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At least 109 records · Page 6

Comparison of Two Methodologies for Calibrating Satellite Instruments in the Visible and Near Infrared

Traditionally, satellite instruments that measure Earth-reflected solar radiation in the visible and near infrared wavelength regions have been calibrated for radiance response in a two-step method. In the first step, the spectral response of the instrument is determined using a nearly monochromatic light source, such a lamp-illuminated monochromator. Such sources only provide a relative spectral response (RSR) for the instrument, since they do not act as calibrated sources of light nor do they typically fill the field-of-view of the instrument. In the second step, the instrument views a calibrated source of broadband light, such as lamp-illuminated integrating sphere. In the traditional method, the RSR and the sphere spectral radiance are combined and, with the instrument's response, determine the absolute spectral radiance responsivity of the instrument. More recently, an absolute calibration system using widely tunable monochromatic laser systems has been developed, Using these sources, the absolute spectral responsivity (ASR) of an instrument can be determined on a wavelength-hy-wavelength basis. From these monochromatic ASRs. the responses of the instrument bands to broadband radiance sources can be calculated directly, eliminating the need for calibrated broadband light sources such as integrating spheres. Here we describe the laser-based calibration and the traditional broad-band source-based calibration of the NPP VIIRS sensor, and compare the derived calibration coefficients for the instrument. Finally, we evaluate the impact of the new calibration approach on the on-orbit performance of the sensor.

Barnes, Robert A.↗

Causal Factors and Adverse Events of Aviation Accidents and Incidents Related to Integrated Vehicle Health Management

Causal factors in aviation accidents and incidents related to system/component failure/malfunction (SCFM) were examined for Federal Aviation Regulation Parts 121 and 135 operations to establish future requirements for the NASA Aviation Safety Program s Integrated Vehicle Health Management (IVHM) Project. Data analyzed includes National Transportation Safety Board (NSTB) accident data (1988 to 2003), Federal Aviation Administration (FAA) incident data (1988 to 2003), and Aviation Safety Reporting System (ASRS) incident data (1993 to 2008). Failure modes and effects analyses were examined to identify possible modes of SCFM. A table of potential adverse conditions was developed to help evaluate IVHM research technologies. Tables present details of specific SCFM for the incidents and accidents. Of the 370 NTSB accidents affected by SCFM, 48 percent involved the engine or fuel system, and 31 percent involved landing gear or hydraulic failure and malfunctions. A total of 35 percent of all SCFM accidents were caused by improper maintenance. Of the 7732 FAA database incidents affected by SCFM, 33 percent involved landing gear or hydraulics, and 33 percent involved the engine and fuel system. The most frequent SCFM found in ASRS were turbine engine, pressurization system, hydraulic main system, flight management system/flight management computer, and engine. Because the IVHM Project does not address maintenance issues, and landing gear and hydraulic systems accidents are usually not fatal, the focus of research should be those SCFMs that occur in the engine/fuel and flight control/structures systems as well as power systems.

Reveley, Mary S.↗

Analysis of Aviation Safety Reporting System Incident Data Associated With the Technical Challenges of the Vehicle Systems Safety Technology Project

This analysis was conducted to support the Vehicle Systems Safety Technology (VSST) Project of the Aviation Safety Program (AVsP) milestone VSST4.2.1.01, "Identification of VSST-Related Trends." In particular, this is a review of incident data from the NASA Aviation Safety Reporting System (ASRS). The following three VSST-related technical challenges (TCs) were the focus of the incidents searched in the ASRS database: (1) Vechicle health assurance, (2) Effective crew-system interactions and decisions in all conditions; and (3) Aircraft loss of control prevention, mitigation, and recovery.

Withrow, Colleen A.↗

An Analysis of the Role of Safety Nets in the National Airspace System

Safe operations of aircraft in the National Airspace System (NAS) may be attributed to many factors, including the application of a variety of safety nets (SNs) as a last line of defense. In preparation for the Next Generation Air Transportation System (NextGen), a review of Aviation Safety Reporting System (ASRS) reports for incidents with positive outcomes was conducted to investigate the importance of current safety nets. The examination of positive outcomes not only shows what went wrong, but also what went right to prevent accidents and “save the day.” More than 400 incident reports for 2015 from the voluntary ASRS reporting database were studied in detail to create event sequence diagrams (ESDs), illustrating the effectiveness of SNs. The developed ESDs are considered top-level, representative models and are limited with respect to being reliably quantitative because they are based on only reports from a single year. The ESDs could offer insights into human systems integration research, such as strategically using technologies as SNs without human interface or alleviating human workload with new technologies to provide resilient recovery from off-nominal conditions ensuring flight safety.

Geuther, Steven↗

Reports of Resilient Performance: Investigating Operators' Descriptions of Safety-producing Behaviors in the Aviation Safety Reporting System

While many existing taxonomies and frameworks provide a common vocabulary for describing how human operators fail in the context of sociotechnical systems, at present, there is no common vocabulary to describe how humans succeed. Such a framework would facilitate systematically collecting and analyzing data on how human performance can produce safety, not just how it can reduce safety. One potentially rich source of currently available information for exploring desired performance is the reports submitted to NASA’s Aviation Safety Reporting System (ASRS). These de-identified, confidential, and voluntary narrative reports are submitted by pilots, controllers, ground operators, and others within aviation operations. While these reports are primarily submitted to describe safety risks, incidents, and problems, they also often describe how those risks were mitigated, and provide a window into aspects of everyday work in aviation. This paper describes an analysis of ASRS narratives to understand how operators talk about their own resilient behaviors during adverse safety conditions and events. Guided by Erik Hollnagel’s Resilience Assessment Grid framework (i.e., anticipate, monitor, respond, learn), we illustrate our approach and methodology with examples from reports. We also highlight some of the challenges and how further research is needed in developing a taxonomy of operators’ descriptions of resilient performance.

resilient behaviors↗

Perceive: Proactive Exploration of Risky Concept Emergence for Identifying Vulnerabilities & Exposures

National databases that collect various kinds of textual threat reports such as ASRS, CERT, and NVD manually process their reports individually. They then offer data products to disseminate the aggregate information, like newsletters, alerts or individual report searching. The goal of this research is to connect these individual reports thematically and temporally to identify emerging or recurring threats, by analyzing large collections of text, source code, collaboration and communication patterns. This capability, I argue, enables us to identify the emergence and recurrence of such themes, and the contexts in which they re-occur, facilitating faster and more capable mitigation. I propose two models to shed light on this goal: An empirical model of vulnerabilities as bugs, the commit flow model, and one of the vulnerabilities and aviation safety threats as topics, the topic flow model. I use as gold standard existing manual workflows in both domains, reflected in the existing data products by these organizations, and empirically evaluate if the automated model scan match or outperform existing manual practices.

ASRS↗

Chapter 5: Climate Science

Biological and Environmental Research (BER) conducts climate science research activities under three programs: the Atmospheric Radiation Measurement (ARM) user facility, the Atmospheric System Research (ASR) program, ad the Earth and Environmental Systems Modeling (EESM) program. This document provides key findings and recommendations from the Biological and Environmental Research Advisory Committee (BERAC) Climate Science Working Group.

Biological and Environmental Research Advisory Com↗

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically Air Traffic Control System Command Center (ATCSCC) planning telecon audio transcriptions. The ATCSCC hosts bi-hourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. Provided speech transcripts, ITN is the process of converting unformatted raw Automated Speaker Recognition (ASR) model transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a fine-tuned Bidirectional Encoder Representations from Transformers neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With an overall Punctuation Error Rate (PER) of 25.56 and Word Error Rate with Punctuation and Capitalization (WER PC) of 5.47, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

ATM↗

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically Air Traffic Control System Command Center (ATCSCC) planning telecon audio transcriptions. The ATCSCC hosts bi-hourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. Provided speech transcripts, ITN is the process of converting unformatted raw Automated Speaker Recognition (ASR) model transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a fine-tuned Bidirectional Encoder Representations from Transformers neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With an overall Punctuation Error Rate (PER) of 25.56 and Word Error Rate with Punctuation and Capitalization (WER PC) of 5.47, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

ATM↗

Kaona: Deep Searching and Curating Data from Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given to augmenting existing processes for mining these safety reporting system databases. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety database mining activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using publicly available NASA’s ASRS narratives and another using publicly available C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

ASRS↗

Kaona: Deep Searching and Curating Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗

Kaona: Deep Searching and Curating Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗

NASA aviation safety reporting system

The study deals with 165 inadvertent operations on or into inappropriate portions of the aircraft areas at controlled airports. Pilot-initiated and controller-initiated incursions are described and discussed. It was found that a majority of the pilot-initiated occurrences involved operation without a clearance; controller-initiated occurrences usually involved failure to maintain assured separation. The factors associated with these occurrences are analyzed. It appears that a major problem in these occurrences is inadequate coordination among the various system participants. Reasons for this, and some possible solutions to various aspects of the problem, are discussed. A sample of reports from pilots and controllers is presented. These relate to undesired occurrences in air transport, general aviation, and air traffic control operations; to ATC coordination problems; and to a recurrent problem in ASRS reports, parachuting operations. A sample of alert bulletins and responses to them is presented.

Source record↗

NASA Aviation Safety Reporting System

A comprehensive study of near midair collisions in terminal airspace, derived from the ASRS database is presented. A selection of controller and pilot reports on airport perimeter security, unauthorized takeoffs and landings, and on winter operations is presented. A sampling of typical Alert Bulletins and their responses is presented.

Source record↗

An investigation of reports of Controlled Flight Toward Terrain (CFTT)

Some 258 reports from more than 23,000 documents in the files of the Aviation Safety Reporting System (ASRS) were found to be to the hazard of flight into terrain with no prior awareness by the crew of impending disaster. Examination of the reports indicate that human error was a casual factor in 64% of the incidents in which some threat of terrain conflict was experienced. Approximately two-thirds of the human errors were attributed to controllers, the most common discrepancy being a radar vector below the Minimum Vector Altitude (MVA). Errors by pilots were of a much diverse nature and include a few instances of gross deviations from their assigned altitudes. The ground proximity warning system and the minimum safe altitude warning equipment were the initial recovery factor in some 18 serious incidents and were apparently the sole warning in six reported instances which otherwise would most probably have ended in disaster.

Porter, R. F.↗

Operational problems experienced by single pilots in instrument meteorological conditions

The development and implementation of a search strategy to extract pertinent reports from the Aviation Safety Reporting System-2 (ASRS-2) database are described. For any particular occurence to be pertinent to the study, it must have satisfied the following conditions: the aircraft must be of the type usually flown by a single pilot; operation on an IFR flight plan in instrument meteorological conditions; pilot experienced an operational problem. The occurances consist of reports by the pilot about his own performance, by the pilot about the system performance, or by an air traffic controller about a pilot's performance.

Weislogel, S.↗

A summary and integration of research concerning single pilot IFR operational problems

A review of seven research studies pertaining to Single Pilot IFR (SPIFR) operations was performed. Two studies were based on questionnaire surveys; two based on National Transportation Safety Board (NTSB) reports; two were based on Aviation Safety Reporting System (ASRS) incident reports, and one report used event analysis and statistics to forecast problems. The results obtained in each study were extracted and integrated. Results were synthesized and key issues pertaining to SPIFR operations problems were identified. The research that was recommended by the studies and that addressed the key issues is catalogued for each key issue.

Chapman, G. C.↗

Analysis of general aviation single-pilot IFR incident data obtained from the NASA Aviation Safety Reporting System

An analysis of incident data obtained from the NASA Aviation Safety Reporting System (ASRS) has been made to determine the problem areas in general aviation single-pilot IFR (SPIFR) operations. The Aviation Safety Reporting System data base is a compilation of voluntary reports of incidents from any person who has observed or been involved in an occurrence which was believed to have posed a threat to flight safety. This paper examines only those reported incidents specifically related to general aviation single-pilot IFR operations. The frequency of occurrence of factors related to the incidents was the criterion used to define significant problem areas and, hence, to suggest where research is needed. The data was cataloged into one of five major problem areas: (1) controller judgment and response problems, (2) pilot judgment and response problems, (3) air traffic control (ATC) intrafacility and interfacility conflicts, (4) ATC and pilot communication problems, and (5) IFR-VFR conflicts. In addition, several points common to all or most of the problems were observed and reported. These included human error, communications, procedures and rules, and work load.

Bergeron, H. P.↗