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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Updated Commercial Aviation Non-Airport Crash Density Values Using Data Obtained from the U.S. National Transportation Safety Board for 2000 through 2019

This report documents the calculation of the commercial aviation (CA) non-airport crash density for Air Route Traffic Control Center (ARTCC) area associated with the Contiguous United States (CONUS) using the methodology outlined in the Department of Energy (DOE) Standard 3014-2006, Accident Analysis for Aircraft Crash Into Hazardous Facilities. For analytical purposes, the CA aircraft fleet is comprised of aircraft engaged in operations under Title 14 of the Code of Federal Regulations (CFR) Part 121 (i.e., Air Carrier) and Part 135 (i.e., Air Taxi).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Updated General Aviation Non-Airport Crash Density Values Using Data Obtained from the U.S. National Transportation Safety Board for 2000 through 2019

This report documents the calculation of the General Aviation (GA) non-airport crash density for Department of Energy (DOE) sites and power generating facilities licensed by the Nuclear Regulatory Commission (NRC) using the methodology outlined in DOE-STD-3014-2006, Accident Analysis for Aircraft Crash Into Hazardous Facilities. The results of this report will be used by the American Nuclear Society (ANS) for the development of ANS standard 2.36, Accident Analysis for Aircraft Crash into Reactor and Nonreactor Nuclear Facilities.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2005

The Role of Spatial Disorientation in Fatal General Aviation Accidents

In-flight Spatial Disorientation (SD) in pilots is a serious threat to aviation safety. Indeed, SD may play a much larger role in aviation accidents than the approximate 6-8% reported by the National Transportation Safety Board (NTSB) each year, because some accidents coded by the NTSB as aircraft control-not maintained (ACNM) may actually result from SD. The purpose of this study is to determine whether SD is underestimated as a cause of fatal general aviation (GA) accidents in the NTSB database. Fatal GA airplane accidents occurring between January 1995 and December 1999 were reviewed from the NTSB aviation accident database. Cases coded as ACNM or SD as the probable cause were selected for review by a panel of aerospace medicine specialists. Using a rating scale, each rater was instructed to determine if SD was the probable cause of the accident. Agreement between the raters and agreement between the raters and the NTSB were evaluated by Kappa statistics. The raters agreed that 11 out of 20 (55%) accidents coded by the NTSB as ACNM were probably caused by SD (p less than 0.05). Agreement between the raters and the NTSB did not reach significance (p greater than 0.05). The 95% C.I. for the sampling population estimated that between 33-77% of cases that the NTSB identified as ACNM could be identified by aerospace medicine experts as SD. Aerospace medicine specialists agreed that some cases coded by the NTSB as ACNM were probably caused by SD. Consequently, a larger number of accidents may be caused by the pilot succumbing to SD than indicated in the NTSB database. This new information should encourage regulating agencies to insure that pilots receive SD recognition training, enabling them to take appropriate corrective actions during flight. This could lead to new training standards, ultimately saving lives among GA airplane pilots.

Scheuring, RIchard↗
NASA NTRSDate not supplied

Defining Services, Functions, and Capabilities for an Advanced Air Mobility (AAM) In-time Aviation Safety Management System (IASMS)

NASA’s vision for Advanced Air Mobility (AAM) Mission is to help emerging aviation markets to safely develop an air transportation system that moves people and cargo between places previously not served or underserved by aviation. The integration of new operational paradigms and vehicle classes in this system requires a transformation of the National Airspace System (NAS) that includes substantive changes critical for assuring safety. These changes are compelled by unique challenges posed by AAM to the safety management system (SMS). These challenges were assessed by committees of the National Academies in their reports on a vision for an In-time Aviation Safety Management System (IASMS) and a blueprint for AAM [1,2]. In their description of an IASMS, the top recommendation was development of a concept of operations (ConOps) for IASMS. This paper describes the high-priority recommendations from the National Academies for its IASMS vision and how they are addressed through a distributed system-of-systems architecture. The IASMS architecture is structured on the services, functions, and capabilities (SFCs) necessary for In-time System-wide Safety Assurance (ISSA)initially developed for urban air mobility (UAM). The paper then posits where these SFCs would reside across vehicles, airspace, or service suppliers such as Supplemental Data Service Providers (SDSPs), and how SFCs scale with increasing complexity in design and operations of AAM. SFCs are foundational building blocks for a system that targets an individual or family of risks using a Monitor-Assess-Mitigate risk paradigm for anomalies, precursors and trends. An IASMS could be conceived that uses a portfolio of SFCs for AAM in general or prioritizes SFCs for a specific domain or operation.

K Ellis↗
NASA NTRS2019

Overcoming the Challenges of Data Integration and Automation

Artificial Intelligence (AI) and machine learning (ML) are gaining increased attention as a way to leverage the world's data to solve problems. Although AI and ML offer much potential, there are often misconceptions about the application of such techniques. This panel discussion includes speakers from airlines and the research community who will present machine learning approaches they have developed on a variety of aviation data including digital flight data, safety reporting data, and traffic flow data. They will explain the purpose of the application, the data used, and the lessons learned in the development and deployment of their solutions. The panel discussion will focus on common pitfalls in developing and AI solution, the dangers of the current hype around AI, tips for gaining value from a machine learning solution, how to determine whether a machine learning approach is appropriate for a problem, and more.

Matthews, Bryan L.↗
NASA NTRS2019

Artificial Intelligence in Aviation Safety Applications - Exploring Myths and Truths of AI and ML

Artificial Intelligence (AI) and machine learning (ML) are gaining increased attention as ways to leverage the world's data to solve problems. Although AI and ML offer much potential, there are often misconceptions about the application of such techniques.Panel speakers will present machine learning approaches they have developed on a variety of aviation data, including digital flight data, safety reporting data, and voice communications data. They will discuss the purpose of the application, the data used, and the lessons learned in the development and deployment of their solutions. The panel will also discuss common pitfalls in developing an AI solution, the dangers of the current hype around AI, tips for gaining value from a ML solution, how to determine whether a ML approach is appropriate for a problem, and more.

Reeves, Scott (Capt.)↗
NASA NTRS1998

The Aviation Performance Measuring System (APMS): An Integrated Suite of Tools for Measuring Performance and Safety

This is a report of work in progress. In it, I summarize the status of the research and development of the Aviation Performance Measuring System (APMS) for managing, processing, and analyzing digital flight-recorded data, The objectives of the NASA-FAA APMS research project are to establish a sound scientific and technological basis for flight-data analysis, to define an open and flexible architecture for flight-data analysis systems, and to articulate guidelines for a standardized database structure on which to continue to build future flight-data-analysis extensions. APMS offers to the air transport community an open, voluntary standard for flight-data-analysis software; a standard that will help to ensure suitable functionality and data interchangeability among competing software programs. APMS will develop and document the methodologies, algorithms, and procedures for data management and analyses to enable users to easily interpret the implications regarding safety and efficiency of operations. APMS does not entail the implementation of a nationwide flight-data-collection system. It is intended to provide technical tools to ease the large-scale implementation of flight-data analyses at both the air-carrier and the national-airspace levels in support of their Flight Operations and Quality Assurance (FOQA) Programs and Advanced Qualifications Programs (AQP). APMS cannot meet its objectives unless it develops tools that go substantially beyond the capabilities of the current commercially available software and supporting analytic methods that are mainly designed to count special events. These existing capabilities, while of proven value, were created primarily with the needs-of aircrews in mind. APMS tools must serve the needs of the government and air carriers, as well as aircrews, to fully support the FOQA and AQP programs. They must be able to derive knowledge not only through the analysis of single flights (special-event detection), but also through statistical evaluation of the performance of large groups of flights. This paper describes the integrated suite of tools that will assist analysts in evaluating the operational performance and safety of the national air transport system, the air carrier, and the aircrew.

Statler, Irving C.↗
NASA NTRSDate not supplied

An Approach for Identifying IASMS Services, Functions, and Capabilities From Data Sources

Assuring safety in the NAS with the inclusion of new entrants that are part of Advanced Air Mobility (AAM) will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using semi-autonomous/autonomous vehicles. Overcoming these AAM safety assurance challenges is the focus of the In-time Aviation Safety Management System (IASMS). The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs)designed to manage operational risks, identify unknown risks, and inform system design to mitigate risk. This paper describes a broad approach for identifying SFCs involving technology trends in research, assessment of known and unknown risks in safety reports, and causal and contributing factors in aviation accidents and incidents. This approach leverages these sources to identify potential SFCs that enable the Monitor, Assess, and Mitigate (M-A-M)functionality that represents the enabling framework of the IASMS.

Kyle Ellis↗
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 NTRS2007

NASA Turbulence Technologies In-Service Evaluation: Delta Air Lines Report-Out

Concluding an in-service evaluation of two new turbulence detection technologies developed in the Turbulence Prediction and Warning Systems (TPAWS) element of the NASA Aviation Safety and Security Program's Weather Accident Prevention Project (WxAP), this report documents Delta's experience working with the technologies, feedback gained from pilots and dispatchers concerning current turbulence techniques and procedures, and Delta's recommendations regarding directions for further efforts by the research community. Technologies evaluated included an automatic airborne turbulence encounter reporting technology called the Turbulence Auto PIREP System (TAPS), and a significant enhancement to the ability of modern airborne weather radars to predict and display turbulence of operational significance, called E-Turb radar.

Amaral, Christian↗
NASA NTRS2015

Dynamic Open-Rotor Composite Shield Impact Test Report

The Federal Aviation Administration (FAA) is working with the European Aviation Safety Agency to determine the certification base for proposed new engines that would not have a containment structure on large commercial aircraft. Equivalent safety to the current fleet is desired by the regulators, which means that loss of a single fan blade will not cause hazard to the aircraft. NASA Glenn and Naval Air Warfare Center (NAWC) China Lake collaborated with the FAA Aircraft Catastrophic Failure Prevention Program to design and test a shield that would protect the aircraft passengers and critical systems from a released blade that could impact the fuselage. This report documents the live-fire test from a full-scale rig at NAWC China Lake. NASA provided manpower and photogrammetry expertise to document the impact and damage to the shields. The test was successful: the blade was stopped from penetrating the shield, which validates the design analysis method and the parameters used in the analysis. Additional work is required to implement the shielding into the aircraft.

Shielding↗
NASA NTRS1927

Safety in airplane flight

This report presents methods to reduce the incidence of aviation accidents. Some of the methods discussed include enlistment and training of aviators, improvement of controls and control surfaces, and upgrading of power plants.

FIRE PREVENTION↗
NASA NTRS2012

The National Aviation Operational Monitoring Service (NAOMS): A Documentation of the Development of a Survey Methodology

The National Aviation Operational Monitoring Service (NAOMS) was a research project under NASA s Aviation Safety Program during the years from 2000 to 2005. The purpose of this project was to develop a methodology for gaining reliable information on changes over time in the rates-of-occurrence of safety-related events as a means of assessing the safety of the national airspace. The approach was a scientifically designed survey of the operators of the aviation system concerning their safety-related experiences. This report presents the results of the methodology developed and a demonstration of the NAOMS concept through a survey of nearly 20,000 randomly selected air-carrier pilots. Results give evidence that the NAOMS methodology can provide a statistically sound basis for evaluating trends of incidents that could compromise safety. The approach and results are summarized in the report and supporting documentation and complete analyses of results are presented in 14 appendices.

Connors, Mary M.↗
NASA NTRS2006

What Happened, and Why: Toward an Understanding of Human Error Based on Automated Analyses of Incident Reports

The objective of the Aviation System Monitoring and Modeling project of NASA's Aviation Safety and Security Program was to develop technologies to enable proactive management of safety risk, which entails identifying the precursor events and conditions that foreshadow most accidents. Information about what happened can be extracted from quantitative data sources, but the experiential account of the incident reporter is the best available source of information about why an incident happened. In Volume I, the concept of the Scenario was introduced as a pragmatic guide for identifying similarities of what happened based on the objective parameters that define the Context and the Outcome of a Scenario. In this Volume II, that study continues into the analyses of the free narratives to gain understanding as to why the incident occurred from the reporter s perspective. While this is just the first experiment, the results of our approach are encouraging and indicate that it will be possible to design an automated analysis process guided by the structure of the Scenario that can achieve the level of consistency and reliability of human analysis of narrative reports.

Ferryman, Thomas A.↗
NASA NTRS2002

Aircraft Icing Weather Data Reporting and Dissemination System

The long-term operational concept of this research is to develop an onboard aircraft system that assesses and reports atmospheric icing conditions automatically and in a timely manner in order to improve aviation safety and the efficiency of aircraft operations via improved real-time and forecast weather products. The idea is to use current measurement capabilities on aircraft equipped with icing sensors and in-flight data communication technologies as a reporting source. Without requiring expensive avionics upgrades, aircraft data must be processed and available for downlink. Ideally, the data from multiple aircraft can then be integrated (along with other real-time and modeled data) on the ground such that aviation-centered icing hazard metrics for volumes of airspace can be assessed. As the effect of icing on different aircraft types can vary, the information should be displayed in meaningful ways such that multiple types of users can understand the information. That is, information must be presented in a manner to allow users to understand the icing conditions with respect to individual concerns and aircraft capabilities. This research provides progress toward this operational concept by: identifying an aircraft platform capable of digitally capturing, processing, and downlinking icing data; identifying the required in situ icing data processing; investigating the requirements for routing the icing data for use by weather products; developing an icing case study in order to gain insight into major air carrier needs; developing and prototyping icing display concepts based on the National Center for Atmospheric Research's existing diagnostic and forecast experimental icing products; and conducting a usability study for the prototyped icing display concepts.

Bass, Ellen J.↗
NASA NTRS2006

What Happened, and Why: Toward an Understanding of Human Error Based on Automated Analyses of Incident Reports

The objective of the Aviation System Monitoring and Modeling (ASMM) project of NASA s Aviation Safety and Security Program was to develop technologies that will enable proactive management of safety risk, which entails identifying the precursor events and conditions that foreshadow most accidents. This presents a particular challenge in the aviation system where people are key components and human error is frequently cited as a major contributing factor or cause of incidents and accidents. In the aviation "world", information about what happened can be extracted from quantitative data sources, but the experiential account of the incident reporter is the best available source of information about why an incident happened. This report describes a conceptual model and an approach to automated analyses of textual data sources for the subjective perspective of the reporter of the incident to aid in understanding why an incident occurred. It explores a first-generation process for routinely searching large databases of textual reports of aviation incident or accidents, and reliably analyzing them for causal factors of human behavior (the why of an incident). We have defined a generic structure of information that is postulated to be a sound basis for defining similarities between aviation incidents. Based on this structure, we have introduced the simplifying structure, which we call the Scenario as a pragmatic guide for identifying similarities of what happened based on the objective parameters that define the Context and the Outcome of a Scenario. We believe that it will be possible to design an automated analysis process guided by the structure of the Scenario that will aid aviation-safety experts to understand the systemic issues that are conducive to human error.

Maille, Nicolas P.↗
NASA NTRS2020

Identification of Scenarios for System Interface Design Evaluation: CAST SE-210 Output 2 Report 5 of 6

This report is one in a series of reports describing research to develop enhanced approaches to design and evaluation of flight deck interaction. The research was conducted to support the Commercial Aviation Safety Team (CAST) response to incidents and accidents caused by failure of the flight crew to maintain aircraft attitude or energy state awareness. This report partially responds to Safety Enhancement (SE) 210.2 (CAST, 2014) by describing development of operational scenarios for evaluation of flight crew interaction. Evaluations of human performance with an interface rely on asking humans to perform operational tasks in an appropriate operational context. The report includes the major sources of material for developing operational scenarios—which include system state, operational tasks, operational context, and safety events—and a method for developing an appropriate set of operational scenarios for interface evaluation.

commercial aviation↗
NASA NTRS2020

Changes in Frequency of the Severity and Type of Aviation Accidents (1987 to 2016)

This document reports the fourth analysis to identify the types of accidents with the greatest impact on the overall safety risk in U.S. civil aviation. The first three analyses examined accidents in 1997-20061, in 2001-20102 and in 2005-20143. The safety risks herein are defined to include four elements: (1) the number of total accidents; (2) the number of fatal accidents; (3) the number of total injuries; (4) the number of fatal injuries. Two of the previous analyses also included the number of incidents, but incident data since 2007 are difficult to separate by flight operation. Other incident details are no longer recorded as well. Due to these changes, the author’s working copy of the incident data has not been updated since 2011 (for incidents through 2010), and the incident data were not included in this analysis. Powerplant and non-powerplant system component failures were the only categories with a greater contribution to the overall safety risk from incidents than from accidents. Accident types, as well as accident rates, have been shown to vary considerably among different flight operations (e.g., large air carriers versus general aviation). For this reason, all analyses were done separately for four types of flight operations (Part 121, Scheduled Part 135, Non- Scheduled Part 135 and Part 91).

Evans, Joni K.↗