVE) has been developing the space-related VR applications since 1990. The VR systems in CAVE lab are based on VPL RB2 system which consists of a VPL RB2 control tower, an LX eyephone, an Isotrak polhemus sensor, two Fastrak polhemus sensors, a folk of Bird sensor, and two VPL DG2 DataGloves. A dynamics animator called Body Electric from VPL is used as the control system to interface with all the input/output devices and to provide the network communications as well as VR programming environment. The RB2 Swivel 3D is used as the modelling program to construct the VW's. A severe limitation of the VPL VR system is the use of RB2 Swivel 3D, which restricts the files to a maximum of 1020 objects and doesn't have the advanced graphics texture mapping. The other limitation is that the VPL VR system is a turn-key system which does not provide the flexibility for user to add new sensors and C language interface. Recently, NASA/MSFC CAVE lab provides VR systems built on Sense8 WorldToolKit (WTK) which is a C library for creating VR development environments. WTK provides device drivers for most of the sensors and eyephones available on the VR market. WTK accepts several CAD file formats, such as Sense8 Neutral File Format, AutoCAD DXF and 3D Studio file format, Wave Front OBJ file format, VideoScape GEO file format, Intergraph EMS stereolithographics and CATIA Stereolithographics STL file formats. WTK functions are object-oriented in their naming convention, are grouped into classes, and provide easy C language interface. Using a CAD or modelling program to build a VW for WTK VR applications, we typically construct the stationary universe with all the geometric objects except the dynamic objects, and create each dynamic object in an individual file.

Wang, Peter Hor-Ching↗
NASA NTRS1989

Application of optical distributed sensing and computation to control of a large flexible spacecraft

Advances in real-time holography make possible the development of new distributed optical sensors and processors that may have application to the control of flexible structures. This paper presents the analytic evaluation of control system concepts utilizing this new technology on realistic spacecraft. The design of a distributed estimator based on this new optical sensing technique is targeted to vibration control of a complex spacecraft with multiple optical sensors, each of which views a portion of the spacecraft. A simulation of a complex truss structure that was flown in the Solar Array Flight Experiment is utilized to evaluate the performance of the estimator. It is shown that good performance can be obtained from a distributed estimator even in the presence of significant sensor noise.

Montgomery, R. C.↗
NASA NTRS2011

Virtual Sensor Test Instrumentation

Virtual Sensor Test Instrumentation is based on the concept of smart sensor technology for testing with intelligence needed to perform sell-diagnosis of health, and to participate in a hierarchy of health determination at sensor, process, and system levels. A virtual sensor test instrumentation consists of five elements: (1) a common sensor interface, (2) microprocessor, (3) wireless interface, (4) signal conditioning and ADC/DAC (analog-to-digital conversion/ digital-to-analog conversion), and (5) onboard EEPROM (electrically erasable programmable read-only memory) for metadata storage and executable software to create powerful, scalable, reconfigurable, and reliable embedded and distributed test instruments. In order to maximize the efficient data conversion through the smart sensor node, plug-and-play functionality is required to interface with traditional sensors to enhance their identity and capabilities for data processing and communications. Virtual sensor test instrumentation can be accessible wirelessly via a Network Capable Application Processor (NCAP) or a Smart Transducer Interlace Module (STIM) that may be managed under real-time rule engines for mission-critical applications. The transducer senses the physical quantity being measured and converts it into an electrical signal. The signal is fed to an A/D converter, and is ready for use by the processor to execute functional transformation based on the sensor characteristics stored in a Transducer Electronic Data Sheet (TEDS). Virtual sensor test instrumentation is built upon an open-system architecture with standardized protocol modules/stacks to interface with industry standards and commonly used software. One major benefit for deploying the virtual sensor test instrumentation is the ability, through a plug-and-play common interface, to convert raw sensor data in either analog or digital form, to an IEEE 1451 standard-based smart sensor, which has instructions to program sensors for a wide variety of functions. The sensor data is processed in a distributed fashion across the network, providing a large pool of resources in real time to meet stringent latency requirements.

Wang, Roy↗
NASA NTRS2021

Autonomous Off-road Navigation over Extreme Terrains with Perceptually-challenging Conditions

We propose a framework for resilient autonomous navigation in perceptuallychallenging unknown environments with mobility-stressing elements such asuneven surfaces with rocks and boulders, steep slopes, negative obstacles like cliffsand holes, and narrow passages. Environments are GPS-denied and perceptuallydegradedwith variable lighting from dark to lit and obscurants (dust, fog, smoke).Lack of prior maps and degraded communication eliminates the possibility of prioror off-board computation or operator intervention. This necessitates real-time onboardcomputation using noisy sensor data. To address these challenges, we proposea resilient architecture that exploits redundancy and heterogeneity in sensing modalities.Further resilience is achieved by triggering recovery behaviors upon failure.We propose a fast settling algorithm to generate robust multi-fidelity traversabilityestimates in real-time. The proposed approach was deployed on multiple physicalsystems including skid-steer and tracked robots, high-speed RC car and legged robotsand as a part of Team CoSTAR’s effort to theDARPASubterranean Challenge, wherethe team won 2nd and 1st place in the Tunnel and Urban Circuit, respectively.

Agha-mohammadi, Ali-akbar↗
NASA NTRSDate not supplied

Evaluating near-real time satellite flood mapping for humanitarian early action: a case study on the 2020 Cambodia floods

Forecast-based early action is an increasingly popular framework advocating for the use of numerical weather prediction to set objective, automatic conditions for roll-out of proactive flood risk reduction efforts. Within this field, there is a relatively young discourse regarding the potential value of satellite Earth observations and the optimal role that remote sensing should play in improving the efficacy and value of forecast-based early action for flood management. The Hydrological Remote Sensing Analysis for Floods tool (HYDRAFloods) was developed to provide automated, near real-time satellite-based flood extent maps to local governments, disaster managers, and humanitarian organizations. This research evaluates (a.) whether HYDRAFloods satisfactorily met needs identified by humanitarian partners during the October 2020 floods in Cambodia, and (b.) whether the novel additions of near real-time data and flood extent mapping resulted in demonstrable advantages over previous forecast-based flood early action systems as identified in the literature. From these results, the authors identify the technological and logistical limitations of the HYDRAFloods methodology and synthesize actionable recommendations for Earth observations practitioners seeking to better support forecast-based early action.

floods↗
DOE OSTI2022

Advanced modeling and simulation of research reactors using dynamic mode decomposition

Full text of publication follows. Due to the ever-increasing safety requirements, the current trend of nuclear reactor analysis is shifting towards high-fidelity multi-physics models, which have a very high computational cost and modelling complexity. As the cost of even a single model run makes it impossible to analyse the behaviour and performance of these models on large-scale commercial plants, it has become even more significant to provide suitable benchmarks to validate and test them extensively. In this sense, research reactors offer a promising solution for the initial validation of high-fidelity models, as they are significantly smaller than commercial reactors and their characteristics are well known. In particular, the reactors of the TRIGA family have been used to assess and validate models and methods for Generation-IV designs, as they have some similar features (such as the dominance of natural convection as cooling mechanism and the difficulties in performing sub-channel analysis using standard codes). Still, the computational requirements of high-fidelity models make them unsuitable for real-time analysis, even following their assessment on research reactors. In this sense, Model Order Reduction (MOR) techniques give an additional strategy to reduce the computational cost of high-fidelity models (whilst preserving sufficient accuracy). In particular, this work focuses on Dynamic Mode Decomposition (DMD), a non-intrusive MOR technique that aims at representing models with explicit temporal dynamics by extracting the time-varying characteristics and the governing structures based only on a set of available data, thus without needing any underlying knowledge of the governing equations. In addition, DMD also computes a low-dimensional surrogate of the dynamic matrix of the system, making it suited for stability analysis and real-time evaluations. This work focuses on the application and validation of the DMD method on the Computational Fluid-Dynamics (CFD) model TRIGA Mark II reactor, also discussing in detail the potentiality of this algorithm as an advanced modelling tool for nuclear reactor analysis. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Real-time mass spectrometric characterization of the solid–electrolyte interphase of a lithium-ion battery

Solid-electrolyte interphase (SEI) is a key component that dictates the performance of most electrochemical devices, but the understanding of its chemistry and structure has been limited by the lack of in-situ tools. In this work, we report SEI live-formation in Li-ion battery under operando condition with liquid secondary ion mass spectrometry (SIMS), which, in combination with molecular dynamics (MD) simulation, presents the first dynamic picture with molecular-accuracy about this key component. Before any interphasial chemistry occurs during the initial charging, an electric double layer forms at the electrode-electrolyte interface via the self-assembly of solvent molecules directed by both Li+ and potential of the electrified surface. Such double layer structure predicts the eventual interphasial chemistries formed from the electrolytes, where the negatively-charged electrode surface repels salt anions from the inner-Helmholtz layer and results in an inner SEI that is thin, dense and inorganic in nature but LiF-depleted. It was this dense layer that exercises the major functions of an interphase, i.e., conducting Li+ but insulating electrons. An outer layer that is electrolyte-permeable and organic-rich appears after formation of the inner SEI. In highly-concentrated electrolyte, the presence of LiF in the inner-SEI is raised due to the high population of salt anions in the double layer. These real-time observations at nano-scale reveal in general sense how an interphase inherits chemistry from inner-Helmholtz layer structure, and establish guidelines in engineering desirable interphases for the future battery chemistries.

Zhou, Yufan↗
DOE OSTI2024

Enhanced Machine-Learning Flow for Microwave-Sensing Systems for Contaminant Detection in Food

The presence of foreign bodies in packaged food is a serious concern for both fnal consumers (allergies, injuries, choking) and food manufacturers (reputation and economic losses). In particular, low-density plastics, glass and wood splinters are hard to detect even by the most advanced X-ray imagers. One solution is Machine-Learning-based Microwave Sensing (MLMWS): a non-invasive, contactless, and real-time method which uses a machine-learning (ML) classifer to analyze the scattered microwaves from the irradiated target object. In this paper, we want to extend our previous work about contaminant detection in cocoa-hazelnut spread jars by proposing an enhanced ML flow to increase the accuracy of the ML classifier. For the first time in this case study, we use a multi-class classifier, we train it with scattering parameters measured at multiple microwave frequencies, with a new pre-processing scaler, data augmentation, quantization-aware training and a pruning schedule. The results show a contaminant detection multi-class accuracy of 94.167% with a latency of 26 µs when targeting an AMD/Xilinx Kria K26 FPGA. Finally, we released our datasets publicly to OpenML.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1974

Cluster analysis based on dimensional information with applications to feature selection and classification

A new clustering algorithm is presented that is based on dimensional information. The algorithm includes an inherent feature selection criterion, which is discussed. Further, a heuristic method for choosing the proper number of intervals for a frequency distribution histogram, a feature necessary for the algorithm, is presented. The algorithm, although usable as a stand-alone clustering technique, is then utilized as a global approximator. Local clustering techniques and configuration of a global-local scheme are discussed, and finally the complete global-local and feature selector configuration is shown in application to a real-time adaptive classification scheme for the analysis of remote sensed multispectral scanner data.

Eigen, D. J.↗
NASA NTRS1999

Spaceborne Fiber Optic Data Bus (SFODB)

Spaceborne Fiber Optic Data Bus (SFODB) is an IEEE 1393 compliant, gigabit per second, fiber optic network specifically designed to support the real-time, on-board data handling requirements of remote sensing spacecraft. The network is fault tolerant highly reliable, and capable of withstanding the rigors of launch and the harsh space environment. SFODB achieves this operational and environmental performance while maintaining the small size, light weight, and low power necessary for spaceborne applications. On December 9, 1998, SFODB was successfully demonstrated at NASA's Goddard Space Flight Center (GSFC).

Bretthauer, Joy W.↗
NASA NTRS1999

IEEE 1393 Spaceborne Fiber Optic Data Bus: A Standard Approach to On-Board Payload Data Handling Networks for the AIAA Space Technology Conference and Exposition "Partnering in the 21th Century"

The Spaceborne Fiber Optic Data Bus (SFODB) is the next generation in on-board data handling networks. It will do for high speed payloads what SAE 1773 has done for on-board command and telemetry systems. That is, it will significantly reduce the cost of payload development, integration and test through interface standardization. As defined in IEEE 1393, SFODB is a 1 Gb/s, fiber optic network specifically designed to support the real-time, on-board data handling requirements of remote sensing spacecraft. The network is highly reliable, fault tolerant, and capable of withstanding the rigors of launch and the harsh space environment. SFODB achieves this operational and environmental performance while maintaining the small size, light weight, and low power necessary for spaceborne applications. SFODB was developed jointly by DoD and NASA GSFC to meet the on-board data handling needs of Remote Sensing satellites. This jointly funded project produced a complete set of flight transmitters, receivers and protocol ASICS; a complete Development & Evaluation System; and, the IEEE 1393 standard.

Andrucyk, Dennis J.↗