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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Self-activating System and Method for Alerting When an Object or a Person is Left Unattended

A system and method use a wireless tether comprising a transmitter and a receiver to alert a caregiver that an object has been left unattended. A detector senses the presence of the object, usually a child, located in a position such as a safety seat. The detector is operatively coupled to the transmitter. which is located near the object. The transmitter transmits at least one wireless signal when the object is in the position. The receiver, which is remotely located from the transmitter, senses at least one signal as long as the receiver is within a prescribed range of transmission. By performing a timing function, the receiver monitors the proximity of the caregiver, who maintains possession of the receiver, to the transmitter. The system communicates an alarm to the caregiver when the caregiver ventures outside the range of transmission without having removed the object from the position.

Edwards, William C.↗
NASA NTRS2019

ISEP: A Joint SRAG/CCMC Collaboration to Improve Mitigation of Space Weather Effects on Crew Health in the Exo-LEO Era

The Space Radiation Analysis Group (SRAG) at Johnson Space Center (JSC) is tasked with monitoring changes to space weather and mitigating any resultant impacts to crew health and safety. As human spaceflight goals extend from Low-Earth Orbit (LEO) missions like the International Space Station (ISS) to the moon, Mars and beyond, SRAG will need to update their current approach for crew monitoring of and protection from radiation exposure due to energetic Solar Particle Events (ESPEs). Challenges faced in planning exo-LEO missions include the lack of protection from the Earth’s geomagnetic field employed by the ISS in addition to limited communication capability between the crew and the ground. In the event of an ESPE, the current ISS trajectory ensures that the vehicle is only traveling through fields of higher radiation exposure for a brief period of time; the Earth’s geomagnetic field prevents the penetration of the high-energy particles of concern throughout the majority of the orbit. Exo-LEO missions, on the other hand, require that the vehicle travel through free space, exposing vehicle and crew to the full impact of the ESPE. NASA has combined multiple approaches to resolve this radiation exposure issue. New vehicles are designed to take advantage of advances in particle transport modeling capabilities and shielding technology, allowing redistribution of mass throughout the vehicle to areas of thinner shielding when the energetic particle flux has increased to levels of concern. Although vehicle shielding is an important aspect of radiation exposure protection, there is a continued requirement to monitor and predict the space weather environment. To this end, SRAG maintains a console position in Mission Control with 24/7 mission support capability. In the event of increased solar activity, SRAG collaborates with the Flight Control Team (FCT) to determine if crew action (i.e., shelter) is required. During any increase in solar activity, the FCT needs three pieces of information to effectively decide the crew response in light of other required mission tasks: if an event (ESPE) will occur, how ‘intense’ an observed event will be, and how long will an observed event will last. An ideal alert system limits false alarms, therefore causing the crew to take action unnecessarily, without ignoring events that pose a hazard to the crew. SRAG’s current operational concept for ISS missions focuses on short-term forecasts, best described as ‘now-casting’. Console operators are in daily communication with the Space Weather Prediction Center (SWPC) for situational awareness purposes. When conditions exist that may lead to increased solar activity, operators receive notifications from SWPC. In the case of a well-connected ESPE, the console operator may only have on the order of minutes to several hours to notify the FCT of the event and provide a recommendation for crew action. As NASA shifts to exo-LEO missions, the increased time in free space as well as the reduced ability to communicate with the crew will force a transition in crew protection strategy that emphasizes improvments to both the accuracy and the lead time in forecasting capabilities.

Barzilla, Janet E.↗
NASA NTRSDate not supplied

Space Biofilms - Phenotypic and Transcriptomic Behaviour of Pseudomonas Aeruginosa Biofilms on Board the International Space Station

Bacterial biofilms in space can have a positive or negative impact on the success of a mission. For example, in some instances, biofilms can improve plant growth, facilitate synthesis/recovery of metals from regolith, or bioremediate wastewater. On the other hand, biofilms can deteriorate or cause malfunctions of spaceflight hardware. Biofilms have been found on the wastewater tank of the Environmental Control and Life Support System (ECLSS), which poses a risk to the system. Even more alarming, some biofilms cause infections that may threaten astronauts’ health, like urinary tract infections that if left unclear could cause permanent damage to the kidneys. Given that biofilms can contribute to or hinder the efforts of space exploration, it is necessary to understand the effects of microgravity on biofilm behaviour. The Space Biofilms experiment intends to contribute to such understanding by analysing the morphology and transcriptomic profiles of Pseudomonas aeruginosa PA14 biofilms grown in spaceflight compared to matched ground controls. P. aeruginosa biofilms were grown onboard the International Space Station for 1, 2, or 3 days at 37°C over six surface materials: Stainless Steel 316 (SS316), passivated SS316, and a novel Lubricant Impregnated Surface (LIS) were grown in rich media supplemented with potassium nitrate (LBK) to simulate wastewater. While cellulose membrane, catheter grade silicone, and silicone with special nanotopography (DLIP) were grown in modified Artificial Urine Media supplemented with glucose and high phosphate (mAUMg-hi Pi) to simulate urine. Asynchronous ground controls replicated spaceflight procedures. Morphology analysis revealed that flight samples had a significant decrease in mass, thickness and surface area coverage in LBK. Additionally, biofilm surface coverage on LIS was only 11% of the equivalent samples on SS316 (p<0.001). Associated preliminary transcriptomic data will also be addressed.

Pamela Flores↗
NASA NTRS1989

Neural computing for numeric-to-symbolic conversion in control systems

A type of neural network, the multilayer perceptron, is used to classify numeric data and assign appropriate symbols to various classes. This numeric-to-symbolic conversion results in a type of information extraction, which is similar to what is called data reduction in pattern recognition. The use of the neural network as a numeric-to-symbolic converter is introduced, its application in autonomous control is discussed, and several applications are studied. The perceptron is used as a numeric-to-symbolic converter for a discrete-event system controller supervising a continuous variable dynamic system. It is also shown how the perceptron can implement fault trees, which provide useful information (alarms) in a biological system and information for failure diagnosis and control purposes in an aircraft example.

Passino, Kevin M.↗
NASA NTRS1980

A study of the comparative performance of six lightning warning systems

An analysis of mining explosive accident reports indicates a need for clear and ample warning of approaching electrical storms to reduce injuries/fatalities due to lightning induced premature detonation. Six lightning warning devices were comparatively evaluated at three test sites. The devices tested were: (1) flash counter, (2) corona point, (3) radioactive probe, (4) field mill, (5) azimuth/range locator, and (6) triangulation locator. The test sites were chosen to provide system evaluation under varied thunderstorm conditions. The devices were tested at San Antonio, Texas, Kennedy Space Center, Florida and Langmuir Laboratory, New Mexico. Comparative performance is reviewed in terms of alarm reliability, false alarm, and failure to alarm probabilities. Lightning warning system requirements and methods of relating warning criteria to explosive hazard are discussed.

Johnson, R. L.↗
NASA NTRS2007

A Small Angle Scattering Sensor System for the Characterization of Combustion Generated Particulate

One of the critical issues for the US space program is fire safety of the space station and future launch vehicles. A detailed understanding of the scattering signatures of particulate is essential for the development of a false alarm free fire detection system. This paper describes advanced optical instrumentation developed and applied for fire detection. The system is being designed to determine four important physical properties of disperse fractal aggregates and particulates including size distribution, number density, refractive indices, and fractal dimension. Combustion generated particulate are the primary detection target; however, in order to discriminate from other particulate, non-combustion generated particles should also be characterized. The angular scattering signature is measured and analyzed using two photon optical laser scattering. The Rayleigh-Debye-Gans (R-D-G) scattering theory for disperse fractal aggregates is utilized. The system consists of a pulsed laser module, detection module and data acquisition system and software to analyze the signals. The theory and applications are described.

Feikema, Douglas A.↗
NASA NTRS1980

A command and data subsystem for deep space exploration based on the RCA 1802 microprocessor in a distributed configuration

The Command and Data Subsystem (CDS) is an RCA 1802microprocessor based subsystem that acts as the central nervous system for the Galileo Orbiter Spacecraft. All communication between the ground and spacecraft flows through the CDS. The CDS also distributes commands in real time, algorithmetrically expanded from a data base loaded from the ground and in response to spacecraft alarms. The distributed microprocessor system is configured as a redundant set of hardware with three microprocessors on each half. The microprocessors are surrounded by a group of special purpose hardware components which greatly enhance the ability of the software to perform its task. It is shown how the software architecture makes a distributed system of six microprocessors appear to each user as a single virtual machine, and collectively as a set of cooperating virtual machines that prevent the simultaneous presence of the several users from interfering destructively with each other.

Thomas, J. S.↗
NASA NTRSDate not supplied

On the Prediction of Surface Melt Over the Greenland Ice Sheet at NWP and S2S Timescales

Greenland surface melt “events” – encompassing large swaths of the ice sheet over approximately 4-10 day periods – have occurred with increasing frequency in the 21st Century. Surface processes are significant to the ice sheet’s overall contribution to sea level. In addition, the sudden onset of widespread surface melt produces hazardous conditions for researchers and for communities adjacent to the ice sheet. The mechanisms producing melt events, their associated large-scale forcing, and timescales of interest are highly variable and poorly understood. Here we examine the predictability of melt events in a numerical weather prediction system (NWP) and a subseasonal-to-seasonal system (S2S). The NASA Global Modeling and Assimilation Office forward processing (GMAO-FP) is an NWP system that incorporates an evolving, global hybrid 4D ensemble–variational (4DEnVar) data assimilation system and a state-of-the-art model that is run twice-daily with forecasts out to five and ten days. The GMAO S2S system is a hindcast-anomaly, coupled-model prediction system initialized with an atmospheric analysis, and in situ and satellite ocean data assimilation. Both systems represent ice sheet surface hydrology and snowpack processes. We examine the performance of the systems over the period 2018-2023, a span that includes approximately nine significant events, against analyses and satellite-derived melt extent. In addition to extent, we examine related conditions and their role in the melt forecast, including the onset of both omega and Rex atmospheric blocking patterns, sea surface temperatures, sea ice extent, water vapor transport, precipitation, and surface preconditioning. We further examine the tendency for false-alarm events in each system and assess reasons for the forecast performance. North Atlantic atmospheric blocking patterns leading to surface melt are well forecast by the NWP system out to around eight days, while the S2S system generally underestimates the magnitude of such events at monthly lead times. These systems suggest that while short term forecasts of ice sheet melt and melt events are relatively robust, S2S predictions of surface conditions are highly dependent on the ability of a coupled system to generate the short-term atmospheric conditions associated with surface melt events.

Richard Cullather↗
NASA NTRS1994

Aided targeting system simulation evaluation

Simulation research was conducted at the Crew Station Research and Development Facility on the effectiveness and ease of use of three targeting systems. A manual system required the aviator to scan a target array area with a simulated second generation forward looking infrared (FLIR) sensor, locate and categorize targets, and construct a target hand-off list. The interface between the aviator and the system was like that of an advanced scout helicopter (manual mode). Two aided systems detected and categorized targets automatically. One system used only the FLIR sensor and the second used FLIR fused with Longbow radar. The interface for both was like that of an advanced scout helicopter aided mode. Exposure time while performing the task was reduced substantially with the aided systems, with no loss of target hand-off list accuracy. The fused sensor system showed lower time to construct the target hand-off list and a slightly lower false alarm rate than the other systems. A number of issues regarding system sensitivity and criterion, and operator interface design are discussed.

Demaio, Joe↗
NASA NTRS2007

NASA Tech Briefs, December 2007

Topics include: Ka-Band TWT High-Efficiency Power Combiner for High-Rate Data Transmission; Reusable, Extensible High-Level Data-Distribution Concept; Processing Satellite Imagery To Detect Waste Tire Piles; Monitoring by Use of Clusters of Sensor-Data Vectors; Circuit and Method for Communication Over DC Power Line; Switched Band-Pass Filters for Adaptive Transceivers; Noncoherent DTTLs for Symbol Synchronization; High-Voltage Power Supply With Fast Rise and Fall Times; Waveguide Calibrator for Multi-Element Probe Calibration; Four-Way Ka-Band Power Combiner; Loss-of-Control-Inhibitor Systems for Aircraft; Improved Underwater Excitation-Emission Matrix Fluorometer; Metrology Camera System Using Two-Color Interferometry; Design and Fabrication of High-Efficiency CMOS/CCD Imagers; Foam Core Shielding for Spacecraft CHEM-Based Self-Deploying Planetary Storage Tanks Sequestration of Single-Walled Carbon Nanotubes in a Polymer PPC750 Performance Monitor Application-Program-Installer Builder Using Visual Odometry to Estimate Position and Attitude Design and Data Management System Simple, Script-Based Science Processing Archive Automated Rocket Propulsion Test Management Online Remote Sensing Interface Fusing Image Data for Calculating Position of an Object Implementation of a Point Algorithm for Real-Time Convex Optimization Handling Input and Output for COAMPS Modeling and Grid Generation of Iced Airfoils Automated Identification of Nucleotide Sequences Balloon Design Software Rocket Science 101 Interactive Educational Program Creep Forming of Carbon-Reinforced Ceramic-Matrix Composites Dog-Bone Horns for Piezoelectric Ultrasonic/Sonic Actuators Benchtop Detection of Proteins Recombinant Collagenlike Proteins Remote Sensing of Parasitic Nematodes in Plants Direct Coupling From WGM Resonator Disks to Photodetectors Using Digital Radiography To Image Liquid Nitrogen in Voids Multiple-Parameter, Low-False-Alarm Fire-Detection Systems Mosaic-Detector-Based Fluorescence Spectral Imager Plasmoid Thruster for High Specific-Impulse Propulsion Analysis Method for Quantifying Vehicle Design Goals Improved Tracking of Targets by Cameras on a Mars Rover Sample Caching Subsystem Multistage Passive Cooler for Spaceborne Instruments GVIPS Models and Software Stowable Energy-Absorbing Rocker-Bogie Suspensions

Source record↗
NASA NTRSDate not supplied

A New ML-Based Adaptive Thinning Methodology to Improve the Impact of AIRS and CrIS Assimilation on Global Tropical Cyclone Forecasts

This work builds on previous research performed by this team to improve the forecast of Tropical Cyclones (TCs) by assimilating AIRS and CrIS radiances into the NASA Global Earth Observing System (GEOS). Past published work demonstrated that the assimilation of radiances with variable density was beneficial to TC forecasting in the GEOS. In the previous setup, a fixed-size moving square named 'TC domain' was activated by the so-called TC-vitals, an international real-time message accessible to all NWP forecasting centers, that documents the existence of a TC, its estimated position, and its size. The information from TC-vitals activated a switch in the GEOS, which allowed to reduce the distance used for thinning AIRS and CrIS data inside a 15 degrees by 15 degrees moving TC domain centered on the storm, so that more data were assimilated in the vicinity of the TC during its lifetime. The methodology produced improved TC analyses and led to better forecasts, particularly related to intensity, without damaging the global forecast skill. In the new version, the adaptive thinning methodology is based on a machine-learning technique. The technique searches for TCs and creates TC masks by using cloud-top temperatures from all geostationary satellites without the need for additional information. It is being trained against the International Best Track Archive for Climate Stewardship (IBTrACS) data base. Once a TC mask is created, a switch identical to the one used in the previous adaptive thinning method is activated, allowing the GEOS to ingest more data in the TC-shaped size-changing domain that follows the storm. As of today, the team has been able to successfully assimilate data inside the ML-detected TC domains. Future work includes an improved capability of reducing false alarm rates (i.e., cloud systems that are erroneously labeled as TCs).

Oreste Reale↗
NASA NTRS1985

Frequency-Discriminating Acoustic-Event Counter

Broadband events rejected. Acoustic-event counter discriminates against signals that simultaneously exceed preset amplitude thresholds in both low and high-frequency bands of its spectrum. Counter acts as spectral analyzer for mechanical vibrations. In combination with broadband acoustic transducer discriminates between signals and noise in acoustical destructive or nondestructive testing, vibration monitoring for machinery, burglar alarms, and other monitoring/warning systems.

Sugg, F. E.↗
NASA NTRSDate not supplied

Multi-Class Anomaly Detection in Flight Data using Semi-Supervised Explainable Deep Learning Model

Identifying precursor for safety incidents in aviation data is a crucial task, yet extremely challenging. The main approach, in practice, leverages domain expertise to define expected tolerances in system’s behavior and alarm exceedance from such safety margins. However, this approach is incapable of identifying unknown risk and vulnerabilities. Machine learning has been long studied and deployed to identify precursors for such anomalies, with the great challenge of the need for sufficient labelled set of data to achieve a reliable and accurate performance. In this article, we develop an explainable deep semi-supervised model for anomaly detection in aviation, building upon recent advancements in the machine learning literature. The proposed model combines feature engineering and classification in the feature space, while leveraging all available data (labelled and unlabeled). Validating on two case studies of anomaly detection in take-off and landing phases of commercial aircraft, we show that our model is able to outperform state-of-the-art supervised anomaly detection model and reach significantly high accuracy and low false alarm with minimum amount of available labelled data.

Anomaly Detection↗
NASA NTRS2003

"Smoke": Characterization Of Smoke Particulate For Spacecraft Fire Detection

The "Smoke" experiment is a flight definition investigation that seeks to increase our understanding of spacecraft fire detection through measurements of particulate size distributions of preignition smokes from typical spacecraft materials. Owing to the catastrophic risk posed by even a very small fire in a spacecraft, the design goal for spacecraft fire detection is to detect the fire as quickly as possible, preferably in the preignition phase before a real flaming fire has developed. Consequently the target smoke for detection is typically not soot (typical of established hydrocarbon fires) but instead, pyrolysis products, and recondensed polymer particles. At the same time, false alarms are extremely costly as the crew and the ground team must respond quickly to every alarm. The U.S. Space Shuttle (STS: Space Transportation System) and the International Space Station (ISS) both use smoke detection as the primary means of fire detection. These two systems were designed in the absence of any data concerning low-gravity smoke particle (and background dust) size distributions. The STS system uses an ionization detector coupled with a sampling pump and the ISS system is a forward light scattering detector operating in the near IR. These two systems have significantly different sensitivities with the ionization detector being most sensitive (on a mass concentration basis) to smaller particulate and the light scattering detector being most sensitive to particulate that is larger than 1 micron. Since any smoke detection system has inherent size sensitivity characteristics, proper design of future smoke detection systems will require an understanding of the background and alarm particle size distributions that can be expected in a space environment.

Urban, David L.↗
NASA NTRS2003

Thanksgiving Hocus Pocus

I was managing the construction project, and I thought my biggest challenge was simply finishing the work in time for start of the holiday shopping season. The store opened three weeks before Thanksgiving. Everything looked great. Business picked up steadily as the serious spending season approached. Then, two days before Thanksgiving, disaster struck. The fire protection system was designed to prevent smoke and fire from reaching the merchandise. If a fire alarm went off anywhere in the building, the system went into a massive pressurization mode. Dampers would open and the system would pump in hundreds of cubic feet of air from outside into the store, pressurizing every square foot, preventing fire or smoke from spreading into the store. That night an unknown event tripped the alarm-and it sounded for six hours. The air conditioning system was still operational as the outside air temperatures had been warm all month. That night, however, temperatures plummeted to 20 degrees. With an alarm sounding in a building complex that covers many millions of square feet, no one paid attention to the cold air flowing into the space. Pipes froze and burst. Hundreds of gallons of water came down through the drywall, soaking merchandise, the carpet and the hardwood racks. This state of the art system, which had been designed to protect, was now responsible for unthinkable damage. You could be the among greatest project managers in world, but if you have an attitude and you give the client heartburn, unnecessary heartburn, you're not going to do more work with him. If you have a disaster like this one, and you manage to make everybody feel good and believe that you are going to take care of them, then everybody looks back on it and says, "You know what, this is a good project team; we work well together, so let's do another one."

Zazzali, Christian↗
NASA NTRS1989

Causal simulation and sensor planning in predictive monitoring

Two issues are addressed which arise in the task of detecting anomalous behavior in complex systems with numerous sensor channels: how to adjust alarm thresholds dynamically, within the changing operating context of the system, and how to utilize sensors selectively, so that nominal operation can be verified reliably without processing a prohibitive amount of sensor data. The approach involves simulation of a causal model of the system, which provides information on expected sensor values, and on dependencies between predicted events, useful in assessing the relative importance of events so that sensor resources can be allocated effectively. The potential applicability of this work to the execution monitoring of robot task plans is briefly discussed.

Doyle, Richard J.↗
NASA NTRS2018

Efficient Runtime Verification of First-Order Temporal Properties

Runtime verification allows monitoring the execution of a system against a temporal property, raising an alarm if the property is violated. In this paper we present a theory and system for runtime verification of a first-order past time linear temporal logic. The first-order nature of the logic allows a monitor to reason about events with data elements. While runtime verification of propositional temporal logic requires only a fixed amount of memory, the first-order variant has to deal with a number of data values potentially growing unbounded in the length of the execution trace. This requires special compactness considerations in order to allow checking very long executions. In previous work we presented an efficient use of BDDs for such first-order runtime verification, implemented in the tool DEJAVU. We first summarize this previous work. Subsequently, we look at the new problem of dynamically identifying when data observed in the past are no longer needed, allowing to reclaim the data elements used to represent them. We also study the problem of adding relations over data values. Finally, we present parts of the implementation, including a new concept of user defined property macros.

Peled, Doron↗
NASA NTRS2000

Aircraft Conflict Analysis and Real-Time Conflict Probing Using Probabilistic Trajectory Modeling

Methods for maintaining separation between aircraft in the current airspace system have been built from a foundation of structured routes and evolved procedures. However, as the airspace becomes more congested and the chance of failures or operational error become more problematic, automated conflict alerting systems have been proposed to help provide decision support and to serve as traffic monitoring aids. The problem of conflict detection and resolution has been tackled from a number of different ways, but in this thesis, it is recast as a problem of prediction in the presence of uncertainties. Much of the focus is concentrated on the errors and uncertainties from the working trajectory model used to estimate future aircraft positions. The more accurate the prediction, the more likely an ideal (no false alarms, no missed detections) alerting system can be designed. Additional insights into the problem were brought forth by a review of current operational and developmental approaches found in the literature. An iterative, trial and error approach to threshold design was identified. When examined from a probabilistic perspective, the threshold parameters were found to be a surrogate to probabilistic performance measures. To overcome the limitations in the current iterative design method, a new direct approach is presented where the performance measures are directly computed and used to perform the alerting decisions. The methodology is shown to handle complex encounter situations (3-D, multi-aircraft, multi-intent, with uncertainties) with relative ease. Utilizing a Monte Carlo approach, a method was devised to perform the probabilistic computations in near realtime. Not only does this greatly increase the method's potential as an analytical tool, but it also opens up the possibility for use as a real-time conflict alerting probe. A prototype alerting logic was developed and has been utilized in several NASA Ames Research Center experimental studies.

Yang, Lee C.↗