Development of a Runway Veer-Off Location Distribution Risk Assessment and Reporting Template (2014)

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123 Location Models for Other Normalization Alternatives Three alternatives to normalize the longitudinal distances for veer-off path were evaluated in this study: runway dis- tance available (RDA), raw distances, and runway distance required (RDR). Only the models for RDA were presented in the body of the report and this appendix shows the results for the remaining two alternatives. Normalization Alternative 2—Raw Distances For this scenario, the raw longitudinal and lateral distances were used in the modeling process. To model the longitudi- nal probability distributions, 10 subareas were defined, each with length of 800 ft, with the last segment comprising all distances above 7200 ft. Longitudinal Probability Distribution Figure G1 illustrates the longitudinal probability distribu- tion for both landing and takeoff veer-offs when using raw longitudinal distances. Figures G2 and G3 represent the lon- gitudinal probability distributions for landing and takeoff veer-offs, respectively. The cumulative probability plot and corresponding poly- nomial model is represented in Figure G4. It should be noted that this model was developed based on a maximum lon- gitudinal length of 10,000 ft. The application of this model to runways with more than 7,200 ft should assume a linear trend for the last subarea; however, it should be recognized that this is a fundamental weakness of the approach using raw distances. The cumulative probability model (R2 = 100%) is represented by the following equation. CP E D E D E D= − + − − − −4 3285 2 2632 4 2519 3 24 6 19 5 15 4. . . . . .6387 1 2812 3 583011 3 07 2 05E D E D E D− − −+ + where D is the longitudinal distance from the beginning of the runway and CP is the cumulative probability that a veer-off will occur within D. Lateral Probability Distribution The lateral deviation models were developed using the mathematical structure described for the previous set of lat- eral deviation models. A model was developed for each sub- area using the lateral deviations identified for each landing veer-off and takeoff veer-off event challenging the specific subarea. Table G1 summarizes the model coefficients for each subarea. Figures illustrating the mathematical mod- els with the actual data used for modeling are presented in Appendix D. Based on the lateral deviation models, risk contour lines were derived to cover the subareas defined, as shown in Figure G5. The contour lines in this figure represent both sides of the runway. Aircraft deviations are referenced to the center point of the aircraft between the main gears. The ISO-risk lines can be used to estimate the probability that an aircraft exceeds the lateral distance in a given subarea. It should be noted that the risk contour curves presented in Figure G5 are applied to individual subareas and it is not possible to calculate the risk of an accident for a given scenario where the safety area may have limits and some obstacles may be present. However, it is possible to combine the lateral devia- tion models with the probability that an aircraft will challenge specific subareas of the runway. Figure G6 combines the results from Figure G5 and the lateral deviation models in Table G1, where the probabilities for a given distance are multiplied by the subarea probability. In this case, the contour lines represent the probabilities that an aircraft will exceed a given lateral distance during a runway excursion. The two previous plots present very high variability as a function of the raw distance, particularly for the outer con- tour lines. This is an indication that using raw distances may not be very accurate and not the best alternative for modeling. A P P E N D I X G

124 Figure G1. Longitudinal probability distribution: both landing and takeoff veer-offs—raw distances in feet. 82 138 161 139 111 78 56 38 23 27 0 20 40 60 80 100 120 140 160 180 800 1600 2400 3200 4000 4800 5600 6400 7200 <7200 N um be r o f C ha lle ng es Subarea Figure G2. Longitudinal probability distribution: landing veer-offs only— raw distances in feet. 30 85 125 115 92 58 44 31 19 22 0 20 40 60 80 100 120 140 800 1600 2400 3200 4000 4800 5600 6400 7200 <7200 N um be r o f C ha lle ng es Subarea Figure G3. Longitudinal probability distribution: takeoff veer-offs only— raw distances in feet. 52 53 36 24 19 20 12 7 4 5 0 10 20 30 40 50 60 800 1600 2400 3200 4000 4800 5600 6400 7200 <7200 N um be r o f C ha lle ng es Subarea

125 Normalization Alternative 3— Runway Distance Required For this scenario, the raw longitudinal distances were divided by the runway distance required (RDR) by the aircraft involved in the event under its specific operational conditions. To model the longitudinal probability distributions, 10 subareas were defined. Subareas 1 through 7 had a length of 0.2*RDR each; the 8th segment had a length of 0.4*RDR; the 9th segment had a length 0.8*RDR; and the last segment comprised all distances above 2.4*RDR. The length of segments was selected such that the longitudinal probability distribution could be character- ized with at least 5% of occurrences in each segment in the consolidated frequency histogram. In addition to the basic RDR by each aircraft under ISO conditions (sea level, 15 degrees Centigrade), the following corrections were applied to RDR for each event: • Elevation, • Air temperature, and • Longitudinal Runway slope. Longitudinal Probability Distribution Figure G7 illustrates the longitudinal probability distri- bution for both landing and takeoff veer-offs when using longitudinal distances normalized for RDR. Figures G8 and G9 depict the longitudinal probability distributions for landing and takeoff veer-offs, respectively. 0% 20% 40% 60% 80% 100% 120% 0 1600 3200 4800 6400 8000 9600 Cu m ul ati ve P ro ba bi lit y Raw Distance (ft) Figure G4. Longitudinal cumulative probability distribution—raw distances. Subarea Range a b R2 1 0–800  -0.02092 0.92906 98.1% 2 800–1,600  -0.00718 1.072515 99.6% 3 1,600–2,400  -0.00837 1.094611 98.5% 4 2,400–3,200  -0.00314 1.288615 98.8% 5 3,200–4,000  -0.00908 1.049775 98.3% 6 4,000–4,800  -0.02169 0.811623 99.0% 7 4,800–5,600  -0.00510 1.128748 99.2% 8 5,600–6,400  -0.00315 1.126453 98.4% 9 6,400–7,200  -0.00916 0.971838 98.4% 10 Above 7,200  -0.00265 1.108277 98.7% Table G1. Lateral deviation models using raw distances. 35% 25% 10% 5% 2.5% 35% 25% 10% 5% 2.5% -600 -400 -200 0 200 400 600 0 1 2 3 4 5 6 7 8 9 10 De vi ati on D is ta nc e fr om R un w ay E dg e (ft ) Subarea Direction of Operation Left Right Figure G5. Risk contours: – probability of deviations exceeding a given distance L1 for each subarea—raw distances.

5% 2% 1% 0.1% 5% 2% 1% 0.1% -600 -500 -400 -300 -200 -100 0 100 200 300 400 500 600 0 1 2 3 4 5 6 7 8 9 10 De vi ati on D is ta nc e fr om R un w ay E dg e (ft ) Subarea Direction of Operation Left Right Figure G6. Risk contours: adjusted probability of deviations exceeding a given distance L1—raw distances. 7.4% 11.2% 12.7% 13.3% 13.7% 12.9% 9.3% 8.5% 5.8% 5.2% 0% 2% 4% 6% 8% 10% 12% 14% 16% 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 2.4 >2.4 Pe rc en t C ha lle ng es Subarea Figure G7. Longitudinal probability distribution: both landing and takeoff veer-offs—distances normalized by runway distance required. 3.4% 8.5% 13.0% 13.1% 15.4% 14.1% 10.4% 9.4% 6.4% 6.4% 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 2.4 >2.4 Pe rc en t C ha lle ng es Subarea Figure G8. Longitudinal probability distribution: landing veer-offs only— distances normalized by runway distance required.

127 18.1% 18.5% 12.2% 13.9% 9.2% 9.7% 6.3% 5.9% 4.2% 2.1% 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 2.4 >2.4 Pe rc en t C ha lle ng es Subarea Figure G9. Longitudinal probability distribution: takeoff veer-offs only—distances normalized by runway distance required. 0% 20% 40% 60% 80% 100% 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Cu m ul ati ve P ro ba bi lit y Distance Normalized for Runway Distance Required Figure G10. Longitudinal cumulative probability distribution: distances normalized by runway distance required. Based on the results presented in Figure G7 for both landing and takeoff veer-offs, the cumulative probability distribu- tion curve for the runway distance required was developed and is shown in Figure G10. No mathematical model was developed for this scenario. If necessary, a polynomial of degree higher than 6 may be applied for the modeling. As indicated in ensuing paragraphs, this alternative for nor- malization was not selected for incorporation in the analy- sis software. Lateral Probability Distribution Similar to previous normalization alternatives, exponen- tial models were developed for each subarea using the lateral deviations identified for each landing and takeoff veer-off event challenging the specific subarea. Table G2 summarizes the model coefficients for each subarea and the figures pre- sented in Appendix E illustrate the mathematical models with the actual data used for modeling. The last column in Table G2 shows the models’ R2. Risk contour lines were also derived for this normaliza- tion scenario, as shown in Figure G11. It should be noted that the contour lines represent both sides of the runway. Aircraft deviations are referenced to the center point of the aircraft between the main gears. The ISO-risk lines can be used to estimate the probability that an aircraft exceeds the lateral distance in a given subarea. It can be noted from Figure G11 that the contour lines are quite variable. This trend may be an indication that this nor- malization alternative may lead to larger errors if these risk contour curves are applied to individual subareas. Combining the lateral deviation models with the probability that an aircraft will challenge specific subareas of the runway makes it possible to obtain Figure G12. In this figure, the probabilities for a given distance are multiplied by the subarea probability. In this case, the contour lines represent the probabilities that an aircraft will exceed a given lateral distance during a runway excursion.

35% 25% 10% 5% 2.5% 35% 25% 10% 5% 2.5% -500 -400 -300 -200 -100 0 100 200 300 400 500 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 De vi at io n Di st an ce fr om R un w ay E dg e (ft ) Subarea Normalized for Runway Distance Available Direction of Operation Left Right Figure G11. Risk contours:—probability of deviations exceeding a given distance L1 for each subarea—distances normalized by RDR. Subarea Range a b R2 1 0 – 0.2*RDR -0.03258 0.8837 98.2% 2 0.2–0.4*RDR -0.01392 0.9496 99.5% 3 0.4–0.6*RDR -0.00905 1.0568 99.5% 4 0.6–0.8*RDR -0.00811 1.0989 99.2% 5 0.8–1.0*RDR -0.00766 1.0869 99.6% 6 1.0–1.2*RDR -0.01757 0.8890 99.2% 7 1.2–1.4*RDR -0.02405 0.8434 99.3% 8 1.4–1.8*RDR -0.01238 0.9301 98.5% 9 1.8–2.4*RDR -0.02139 0.8632 98.6% 10 > 2.4*RDR -0.00716 1.1380 98.4% Table G2. Lateral deviation models— normalization using RDR. 5% 2% 1% 0.1% 5% 2% 1% 0.1% -600 -500 -400 -300 -200 -100 0 100 200 300 400 500 600 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 De vi ati on D ist an ce fr om R un w ay E dg e (ft ) Subarea Normalized for Runway Distance Available Direction of Operation Left Right Figure G12. Risk contours:—adjusted probability of deviations exceeding a given distance L1—distances normalized by RDR.

Abbreviations and acronyms used without definitions in TRB publications: A4A Airlines for America AAAE American Association of Airport Executives AASHO American Association of State Highway Officials AASHTO American Association of State Highway and Transportation Officials ACI–NA Airports Council International–North America ACRP Airport Cooperative Research Program ADA Americans with Disabilities Act APTA American Public Transportation Association ASCE American Society of Civil Engineers ASME American Society of Mechanical Engineers ASTM American Society for Testing and Materials ATA American Trucking Associations CTAA Community Transportation Association of America CTBSSP Commercial Truck and Bus Safety Synthesis Program DHS Department of Homeland Security DOE Department of Energy EPA Environmental Protection Agency FAA Federal Aviation Administration FHWA Federal Highway Administration FMCSA Federal Motor Carrier Safety Administration FRA Federal Railroad Administration FTA Federal Transit Administration HMCRP Hazardous Materials Cooperative Research Program IEEE Institute of Electrical and Electronics Engineers ISTEA Intermodal Surface Transportation Efficiency Act of 1991 ITE Institute of Transportation Engineers MAP-21 Moving Ahead for Progress in the 21st Century Act (2012) NASA National Aeronautics and Space Administration NASAO National Association of State Aviation Officials NCFRP National Cooperative Freight Research Program NCHRP National Cooperative Highway Research Program NHTSA National Highway Traffic Safety Administration NTSB National Transportation Safety Board PHMSA Pipeline and Hazardous Materials Safety Administration RITA Research and Innovative Technology Administration SAE Society of Automotive Engineers SAFETEA-LU Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (2005) TCRP Transit Cooperative Research Program TEA-21 Transportation Equity Act for the 21st Century (1998) TRB Transportation Research Board TSA Transportation Security Administration U.S.DOT United States Department of Transportation