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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 181 records · Page 10

All sources NASA NTRS DOE OSTI

NASA NTRS1993

Development of an infrared absorption transducer to monitor partial pressure of carbon dioxide for space applications

An infrared (IR) carbon dioxide (CO2) transducers has been designed, developed, and produced for space applications. The transducer provides measurement of partial pressure of CO2 in life support applications, including the Extravehicular Mobility Unit (EMU), Space Shuttle Orbiter and Spacehab. The electrochemical sensor presently used for these applications has a slow reponse time and has reliability concerns due to the electrolyte. The new microprocessor based unit has a fast response time and can be tailored to other space applications.

Lutz, Glenn↗

NASA NTRS2007

NASA Lunar Base Wireless System Propagation Analysis

There have been many radio wave propagation studies using both experimental and theoretical techniques over the recent years. However, most of studies have been in support of commercial cellular phone wireless applications. The signal frequencies are mostly at the commercial cellular and Personal Communications Service bands. The antenna configurations are mostly one on a high tower and one near the ground to simulate communications between a cellular base station and a mobile unit. There are great interests in wireless communication and sensor systems for NASA lunar missions because of the emerging importance of establishing permanent lunar human exploration bases. Because of the specific lunar terrain geometries and RF frequencies of interest to the NASA missions, much of the published literature for the commercial cellular and PCS bands of 900 and 1800 MHz may not be directly applicable to the lunar base wireless system and environment. There are various communication and sensor configurations required to support all elements of a lunar base. For example, the communications between astronauts, between astronauts and the lunar vehicles, between lunar vehicles and satellites on the lunar orbits. There are also various wireless sensor systems among scientific, experimental sensors and data collection ground stations. This presentation illustrates the propagation analysis of the lunar wireless communication and sensor systems taking into account the three dimensional terrain multipath effects. It is observed that the propagation characteristics are significantly affected by the presence of the lunar terrain. The obtained results indicate the lunar surface material, terrain geometry and antenna location are the important factors affecting the propagation characteristics of the lunar wireless systems. The path loss can be much more severe than the free space propagation and is greatly affected by the antenna height, surface material and operating frequency. The results from this paper are important for the lunar wireless system link margin analysis in order to determine the limits on the reliable communication range, achievable data rate and RF coverage performance at planned lunar base work sites.

Hwu, Shian U.↗

NASA NTRSDate not supplied

Systems Health Monitoring: Integrating FMEA into Bayesian Networks

The foreseeable high traffic density suggests that a large number of electric propulsion systems will enter the airspace, and that they will also operate at high frequency, e.g., large number of take offs and landings per unit time. The reliability of such critical systems is therefore key to ensure high safety standards in the low-altitude airspace. Diagnostic systems, which aim at identifying incipient faults, can mitigate unexpected failures or lower-than-expected reliability by performing early fault detection by monitoring the systems. A key element of fault diagnosis is fault detection and isolation (FDI), which complexity increases with the complexity of the system itself, namely the number of subsystems and components, interactions among sub-systems, and the number of sensors available. The proposed approach leverages combination of failure mode and effect analysis (FMEA) integrated with Bayesian networks, thus introducing dependability structures into a diagnostic framework to aid FDI. Faults and failure events from the FMEA are mapped within a Bayesian network, where network edges replicate the links embedded within FMEAs. The integrated framework enables the fault isolation process by identifying the probability of occurrence of specific faults or root causes given evidence observed through sensor signals. In this work, sub systems of Urban Air Mobility (UAM) type vehicle like avionics, structures, power-train etc. are taken into account to show the approach at the system level. This work integrates early design phase in the development of UAM type vehicles with diagnostic tools, which are often developed later in the product life-cycle, or retrofitted at a later time on systems. Failure mode and effect analysis (FMEA) derived for the system in the design phase is embedded within a Bayesian network (BN).

UAM↗

NASA NTRS1999

Biomorphic Explorers

UNKNOWN

Biomorphic↗

NASA NTRS2021

Spatial Variation of Fine Particulate Matter Levels in Nairobi Before and During the COVID-19 Curfew: Implications for Environmental Justice

The temporary decrease of fine particulate matter (PM(sub 2.5)) concentrations in many parts of the world due to the COVID-19 lockdown spurred discussions on urban air pollution and health. However there has been little focus on sub-Saharan Africa, as few African cities have air quality monitors and if they do, these data are often not publicly available. Spatial differentials of changes in PM(sub 2.5) concentrations as a result of COVID also remain largely unstudied. To address this gap, we use a serendipitous mobile air quality monitoring deployment of eight Sensirion SPS 30 sensors on motorbikes in the city of Nairobi starting on 16 March 2020, before a COVID-19 curfew was imposed on 25 March and continuing until 5 May 2020. We developed a random-forest model to estimate PM(sub 2.5) surfaces for the entire city of Nairobi before and during the COVID-19 curfew. The highest PM(sub 2.5) concentrations during both periods were observed in the poor neighborhoods of Kariobangi, Mathare, Umoja, and Dandora, located to the east of the city center. Changes in PM(sub 2.5) were heterogeneous over space. PM(sub 2.5) concentrations increased during the curfew in rapidly urbanizing, the lower-middle-class neighborhoods of Kahawa, Kasarani, and Ruaraka, likely because residents switched from LPG to biomass fuels due to loss of income. Our results indicate that COVID-19 and policies to address it may have exacerbated existing air pollution inequalities in the city of Nairobi. The quantitative results are preliminary, due to sampling limitations and measurement uncertainties, as the available data came exclusively from low-cost sensors. This research serves to highlight that spatial data that is essential for understanding structural inequalities reflected in uneven air pollution burdens and differential impacts of events like the COVID pandemic. With the help of carefully deployed low cost sensors with improved spatial sampling and at least one reference-quality monitor for calibration, we can collect data that is critical for developing targeted interventions that address environmental injustice in the African context.

Environmental justice↗

NASA NTRSDate not supplied

Enhancing In-Flight Structural Health Monitoring of Vertical Lift Vehicles Operating in an Urban Environment

In-situ airframe sensors have long been considered a potential solution for structural health monitoring that could change the design, certification, operation and maintenance paradigms of flight vehicles. In this approach, large networks of sensors covering the entire, or most of, an airframe throughout its operational lifetime would support real-time decisions on airworthiness and obviate the need to overbuild components or perform multiple cycles of structural qualification testing and inspections. This concept would go beyond the current practice of placing select sensors in strategic locations or relying on such sensors only during airframe qualification flights and inspections. For vehicles in the emerging urban air mobility space, reducing weight associated with overbuilds and shortening down-time associated with inspections are critical for improving safety and affordability. In practice, the wide-scale use of in-situ sensors as primary assurance for structural health has not been demonstrated to be feasible or the best solution. A sensor integration testbed was developed as a platform to evaluate the potential of multiple sensor types to enable decision making on airworthiness. We report on the initial runs of this testbed with multiple sensors attached to a common test article. Metal foil strain gauges, eddy current, fiber optic, guided wave (acoustic emission and ultrasonic)and carbon nanotube roving sensors were affixed to the test article. Baseline as well as post damage initiation and fatiguing data are presented and discussed. Despite the relative simplicity of the test article, the interpretation of the as-captured test data was generally not conclusive or did not have wide enough coverage. This result emphasizes the challenges and current limitations both in testing and the practical broad application of embedded sensors as the determinative elements in critical decision making on wide-scale structural health.

Vertical Lift Vehicles↗

NASA NTRSDate not supplied

Enhancing In-Flight Structural Health Monitoring of Vertical Lift Vehicles Operating in an Urban Environment

In-situ airframe sensors have long been considered a potential solution for structural health monitoring that could change the design, certification, operation, and maintenance paradigms of flight vehicles. In this approach, large networks of sensors covering the entire, or most of, an airframe throughout its operational lifetime would support real-time decisions on airworthiness and obviate the need to overbuild components or perform multiple cycles of structural qualification testing and inspections. This concept would go beyond the current practice of placing select sensors in strategic locations or relying on such sensors only during airframe qualification flights and inspections. For vehicles in the emerging urban air mobility space, reducing weight associated with overbuilds and shortening down-time associated with inspections are critical for improving safety and affordability. In practice, the wide-scale use of in-situ sensors as primary assurance for structural health has not been demonstrated to be feasible or the best solution. A sensor integration testbed was developed as a platform to evaluate the potential of multiple sensor types to enable decision making on airworthiness. We report on the initial runs of this testbed with multiple sensors attached to a common test article. Metal foil strain gauges, eddy current, fiber optic, guided wave (acoustic emission and ultrasonic) and carbon nanotube roving sensors were affixed to the test article. Baseline as well as post damage initiation and fatiguing data are presented and discussed. Despite the relative simplicity of the test article, the interpretation of the as-captured test data was generally not conclusive or did not have wide enough coverage. This result emphasizes the challenges and current limitations both in testing and the practical broad application of embedded sensors as the determinative elements in critical decision making on wide-scale structural health.

Vertical Lift Vehicles↗

DOE OSTI2023

Field Validation of Cloud Properties Sensor (SAIL Field Campaign Report)

The purpose of the Field Validation of Cloud Properties Sensor – SAIL campaign was to deploy Aerodyne’s extended-wavelength TWST cloud optical properties sensor (TWST-CPS) in an operationally relevant environment with co-located, externally validated sensors. Colocation with The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s deployment of its second Mobile Facility (AMF2) on the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign at Crested Butte, Colorado was ideal because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance over 440-1700 nm and retrieves cloud optical depth (COD), droplet effective radius (Reff), and thermodynamic phase (Phase). Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A low-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Instrument deployment to test robust operations and a new stray-light baffle design, and the continued development of analysis and retrieval algorithms using the data from this deployment, are central technical objectives of Aerodyne Research’s U.S. Department of Energy Small Business Innovative Research Phase 2 contract (DE-SC0020473, Low-cost shortwave spectroradiometer for retrieval of cloud properties).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Field Validation of Cloud Properties Sensor – SAIL Field Campaign Report

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1989

A tesselated probabilistic representation for spatial robot perception and navigation

The ability to recover robust spatial descriptions from sensory information and to efficiently utilize these descriptions in appropriate planning and problem-solving activities are crucial requirements for the development of more powerful robotic systems. Traditional approaches to sensor interpretation, with their emphasis on geometric models, are of limited use for autonomous mobile robots operating in and exploring unknown and unstructured environments. Here, researchers present a new approach to robot perception that addresses such scenarios using a probabilistic tesselated representation of spatial information called the Occupancy Grid. The Occupancy Grid is a multi-dimensional random field that maintains stochastic estimates of the occupancy state of each cell in the grid. The cell estimates are obtained by interpreting incoming range readings using probabilistic models that capture the uncertainty in the spatial information provided by the sensor. A Bayesian estimation procedure allows the incremental updating of the map using readings taken from several sensors over multiple points of view. An overview of the Occupancy Grid framework is given, and its application to a number of problems in mobile robot mapping and navigation are illustrated. It is argued that a number of robotic problem-solving activities can be performed directly on the Occupancy Grid representation. Some parallels are drawn between operations on Occupancy Grids and related image processing operations.

Elfes, Alberto↗

DOE OSTI2026

Predicting multiphase flow and tracer transport for an underground chemical explosive test

Detecting radionuclide gas seepage from clandestine underground nuclear tests is central to nonproliferation explosion monitoring research. Yet, early-time (<6 day) gas transport driven by the explosive pressure wave remains poorly constrained due to scarcity of field data. We simulate multi-phase gas transport in the vadose zone using pre-shot data from a recent chemical explosion in P-Tunnel at the Nevada National Security Site, USA. Despite using a simplified 2D-radial model, predictions of tracer arrival matched observations within one order-of-magnitude. Our results show how transient blast forcing rapidly mobilizes gases from the cavity into surrounding rock – critical for optimizing sensor placement and test planning. This unique integration of field data and modeling represents a significant improvement in our ability to predict gas migration from underground explosions. More broadly, it offers insights into the coupled dynamics of pressure waves and contaminant transport in the vadose zone, with implications for monitoring and hazard assessment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

GEMINI Case Study

Sandia's GEMINI-Scout Mine Rescue Robot is an unmanned ground vehicle designed to enter potentially hazardous environments to explore, assess, and evaluate dangerous situations first responders may face when conducting a rescue mission. GEMINI is approximately four feet long and two feet tall, which enables the robot to maneuver through small locations on rough terrains caused by earthquakes, fires, or radiological incidents. GEMINI uses track propulsion to climb stairs, travel through gravel and sand pits, pivot in place, and traverse 45-degree climbs with few problems. Furthermore, the vehicle's dual tracked-chassis design allows it to operate in hostile, dark, muddy, high-temperature, and explosive debris-strewn environments, while maintaining efficient ground mobility. The mobility and modularity of the vehicle allow for easy integration of sensors to conduct gas and temperature sensing and offers pan/tilt, zoom color, and thermal camera video streaming capabilities. The vehicle is also able to carry a payload of about 50 pounds of batteries and can handle an additional 200 pounds of payload, whether for additional diagnostics, supplies, or clothing for those trapped in an effected area. GEMINI is remotely operated through a wireless connection and an onboard computer running a customized embedded control application, which directly communicates to all onboard components except for the audio and video systems. When line of sight is not possible, operators use a shockresistant fiber optic cable to ensure continuous functionality of the vehicle. This allows for direct local control of the vehicle, which streams collected data back to the operator for enhanced situational awareness. In addition, the vehicle incorporates safety features such as explosion proof housing to ensure safe electronic operations in hazardous gas or flooded environments; a four-channel video link and two-way audio to ensure located survivors can communicate with operators; and an MSHA-approved multi-gas sensor to monitor air quality.

42 ENGINEERING↗

NASA NTRS1988

Frequency-dependent dielectric analysis - Monitoring the chemistry and rheology of thermosets during cure

Frequency-dependent dielectric measurements in a curing resin sample were performed using an impedance analyzer and a permittivity sensor, to separate and measure the ionic (sigma) and dipolar (tau) mobilities, used as molecular probes of the cure reaction in the resin. The resin samples were tetraglycidyl 4,4-prime-diaminodiphenylmethane epoxy resins which included catalyzed (Hercules 3501-6) and uncatalyzed l3502 resin samples. The values of sigma and tau were used to quantitatively determine the viscosity, the degree of cure, and the T(g) of the resin. It is shown that the values of the Arrhenius and WLF constants during the cure process reflect the buildup of the crosslink network.

Kranbuehl, D.↗

NASA NTRS2000

Mechanical Abrasion as a Low Cost Technique for Contamination-Free Sample Acquisition from a Category IVA Clean Platform

The proposed Mars Sample Transfer Chain Architecture provides Planetary Protection Officers with clean samples that are required for the eventual release from confinement of the returned Martian samples. At the same time, absolute cleanliness and sterility requirement is not placed of any part of the Lander (including the deep drill), Mars Assent Vehicle (MAV), any part of the Orbiting Sample container (OS), Rover mobility platform, any part of the Minicorer, Robotic arm (including instrument sensors), and most of the caching equipment on the Rover. The removal of the strict requirements in excess of the Category IVa cleanliness (Pathfinder clean) is expected to lead to significant cost savings. The proposed architecture assumes that crosscontamination renders all surfaces in the vicinity of the rover(s) and the lander(s) contaminated. Thus, no accessible surface of Martian rocks and soil is Earth contamination free. As a result of the latter, only subsurface samples (either rock or soil) can be and will be collected for eventual return to Earth. Uncontaminated samples can be collected from a Category IVa clean platform. Both subsurface soil and rock samples can be maintained clean if they are collected by devices that are self-contained and clean and sterile inside only. The top layer of the sample is removed in a manner that does not contaminate the collection tools. Biobarrier (e.g., aluminum foil) covering the moving parts of these devices may be used as the only self removing bio-blanket that is required. The samples never leave the collection tools. The lids are placed on these tools inside the collection device. These single use tools with the lid and the sample inside are brought to Earth in the OS. The lids have to be designed impenetrable to the Earth organisms. The latter is a well established art.

Dolgin, B.↗

NASA NTRS1992

High-resolution terrain map from multiple sensor data

The authors present 3-D vision techniques for incrementally building an accurate 3-D representation of rugged terrain using multiple sensors. They have developed the locus method to model the rugged terrain. The locus method exploits sensor geometry to efficiently build a terrain representation from multiple sensor data. The locus method is used to estimate the vehicle position in the digital elevation map (DEM) by matching a sequence of range images with the DEM. Experimental results from large-scale real and synthetic terrains demonstrate the feasibility and power of the 3-D mapping techniques for rugged terrain. In real world experiments, a composite terrain map was built by merging 125 real range images. Using synthetic range images, a composite map of 150 m was produced from 159 images. With the proposed system, mobile robots operating in rugged environments can build accurate terrain models from multiple sensor data.

Kweon, In S.↗

DOE OSTI2021

Advanced Computing, Data Science, and Artificial Intelligence Research Opportunities for Energy-Focused Transportation Science

The Energy Efficient Mobility Systems (EEMS) technology landscape is complex and rapidly evolving, which provides both tremendous opportunities and formidable challenges. Significant alterations to the mobility landscape are underway due to the advent of vehicle and infrastructure connectivity, autonomous driving, and rapid passenger- and freight-vehicle electrification. Advanced computing will play an increasingly important role in enabling the EEMS program to understand and identify the most important levers to improve the energy productivity of future integrated mobility systems. It is also driving new approaches to mobility and the research to unlock an affordable, efficient, safe, and accessible transportation future. Driving much of this change is the collection, analysis, and strategic use of massive amounts of diverse, complex data from infrastructure and vehicles with on-board sensors and data storage and transmission capabilities. Diverse and representative data are key to implementing approaches to maximize mobility energy productivity. While high-fidelity modeling of integrated transportation networks has strengthened our understanding of dynamic movement and behavior patterns, existing tools must be expanded beyond their current focus. This work necessitates data infrastructure investments (e.g., secure-streaming data platforms driven by ubiquitous sensors and video analytics) as well as investments in critical capabilities for large-scale automated analysis and organization using modern machine learning, statistics, and artificial intelligence. Other chief needs include agile, large-scale storage that can be quickly searched and queried for relevant data to support validation and model development, data-sharing agreements, and formatting standards for key data types. The future of public transit must be explored in greater detail, research must inform design, and opportunities must be identified for improving the mobility productivity of public transit in both urban and rural America.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2002

Microgravity Investigation of Crew Reactions in 0-G (MICR0-G): Ground-Based Development Effort

This report describes the technology development of an advanced load sensor ground-based prototype and details the preliminary tests in microgravity during parabolic flights. The research effort is entitled, the Microgravity Investigation and Crew Reactions in 0-G (MICR0-G), a ground-based research effort funded by the National Aeronautics and Space Administration (NASA). The MICR0-G project was a follow-on to the Enhanced Dynamic Load Sensors (EDLS) spaceflight experiment flown on the Russian Space Station Mir. The technology development of the advanced load sensor prototype has been carried out by the Massachusetts Institute of Technology (MIT), with collaboration from Politecnico di Milano University and the Italian Space Agency (ASI). The key hardware of the advanced sensor prototype is a set of two types of load sensors - a hand-hold and foot restraints - similar in appearance to the mobility aids found in the Space Shuttle orbiter to assist the crew in moving inside the spacecraft, but able to measure the applied forces and moments about the x-, y-, and z- axes. The aim of Chapter 1 is to give a brief overview of the report contents. The first section summarizes the previous research efforts on astronaut-induced loads in microgravity. The second section provides information on the MICR0-G research project and the technology development work conducted at MIT. Section 1.3 details the motivation for designing a new generation of load sensors and describes the main enhancements and contributions of the MICR0-G advanced load sensors system compared to the EDLS system. Finally, the last section presents the outline of the report.

Newman, Dava J.↗

DOE OSTI2025

Surface Energy Balance System (SEBS) Instrument Handbook

A Surface Energy Balance System (SEBS) has been installed collocated with each deployed ECOR system at the Southern Great Plains (SGP), North Slope of Alaska (NSA), Tropical Western Pacific (TWP), ARM Mobile Facility 1 (AMF1), and ARM Mobile Facility 2 (AMF2). The surface energy balance system consists of upwelling and downwelling solar and infrared radiometers within one net radiometer, a wetness sensor, and soil measurements. The SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.

54 ENVIRONMENTAL SCIENCES↗