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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Coded acoustic wave sensors and system using time diversity

An apparatus and method for distinguishing between sensors that are to be wirelessly detected is provided. An interrogator device uses different, distinct time delays in the sensing signals when interrogating the sensors. The sensors are provided with different distinct pedestal delays. Sensors that have the same pedestal delay as the delay selected by the interrogator are detected by the interrogator whereas other sensors with different pedestal delays are not sensed. Multiple sensors with a given pedestal delay are provided with different codes so as to be distinguished from one another by the interrogator. The interrogator uses a signal that is transmitted to the sensor and returned by the sensor for combination and integration with the reference signal that has been processed by a function. The sensor may be a surface acoustic wave device having a differential impulse response with a power spectral density consisting of lobes. The power spectral density of the differential response is used to determine the value of the sensed parameter or parameters.

Solie, Leland P.↗
NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗
NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗
NASA NTRS1989

Precision Segmented Reflector figure control system architecture

A control system architecture for an actively controlled segmented reflector is described along with a design realization for achieving precision alignment of reflector panels. Performance requirements are derived in part from the Large Deployable Reflector, which is a representative mission, and error allocations are made which consider mirror panel surface errors, position measurement and figure estimation, and position control of both quasi-static and dynamic disturbances. The design uses multiple wavelength interferometric edge sensors and voice coil actuators in conjunction with a hybrid control strategy to correct panel position errors. A unit cell shown to be central to the concept is analyzed. The cell integrates the sensing, actuation, and mechanical functions of a control module together with a reflector panel to form a unitized assembly.

Mettler, E.↗
NASA NTRS1993

Advanced microfabrication technologies for microspacecraft

Advanced microfabrication technologies offer the prospect of reducing the weight and size of spacecraft through the use of lighter and stronger materials in conjunction with new mechanical/structural design concepts and design optimization methods. At the same time, electronic components have been scaled down while increasing functional utility. A two-fold benefit is derived for space applications through the use of less expensive components and the lower launch costs associated with lighter components. GE-CRD is actively pursuing research in these key technologies for a wide range of applications including satellites. These key technologies will be reviewed and an update on GE progress will be given. The need to reduce weight and lower cost, while maintaining product quality and reliability are primary drivers in the design of satellites, in general, and microsatellites in particular. For the structural subsystem, these requirements pose a complex design problem unless new mechanical design concepts and computer-aided design optimization methods are employed. Several new concepts, such as battery packs doubling as panel reinforcements and fuel tanks as integral structural members, need to utilized. In addition, new viscoelastic material damping concepts for spacecraft components provide for lighter weight/lower cost designs, while satisfying the structural dynamics requirements. High density interconnect (HDI) technology permits the use of bare IC's on a ceramic substrate with 90 percent active area utilization. A copper/polyimide multilayer structure is the backbone of the technology, which has demonstrated a size/weight reduction of greater than 10x compared to printed circuit board with performance up to the GHz level. HDI modules have exceptional mechanical robustness as evidenced by survival of 180 kg rapid acceleration tests. Microelectromechanical systems (MEMS) are redefining sensors and actuators by miniaturization through micromachining techniques. Sharing many fabrication steps with HDI, we have developed a new technique for surface micromachining of copper/polyimide structures using computer-aided laser patterning.

Ghezzo, M.↗
NASA NTRS2012

Landsat Data Continuity Mission Expected Instrument Performance

The Landsat Data Continuity Mission (LDCM) is scheduled for a December 2012 launch date. LDCM is being managed by an interagency partnership between NASA and the U.S. Geological Survey (USGS). In order to provide the necessary spectral coverage of the visible through shortwave-infrared (SWIR) and the thermal-infrared (TIR), the satellite will carry two sensors. The Operational Land Imager (OLI) will collect data for nine visible to shortwave spectral bands with a spatial resolution of 30 m (with a 15 m panchromatic band). The Thermal Infrared Sensor (TIRS) will collect coincident image data for two TIR bands with a spatial resolution of 100 m. The OLI is fully assembled and tested and has been shipped by it's manufacturer, Ball Aerospace and Technology Corporation, to the Orbital Sciences Corporation (Orbital) facility where it is being integrated onto the LDCM spacecraft. Pre-launch testing indicates that OLI will meet all performance specification with margin. TIRS is in development at the NASA Goddard Space F!ight Center (GSFC) and is in final testing before shipping to the Orbital facility in January, 2012. The presentation will describe the LDCM satellite instrument systems, present pre-launch performance data for OLI and TIRS, and present simulated images to highlight notable features and expected imaging performance.

Dabney, Philip W.↗
NASA NTRS2024

Physiological and Subjective Responses of Pilots during Advanced Air Mobility Flight Testing with Automated Systems

Aviation is constantly evolving, mostly due to the integration of automated systems into the National Airspace System. This presents a host of challenges and opportunities. NASA’s Advanced Air Mobility (AAM) project has taken a significant leap forward with a research flight test led by the Integration of Automated Systems (IAS) sub-project. This effort focused on assessing automated flight deck algorithms essential for supporting high-density Urban Air Mobility (UAM) operations. Carrying out a two-ship flight test in UAM Maturity Level 4 scenarios, the team evaluated state-of-the-art algorithms, including Hazard Perception and Avoidance (HPA) and flight path management (FPM) systems. This paper investigates into pilots’ physiological and subjective responses during the flight scenarios conducted. In collaboration with Lockheed Martin Advanced Technology Laboratories (ATL), we collected and analyzed live-flight biometric data using eye tracking, mobile brain imaging, and heart rate sensors. The study provides insights into pilots’ workload and cognitive engagement while navigating automated tools, leveraging both biometric data and post-encounter subjective assessments. The research highlights the interaction between human operators and automated systems, contributing valuable lessons learned about gathering human data in live-flight environments. The knowledge acquired from this study enhances our understanding of human factors in automated flight and informs future studies attempting to undertake similar feats.

Kevin J. Monk↗
NASA NTRS2014

Spinoff 2013

Topics covered include: Innovative Software Tools Measure Behavioral Alertness; Miniaturized, Portable Sensors Monitor Metabolic Health; Patient Simulators Train Emergency Caregivers; Solar Refrigerators Store Life-Saving Vaccines; Monitors Enable Medication Management in Patients' Homes; Handheld Diagnostic Device Delivers Quick Medical Readings; Experiments Result in Safer, Spin-Resistant Aircraft; Interfaces Visualize Data for Airline Safety, Efficiency; Data Mining Tools Make Flights Safer, More Efficient; NASA Standards Inform Comfortable Car Seats; Heat Shield Paves the Way for Commercial Space; Air Systems Provide Life Support to Miners; Coatings Preserve Metal, Stone, Tile, and Concrete; Robots Spur Software That Lends a Hand; Cloud-Based Data Sharing Connects Emergency Managers; Catalytic Converters Maintain Air Quality in Mines; NASA-Enhanced Water Bottles Filter Water on the Go; Brainwave Monitoring Software Improves Distracted Minds; Thermal Materials Protect Priceless, Personal Keepsakes; Home Air Purifiers Eradicate Harmful Pathogens; Thermal Materials Drive Professional Apparel Line; Radiant Barriers Save Energy in Buildings; Open Source Initiative Powers Real-Time Data Streams; Shuttle Engine Designs Revolutionize Solar Power; Procedure-Authoring Tool Improves Safety on Oil Rigs; Satellite Data Aid Monitoring of Nation's Forests; Mars Technologies Spawn Durable Wind Turbines; Programs Visualize Earth and Space for Interactive Education; Processor Units Reduce Satellite Construction Costs; Software Accelerates Computing Time for Complex Math; Simulation Tools Prevent Signal Interference on Spacecraft; Software Simplifies the Sharing of Numerical Models; Virtual Machine Language Controls Remote Devices; Micro-Accelerometers Monitor Equipment Health; Reactors Save Energy, Costs for Hydrogen Production; Cameras Monitor Spacecraft Integrity to Prevent Failures; Testing Devices Garner Data on Insulation Performance; Smart Sensors Gather Information for Machine Diagnostics; Oxygen Sensors Monitor Bioreactors and Ensure Health and Safety; Vision Algorithms Catch Defects in Screen Displays; and Deformable Mirrors Capture Exoplanet Data, Reflect Lasers.

Source record↗
NASA NTRS2008

Multifunctional Nanotube Polymer Nanocomposites for Aerospace Applications: Adhesion between SWCNT and Polymer Matrix

Multifunctional structural materials can enable a novel design space for advanced aerospace structures. A promising route to multifunctionality is the use of nanotubes possessing the desired combination of properties to enhance the characteristics of structural polymers. Recent nanotube-polymer nanocomposite studies have revealed that these materials have the potential to provide structural integrity as well as sensing and/or actuation capabilities. Judicious selection or modification of the polymer matrix to promote donor acceptor and/or dispersion interactions can improve adhesion at the interface between the nanotubes and the polymer matrix significantly. The effect of nanotube incorporation on the modulus and toughness of the polymer matrix will be presented. Very small loadings of single wall nanotubes in a polyimide matrix yield an effective sensor material that responds to strain, stress, pressure, and temperature. These materials also exhibit significant actuation in response to applied electric fields. The objective of this work is to demonstrate that physical properties of multifunctional material systems can be tailored for specific applications by controlling nanotube treatment (different types of nanotubes), concentration, and degree of alignment.

Park, Cheol↗
NASA NTRS2015

Development of Double and Triple-Pulsed 2-micron IPDA Lidars for Column CO2 Measurements

Carbon dioxide (CO2) is an important greenhouse gas that significantly contributes to the carbon cycle and globalradiation budget on Earth. CO2 role on Earth’s climate is complicated due to different interactions with various climatecomponents that include the atmosphere, the biosphere and the hydrosphere. Although extensive worldwide efforts formonitoring atmospheric CO2 through various techniques, including in-situ and passive sensors, are taking place highuncertainties exist in quantifying CO2 sources and sinks. These uncertainties are mainly due to insufficient spatial andtemporal mapping of the gas. Therefore it is required to have more rapid and accurate CO2 monitoring with higheruniform coverage and higher resolution. CO2 DIAL operating in the 2-μm band offer better near-surface CO2measurement sensitivity due to the intrinsically stronger absorption lines. For more than 15 years, NASA LangleyResearch Center (LaRC) contributed in developing several 2-m CO2 DIAL systems and technologies. This paperfocuses on the current development of the airborne double-pulsed and triple-pulsed 2-m CO2 integrated pathdifferential absorption (IPDA) lidar system at NASA LaRC. This includes the IPDA system development andintegration. Results from ground and airborne CO2 IPDA testing will be presented. The potential of scaling suchtechnology to a space mission will be addressed.

Singh, Upendra N.↗
NASA NTRSDate not supplied

Distributed Pressure Sensing for Enabling Self-Aware Autonomous Aerial Vehicles

Autonomous aerial transportation will be a fixture of future robotic societies, simultaneously requiring more stringent safety requirements and fewer resources for characterization than current commercial air transportation. More robust, adaptable, self-state estimation will be necessary to create such autonomous systems. We present a modular, scalable, distributed pressure sensing skin for aerodynamic state estimation of a large, flexible aerostructure. This skin used a network of 22 nodes that performed in-situ computation and communication of data collected from 74 pressure sensors, which were embedded into the skin panels of an ultra-lightweight 14-foot wingspan made from commutable, lattice-based subcomponents, and tested at NASA Langley Research Center's 14X22 wind tunnel. The density of the pressure sensors allowed for the use of a novel distributed algorithm to generate estimates of the wing lift contribution that were more accurate than the direct integration of the pressure distribution over the wing surface.

Daniel Cellucci↗
NASA NTRS1994

Mission planning for space based satellite surveillance experiments with the MSX

The Midcourse Space Experiment is a BMDO-sponsored scientific satellite set for launch within the year. The satellite will collect phenomenology data on missile targets, plumes, earth limb backgrounds and deep space backgrounds in the LWIR, visible and ultra-violet spectral bands. It will also conduct functional demonstrations for space-based space surveillance. The Space-Based Visible sensor, built by Lincoln Laboratory, Massachusetts Institute of Technology, is the primary sensor on board the MSX for demonstration of space surveillance. The SBV Processing, Operations and Control Center (SPOCC) is the mission planning and commanding center for all space surveillance experiments using the SBV and other MSX instruments. The guiding principle in the SPOCC Mission Planning System was that all routine functions be automated. Manual analyst input should be minimal. Major concepts are: (I) A high level language, called SLED, for user interface to the system; (2) A group of independent software processes which would generally be run in a pipe-line mode for experiment commanding but can be run independently for analyst assessment; (3) An integrated experiment cost computation function that permits assessment of the feasibility of the experiment. This paper will report on the design, implementation and testing of the Mission Planning System.

Sridharan, R.↗
NASA NTRS1995

Hidden Markov models for fault detection in dynamic systems

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Smyth, Padhraic J.↗
NASA NTRS2005

Monitoring a Complex Physical System using a Hybrid Dynamic Bayes Net

The Reverse Water Gas Shift system (RWGS) is a complex physical system designed to produce oxygen from the carbon dioxide atmosphere on Mars. If sent to Mars, it would operate without human supervision, thus requiring a reliable automated system for monitoring and control. The RWGS presents many challenges typical of real-world systems, including: noisy and biased sensors, nonlinear behavior, effects that are manifested over different time granularities, and unobservability of many important quantities. In this paper we model the RWGS using a hybrid (discrete/continuous) Dynamic Bayesian Network (DBN), where the state at each time slice contains 33 discrete and 184 continuous variables. We show how the system state can be tracked using probabilistic inference over the model. We discuss how to deal with the various challenges presented by the RWGS, providing a suite of techniques that are likely to be useful in a wide range of applications. In particular, we describe a general framework for dealing with nonlinear behavior using numerical integration techniques, extending the successful Unscented Filter. We also show how to use a fixed-point computation to deal with effects that develop at different time scales, specifically rapid changes occuring during slowly changing processes. We test our model using real data collected from the RWGS, demonstrating the feasibility of hybrid DBNs for monitoring complex real-world physical systems.

Lerner, Uri↗
NASA NTRS2010

Considerations for Architecture Level Trade Studies for Environmental Sensors

Comparisons of key characteristics of environmental sensors such as technology readiness levels, mass, power, volume, and detection capabilities are essential for initial trade studies to determine likely candidates for further development and evaluation. However, these trade studies only provide part of the information necessary to make selection decisions. Ultimately, the sensors must be judged based on the overall system architectures and operational scenarios for which they are intended. This means that additional characteristics, such as architectural needs for redundancy, operational lifetime, ability to maintain calibration, and repair and replacement strategies, among others, must also be considered. Given that these characteristics can be extremely time-consuming and costly to obtain, careful planning is essential to minimize the effort involved. In this paper, an approach is explored for determining an effective yet comprehensive set of architecture level trades which is minimally impacted by the inevitable changes in operational (mission) scenarios. The approach will also identify and integrate the various facilities and opportunities required to obtain the desired architecture level trade information.

Peterson, Craig↗
NASA NTRSDate not supplied

Physiological and Subjective Responses of Pilots During Advanced Air Mobility Flight Testing With Automated Systems

Aviation is constantly evolving, mostly due to the integration of automated systems into the National Airspace System. This presents a host of challenges and opportunities. NASA's Advanced Air Mobility (AAM) project has taken a significant leap forward with a research flight test led by the Integration of Automated Systems (IAS) sub-project. This effort focused on assessing automated flight deck algorithms essential for supporting high-density Urban Air Mobility (UAM) operations. Carrying out a two-ship flight test in UAM Maturity Level 4 scenarios, the team evaluated state-of-the-art algorithms, including Hazard Perception and Avoidance (HPA) and flight path management (FPM) systems. This presentation focuses on results of pilots' physiological and subjective responses during the flight scenarios conducted. In collaboration with Lockheed Martin Advanced Technology Laboratories (ATL), we collected and analyzed live-flight biometric data using eye tracking, mobile brain imaging, and heart rate sensors. The data provides insights into pilots' workload and cognitive engagement while navigating automated tools, leveraging both biometric data and post-encounter subjective assessments. The research highlights the interaction between human operators and automated systems, contributing valuable lessons learned about gathering human data in live-flight environments. The knowledge acquired from this endeavor enhances our understanding of human factors in automated flight and informs future studies attempting to undertake similar feats.

air mobility↗
NASA NTRS1993

Hidden Markov models for fault detection in dynamic systems

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) perpendicular to x), 1 less than or equal to i is less than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Smyth, Padhraic J.↗
NASA NTRS2012

Performance of an Advanced Stirling Convertor Based on Heat Flux Sensor Measurements

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two highefficiency Advanced Stirling Convertors (ASCs), developed by Sunpower, Inc., and NASA Glenn Research Center. The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot-end and cold-end temperatures, and specified electrical power output for a given heat input. It is difficult to measure heat input to Stirling convertors due to the complex geometries of the hot components, temperature limits of sensor materials, and invasive integration of sensors. A thin-film heat flux sensor was used to directly measure heat input to an ASC. The effort succeeded in designing and fabricating unique sensors, which were integrated into a Stirling convertor ground test and exposed to test temperatures exceeding 700 C in air for 10,000 hr. Sensor measurements were used to calculate thermal efficiency for ASC-E (Engineering Unit) #1 and #4. The post-disassembly condition of the sensors is also discussed.

Wilson, Dcott D.↗