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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 1,135 records · Page 63

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NASA NTRS2011

Structural health monitoring apparatus and methodology

Disclosed is an apparatus and methodology for structural health monitoring (SHM) in which smart devices interrogate structural components to predict failure, expedite needed repairs, and thus increase the useful life of those components. Piezoelectric wafer active sensors (PWAS) are applied to or integrated with structural components and various data collected there from provide the ability to detect and locate cracking, corrosion, and disbanding through use of pitch-catch, pulse-echo, electro/mechanical impedance, and phased array technology. Stand alone hardware and an associated software program are provided that allow selection of multiple types of SHM investigations as well as multiple types of data analysis to perform a wholesome investigation of a structure.

Giurgiutiu, Victor↗

NASA NTRS2011

Overview of CMC Research at NASA Glenn Research Center

CMC technology development in the Ceramics Branch at NASA Glenn Research Center addresses Aeronautics propulsion goals across subsonic, supersonic and hypersonic flight regimes. Combustor, turbine and exhaust nozzle applications of CMC materials will enable NASA to demonstrate reduced fuel consumption, emissions, and noise in advanced gas turbine engines. Applications ranging from basic Fundamental Aeronautics research activities to technology demonstrations in the new Integrated Systems Research Program will be discussed.

Grady, Joseph E.↗

NASA NTRS2012

A Proposed Strategy for the U.S. to Develop and Maintain a Mainstream Capability Suite ("Warehouse") for Automated/Autonomous Rendezvous and Docking in Low Earth Orbit and Beyond

The ability of space assets to rendezvous and dock/capture/berth is a fundamental enabler for numerous classes of NASA fs missions, and is therefore an essential capability for the future of NASA. Mission classes include: ISS crew rotation, crewed exploration beyond low-Earth-orbit (LEO), on-orbit assembly, ISS cargo supply, crewed satellite servicing, robotic satellite servicing / debris mitigation, robotic sample return, and robotic small body (e.g. near-Earth object, NEO) proximity operations. For a variety of reasons to be described, NASA programs requiring Automated/Autonomous Rendezvous and Docking/Capture/Berthing (AR&D) capabilities are currently spending an order-of-magnitude more than necessary and taking twice as long as necessary to achieve their AR&D capability, "reinventing the wheel" for each program, and have fallen behind all of our foreign counterparts in AR&D technology (especially autonomy) in the process. To ensure future missions' reliability and crew safety (when applicable), to achieve the noted cost and schedule savings by eliminate costs of continually "reinventing the wheel ", the NASA AR&D Community of Practice (CoP) recommends NASA develop an AR&D Warehouse, detailed herein, which does not exist today. The term "warehouse" is used herein to refer to a toolbox or capability suite that has pre-integrated selectable supply-chain hardware and reusable software components that are considered ready-to-fly, low-risk, reliable, versatile, scalable, cost-effective, architecture and destination independent, that can be confidently utilized operationally on human spaceflight and robotic vehicles over a variety of mission classes and design reference missions, especially beyond LEO. The CoP also believes that it is imperative that NASA coordinate and integrate all current and proposed technology development activities into a cohesive cross-Agency strategy to produce and utilize this AR&D warehouse. An initial estimate indicates that if NASA strategically coordinates the development of a robust AR&D capability across the Agency, the cost of implementing AR&D on a spacecraft could be reduced from roughly $70M per mission to as low as $7M per mission, and the associated development time could be reduced from 4 years to 2 years, after the warehouse is completely developed. Table 1 shows the clear long-term benefits to the Agency in term of costs and schedules for various missions. (The methods used to arrive at the Table 1 numbers is presented in Appendices A and B.)

Krishnakumar, Kalmanje S.↗

NASA NTRS2004

Latency Requirements for Head-Worn Display S/EVS Applications

NASA s Aviation Safety Program, Synthetic Vision Systems Project is conducting research in advanced flight deck concepts, such as Synthetic/Enhanced Vision Systems (S/EVS), for commercial and business aircraft. An emerging thrust in this activity is the development of spatially-integrated, large field-of-regard information display systems. Head-worn or helmet-mounted display systems are being proposed as one method in which to meet this objective. System delays or latencies inherent to spatially-integrated, head-worn displays critically influence the display utility, usability, and acceptability. Research results from three different, yet similar technical areas flight control, flight simulation, and virtual reality are collectively assembled in this paper to create a global perspective of delay or latency effects in head-worn or helmet-mounted display systems. Consistent definitions and measurement techniques are proposed herein for universal application and latency requirements for Head-Worn Display S/EVS applications are drafted. Future research areas are defined.

Bailey, Randall E.↗

NASA NTRS2012

Ascent/Descent Software

The Ascent/Descent Software Suite has been used to support a variety of NASA Shuttle Program mission planning and analysis activities, such as range safety, on the Integrated Planning System (IPS) platform. The Ascent/Descent Software Suite, containing Ascent Flight Design (ASC)/Descent Flight Design (DESC) Configuration items (Cis), lifecycle documents, and data files used for shuttle ascent and entry modeling analysis and mission design, resides on IPS/Linux workstations. A list of tools in Navigation (NAV)/Prop Software Suite represents tool versions established during or after the IPS Equipment Rehost-3 project.

Brown, Charles↗

NASA NTRS2012

NASA Astrophysics Technology Needs

July 2010, NASA Office of Chief Technologist (OCT) initiated an activity to create and maintain a NASA integrated roadmap for 15 key technology areas which recommend an overall technology investment strategy and prioritize NASA?s technology programs to meet NASA?s strategic goals. Science Instruments, Observatories and Sensor Systems(SIOSS) roadmap addresses technology needs to achieve NASA?s highest priority objectives -- not only for the Science Mission Directorate (SMD), but for all of NASA.

Stahl, H. Philip↗

NASA NTRS2016

Preliminary On-Orbit Neutron Dose Equivalent and Energy Spectrum Results from the ISS-RAD Fast Neutron Detector (FND)

The ISS-RAD instrument was activated on ISS on February 1st, 2016. Integrated in ISS-RAD, the Fast Neutron Detector (FND) performs, for the first time on ISS, routine and precise direct neutron measurements between 0.5 and 8 MeV. Preliminary results for neutron dose equivalent and neutron flux energy distributions from online/on-board algorithms and offline ground analyses will be shown, along with comparisons to simulated data and previously measured neutron spectral data. On-orbit data quality and pre-launch analysis validation results will be discussed as well.

Semones, Edward↗

NASA NTRS2017

NASA's Hybrid Reality Lab: One Giant Leap for Full Dive

This presentation demonstrates how NASA is using consumer VR headsets, game engine technology and NVIDIA's GPUs to create highly immersive future training systems augmented with extremely realistic haptic feedback, sound, additional sensory information, and how these can be used to improve the engineering workflow. Include in this presentation is an environment simulation of the ISS, where users can interact with virtual objects, handrails, and tracked physical objects while inside VR, integration of consumer VR headsets with the Active Response Gravity Offload System, and a space habitat architectural evaluation tool. Attendees will learn how the best elements of real and virtual worlds can be combined into a hybrid reality environment with tangible engineering and scientific applications.

Delgado, Francisco J.↗

NASA NTRS2017

Technical Challenges and Barriers Affecting Turbo-Electric and Hybrid Electric Aircraft Propulsion

In order to meet aggressive aircraft performance goals set by NASA's Aeronautics Research Mission Directorate, the Glenn Research Center (GRC) is leading research and development of electrified aircraft propulsion systems with electricity being generated from a gas turbine engine or combination of gas turbine engine and an alternate energy source. The presentation will provide an overview of technical challenges and barriers affecting the development and implementation of turboelectric and hybrid electric systems. Advances will be required in multiple areas, which include energy storage, electrical machines, power transmission, power electronics, control systems, materials, thermal management, and multi-scale modeling tools. The presentation will summarize current GRC activities in these areas. Challenges associated with integration and demonstration of multiple technologies at the system level will be presented.

Propulsion↗

NASA NTRS2018

Upgrades to the International Space Station Water Processor Assembly

The International Space Station Water Processor Assembly provides contaminant control and deionization to the Water Recovery System. The Water Processor Assembly presently utilizes sorbent-based Multifiltration Beds and a downstream Catalytic Reactor for these operations. Upgrades and process improvements are desired to improve performance, increase reliability, and decrease consumable resupply. To this end, reverse osmosis membrane separation technologies were evaluated to reduce influent contaminant loads, candidate additives to inhibit wastewater biofilm formation were studied, and life stability testing was completed for a recently developed high-activity catalyst. Evaluation of an adsorption media integration concept was also completed. The performance and applicability of these new technologies within the Water Processor Assembly, as well as their suitability for exploration missions, are discussed herein.

Kayatin, Matthew J.↗

NASA NTRS2018

A13H-2537: Above Cloud Aerosol Optical Properties in the South East Atlantic from airborne observations during ORACLES

Aerosol overlying marine stratocumulus clouds is a persistent feature in the southeast Atlantic during the biomass burning season, July through November. We sampled aerosol and cloud from an airborne research platform, the NASA P3, during the deployments of ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) encompassing the peak biomass burning season. We used the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) to quantify the aerosol’s optical properties, notably the aerosol optical depth (AOD) by directly measuring the amount of light attenuation. We present an overview of very recent AOD measurements and contrast those to previous deployments. We observed an average AOD at 500 nm of 0.33 (0.30) in September 2016 (August 2017), with similar spatial dependence as observed by the MODIS instrument on board the TERRA and AQUA satellites. We also show full spectral vertical dependence of AOD from flight profiles, which compares favorably to the integrated aerosol extinction profile obtained by the active remote sensing High Spectral Resolution Lidar-2 (HSRL-2). We also present a quantification of the gap extent separating cloud top and aerosol layer bottom. Using hyperspectral transmitted light measurements from 4STAR, in conjunction with hyperspectral hemispheric irradiance measurements from the Solar Spectral Flux Radiometers (SSFR), we retrieved aerosol intensive properties (asymmetry parameter, single scattering albedo), aerosol size distributions, cloud optical depth (COD), cloud particle effective radius, and cloud thermodynamic phase. Cloud properties, also presented here, are obtained from 4STAR measurements of scattered light below clouds.

Samuel E LeBlanc↗

NASA NTRSDate not supplied

Artemis Lunar Surface VR/ARGOS Trainer

This proposal aims to provide insight by identifying potential risks and unknowns of lander egress and surface operations through a Mixed Reality (MR) planning, training, and analysis capability that integrates Virtual Reality (VR) simulations and the Active Response Gravity Offload System (ARGOS) in support of Artemis missions to the moon. The VR simulation will incorporate lunar digital elevation map data and imagery to provide accurate terrain of the south pole and Shackleton Crater. Date specific ephemerides will used to simulate the extreme lighting environment. Virtual representations of a lunar lander vehicle will be represented with a physical mockup of the porch and ladder assembly. Human-in-the-loop engineering test runs within ARGOS will be used to refine performance of the Mixed Reality interface with the mockup platform and define procedures for training.

Lee K Bingham↗

NASA NTRS2021

Lunar Surface VR/ARGOS Trainer

Lee K Bingham↗

NASA NTRS2009

Roadmaps and Strategies for Crop Research for Bioregenerative Life Support Systems A Compilation of Findings from NASA’s Advanced Life Support Meetings

Extensive testing with plants for bioregenerative life support systems has been conducted by NASA for nearly 40 years, both through university grants and work at NASA field centers. During this time, numerous meetings were held to develop strategies and roadmaps for implementing bioregenerative life support systems. Findings from several of these meetings are summarized in this report. In nearly all cases, the recommendations included an active ground-based research program and integration tests with other life support subsystems, followed by eventual spaceflight testing. The most recent roadmap of NASA’s Exploration Life Support Crop Element suggests a sequence of first developing a modular vegetable production unit (VPU) to provide perishable foods to supplement the crew’s diet. A similar system could then be used on the lunar surface, with additional modules added as the lunar outpost expands. Eventually, these modules could be transferred to a dedicated pressurized logistics module (PLM) for crop production. Experience from the lunar tests could then be used to conduct a similar buildup for Mars missions, where in situ food production and bioregeneration would be important for achieving outpost autonomy. To date, most trade studies of bioregenerative life support systems indicate that reducing the costs associated with crop lighting systems are key, and use of light-emitting diodes (LEDs) or direct solar lighting offers promising options. Likewise, sustaining high yields and high harvest index (% edible biomass) will be important for minimizing costs, and this can be achieved by optimizing growth environments and through selecting, breeding, and genetically engineering crops suitable for space environments. Collectively, these strategies and roadmaps suggest that a combined approach of fundamental research, hardware (plant chamber) development, and operational testing is required to achieve reliable bioregenerative life support systems.

Bioregenerative↗

NASA NTRSDate not supplied

Experimental Testing of Data Fusion in A Distributed Ground-Based Sensing Network for Advanced Air Mobility

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles(UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with two independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10%increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by one of the two radars.

Federica Vitiello↗

NASA NTRS2024

Integration of Automated Systems Test Campaign NC-IAS

NASA’s 2022 strategic plan included the goal to catalyze economic growth and drive innovation in the aviation industry, and to address challenges in air transportation and airspace management within the National Airspace System (NAS). The Aeronautics Research Mission Directorate (ARMD) specifically was tasked with leading aviation innovation to enable safe and sustainable air transportation through revolutionary vehicle advances and efficient flight operations. As a part of meeting these objectives and advancing air mobility concepts, NASA initiated the National Campaign (NC) in the Advanced Air Mobility (AAM) Project within the Airspace Operations and Safety Program (AOSP). The NC was designed to support operational demonstrations with industry as well as the research and development needed to support NASA-led research flight demonstrations. Within NC, the Integration of Automated Systems (IAS), an NC activity, tested and evaluated flight deck automation and airspace operations management functions needed to enable Urban Air Mobility (UAM) operations. This was accomplished through a partnership with Sikorsky Aircraft (specifically Sikorsky Innovations), a Lockheed Martin company, and DARPA (Defense Advanced Research Projects Agency), by leveraging two automation-enabled helicopters equipped with unique capabilities that enabled NASA to develop and test two-ship conflict encounters to demonstrate flight path management and hazard avoidance technologies. The enabler in this testing was NASA-developed “Middleware” (MW) software (also known as Expandable Variable Autonomy Architecture, or EVAA), which among other things allowed multiple algorithms to be incorporated into one software build that was hosted on the dissimilar-type Sikorsky helicopters. The IAS test campaign period of performance was from March 2022 through October 2023 and was structured as a phased, or spiral, approach that ultimately led to the first-ever demonstration of two-ship UAM/AAM operations designed to safely choreograph specific conflict encounters and mission scenarios to test the research algorithms for strategic and tactical aircraft deconfliction. Lessons learned are included in the body of the report. Data collected will be used to inform FAA and industry standards groups on the increasingly automated systems needed for future AAM operations. The test encounters developed for these flight tests were proven to be highly predictable, repeatable, and safely exercised flight path planning and Detect and Avoid (DAA) algorithms. These same test encounters should be leveraged by future flight test campaigns to verify that operational safety is not compromised as the AAM architecture matures. Next steps include repeating similar encounters using unmanned aircraft carrying DAA sensors in the National Airspace.

AAM↗

NASA NTRSDate not supplied

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗

NASA NTRS2025

Demonstration of Data Processing and Fusion from Distributed Radars for AAM Surveillance

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles (UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with three independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10% increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by two of the radars.

Federica Vitiello↗