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Page 13
Suggested Citation:"FAA 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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Suggested Citation:"FAA 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 14
Page 15
Suggested Citation:"FAA 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.
×
Page 15
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Suggested Citation:"FAA 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 16

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

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;

14 make queries about the data stored in the database; and produce reports summarizing selected contents. Figure 9 illustrates the database organization. The database includes for each individual event or opera- tion the reporting agency, the characteristics of the aircraft involved, the runway and environmental conditions, event classification (accident or incident), and other relevant infor- mation such as consequences (fatalities, injuries, and damage) and causal or contributing factors. A unique identifier was assigned to each event. Normal Operations Data (NOD) Another key approach in this study was the use of normal operations (i.e., non-accident/incident flight) data for prob- ability modeling of runway veer-offs. In the absence of infor- mation on risk exposure, even though the occurrence of a factor (e.g., contaminated runway) could be identified as a contributor to many accidents, it is impossible to know how critical the factor was since other flights may have experienced the factor without incidents. With NOD, the number of opera- tions that experience the factor benignly, singly, and in combi- nation can be calculated; risk ratios can be generated; and the importance of risk factors can be quantified. This assessment may allow the prioritization of resource allocation for safety improvement. The NOD from the research reported in ACRP Report 3: Analysis of Aircraft Overruns and Undershoots for Runway Safety Areas was used in this study (Hall et al., 2008). The database was complemented with data for general aviation (GA) air- craft with a maximum takeoff weight (MTOW) of less than 12,500 lb and greater than 6,000 lb. These data are a large and representative sample of disaggregated U.S. NOD covering a range of risk factors associated with runway veer-offs, allow- ing their criticality to be quantified. The data on U.S. incidents and accidents were used as a sample to develop the frequency models for runway veer-offs only. A sample of the NOD data is available in Appendix E. Incorporating this risk exposure information into the accident frequency model enhances its predictive power and provides the basis for formulating more risk-sensitive and responsive RSA assessments. Accident frequency models no Filter # Description Justification 1 Remove non-fixed-wing aircraft entries. Study is concerned with fixed-wing aircraft accidents and incidents only. 2 Remove entries for airplanes with certified max gross weight < 6,000 lb. Cut-off criteria to maintain comparable level of pilot qualifications and aircraft performance to increase the validity of the modeling. 3 Remove entries with unwanted Federal Aviation Regulation (FAR) parts. Kept Part 121, 125, 129, 135, and selected Part 91 operations. Some FAR parts have significantly different safety regulations (e.g., pilot qualifications). The following cases were removed: Part 91F: Special Flt Ops Part 103: Ultralight Part 105: Parachute Jumping Part 133: Rotorcraft Ext. Load Part 137: Agricultural Part 141: Pilot Schools Armed Forces 4 Remove occurrences for unwanted phases of flight. Study focus is the RSA. Situations when the RSA cannot help mitigating accident and incident consequences were discarded to increase model validity. 5 Remove all single-engine aircraft and all piston-engine aircraft entries. Piston-engine aircraft are used infrequently in civil aviation and have been removed to increase the validity of the modeling. Moreover, single- and piston-engine aircraft behave differently in accidents due to the lower energy levels involved. Finally, the major focus of this study is air carrier aircraft. 6 Remove all accidents and incidents when the wreckage final location is beyond 1,000 ft from runway centerline. It would be infeasible to have an RSA more than 1,000 ft from the runway centerline; the gain in safety is not significant. Table 3. Filtering criteria for accidents and incidents.

longer need to rely on simple crash rates based on only aircraft, engine, or operation type. Aircraft Data The runway veer-off models incorporate an important factor to address the impact of aircraft performance and available runway length on the probability of veer-off incidents. For many of these events, particularly those taking place during the landing phase, if the runway length available is close to the runway length required by the aircraft for the operation, there may be a higher probability that a veer-off will take place because the safety margin is lower and more intense braking is required. Two factors were included in the models that required additional data on aircraft performance: the runway distance available for the operation (takeoff or landing) and the air- craft runway distance required for the operation. The runway distance available was gathered for each accident, incident, and normal operation based on airport data. Aircraft performance data were gathered from various sources, including aircraft manufacturers’ websites and the following databases: • FAA Aircraft Characteristics Database • Eurocontrol Aircraft Performance Database V2.0 • FAA Aircraft Situation Display to Industry—Aircraft Types • Boeing Airplane Characteristics for Airport Planning • Airbus Airplane Characteristics for Airport Planning • Embraer Aircraft Characteristics for Airport Planning Aircraft performance data were used to develop the proba- bility models. A summary of the aircraft database is presented in Appendix F. Figure 9. Accident and incident database for aircraft veer-offs. 15

16 The basic goal of this study was to develop a methodology to evaluate airfield separations. There are a few different sce- narios for the analysis of airfield separations, and each requires a different set of models and a specific procedure for the analy- sis. For example, the evaluation of a separation between a run- way and a parallel taxiway requires a different set of models than a separation between a taxiway and an object. The methodology presented in this report is applicable only to runways and straight parallel sections of taxiways and taxi- lanes and to straight sections of taxiways and taxilanes when the separation involves an object. The methodology also assumes that the pilot has full directional control of the aircraft, a good visual indication of the taxiway/taxilane centerline, and no assistance from a marshaller. The following are the types of separations that may be evaluated with the methodology: • Taxiway to parallel taxiway • Taxiway to parallel taxilane • Taxiway to object • Taxilane to parallel taxilane • Taxilane to object • Runway to parallel taxiway or taxilane • Runway to object The bases for the developed approach are the random lateral and vertical (airborne phase) deviations that may occur during normal operations and veer-off incidents. The risk of collision is related to the probability of large deviations from the nomi- nal flight path and from the runway, taxiway, and taxilane cen- terlines when aircraft are moving on parallel routes. Despite intensive efforts to identify taxiway and taxilane incidents, it was not possible to develop two-part models (fre- quency and location) for taxiway and taxilane veer-offs due to the difficulty in obtaining location data for close to 300 incidents occurring in straight segments of taxiways and very few relevant incidents occurring on taxilanes. However, it was noted that taxiway and taxilane incidents due to aircraft devi- ations do not lead to departures from the paved area of large distances. In the great majority of the cases, the pilots imme- diately stopped the aircraft when the aircraft departed the paved area. The following assumptions can be made regard- ing taxiway operations: • Aircraft travel at slower speeds relative to runway operations; • The end of the paved area is a discontinuity that signals to pilots that they are off the taxiway; • Because the aircraft is traveling slower, the pilot usually has some control and can stop the aircraft almost immediately after departing the taxiway; • These three factors combined lead to the assumption that the location probability distribution can be truncated for non-ramp taxiways. Most taxiway and taxilane incidents and accidents occurred in curved segments or because another aircraft or ground equipment was located inside the taxiway or taxilane OFA. In most cases, events with large lateral deviations occurred during poor weather conditions and situations of low surface friction (low visibility, rain, and ice). Modeling of aircraft lateral and vertical deviations on the runway involved different phases of flight, and for each phase a specific model was developed or used. For approach and landing, the airborne phase was modeled using the FAA/ICAO CRM, and for the rollout phase after aircraft touchdown, a two-part model (frequency and location) was developed and is described in ensuing sections. During takeoff, the factors and risk of veer-off are different from the models for landing, and another set of models (frequency and location) was required for this phase of flight. Taxiway and Taxilane Deviation Modeling Initially, the approach for modeling taxiway deviations was a two-part model composed of a frequency model and a loca- tion model. Taxiway veer-off incident data were collected to C H A P T E R 4 Methodology Approach

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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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