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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Fiber optic sensor technology - An opportunity for smart aerospace structures

Fiber optic sensors provide the opportunity for fabricating materials with internal sensors which can serve as lifetime health monitors, analogous to a central nervous system. The embedded fiber optic sensors can be interrogated by various techniques to measure internal strain, temperature, pressure, acoustic waves and other parameters indicative of structural integrity. Experiments have been conducted with composite samples with embedded sensors to measure strain using optical time domain reflectometry, modal interference and an optical phase locked loop. Fiber optic sensors have been developed to detect acoustic emission and impact damage and have been demonstrated for cure monitoring. These sensors have the potential for lifetime monitoring of structural properties, providing real time nondestructive evaluation.

Heyman, J. S.↗
NASA NTRS2006

Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

One of the responsibilities of the NASA Glenn Principal Investigator Microgravity Services is to support NASA sponsored investigators in the area of reduced-gravity acceleration data analysis, interpretation and the monitoring of the reduced-gravity environment on-board various carriers. With the International Space Station currently operational, a significant amount of acceleration data is being down-linked and processed on ground for both the space station onboard environment characterization (and verification) and scientific experiments. Therefore, to help principal investigator teams monitor the acceleration level on-board the International Space Station to avoid undesirable impact on their experiment, when possible, the NASA Glenn Principal Investigator Microgravity Services developed an artificial intelligence monitoring system, which detects in near real time any change in the environment susceptible to affect onboard experiments. The main objective of the monitoring system is to help research teams identify the vibratory disturbances that are active at any instant of time onboard the International Space Station that might impact the environment in which their experiment is being conducted. The monitoring system allows any space research scientist, at any location and at any time, to see the current acceleration level on-board the Space Station via the World Wide Web. From the NASA Glenn s Exploration Systems Division web site, research scientists can see in near real time the active disturbances, such as pumps, fans, compressor, crew exercise, re-boost, extra-vehicular activity, etc., and decide whether or not to continue operating or stopping (or making note of such activity for later correlation with science results) their experiments based on the g-level associated with that specific event. A dynamic graphical display accessible via the World Wide Web shows the status of all the vibratory disturbance activities with their degree of confidence as well as their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗
NASA NTRS1992

NCC Simulation Model: Simulating the operations of the network control center, phase 2

The simulation of the network control center (NCC) is in the second phase of development. This phase seeks to further develop the work performed in phase one. Phase one concentrated on the computer systems and interconnecting network. The focus of phase two will be the implementation of the network message dialogues and the resources controlled by the NCC. These resources are requested, initiated, monitored and analyzed via network messages. In the NCC network messages are presented in the form of packets that are routed across the network. These packets are generated, encoded, decoded and processed by the network host processors that generate and service the message traffic on the network that connects these hosts. As a result, the message traffic is used to characterize the work done by the NCC and the connected network. Phase one of the model development represented the NCC as a network of bi-directional single server queues and message generating sources. The generators represented the external segment processors. The served based queues represented the host processors. The NCC model consists of the internal and external processors which generate message traffic on the network that links these hosts. To fully realize the objective of phase two it is necessary to identify and model the processes in each internal processor. These processes live in the operating system of the internal host computers and handle tasks such as high speed message exchanging, ISN and NFE interface, event monitoring, network monitoring, and message logging. Inter process communication is achieved through the operating system facilities. The overall performance of the host is determined by its ability to service messages generated by both internal and external processors.

Benjamin, Norman M.↗
DOE OSTI2026

Alpha-Imaging Detector System Development for Large Area Monitoring

Effective management and disposal of legacy nuclear waste are essential for ensuring safe work environments and minimizing environmental impacts. Monitoring airborne actinide contamination is particularly critical due to the high internal dose potential of alpha-emitting radionuclides. Traditional continuous air monitoring systems (CAMs) used in the industry are limited in the volume of air they can sample, potentially leading to inaccurate radiation detection over large areas. For example, in 2018, elevated levels of airborne Plutonium-239 were detected beyond the controlled areas of the Hanford Plutonium Finishing Plant, highlighting the potential risks to both plant workers and nearby residents. To address these challenges, high-efficiency particulate absorbing (HEPA) air purifiers can enhance air flow by up to 1.5 orders of magnitude, thereby increasing monitoring efficiency and providing a cost-effective solution for large-area surveillance. To quantify the activities of alpha-emitting radionuclides on HEPA filters, the Savannah River National Laboratory is developing an advanced alpha-imaging detection system. This system includes scintillating materials combined with a digital scientific camera. A significant concern in operating such a large-area airborne monitoring system is the handling of HEPA filters, which may be contaminated with radioactive particles. To mitigate these hazards, it is crucial to ensure that any contamination is securely fixed onto the filters. Efforts have been made to optimize the sensitivity of scintillator-epoxy composites and apply them to HEPA filters. These materials were characterized using fluoroscence spectroscopy. These techniques confirmed the purity of the raw materials, the dispersion of scintillators in the epoxy matrix, and the stability of their optical and structural properties post-modification. The optimal scintillator-epoxy composite was selected for use on alpha-spiked HEPA filters to evaluate the efficiency of the sprayer. HEPA filters, embedded with alpha particles collected by an air purifier deployed in an airborne radiation area, have been tested to assess detection efficiency. Future work will focus on employing multiple imaging sensors simultaneously to enhance sensitivity across different regions of the HEPA filter.

Pham, Phuong [Savannah River National Laboratory (↗
NASA NTRS1992

Observation of Stratospheric Ozone with NIES Lidar System in Tsukuba, Japan

Lidars are expected to play important roles in an international monitoring network of the stratosphere such as the Network for the Detection of Stratospheric Change (NDSC). The National Institute for Environmental Studies (NIES) in Tsukuba constructed an ozone lidar system in March 1988 and started observation in August 1988. The lidar system has a 2-m telescope and injection locked XeCl and XeF excimer lasers which can measure ozone profiles (15-45 km) and temperature profiles (30-80 km). From December 1991, lidar observations have been carried out in which the second Stokes line of the stimulated Raman scattering of a KrF laser has been used. Ozone profiles obtained with the NIES lidar system are compared with the data provided by the SAGE II satellite sensor. Results showed good agreement for the individual and the zonal mean profiles. Variations of ozone with various time scales at each altitude can be studied using the data obtained with the NIES ozone lidar system. Seasonal variations are easily found at 20 km, 30 km, and 35 km, which are qualitatively understood as a result of dynamical and photochemical effects. Systematic errors of ozone profiles due to the Pinatubo stratospheric aerosols have been detected using multi-wavelength observation.

Nakane, H.↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments.

Iverson, David L.↗
DOE OSTI2020

Success Using A Granular-Activated Carbon Filtration Swab to Rehabilitate Westbay{sup R} Multi-level Groundwater Monitoring Wells at the INL - 20544

In November 2015, tetrachloroethylene (PCE) was discovered in groundwater samples collected from a Westbay{sup R} multi-level groundwater monitoring well at the Idaho National Laboratory (INL).a Subsequent investigation determined that PCE was not present in the groundwater. The detected PCE was instead due to inadvertent contamination of the internal tubing fluid in the Westbay well-monitoring system, which is isolated from the surrounding groundwater. Further investigation showed that three of the 11 Westbay wells at the INL contained PCE-contaminated tubing fluid at concentrations above the U.S. Environmental Protection Agency's maximum contaminant level for drinking water (5 μg/L). Loose sediment at the bottom of some Westbay wells was also found to contain PCE; the three wells were then identified for rehabilitation as part of the INL well maintenance program. The unique construction of the Westbay wells - i.e., the small diameter (5.72 cm [2.25 in.]) and the depths of the tubing fluid ranging from 144.8 to 419 m (475 to 1,376 ft) below ground surface - posed unique challenges to the rehabilitation. Because the tubing fluid provides structural integrity, the fluid cannot be removed and then replaced without damaging the integrity of the Westbay well. Additionally, the small diameter of the systems and the associated depths limit the availability of equipment that can be used for the rehabilitation. After an evaluation of potential methods, it was determined that the use of an in-well, custom-fabricated, granular-activated-carbon filtration swab deployed via a wire line would provide the safest and most cost-effective method for rehabilitation. Westbay well rehabilitation started at well MIDDLE-2051 in late June 2018 and paused in December 2018 for the season. The PCE concentration in the tubing fluid at MIDDLE-2051 was initially reduced to a maximum concentration of 3.81 μg/L from a maximum of 642 μg/L, while the concentration of PCE in the sediment had been reduced from 5,360 to 2,270 μg/kg. Sampling was performed at MIDDLE-2051 again in August 2019, and the tubing fluid increased to a maximum concentration of 45.4 μg/L, while the concentration in the sediment decreased further to 1,890 μg/kg due to desorption of PCE from the sediment to the tubing fluid. Rehabilitation resumed at well MIDDLE-2050A in late August 2019, and the PCE concentration in the tubing fluid had been reduced to a maximum concentration of 19.0 μg/L. Although the method has been shown to be time-consuming, it has proven to be effective and safe for personnel performing the work and to the integrity of the well. Future sample data results at all wells will help determine an estimated completion of the rehabilitation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2010

SERVIR: The Regional Visualization and Monitoring System

This slide presentation reviews the SERVIR program. SERVIR is a partnership between NASA and USAID and three international nodes: Central America, Africa, and the Himalaya region. SERVIR,using satellite observations and ground based observations, is used by decision makers to allow for improved monitoring of air quality, extreme weather, biodiversity, and changes in land cove and has also been used to respond to environmental threats, such as wildfires, floods, landslides, harmful algal blooms, and earthquakes.

Irwin, Daniel E.↗
NASA NTRS2012

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, spacecraft vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery

Space Propulsion↗
DOE OSTI2022

Monitoring Fracture Saturation With Internal Seismic Sources and Twin Neural Networks

Seismic coda-wave analysis is a well-developed method for detecting subtle physical changes in complex media by measuring arrival times in the late-arriving energy from multiply scattered or reflected waves. However, a challenge arises when multiply scattered waves are not sufficiently separated in time from the direct arrivals to provide a clear coda wave train. Additional complications for monitoring changes in fracture systems arise when the signals originate from unsynchronized internal sources, such as natural or induced seismicity, from acoustic emission, or from transportable intra-fracture sources (chattering dust), that generate uncontrolled signals that vary in arrival time, amplitude and frequency content. Here, we use a twin neural network (TNN also known as a Siamese neural network) for dimensionality reduction to analyze signals from chattering dust to classify the fluid saturation state of a synthetic fracture system. The TNN with shared weights generates a low-dimensional representation of the data input by minimizing contrastive loss, serving as the input to a multiclass classifier that accurately classifies whether multiple fractures in a fracture system are fully saturated or partially saturated, or whether a change in saturation has occurred in different fractures in the system. Furthermore, these results show that information buried in unresolved codas from uncontrolled sources can be extracted using machine learning to monitor the evolution of fracture systems caused by physical and chemical processes even when the scattered and direct wave fields overlap.

58 GEOSCIENCES↗
DOE OSTI2022

Data for Monitoring Fracture Saturation with Internal Transportable Seismic Sources and Twin Neural Networks

Seismic coda-wave analysis is a well-developed method for detecting subtle physical changes in complex media by measuring arrival times in the late-arriving energy from multiply-scattered or reflected waves. However, a challenge arises when multiply-scattered waves are not sufficiently separated in time from the direct arrivals to provide a clear coda wave train. Additional complications for monitoring changes in fracture systems arise when the signals originate from unsynchronized internal sources, such as natural induced seismicity, from acoustic emission, or from transportable intra-fracture sources (chattering dust), that generate uncontrolled signals that vary in arrival time, amplitude and frequency content. Here, we use a twin neural network (also known as a Siamese neural network) for dimensionality reduction to analyze signals from chattering dust to classify the fluid saturation state of a synthetic fracture system. The twin neural network with shared weights generates a low-dimensional representation of the data input by minimizing contrastive loss, serving as the input to a multiclass classifier that accurately classifies whether multiple fractures in a fracture system are fully saturated or partially saturated, or whether a change in saturation has occurred in different fractures in the system. These results show that information buried in unresolved codas from uncontrolled sources can be extracted using machine learning to monitor the evolution of fracture systems caused by physical and chemical processes even when the scattered and direct wave fields overlap.

58 GEOSCIENCES↗
NASA NTRS1973

Monitor for physical property changes in solid propellants

Specially designed sensor is attached to or imbedded in propellant. When sensor is driven into vibration, it moves with a phase lag directly proportional to internal friction or loss coefficent. Resonance frequency of the system is related to Young's modulus. Modulus or internal friction can be monitored over long period of time.

Black, R. E., Jr.↗
NASA NTRS1988

Temperature Pill

Ingestible Thermal Monitoring System was developed at Johns Hopkins University as means of getting internal temperature readings for treatments of such emergency conditions as dangerously low (hypothermia) and dangerously high (hyperthermia) body temperatures. ITMS's accuracy is off no more than one hundredth of a degree and provides the only means of obtaining deep body temperature. System has additional applicability in fertility monitoring and some aspects of surgery, critical care obstetrics, metabolic disease treatment, gerontology (aging) and food processing research. Three-quarter inch silicone capsule contains telemetry system, micro battery, and a quartz crystal temperature sensor inserted vaginally, rectally, or swallowed.

Source record↗
NASA NTRS1984

Control of Self-Replicating Systems

Three concepts proposed for system management and control. Concepts are: internal system for autonomous management and control, separate system for environment monitoring, and optical intelligent system required in especially chaotic environments. Intelligent system responds by making decisions and solving problems in novel situations preprogramed.

Von Tiesenhausen, G.↗
NASA NTRS2003

Evaluation of Critical Care Monitor Technology During the US Navy Strong Angel Exercise

The NASA critical path road map identifies "trauma and acute medical problems" as a clinical capability risk category (http://criticalDath.isc.nasa.gov). Specific risks include major trauma, organ laceration or contusion, hemoperitoneum, pulmonary failure, pneumo- and hemothorax, burn, open bone fracture, blunt head trauma, and penetrating injury. Mitigation of these risks includes the capability for critical care monitoring. Currently, the International Space Station (ISS) Crew Health Care System (CHeCS) does not provide such a capability. The Clinical Space Medicine Strategic Planning Forum (4/8/97), sponsored by NASA Medical Operations, identified the development of trauma care capabilities as one of the top priorities for space medicine. The Clinical Care Capability Development Project (CCCDP) subsequently undertook the task to address this need.

Johannesen, John↗
NASA NTRS2005

Flight Test Evaluation of Situation Awareness Benefits of Integrated Synthetic Vision System Technology f or Commercial Aircraft

Research was conducted onboard a Gulfstream G-V aircraft to evaluate integrated Synthetic Vision System concepts during flight tests over a 6-week period at the Wallops Flight Facility and Reno/Tahoe International Airport. The NASA Synthetic Vision System incorporates database integrity monitoring, runway incursion prevention alerting, surface maps, enhanced vision sensors, and advanced pathway guidance and synthetic terrain presentation. The paper details the goals and objectives of the flight test with a focus on the situation awareness benefits of integrating synthetic vision system enabling technologies for commercial aircraft.

Prinzel, Lawrence J., III↗
NASA NTRS2014

Spaceflight Microbiology: Benefits for Long Duration Spaceflight and Our Understanding of Microorganisms on Earth

Spaceflight microbiology is composed of both operational and experimental components that complement each other in our understanding of microbial interactions and their responses in the microgravity of spaceflight. Operationally, efforts to mitigate microbiological risk to the crew and the spacecraft have historically focused on minimizing the number of detectable organisms, relying heavily on preventative measures, including appropriate vehicle design, crew quarantine prior to flight, and stringent microbial monitoring. Preflight monitoring targets have included the astronauts, spaceflight foods, potable water systems, the vehicle air and surfaces, and the cargo carried aboard the spacecraft. This approach has been very successful for earlier missions; however, the construction and long-term habitation of the International Space Station (ISS) has created the need for additional inflight monitoring of the environment and potable water systems using hardware designed for both in-flight microbial enumeration and sample collection and return to Earth. In addition to operational activities, the ISS is providing a research platform to advance our understanding of microbiomes in the built environment. Adding to the research possibilities of this system are multiple reports of unique changes in microbial gene expression and phenotypic responses, including virulence and biofilm formation, in response to spaceflight culture. The tremendous potential of the ISS research platform led the National Research Council to recommend that NASA utilize the ISS as a microbial observatory. Collectively, the findings from operational and research activities on the ISS are expected to both enable future space exploration and translate to basic and applied research on Earth.

Ott, C. Mark↗
NASA NTRS1990

Reaction control system/remote manipulator system automation

The objectives of this project is to evaluate the capability of the Procedural Reasoning System (PRS) in a typical real-time space shuttle application and to assess its potential for use in the Space Station Freedom. PRS, developed by SRI International, is a result of research in automating the monitoring and control of spacecraft systems. The particular application selected for the present work is the automation of malfunction handling procedures for the Shuttle Remote Manipulator System (SRMS). The SRMS malfunction procedures will be encoded within the PRS framework, a crew interface appropriate to the RMS application will be developed, and the real-time data interface software developed. The resulting PRS will then be integrated with the high-fidelity On-orbit Simulation of the NASA Johnson Space Center's System Engineering Simulator, and tests under various SRMS fault scenarios will be conducted.

Hiers, Harry K.↗