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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

EXCAP-LR: Exploration Capabilities Logistics Reduction

All human space missions require substantial logistical mass and volume. As our exploration missions increase in distance and duration, reduction of these logistics requirements becomes more important. The movement and tracking of logistics between vehicle elements are increasingly recognized as critical to crew efficiency and on-orbit mission assurance. This project targets the best opportunities to demonstrate logistics reduction, repurposing, and efficient tracking and management of logistics. These technologies and innovations will make future exploration missions more affordable. - REALM-3 (RFID (Radio Frequency Identification) Enabled Autonomous Logistics Management) – Hydra (HYper-Distributed RFID Antenna) Smart Stow: receives RFID signal from readers, use very small % of signal to self-power on-board microcontroller and RF switch, multiplex RFID signal to other nodes in a chain or to a multitude of antennas. ISS HYDRA Smart Stow is over-instrumented to allow evaluation of a branched network HYDRA chain. - UWMS (Universal Waste Management System) – provides a compact, lower mass/volume toilet for exploration missions - ACS (Advanced Clothing Systems) – investigates ways to reduce clothing mass and volume directly or through efficiently cleaning them for reuse.

Patrick Fink↗
NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗
NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗
NASA NTRSDate not supplied

Concepts for Distributed Sensing and Collaborative Airspace Autonomy in Advanced Urban Air Mobility

Emerging concepts for advanced urban air mobility envision responsive air transportation capabilities that will safely move people and cargo in locations presently underserved by aviation. Expanding aviation services to these locales, particularly for high-density autonomous flight operations over urban centers, will require advances beyond the state-of-the-art techniques for airborne sensing. The emerging field of distributed sensing and ‘smart spaces’ – where sensing, processing, communication, and actuation are embedded in the environment in which agents are acting – may provide attractive alternatives over traditional aviation solutions. This paper outlines the challenges and opportunities for distributed sensing and smart space concepts to meet the emerging needs of advanced urban operations in the national airspace. We present an overview of distributed sensing concepts and research currently being investigated under this endeavor.

Distributed sensing↗
NASA NTRS2023

Emperor's new clothes: Novel textile-based supercapacitors using sheep wool fiber as electrode substrate

Textile-based supercapacitors (TSCs) are being used to meet the ever-increasing demand for mobile, safe, and convenient energy sources to power personal electronic devices. To that end, the smart textiles used in wearable technology need to be made from highly conductive yarns that are easily manufacturable. To date, synthetic- and cellulosic-based yarns have been exclusively used for the fabrication of TSCs, while other yarns have not been explored. Here, we used conductive protein-based yarns for TSCs and report on the use of wool coated with Ti 3 C 2 T x MXene as a potential electrode material. To knit TSCs, wool and cotton yarns were coated with MXene flakes and their surfaces were characterized using Scanning Electron Microscopy (SEM) and X-Ray Photoelectron Spectroscopy (XPS). The electrochemical characterization was conducted to examine the performance of wool- and cotton-based MXene electrodes as substrates and determine charge storage and resistive behavior. These tests showed that wool TSCs exhibited more pseudocapacitive behavior, while cotton TSCs exhibited a wider current range. At a scan rate of 5 mV/s, cotton TSCs presented an areal capacitance of 823.9 mF/cm 2 while this value for the wool TSCs was 284 mF/cm 2 . The performance of yarns was also tested under various mechanical deformation conditions and after washing in order to assess the stability of TSCs. This study indicates the potential of protein-based yarns as electrode substrates for integration of MXene to fabricate smart textile-based devices.

Alyssa Grube↗
NASA NTRS2023

Automated Global-Scale Detection and Characterization of Anthropogenic Activity using Multi-Source Satellite-Based Remote Sensing Imagery

Satellite-based remote sensing imagery is an effective means for detecting objects and structures in support of many applications. However, detecting the spatial and temporal bounds of a specific activity in satellite imagery is inherently more complex and research in this area is nascent. One reason for this is that describing an activity implies defining both spatial and temporal bounds and while activity is inherently continuous in nature, the geospatial (imagery) time series for any particular swath of ground provided by satellite imagery is relatively sparse and discrete in comparison. The IARPA Space-Based Machine Automated Recognition Technique (SMART)1 program is the first large-scale research program to target advancing the state of the art for automatically detecting, characterizing, and monitoring large-scale anthropogenic activity in global, multispectral satellite imagery. The program has two primary research objectives: 1) the “harmonization” of multiple imagery sources and 2) automated reasoning at scale to detect, characterize, and monitor activities of interest. This paper provides details on the goals, dataset, metrics, and lessons learned of the IARPA SMART program. By releasing the annotated dataset, the program aims to foster additional research in this area by the community at large.

Hirsh R Goldberg↗
NASA NTRS2024

Enterprise Digital Transformation: Transforming NASA's Workplace

NASA has a long history of serving the Nation and the world, by reaching for new heights and revealing the unknown for the benefit of all humankind. To ensure the agency will deliver on its mission in a hyper-connected, technology-enabled, globally-partnered, and rapidly-changing world, NASA launched a Digital Transformation initiative in late 2020 to modernize the way it works, the experience of its workforce and the agility of its workplace. At the core of its workplace transformation strategy, NASA is on a journey to leverage smart operational technologies, weaving together IoT, AI, intelligent automation, extended reality, and digital twins to build a network of reliable, adaptable and sustainable “Smart Centers” to execute its mission… on planet Earth and beyond. Come hear NASA’s digital strategy, the exciting progress being made, lessons learned from their journey, and how the AIMST community can enable NASA and its partners to serve humanity in a digital future.

Jill Marlowe↗
NASA NTRS2003

Mars Mission Surface Operation Simulation Testing of Lithium-Ion Batteries

The objectives of this program are to 1) Assess viability of using lithium-ion technology for future NASA applications, with emphasis upon Mars landers and rovers which will operate on the planetary surface; 2) Support the JPL 2003 Mars Exploration Rover program to assist in the delivery and testing of a 8 AHr Lithium-Ion battery (Lithion/Yardney) which will power the rover; 3) Demonstrate applicability of using lithium-ion technologyfor future Mars applications: Mars 09 Science Laboratory (Smart Lander) and Future Mars Surface Operations (General). Mission simulation testing was carried out for cells and batteries on the Mars Surveyor 2001 Lander and the 2003 Mars Exploration Rover.

Smart, M. C.↗
NASA NTRS2010

Design of Modular, Shape-transitioning Inlets for a Conical Hypersonic Vehicle

For a hypersonic vehicle, propelled by scramjet engines, integration of the engines and airframe is highly desirable. Thus, the forward capture shape of the engine inlet should conform to the vehicle body shape. Furthermore, the use of modular engines places a constraint on the shape of the inlet sidewalls. Finally, one may desire a combustor cross- section shape that is different from that of the inlet. These shape constraints for the inlet can be accommodated by employing a streamline-tracing and lofting technique. This design technique was developed by Smart for inlets with a rectangular-to-elliptical shape transition. In this paper, we generalise that technique to produce inlets that conform to arbitrary shape requirements. As an example, we show the design of a body-integrated hypersonic inlet on a winged-cone vehicle, typical of what might be used in a three-stage orbital launch system. The special challenge of inlet design for this conical vehicle at an angle-of-attack is also discussed. That challenge is that the bow shock sits relatively close to the vehicle body.

Gollan, Rowan J.↗
NASA NTRS1996

On-board Neural Processor Design for an Intelligent Multi-sensor Microspacecraft

A compact VLSI neural processor based on the Optimization Cellular Neural Network (OCNN)has been under development to provide a wide range of support for an intelligent remote sensing microspacecraft which requires both high bandwidth communication and high-performance computing for on-board data analysis, thematic data reduction, synergy of multiple types of sensors, and other smart-sensor functions. The OCNN architecture is a programmable multi-dimensional array of neurons which are locally connected with their local neurons. The OCNN operation theory, architecture, design and implementation, prototype chip, and system applications have been investigated in detail and presented in this paper.

array↗
NASA NTRS2021

Role of Cyber-Physical Testing in Developing Resilient Extraterrestrial Habitats

Extraterrestrial long-term habitat systems (henceforth referred to as habitat systems) require groundbreaking technological advances to overcome the extreme demands introduced by isolation and challenging environments. A habitat system must operate as intended under continuous disruptive conditions. Designing for the demands that challenging environments will place on habitat systems (e.g., wild temperature fluctuations, galactic cosmic rays, destructive dust, meteoroid impacts, vibrations, and solar particle events) represents one of the greatest challenges in this endeavor. This engineering problem necessitates that we design and manage habitat systems to be resilient. System resilience requires a comprehensive approach that accounts for disruptions through the design process and adapts to them in operation. As the habitat system evolves—growing in physical size, complexity, population, and connectivity—and diversifies in operations, it must continue to be safe and resilient. In this endeavor, we should take advantage of lessons learned in developing civil infrastructure responsive to catastrophic natural hazards, autonomous robotics platforms, smart buildings, cyber-physical testing, complex systems, and diagnostics and prognostics for intelligent health management. This study highlights the importance of system resilience and cyber-physical testing to address the grand challenge of developing habitat systems.

Public health and safety↗
NASA NTRS1978

Sensor data autonomy

'Smart' sensors onboard NASA space missions will require variable data output bandwidth as they respond to phenomena of interest. An Instrument Telemetry Packet (ITP) approach has been developed which encodes experimental instrument data into an autonomous data package, along with pertinent engineering parameters and ancillary data (time, position, attitude, etc.). New requirements for onboard concentration and buffering, as well as for end-to-end error control, arise from this approach. Emphasis is placed on packet protocols compatible with the data link standard ADCCP, to enable one set of ground support equipment to readily support instrument development, launch site checkout and mission operations phases.

Greene, E. P.↗
NASA NTRS1978

On-board data processing for the IRAS telescope system

Onboard data processing has been developed for the Infrared Astronomical Satellite (IRAS) telescope system to effectively utilize the RF bandwidth and minimize the ground-data processing costs. Use of filtering techniques, data deglitching circuits, and data encoding algorithms are combined with a microprocessor-controlled telescope system to achieve a system dynamic range of 100,000 with a noise equivalent flux density of no less than 10 to the minus 19th W/sq cm. Extraneous data, e.g., noise due to radiation hits, will be removed prior to transmission, thereby optimizing ground-data processing for the highest sensitivity and reliability. Simulation results are presented which demonstrate the advantages gained through the use of onboard data processing and illustrate the possible merging of these techniques with an array for the future evolution of 'smart' sensors.

Lum, H.↗
NASA NTRS1979

Implementing a bubble memory hierarchy system

This paper reports on implementation of a magnetic bubble memory in a two-level hierarchial system. The hierarchy used a major-minor loop device and RAM under microprocessor control. Dynamic memory addressing, dual bus primary memory, and hardware data modification detection are incorporated in the system to minimize access time. It is the objective of the system to incorporate the advantages of bipolar memory with that of bubble domain memory to provide a smart, optimal memory system which is easy to interface and independent of user's system.

Segura, R.↗
NASA NTRS1979

Earth feature identification and tracking technology development

The paper discusses needs for smart sensing in terrestrial and atmospheric remote sensing as related to current technology and a scheduled Shuttle experiment. An approach is outlined involving Shuttle-borne experiments to develop earth feature identification and tracking technology including a Feature Identification and Location Experiment (FILE) scheduled for flight on the NASA Shuttle with an objective of classifying earth features into categories of bare land, water, vegetation, and clouds, snow, and ice. The plan for evolution of the FILE-related technology leads to capabilities for pointing instruments to predetermined sites, reacquiring earth features or landmarks, and tracking features such as coastlines and rivers. Technology concepts relative to an overall system transfer function is discussed, and the development status outlined.

Wilson, R. G.↗
NASA NTRS1981

US Army remotely piloted vehicle supporting technology program

Essential technology programs that lead to the full scale engineering development of the Aquila Remotely Piloted Vehicle system for U.S. Army are described. The Aquila system uses a small recoverable and reusable RPV to provide target acquisition, designation, and aerial reconnaissance mission support for artillery and smart munitions. Developments that will provide growth capabilities to the Aquila RPV system, as well as future RPV mission concepts being considered by the U.S. Army are presented.

Gossett, T. D.↗
NASA NTRS1981

The NTF as a national facility

The future evolution of the NTF as a national facility was discussed. The aerodynamic test facility is charged with maintaining the test data and operating the facility with maximum productivity to increase the utility as well as to minimize the test costs. Efforts are under way to increase productivity of the wind tunnels. The future developments needed include: (1) the elimination of wall interference uncertainties; (2) the elimination of minimization of sting interference; and (3) the achievement of free air quality low turbulence airflow. Research in the wall interference area, smart walls, is reported.

Brown, C. E.↗