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Table 3. (Continued).
Category Field Level 1 Field Level 2
Incorrect Flight Planning
Communication/Coordination
Visual Illusion
Human Errors
Fatigue
Pressonitis
Other
Wet
Contaminated - Standing water
Contaminated - Rubber
Contaminated - Oil
Contaminated - Ice
Runway Surface
Contaminated - Slush
Conditions
Contaminated - Snow
Contaminated - Paint
Contaminated - Other
Construction
Down Slope
Wildlife Hazards
Unstabilized - Low Approach
Unstabilized - Low Speed
Approach/Takeoff
Long Touchdown
Procedures
Unstabilized - High Speed
High Above Threshold
Takeoff Rejected
Other
Aircraft Body Type Wide or Narrow
Aircraft Cost 2007 dollar value
Cost
Human Cost 2007 dollar value
Total Event Cost 2007 dollar value
and world occurrences was utilized to develop the location develop risk models. However, operation conditions and
models. levels of risk are different at different airports. In addition,
Incorporating risk exposure information into the accident only raw distances between the final wreckage location and
frequency model enhances its predictive power and provides the runway end have been used to develop current FAA RSA
the basis for formulating more risk-sensitive and responsive recommendations.
RSA policies. Accident frequency models need no longer rely To mitigate this difficulty, information available for differ-
on simple crash rates based on just aircraft, engine, or opera- ent airports was compared by using a normalization procedure,
tion type. As discussed below, factors previously ignored by to transform existing data to a standard nominal airport (Kirk-
airport risk assessments and RSA regulations are accounted land et al., 2003). To normalize aircraft accident data, the "nor-
for using the models developed in this study. Moreover, this mal" airport is an airport situated at the International Standard
normal operations database can be used for future studies. Atmosphere (ISA) conditions, with level surrounding terrain
The detailed source and sampling strategy of the NOD or obstacles and an infinitely long, hard runway.
database is described in Appendix G. In addition, a small sam- Normalization was conducted for the effects of terrain on
ple of the NOD being utilized in this study is included in that wreckage location using the models developed by Kirkland et al.
section. A list of sampled airports is shown in Appendix H and (2003) and the effects of the local atmospheric conditions on
the stratified sampling strata is presented in Appendix I. the aircraft's performance, based on standard corrections for
To derive the weights to be applied to each stratum, it was aircraft distance required. Major factors that affect the runway
necessary to identify the relevant traffic from Terminal Area distance required for the operation and used in the flight man-
Forecasts (TAFs). Details on the calculation of TAF are pre- ual calculations are runway slope, runway elevation, and the air
sented in Appendix J. temperature; however, a correction was not applied to the slope
in the RSA due to missing information for the majority of the
events. The RSA slope is indeed an important factor on the
Normalization of Data
wreckage distance and this information should be collected and
The small pool of relevant data available is a fundamental made available in incident and accident investigation reports.
problem to risk assessment in aviation (Caves and Gosling, Normalization procedures used in this study are presented in
1999). Most studies have used data from different airports to Appendix K.
