Results for “confidential reporting”

NASA NTRS2008

Patterns of Error in Confidential Maintenance Incident Reports

Confidential reports of maintenance incidents are a valuable source of information on maintenance errors and the contexts within which they occur. NASA's Aviation Safety Reporting System (ASRS) has been receiving an increasing number of maintenance incident reports since a specialized maintenance reporting form was introduced in 1996. In a series of studies, the database of ASRS maintenance incidents was examined using correspondence analysis, a statistical technique that converts complex data tables into a visual form. The analyses revealed patterns within the ASRS data set that would have otherwise been difficult to detect. The results have implications for a range of purposes including human factors training, the design of procedures, and the identification of improvements in aircraft design.

Hobbs, Alan↗

NASA NTRS2021

Positive Train Control (PTC) Study: An Analysis of PTC-Related Reports Submitted to the Confidential Close Call Reporting System (C3RS)

A supplemental analysis of reports submitted to the voluntary Confidential Close Call Reporting System (C3RS) was conducted to identify the potential operational risks associated with the integration and operation of Positive Train Control (PTC) systems. This study identified four areas that may merit further investigation by FRA and rail carriers: System/Paperwork synchronization, training, PTC acceptance, and alerting mechanisms.

C3RS↗

NASA NTRS1996

Early Warning: Development of Confidential Incident Reporting Systems

Accidents hardly ever happen without warning. The combination, or sequence, of failures and mistakes that cause an accident may indeed be unique but the individual failures and mistakes rarely are. In the USA in 1974 the crews on two different aircraft misunderstood the same aeronautical chart and descended towards their destination dangerously early towards a mountain. The first crew were in good weather conditions and could see the mountain and resolved their misinterpretation of the chart. The second crew six weeks later were not so lucky. In cloud they had no clues to point out their mistake nor the presence of the mountain. The resulting crash and the ensuing inquiry, which brought to light the previous incident, shocked the country but gave it the impetus to instigate a safety reporting system. This system eventually became the NASA's Aviation Safety Reporting System (ASRS). The programme collects incident reports from pilots, controllers, mechanics, cabin attendants and many others involved in aviation operations. By disseminating this safety information the ASRS has helped enormously to give US airlines and airspace the highest safety standards. Accident prevention is a goal sought by everyone in the aviation industry and establishing effective incident reporting programmes can go a long way toward achieving that goal. This article will describe the steps and issues required to establish an incident reporting system. The authors summarize the lessons learned from the ASRS, now in its twentieth year of operation and from the Confidential Human Factors Reporting (HER) Programme run by British Airways, an airline that is a recognized world leader in safety reporting and analysis. The differences between government and airline operation of confidential safety reporting systems will be addressed.

OLeary, Mike J.↗

NASA NTRS1945

Summary of Airfoil Data

Recent airfoil data for both flight and wind-tunnel tests have been collected and correlated insofar as possible. The flight data consist largely of drag measurements made by the wake-survey method. Most of the data on airfoil section characteristics were obtained in the Langley two-dimensional low-turbulence pressure tunnel. Detail data necessary for the application of NACA 6-serles airfoils to wing design are presented in supplementary figures, together with recent data for the NACA 24-, 44-, and 230-series airfoils. The general methods used to derive the basic thickness forms for NACA 6- and 7-series airfoils and their corresponding pressure distributions are presented. Data and methods are given for rapidly obtaining the approximate pressure distributions for NACA four-digit, five-digit, 6-, and 7-series airfoils. The report includes an analysis of the lift, drag, pitching-moment, and critical-speed characteristics of the airfoils, together with a discussion of the effects of surface conditions. Available data on high-lift devices are presented. Problems associated with lateral-control devices, leading-edge air intakes, and interference are briefly discussed. The data indicate that the effects of surface condition on the lift and drag characteristics are at least as large as the effects of the airfoil shape and must be considered in airfoil selection and the prediction of wing characteristics. Airfoils permitting extensive laminar flow, such as the NACA 6-series airfoils, have much lower drag coefficients at high speed and cruising lift coefficients than earlier types-of airfoils if, and only if, the wing surfaces are sufficiently smooth and fair. The NACA 6-series airfoils also have favorable critical-speed characteristics and do not appear to present unusual problems associated with the application of high-lift and lateral-control devices. Much of the data given in the NACA Advance Confidential Report entitled "Preliminary Low-Drag-Airfoil and Flap Data from Tests at Large Reynolds Number and Low Turbulence," by Eastman N. Jacobs, Ira R. Abbott, and Milton Davidson, March 1942 has been corrected and included in the present paper, which supersedes the previously published paper.

LOW-DRAG↗

NASA NTRS1962

HUMAN CONTROL PERFORMANCE AND TOLERANCE UNDER SEVERE COMPLEX WAVE FORM VIBRATION, WITH A PRELIMINARY HISTORICAL REVIEW OF FLIGHT SIMULATION

What can we do, preparing for these pioneers, to insure that these expected vibrations will not jeopardize their lives nor their missions? This paper will describe one approach, of attempting to simulate the expected and more than the expected complex wave form vibrations to determine tolerance and pilot control capabilities, to attempt to find solutions in simulation before the first flights in reality. The experimental work to be described was done in November, 1959, and June, 1960, on the Johnsville Navy human centrifuge, at the Aviation Medical Acceleration Laboratory, U.S. Naval Air Development Center, Johnsville, Pennsylvania, and in June, 1960, on the North American "G-seat", the vertical accelerator of the North American Aviation Co., Inc., Columbus, Ohio, while the author was Jostle Program Officer at the Aviation Medical Acceleration Laboratory. The experimental work was the subject of the confidential reports NADC-MA-L6005 and NADC-MA-6128, U.S. Naval Air Development Center, and NA60H-444, North American Aviation, Inc., Columbus. Unclassified aspects can now be reported.

Vibration↗

NASA NTRS1997

Aviation Safety Reporting System: Process and Procedures

The Aviation Safety Reporting System (ASRS) was established in 1976 under an agreement between the Federal Aviation Administration (FAA) and the National Aeronautics and Space Administration (NASA). This cooperative safety program invites pilots, air traffic controllers, flight attendants, maintenance personnel, and others to voluntarily report to NASA any aviation incident or safety hazard. The FAA provides most of the program funding. NASA administers the program, sets its policies in consultation with the FAA and aviation community, and receives the reports submitted to the program. The FAA offers those who use the ASRS program two important reporting guarantees: confidentiality and limited immunity. Reports sent to ASRS are held in strict confidence. More than 350,000 reports have been submitted since the program's beginning without a single reporter's identity being revealed. ASRS removes all personal names and other potentially identifying information before entering reports into its database. This system is a very successful, proof-of-concept for gathering safety data in order to provide timely information about safety issues. The ASRS information is crucial to aviation safety efforts both nationally and internationally. It can be utilized as the first step in safety by providing the direction and content to informed policies, procedures, and research, especially human factors. The ASRS process and procedures will be presented as one model of safety reporting feedback systems.

Connell, Linda J.↗

NASA NTRSDate not supplied

NASA C3RS: Communication Works For Those Who Work At It!

The objective of the study is to learn about Communication Breakdown related to safety events reported to the Confidential Close Call Reporting System (C3RS). Studying the reported close calls can yield information about communication breakdowns that may be present in the railroad operations.

Confidential Close Call Reporting System↗

NASA NTRS2013

Ground Operations and ASRS

The Aviation Safety Reporting System (ASRS) in a partnership between the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), participating carriers, and labor organizations. It is designed to improve the National Airspace System by collecting and studying reports detailing unsafe conditions and events in the aviation industry. Employees are able to report safety issues or concerns with confidentiality and without fear of discipline

human factors↗

NASA NTRS2014

Dangers on the Ramp: Aviation Safety Reporting System

The Aviation Safety Reporting System (ASRS) in a partnership between the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), participating carriers, and labor organizations. It is designed to improve the National Airspace System by collecting and studying reports detailing unsafe conditions and events in the aviation industry. Employees are able to report safety issues or concerns with confidentiality and without fear of discipline.

confidential reporting↗

NASA NTRS2011

NASA Aviation Safety Reporting System (ASRS)

The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 900,000 reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 5,500 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides de-identified report information through the online ASRS Database at http://asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation \vill discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.

Connell, Linda↗

NASA NTRS2017

NASA Aviation Safety Reporting System (ASRS)

The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 million reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.

Connell, Linda J.↗

NASA NTRS2016

NASA Aviation Safety Reporting System (ASRS)

The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 M reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.

Connell, Linda↗

NASA NTRS1959

NASA Research Bearing on Jet Engine Reliability

Turbojet engine reliability has long been an intense interest to the military users of this type of aircraft propulsion. With the recent inauguration of commercial jet transport this subject has assumed a new dimension of importance. In January l96 the Lewis Research Center of the NASA (then the MACA) published the results of an extensive study on the factors that affect the opera- center dot tional reliability of turbojet engines (ref. 1). At that time the report was classified Confidential. In July l98 this report was declassified. It is thus appropriate at this time to present some of the highlights of the studies described in the NASA report. In no way is it intended to outline the complete contents of the report; rather it is hoped to direct attention to it among those who are center dot directly concerned with this problem. Since the publication of our study over three years ago, the NASA has completed a number of additional investigations that bear significantly on this center dot subject. A second object of this paper, therefore, is to summarize the results of these recent studies and to interpret their significance in relation to turbojet operational reliability.

Mason, S. S.↗

NASA NTRS2013

On Time Performance Pressure

Within many operations, the pressures for on-time performance are high. Each month, on-time statistics are reported to the Department of Transportation and made public. There is a natural tendency for employees under pressure to do their best to meet these objectives. As a result, pressure to get the job done within the allotted time may cause personnel to deviate from procedures and policies. Additionally, inadequate or unavailable resources may drive employees to work around standard processes that are seen as barriers. However, bypassing practices to enable on-time performance may affect more than the statistics. ASRS reports often highlight on-time performance pressures which may result in impact across all workgroups in an attempt to achieve on-time performance. Reporters often provide in-depth insights into their experiences which can be used by industry to identify and focus on the implementation of systemic fixes.

aviation safety↗

NASA NTRSDate not supplied

Identifying Emerging Safety Threats Through Topic Modeling in the Aviation Safety Reporting System: A Covid-19 Study

The NASA Aviation Safety Reporting System (ASRS) is a voluntary, confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants, and others involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts, and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in many ways, including via an online database, Safety Alert Bulletins, For Your Information Notices, and the CALLBACK newsletter. In this work, we consider whether we can improve the grouping, linking, and understanding of safety concerns through topic modeling. Specifically, we use topic modeling as a building block to identify emerging safety threats over time. This unsupervised approach, we argue, offers the flexibility to identify new emerging themes in this large dataset by constructing different timelines based on the content similarity of ASRS report narratives. This method's unsupervised nature improves upon related research, which is limited to pre-defined labels and therefore can not fully capture emerging safety threats. We apply our method to all ASRS reports in 2020 to assess if the generated timelines can highlight COVID-19 as it is emerging as a safety threat in incoming ASRS reports. We perform both a quantitative and qualitative evaluation of the automatically constructed timelines. The qualitative evaluation is performed by describing the evolution of top terms in the timelines, generated by our method, which we found explicitly convey the themes of COVID-19. Separately, we use a set of 1,213 COVID-19 reports from 2020 that were manually identified by ASRS analysts to quantitatively evaluate the COVID-19 reports distribution across the timelines. Our results have shown that COVID-19 emergence can be identified using the top terms that were generated by topic modeling. The top terms in topic modeling therefore can serve as a summary alternative to manually inspecting reports. Moreover, leveraging the manually identified COVID-19 reports, we found the manually identified timelines accounted for over 70% of the COVID-19 reports curated by the ASRS analysts, which demonstrates the potential of this approach for facilitating the understanding of safety concerns as they emerge and evolve. This method shows great potential to understand aerospace safety threats and other narrative- driven incident report databases.

ASRS↗

NASA NTRSDate not supplied

A Survey Protocol to Assess Meaningfulness and Usefulness of Automated Topic Finding in the NASA Aviation Safety Reporting System

Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants and other involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in a number of ways including entry into an online database, Safety Alert Bulletins and For Your Information Notices, and the CALLBACK newsletter. Key to these publications are the timely processing (de-identification, coding and summarization) of new reports, which is currently done by ASRS expert safety analysts. Thus, we believe topic modelling could decrease effort in ASRS, if topics are comprehensible. Aim: We propose a methodology to evaluate whether automated topic finding using topic modelling provides meaningful and useful topics. Method: We extend the total error survey methodology to evaluate user topic comprehension of machine learning outputs. To accomplish this we performed a literature review to identify existing methods and define a construct for topic comprehension, utilizing existing ASRS synopsis writing practices to more precisely define meaningfulness and usefulness. Results: A survey protocol was created that addresses the limitations of other survey protocols found in the literature review, which we found lacking in rationale and clear protocol definition. Conclusion: The surveying of user understanding in machine learning outputs presents challenges due to the explosion of parameters to control for and the lack of systematic approach presented in the literature. More reproducible work and survey protocols are needed in the literature and our work is one step towards that direction.

topic finding↗

NASA NTRSDate not supplied

Identifying Emerging Safety Threats Through Topic Modeling in the Aviation Safety Reporting System: A COVID-19 Study

The NASA Aviation Safety Reporting System (ASRS) is a voluntary, confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants, and others involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts, and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in many ways, including via an online database, Safety Alert Bulletins, For Your Information Notices, and the CALLBACK newsletter. In this work, we consider whether we can improve the grouping, linking, and understanding of safety concerns through topic modeling. Specifically, we use topic modeling as a building block to identify emerging safety threats over time. This unsupervised approach, we argue, offers the flexibility to identify new emerging themes in this large dataset by constructing different timelines based on the content similarity of ASRS report narratives. This method's unsupervised nature improves upon related research, which is limited to pre-defined labels and therefore can not fully capture emerging safety threats. We apply our method to all ASRS reports in 2020 to assess if the generated timelines can highlight COVID-19 as it is emerging as a safety threat in incoming ASRS reports. We perform both a quantitative and qualitative evaluation of the automatically constructed timelines. The qualitative evaluation is performed by describing the evolution of top terms in the timelines, generated by our method, which we found explicitly convey the themes of COVID-19. Separately, we use a set of 1,213 COVID-19 reports from 2020 that were manually identified by ASRS analysts to quantitatively evaluate the COVID-19 reports distribution across the timelines. Our results have shown that COVID-19 emergence can be identified using the top terms that were generated by topic modeling. The top terms in topic modeling therefore can serve as a summary alternative to manually inspecting reports. Moreover, leveraging the manually identified COVID-19 reports, we found the manually identified timelines accounted for over 70% of the COVID-19 reports curated by the ASRS analysts, which demonstrates the potential of this approach for facilitating the understanding of safety concerns as they emerge and evolve. This method shows great potential to understand aerospace safety threats and other narrative- driven incident report databases.

ASRS↗

NASA NTRSDate not supplied

Assessing the use of UAS-related terms in ASRS using Seed Topic Modeling

Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants and other involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts. The de-identified reports are then disseminated to the aviation community in a number of ways including entry into an online database. Augmenting the discovery of topics of user interest in this online database would therefore be beneficial to the community it serves. Aim: We propose and execute an experiment to assess the use of seed term topic modeling using the database narratives to identify UAS reports. The use of seed term topic modeling would enable users to identify groups of related narratives associated to a topic of their interest. Method: We use a newly curated field in ASRS reports which identify UAS from non-UAS reports in combination of different set of UAS related terms to assess if seed topic modeling can be used in ASRS.

LDA↗