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Risk Assessment Method to Support Modification of Airfield Separation Standards (2011)

Chapter: Chapter 2 - Airfield Separation Rationale

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Suggested Citation:"Chapter 2 - Airfield Separation Rationale." National Academies of Sciences, Engineering, and Medicine. 2011. Risk Assessment Method to Support Modification of Airfield Separation Standards. Washington, DC: The National Academies Press. doi: 10.17226/14501.
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Page 13
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Suggested Citation:"Chapter 2 - Airfield Separation Rationale." National Academies of Sciences, Engineering, and Medicine. 2011. Risk Assessment Method to Support Modification of Airfield Separation Standards. Washington, DC: The National Academies Press. doi: 10.17226/14501.
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Page 12

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13 specialist risk assessors. The objective of the FHA is to explore relevant operational scenarios and identify hazards associated with them. The output of the FHA is typically a “hazard log,” which includes all hazards identified and preliminary informa- tion about them that can be provided by the workshop team. A recent study developed by the Flight Safety Foundation (2009) gathered information worldwide on runway excursion accidents occurring from January 1995 to March 2008. The study presents a matrix of contributing factors that identified common causes and followed trends. The study resulted in the following major conclusions. The major contributing factors for takeoff excursions include the following: • Rejecting takeoff after V1 was the most cited factor, which in turn was caused by – Pilot’s perception of a catastrophic failure – Inability to rotate due to incorrect center of gravity (CG) location, mistake in performance calculation, or flight control anomalies • Loss of directional control, which is generally associated with – Mechanical anomalies (30 percent of cases) – Contaminated runways – Crosswind The major contributing factors for landing excursions include the following: • Human errors and neglect of standard operating procedures such as – Landing long and/or fast during unstabilized approaches – Failing to go around despite unstabilized approach – Other pilot’s errors, such as hard landing • Mechanical problems leading to the following: – Spontaneous collapse of the landing gear – Asymmetric forces due to thrust reverse or braking problems • Environmental factors such as the following: – Crosswind and tailwind conditions – Runway surface under wet or contaminated conditions Information on runway, taxiway, and taxilane events was not readily available to use in this study. Relevant accident and incident reports were identified in worldwide databases. The basic idea was to collect information that could be used to develop risk models based on evidence from past accidents and incidents. Runway and taxiway veer-off accident and incident data were collected from the following sources: • FAA Accident/Incident Data System (AIDS) • FAA/National Aeronautics and Space Administration (NASA) Aviation Safety Reporting System (ASRS) • National Transportation Safety Board (NTSB) Accident Database and Synopses • Transportation Safety Board of Canada (TSB) • Australian Transport Safety Bureau (ATSB) • Bureau d’Enquêtes et d’Analyses pour la Sécurité de l’Avi- ation Civile (BEA) • UK Air Accidents Investigation Branch (AAIB) • New Zealand Transport Accident Investigation Commis- sion (TAIC) • Air Accident Investigation Bureau of Singapore • Ireland Air Accident Investigation Unit (AAIU) • Spain’s Comisión de Investigación de Accidentes e Inci- dentes de Aviación Civil (CIAIAC) • Indonesia’s National Transportation Safety Committee (NTSC) • Netherlands Aviation Safety Board (NASB) • MITRE Corporation Accident and Incident Database A list of accidents and incidents containing the cases used for model development is presented in Appendix D. In addi- tion to the taxiway incidents identified, the list includes run- way veer-off events that occurred within 1,000 ft of the run- way centerline. Every identified event that has occurred since 1978 and for which reports were available was included in the database for this study. Portions of the data are complemented with other sources of information, particularly information sources on aircraft, airport, and meteorological conditions. For example, in many cases information on the weather during the accident was missing, and the research team obtained the actual METAR for the airport to retrieve the data. In other situations, the runway used was missing, and the research team consulted the FAA Enhanced Traffic Management System Counts (ETMSC) and the Aviation System Performance Metrics (ASPM) to retrieve relevant information. Additional filtering criteria were used so that the events were comparable. The first set of filtering criteria was applied so as to retrieve only information from regions of the world having accident rates that are comparable to the U.S. rate. In addition, the filtering criteria described in Table 3 were applied in this study. Filtering was necessary in order to make data collection a feasible task and to ensure that the data used in the modeling process were fairly homogeneous. Aircraft Veer-Off Database Organization The accident and incident database was developed in Microsoft Access. The system provides the software tools needed to utilize the data in a flexible manner and includes facilities to add, modify, or delete data from the database;

12 Airfield Lateral Deviation Studies During the course of study, an attempt was made to obtain data on extreme lateral aircraft deviations for runways, taxi- ways, and taxilanes. Also, information was gathered from previous studies and lateral deviation data and models to determine the best alternatives to use in the approach and the methodology to evaluate airfield separations. Appendix C provides a summary of this literature review. Ensuing sections of this report provide summaries of data collected in this research and describe previous studies evalu- ating the magnitude of lateral aircraft deviations during airfield operations as well as the attempts to model the probability distributions of these lateral deviations. A major consideration is random lateral deviations of air- craft during runway, taxiway, and taxilane operations. The probability distribution of such deviations relative to the centerline/guideline of runways and taxiways is crucial to assessing the adequacy of existing separation/clearance dis- tances for safe and regular operation of aircraft, both on straight portions and on taxiway curves. The following fac- tors may impact those deviations (Eddowes, Hancox, and MacInnes, 2001): • Quality of aircraft nose wheel guidelines (marking and lighting) • Quality of signs • Visibility conditions • Level of light (day or night) • Surface condition (dry, wet, contaminated by snow/ice, rubber, etc.) • Approach speed and touchdown location • Taxi speed • Pilot’s attention • Pilot’s technique during landing • Stability of approach • Pilot’s technique on negotiation turns • Wind effects (cross-wind) • Aircraft handling characteristics • Mechanical failures In the 1970s, the FAA and the U.S. Army Corps of Engineers (USACE) carried out substantial studies on lateral distribu- tion of aircraft traffic on runways and taxiways (Brown and Thompson, 1973; HoSang, 1975). More recently, Cohen-Nir and Marchi (2003), the FAA, and Boeing (Scholz, 2003a and 2003b) performed statistical analyses of taxiway deviations for large aircraft at John F. Kennedy International Airport (JFK) and Ted Stevens Anchorage International Airport (ANC). Veer-Off Accidents and Incidents Both the FAA and ICAO address the probability of aircraft veer-offs in their rationale for runway/taxiway separations. ICAO (2004) emphasizes that runway separation issues are supported by local airport experience in terms of identifying causes and accident factors specific to the local environment. No less important is the enormous variety and complexity of accident factors for collision risk. One of the subtasks of this project was to carry out a func- tional hazard analysis (FHA) for aircraft veer-offs based on information gathered in the literature review. The objective of this subtask was to identify relevant factors associated with such events to support the data collection effort for accidents and incidents. The research team collected information that could be used in the modeling process, particularly data on causal factors and aircraft location. Identifying the most rel- evant factors causing or contributing to such events also was part of the modeling process. An FHA is a formal and systematic process for the identifi- cation of hazards associated with an activity that is typically employed to support risk assessment and management. An FHA is often conducted in the form of a brainstorming work- shop involving a multi-disciplinary team that could include pilots, air-traffic controllers, airside operations personnel, and C H A P T E R 3 Data for Modeling Aircraft Deviations

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TRB’s Airport Cooperative Research Program (ACRP) Report 51: Risk Assessment Method to Support Modification of Airfield Separation Standards is intended to be used to support requests for modification of standards in those circumstances where the design criteria for separations between taxiways/taxilanes and other taxiways/taxilanes and fixed or movable objects as well as separations between taxiways and runways cannot be met.

The following appendices, included in the pdf and print version of the report, will be helpful in understanding the methodology.

  • Appendix A: Risk Assessment Methodology presents a methodology for five different types of circumstances: taxiway/taxilane to taxiway, taxiway to object, taxilane to taxilane, taxilane to an object, and runway to taxiway/taxilane or object;
  • Appendix F: Aircraft Database Summary presents a summary of aircraft characteristics by model; and
  • Appendix H: Analysis of MOS Cases summarizes information collected in the modification of standards survey and presents results of application of the methodology described in Appendix A to each modification of standards case.

Other report appendices, which are available online only, provide detail and information on the development of the methodology.

In addition, the project developed a

PowerPoint presentation

that may be useful for introducing and explaining the methodology to stakeholders.

In July 2021, an errata was posted for this publication: In Table 7 on page 25, the LDVO coefficient was changed from -3.088 to -13.088. The online version of the report has been corrected.

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