Results for “accident detection” — Page 6

NASA NTRS2004

Image Analysis via Fuzzy-Reasoning Approach: Prototype Applications at NASA

A set of imaging techniques based on Fuzzy Reasoning (FR) approach was built for NASA at Kennedy Space Center (KSC) to perform complex real-time visual-related safety prototype tasks, such as detection and tracking of moving Foreign Objects Debris (FOD) during the NASA Space Shuttle liftoff and visual anomaly detection on slidewires used in the emergency egress system for Space Shuttle at the launch pad. The system has also proved its prospective in enhancing X-ray images used to screen hard-covered items leading to a better visualization. The system capability was used as well during the imaging analysis of the Space Shuttle Columbia accident. These FR-based imaging techniques include novel proprietary adaptive image segmentation, image edge extraction, and image enhancement. Probabilistic Neural Network (PNN) scheme available from NeuroShell(TM) Classifier and optimized via Genetic Algorithm (GA) was also used along with this set of novel imaging techniques to add powerful learning and image classification capabilities. Prototype applications built using these techniques have received NASA Space Awards, including a Board Action Award, and are currently being filed for patents by NASA; they are being offered for commercialization through the Research Triangle Institute (RTI), an internationally recognized corporation in scientific research and technology development. Companies from different fields, including security, medical, text digitalization, and aerospace, are currently in the process of licensing these technologies from NASA.

Dominguez, Jesus A.↗

NASA NTRS2020

Honeywell Enhancing Airplane State Awareness (EASA) Project: Final Report on Refinement and Evaluation of Candidate Solutions for Airplane System State Awareness

The loss of pilot airplane state awareness (ASA) has been implicated as a factor in several aviation accidents identified by the Commercial Aviation Safety Team (CAST). These accidents were investigated to identify precursors to the loss of ASA and develop technologies to address the loss of ASA. Based on a gap analysis, two technologies were prototyped and assessed with a formative pilot-in-the-loop evaluation in NASA Langley’s full-motion Research Flight Deck. The technologies address: 1) data source anomaly detection in real-time, and 2) intelligent monitoring aids to provide nominal and predictive awareness of situations to be monitored and a mission timeline to visualize events of interest. The evaluation results indicated favorable impressions of both technologies for mitigating the loss of ASA in terms of operational utility, workload, acceptability, complexity, and usability. The team concludes that there is a feasible retrofit solution for improving ASA that would minimize certification risk, integration costs, and training impact.

Whitlow, Stephen D.↗

NASA NTRS1980

Aviation accidents and the theory of the situation

Social-psychological factors effecting the performance of flight crews are examined. In particular, a crew member's perceptual-psychological constructs of the flight situation (theories of the situation) are discussed. The skills and willingness of a flight crew to be alert to possible errors in the theory become critical to their effectiveness and their ability to ensure a safe flight. Several major factors that determine the likelihood that a faulty theory will be detected and revised are identified.

Bolman, L.↗

NASA NTRS2024

Testing of Advanced Capabilities to Enable In-time Safety Management and Assurance for Future Flight Operations

In order to refine an initial Concept of Operations, explore Concepts of Use, and expose/validate requirements for future In-Time Aviation Safety Management Systems (IASMS), testing architectures were created, along with a set of capabilities and underlying information exchange protocols. These systems were conceived and developed based on hazards associated with two envisioned urban area flight domains: (1) highly autonomous small uncrewed aerial systems (sUAS) operating at low altitudes, and (2) highly autonomous air taxis. The initial scope of this development is described in [1]; this report provides an update, focusing on the subsequent developments and test activities. As stated in [1], it is important to note that there are many capabilities already in use by the industry (or soon to be in use) that will play critical roles in future IASMS designs. Those reported here were developed to address a gap in the current state-of-the-art regarding specific hazards/risks, and/or to allow for investigation of the interplay between and across hazard types — particularly regarding how overall safety risk can be reduced or managed effectively. Results of testing and development activities are organized by the operational phase wherein a particular capability would be employed (i.e., preflight, in-flight, and post-flight/off-line). Pre-flight: A set of capabilities were developed to help mitigate safety risk prior to flight (e.g., during flight and mission planning). Results of testing summarize (1) validation activities to raise the Technology Readiness Level (TRL) and (2) evaluation activities where the capabilities were applied to flight/mission planning procedures and used by operators/pilots. For the latter, flight plans were automatically assessed, and operators/pilots were notified of hazardous flight segments so as to enable adjustment of the flight plan and re-evaluation, and/or to better inform go/no-go decisions. Capabilities addressed hazards associated with power consumption, third-party risk, wind, navigation system performance, radiofrequency interference, and proximity to geo-spatial threats (e.g., buildings, trees, and no-fly zones). In-flight: Flight experiments tested capabilities that detect and respond to hazards encountered during flight. In the first series, safety hazards were monitored and assessed onboard, and system-generated mitigation maneuvers were recorded (but not acted upon by the vehicle). In the second series, mitigation maneuver commands directed the aircraft in response to safety hazards (i.e., auto-mitigation). The sUAS used for testing is described in full, as is the test architecture, which included commercial avionics, research avionics, and onboard software designed to detect, assess, and respond to hazards. The onboard system was designed as a run-time assurance framework, consistent with [2] and supportive of both supervisory and automated modes. The primary functions included: real-time risk assessment (RTRA), auto-pilot monitoring, constraint monitoring, and contingency select/triggering. RTRA performs integrated risk assessment considering data from several hazard-related monitors (e.g., battery, motors, navigation, communications, population density, and loss-of-control). Post-flight/off-line: Data monitored and recorded during flights can enable IASMS capabilities that execute after flights have completed (or “off-line”). These include: (1) the ability to identify anomalies and trends that may only be observable when comparing data spanning a number of similar flights; (2) the ability to update and validate pre-flight and in-flight capabilities and any underlying models to improve their performance; (3) the ability to report anomalies/off-nominals that may indicate design changes or maintenance actions are needed; and (4) the ability for humans involved in operations to report safety-relevant observations to help in understanding the flight data and/or the operational context of a flight. Progress on three such capabilities is summarized; the first investigates anomaly detection given a limited set of flight logs and applies an approach previously used for space operations. The second explores what could be identified using a larger set of flight logs, including from web-based forums where flight logs are posted by sUAS autopilot users. The third creates a new means of collecting information on UAS incidents and accidents via the Aviation Safety Reporting System (ASRS).

sUAS↗

NASA NTRS2003

CFIT Prevention Using Synthetic Vision

In commercial aviation, over 30-percent of all fatal accidents worldwide are categorized as Controlled Flight Into Terrain (CFIT) accidents where a fully functioning airplane is inadvertently flown into the ground, water, or an obstacle. An experiment was conducted at NASA Langley Research Center investigating the presentation of a synthetic terrain database scene to the pilot on a Primary Flight Display (PFD). The major hypothesis for the experiment is that a synthetic vision system (SVS) will improve the pilot s ability to detect and avoid a potential CFIT compared to conventional flight instrumentation. All display conditions, including the baseline, contained a Terrain Awareness and Warning System (TAWS) and Vertical Situation Display (VSD) enhanced Navigation Display (ND). Sixteen pilots each flew 22 approach - departure maneuvers in Instrument Meteorological Conditions (IMC) to the terrain challenged Eagle County Regional Airport (EGE) in Colorado. For the final run, the flight guidance cues were altered such that the departure path went into the terrain. All pilots with a SVS enhanced PFD (12 of 16 pilots) noticed and avoided the potential CFIT situation. All of the pilots who flew the anomaly with the baseline display configuration (which included a TAWS and VSD enhanced ND) had a CFIT event.

Arthur, Jarvis J., III↗

NASA NTRS1995

Technology for Safer Skies

The Bendix RDR-4B airborne weather radar, developed by Allied Signal Commercial Avionic Systems, is the product of a decade-long Federal Aviation Administration (FAA)/NASA/industry/academia research program. Numerous aircraft accidents had occurred because of windshear, a sudden shift in wind direction and velocity. A characteristic of windshear is the microburst, a column of air which cools rapidly in a thunderstorm and generates intense downdrafts. Microbursts can cause an airplane to lose lift and speed and then crash. A Congressional Mandate to the FAA launched the program with NASA to develop the essential technology for detecting and avoiding microbursts. Langley Research Center developed microburst sensors, including Doppler microwave radar, which sends a radio wave ahead of the aircraft to measure windshear velocity. These predictions give pilots time to prepare for the microbursts. After flight tests and the design of certification standards, the FAA required all commercial aircraft to install some type of windshear detector or predictor.

Source record↗

NASA NTRSDate not supplied

Detecting Risk and Anomalies in Airplane Dynamics Through Entropic Analysis of Time Series Data

Despite recent efforts to move away from traditional threshold exceedance detection methods for aircraft state monitoring, modern aircraft still rely on safety thresholds to communicate to pilots the identification of an anomaly in the aircraft when a threshold is surpassed. Current anomaly detection methods mainly depend on uninterpretable machine learning models to learn complex patterns and relationships contained in the time series data of aircraft. Although these methods are capable of identifying known anomalies, their deficiency in interpretability presents a challenge when translating them to different aircraft. To overcome this deficiency, entropic analysis of aircraft dynamics seeks to characterize the complexity, or lack thereof, of the aircraft dynamics prior to the development of a risk scenario. This complexity characterization provides a more straightforward summary of state changes in the dynamics of flight variables. To build a foundation for entropic analysis, we analyzed the complexity of unstable approaches, an anomalous event present in many of today’s aviation accidents. The analysis revealed a statistically significant difference in the complexity distribution of flight variables under a stable approach versus an unstable approach. These differences in complexity were especially notable minutes before an approach was identified as unstable. Moreover, the multiscale entropic analysis revealed the presence of signal complexity at multiple time scales across multiple time windows before landing. By capturing state changes and corrections in the aircraft dynamics using entropy, advanced, yet still interpretable, sensor systems based on entropic frameworks from this study can be constructed in the future using classical machine learning approaches.

Risk detection↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRS1983

Summary Proceedings of a Wind Shear Workshop

A number of recent program results and current issues were addressed: the data collection phase of the highly successful Joint Airport Weather Study (JAWS) Project and the NASA-B5f7B Gust Gradient Program, the use of these data for flight crew training through educational programs (e.g., films) and with manned flight training simulators, methods for post-accident determination of wind conditions from flight data recorders, the microburst wind shear phenomenon which was positively measured and described the ring vortex as a possible generating mechanism, the optimum flight procedure for use during an unexpected wind shear encounter, evaluation of the low-level wind shear alert system (LLWSAS), and assessment of the demonstrated and viable application of Doppler radar as an operational wind shear warning and detection system.

Enders, J. H.↗

NASA NTRS2003

Patent foramen ovale and paradoxical systemic embolism: a bibliographic review

A patent foramen ovale (PFO) has been reported to be an important risk factor for cardioembolic cerebrovascular accidents through paradoxical systemic embolization, and it provides one potential mechanism for the paradoxical systemic embolization of venous gas bubbles produced after altitude or hyperbaric decompressions. Here, we present in a single document a summary of the original findings and views from authors in this field. It is a comprehensive review of 145 peer-reviewed journal articles related to PFO that is intended to encourage reflection on PFO detection methods and on the possible association between PFO and stroke. There is a heightened debate on whether aviators, astronauts, and scuba divers should go through screening for PFO. Because it is a source of an important controversy, we prefer to present the findings in the format of a neutral bibliographic review independent of our own opinions. Each cited peer-reviewed article includes a short summary in which we attempt to present potential parallels with the pathophysiology of decompression bubbles. Two types of articles are summarized, as follows. First, we report the original clinical and physiological findings which focus on PFO. The consistent reporting sequence begins by describing the method of detection of PFO and goal of the study, followed by bulleted results, and finally the discussion and conclusion. Second, we summarize from review papers the issues related only to PFO. At the end of each section, an abstract with concluding remarks based on the cited articles provides guidelines.

NASA Discipline Environmental Health↗

NASA NTRS2024

BLAYER User Guide

Estimation of boundary layer edge or thickness is an essential aspect of utilizing high fidelity aerothermodynamic flow solutions. For viscous flow over a flat plate, the boundary layer thickness is usually defined as the distance from the wall at which the flow velocity (zero at the wall) has increased through some profile to 99% or 99.5% of the free stream velocity. In real gas flows over aerospace vehicles, a total enthalpy profile is employed for edge calculations. The importance of knowing boundary layer thickness and its relation to possible transition from laminar to turbulent flow is illustrated by Space Shuttle mission STS-114, when the appearance of tile gap filler protrusions on the nose was deemed serious enough that a crew member was called upon to exit the vehicle and remove the potential threat prior to its descent from orbit. The BLAYER utility used as part of post-processing Orion/MPCV flow solutions is a generalization of the earlier BLAYER_RESULTS utility developed following the STS-107 Columbia accident. BLAYER handles a variable number of gas species (not just 5), allows for more than one temperature and for optional extra flow quantities, and omits optional handling of Orbiter tile datasets.

momentum thicknes↗

NASA NTRS2006

Nondestructive Evaluation of Foam Insulation on the Space Shuttle External Tank

Foam loss on the External Tank (ET) during launch can be caused by a number of factors. Voids are the best understood mechanism of foam loss, although it is known that delaminations, cracks and crushed foam can also lead to liberation of foam. Shortly after the Columbia accident, work began on non-destructive evaluation of foam targeted at finding voids and delaminations. After several months of searching for candidate methods capable of inspecting ET foam, the five most promising techniques were taken through a blind test and narrowed down to two methods to develop and use for inspection of the ET. These methods were backscatter radiography and terahertz imaging. The backscatter radiography system measures a test part by detecting Compton backscattered x-ray energy generated by a collimated beam of x-rays directed at the test subject. This collimated beam is scanned across the subject, recording scatter intensity data one pixel at a time until the area of interest is covered. The resulting data can be used to generate an image similar to a radiograph. Some depth information can be gathered utilizing apertures or collimation on the detectors. The detectors are located around the collimated source, making this a single sided inspection. The void detection limit with the currently utilized system is around 0.5 inches in diameter by 0.2 inches high. The terahertz imaging system inspects a test part by utilizing a transceiver to emit a pulse focused at the aluminum skin of the ET, which reflects it back to the transceiver where it is analyzed. The transceiver is scanned across the area of interest until a measurement has been taken at every location. Amplitude, time delay and frequency content are examined to note any discontinuities which may be the result of a void or other type of defect. The pulse currently utilized is in the millimeter wave regime. The void detection limit with this system is around 0.5 inches in diameter by 0.2 inches high. With increased interest in other causes of foam loss following the flight of Discovery in July 2005, laser shearography was added to the techniques used for inspecting ET foam. The shearography method records a sheared image of a laser speckle pattern projected on a test part before And after some sort of excitation. The resultant fringe pattern allows the slope of the out of plane displacement to be measured. For crushed and delaminated foam applications, a non-contact air coupled acoustic force is used to excite the surface of the foam. Regions without defects tend to respond differently to the sound energy than do regions with defects, generating a map of the foam integrity. Foam crushed to a depth of about 0.1 inches is detectable with shearography even after it has relaxed to its original shape.

Richter, Joel↗

NASA NTRS1997

Background contamination by coplanar polychlorinated biphenyls (PCBs) in trace level high resolution gas chromatography/high resolution mass spectrometry (HRGC/HRMS) analytical procedures

The addition of the "dioxin-like" polychlorinated biphenyl (PCB) congeners to the assessment of risk associated with the 2,3,7,8-chlorine substituted dioxins and furans has dramatically increased the number of laboratories worldwide that are developing analytical procedures for their detection and quantitation. Most of these procedures are based on established sample preparation and analytical techniques employing high resolution gas chromatography/high resolution mass spectrometry (HRGC/HRMS), which are used for the analyses of dioxin/furans at low parts-per-trillion (ppt) levels. A significant and widespread problem that arises when using these sample preparation procedures for the analysis of coplanar PCBs is the presence of background levels of these congeners. Industrial processes, urban incineration, leaking electrical transformers, hazardous waste accidents, and improper waste disposal practices have released appreciable quantities of PCBs into the environment. This contamination has resulted in the global distribution of these compounds via the atmosphere and their ubiquitous presence in ambient air. The background presence of these compounds in method blanks must be addressed when determining the exact concentrations of these and other congeners in environmental samples. In this study reliable procedures were developed to accurately define these background levels and assess their variability over the course of the study. The background subtraction procedures developed and employed increase the probability that the values reported accurately represent the concentrations found in the samples and were not biased due to this background contamination.

Polychlorinated Biphenyls/analysis/metabolism↗

NASA NTRS1991

Measurement and modification of the EEG and related behavior

Electrophysiological changes in the sensorimotor pathways were found to accompany the effect of rhythmic EEG patterns in the sensorimotor cortex. Additionally, several striking behavioral changes were seen, including in particular an enhancement of sleep and an elevation of seizure threshold to epileptogenic agents. This raised the possibility that human seizure disorders might be influenced therapeutically by similar training. Our objective in human EEG feedback training became not only the facilitation of normal rhythmic patterns, but also the suppression of abnormal activity, thus requiring complex contingencies directed to the normalization of the sensorimotor EEG. To achieve this, a multicomponent frequency analysis was developed to extract and separate normal and abnormal elements of the EEG signal. Each of these elements was transduced to a specific component of a visual display system, and these were combined through logic circuits to present the subject with a symbolic display. Variable criteria provided for the gradual shaping of EEG elements towards the desired normal pattern. Some 50-70% of patients with poorly controlled seizure disorders experienced therapeutic benefits from this approach in our laboratory, and subsequently in many others. A more recent application of this approach to the modification of human brain function in our lab has been directed to the dichotomous problems of task overload and underload in the contemporary aviation environment. At least 70% of all aviation accidents have been attributed to the impact of these kinds of problems on crew performance. The use of EEG in this context has required many technical innovations and the application of the latest advances in EEG signal analysis. Our first goal has been the identification of relevant EEG characteristics. Additionally, we have developed a portable recording and analysis system for application in this context. Findings from laboratory and in-flight studies suggest that we will be able to detect appropriate changes in brain function, and feed this information to on-board computers for modification of mission requirements and/or crew status.

Sterman, M. B.↗

NASA NTRS1996

Second International Airborne Remote Sensing Conference and Exhibition

The conference provided four days of displays and scientific presentations on applications, technology, a science of sub-orbital data gathering and analysis. The twelve displayed aircraft equipped with sophisticated instrumentation represented a wide range of environmental and reconnaissance missions,including marine pollution control, fire detection, Open Skies Treaty verification, thermal mapping, hydrographical measurements, military research, ecological and agricultural observations, geophysical research, atmospheric and meterological observations, and aerial photography. The U.S. Air Force and the On-Site Inspection Agency displayed the new Open Skies Treaty verification Boeing OC 135B that promotes international monitoring of military forces and activities. SRl's Jetstream uses foliage and ground penetrating SAR for forest inventories, toxic waste delineation, and concealed target and buried unexploded ordnance detection. Earth Search Sciences's Gulfstream 1 with prototype miniaturized airborne hyperspectral imaging equipment specializes in accurate mineral differentiation, low-cost hydrocarbon exploration, and nonproliferation applications. John E. Chance and the U.S. Army Corps of Engineers displayed the Bell 2 helicopter with SHOALS that performs hydrographic surveying of navigation projects, coastal environment assessment, and nautical charting surveys. Bechtel Nevada and U.S. DOE displayed both the Beech King AIR B-200 platform equipped to provide first response to nuclear accidents and routine environmental surveillance, and the MBB BO-105 helicopter used in spectral analysis for environmental assessment and military appraisal. NASA Ames Research Center's high-altitude Lockheed ER-2 assists in earth resources monitoring research in atmospheric chemistry, oceanography, and electronic sensors; ozone and greenhouse studies and satellite calibration and data validation. Ames also showcased the Learjet 24 Airborne Observatory that completed missions in Venus cloud cover analysis, Quadantid meteor shower studies, extra-solar far infrared ionic structure lines measurement, Cape Kennedy launch support, and studies in air pollution, The Products and Services Exhibit showcased new sensor and image processing technologies, aircraft data collection services, unmanned vehicle technology, platform equipment, turn-key services, software a workstations, GPS services, publications, and processing and integration systems by 58 exhibitors. The participation of aircraft users and crews provided unique dialogue between those who plan data collection a operate the remote sensing technology, and those who supply the data processing and integration equipment. Research results using hyperspectral imagery, radar and optical sensors, lidar, digital aerial photography, a integrated systems were presented. Major research and development programs and campaigns we reviewed, including CNR's LARA Project and European Space Agency's 1991-1995 Airborne Campaign. The pre-conference short courses addressed airborne video, photogrammetry, hyperspectral data analysis, digital orthophotography, imagery and GIS integration, IFSAR, GPS, and spectrometer calibration.

Source record↗

NASA NTRS1977

NASA's aviation safety research and technology program

Aviation safety is challenged by the practical necessity of compromising inherent factors of design, environment, and operation. If accidents are to be avoided these factors must be controlled to a degree not often required by other transport modes. The operational problems which challenge safety seem to occur most often in the interfaces within and between the design, the environment, and operations where mismatches occur due to ignorance or lack of sufficient understanding of these interactions. Under this report the following topics are summarized: (1) The nature of operating problems, (2) NASA aviation safety research, (3) clear air turbulence characterization and prediction, (4) CAT detection, (5) Measurement of Atmospheric Turbulence (MAT) Program, (6) Lightning, (7) Thunderstorm gust fronts, (8) Aircraft ground operating problems, (9) Aircraft fire technology, (10) Crashworthiness research, (11) Aircraft wake vortex hazard research, and (12) Aviation safety reporting system.

Fichtl, G. H.↗