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OCR for page 105
E-1 APPENDIX E EMAS The Federal Aviation Administration (FAA) requires that To estimate aEMAS, data provided by ESCO were used as standard-size runway safety areas (RSA) be provided to mini- shown next. For aRSA a maximum runway exit speed of v = 70 mize the risks associated with aircraft overruns and under- knots and a standard RSA dimension of S = 1,000 feet was shoots. In some instances, however, natural or manmade obsta- employed in Eq. 1, resulting in aRSA = 2.156 m/s2. cles, local developments, surface conditions, or environmental The data included the necessary lengths and estimated air- constraints make it difficult or impossible to comply with the craft performance in terms of the maximum runway exit speed. FAA standards. The study includes values for a spectrum of aircraft models and As part of the study described in ACRP Report 3, historical maximum takeoff weights (MTOW). Table E1 lists the aircraft records of accidents and incidents were compiled and used to manufacturers, models, and MTOW that are included in the develop risk models for overrun and undershoot events. How- ESCO data. Table E2 shows the data provided by ESCO. ever, the study did not address the evaluation of RSAs when The maximum runway exit speed for all aircrafts models EMAS is used. The models used in the approach developed in was combined in a single dataset and employed in a regression this study are based on data provided by ESCO. analysis to generate the model for the maximum runway exit To evaluate the risk mitigation provided by EMAS, it is nec- speed (v) in terms of the EMAS length and aircraft MTOW. essary to normalize the EMAS distance to an equivalent con- A total of 84 data points were included in the regression. A ventional RSA distance so that the value can be used directly logarithmic transformation was performed on the EMAS in the location probability models for landing and takeoff length and the aircraft weight before performing the analy- overruns. No adjustments are necessary to the distances en- sis. The resulting regression equation is listed next, where W tered into the location models for landing undershoots. is the MTOW of the aircraft in kg and S the EMAS bed length To accomplish this, the length of the conventional RSA is in meters. modified by a runway length factor (RLF), which is calculated by taking into account the effectiveness of the EMAS in de- v = 3.0057 - 6.8329 log (W ) + 31.1482 log ( S ) [Eq. 3] celerating a specific type of aircraft. In other words, the length The R-squared of the linear regression was 0.89, and the of the conventional RSA is increased to provide an equivalent distance where the aircraft can stop when entering the EMAS standard error was equal to 2.91m/s. Figure E2 shows the re- bed at a certain speed. Figure E1 shows the schematics of an lationship between the reported ESCO maximum runway exit RSA with EMAS and its equivalent conventional RSA. speeds and the predicted speed values obtained using Eq. 3. The relationship between the aircraft deceleration, a, the The 45-degree angle dashed line represents the equality line aircraft speed when entering the RSA, v, and the RSA length, between the values. S, is as follows: The maximum runway exit speed estimated using the regres- sion equation (Eq. 3), along with the EMAS bed length (SEMAS), v2 was input in Eq. 1 to estimate the deceleration of the RSA with a= [Eq. 1] 2S EMAS bed (aEMAS). The runway length factor was then esti- mated as follows: In addition, since the speed of the aircraft entering the RSA is assumed to be the same for the same aircraft entering the aEMAS RLF = [Eq. 4] equivalent conventional RSA, it is established that: aRSA aEMAS SEMAS = aRSA SRSA [Eq. 2] where aRSA is 2.156 m/s2 as explained before.

OCR for page 105
E-2 x1 Regular Terrain x1 LRSA-EQ Regular Terrain LRSA-EMAS RLFx2 EMAS x2 a) b) Figure E1. Schematic of a) RSA with EMAS and b) equivalent conventional RSA. Table E1. Aircraft models included in ESCO data. Aircraft Manufacturer Aircraft Model MTOW (103 lb) Airbus A-319 (B737) 141.0 A-320 (B737) 162.0 A-340 567.0 Boeing B-737-400 150.0 B-747 870.0 B-757 255.0 B-767 407.0 B-777 580.0 Cessna CITATION 560 16.3 Canadair CRJ-200 53.0 CRJ-700 75.0 Embraer EMB-120 28.0 ERJ-190 (ERJ170) 51.0 McDonnell Douglas MD-83 (MD 82) 160.0

OCR for page 105
E-3 Table E2. Data provided by ESCO. 50 Predicted max speed entering EMAS bed (m/s) 45 Speed EMAS Speed Aircraft Weight (lb) 40 (knots) (feet) (m/s) A319(B737) 141,000 80 550 41.2 35 A319(B737) 141,000 79 350 40.6 30 A319(B737) 141,000 40 120 20.6 A320(B737) 162,000 80 550 41.2 25 A320(B737) 162,000 75 350 38.6 20 A320(B737) 162,000 37 120 19.0 15 A340 567,000 70 550 36.0 A340 567,000 50 350 25.7 10 A340 567,000 28 120 14.4 5 B747 870,000 66 550 34.0 B747 870,000 47 350 24.2 0 B747 870,000 29 120 14.9 0 10 20 30 40 50 B757 255,000 80 550 41.2 Reported max speed entering EMAS bed (m/s) B757 255,000 58 350 29.8 B757 255,000 31 120 15.9 Figure E2. Relationship between reported and B767 407,000 75 550 38.6 predicted maximum aircraft speeds entering the B767 407,000 54 350 27.8 EMAS bed. B767 407,000 30 120 15.4 B777 580,000 70 550 36.0 B777 580,000 50 350 25.7 B777 580,000 29 120 14.9 Subsequently, based on the relationship established in Eq. 2, CITATION 560 16,300 80 550 41.2 RLF was multiplied by the length of the EMAS bed to estimate CITATION 560 16,300 77 350 39.6 the equivalent length of the conventional RSA: CITATION 560 16,300 48 120 24.7 CRJ 200 53,000 80 550 41.2 aEMAS CRJ 200 53,000 80 350 41.2 SRSA = SEMAS = RLF g SEMAS [Eq. 5] CRJ 200 53,000 45 120 23.1 aRSA CRJ 700 75,000 80 550 41.2 CRJ 700 75,000 77 350 39.6 Note that, depending on the RSA configuration and the type CRJ 700 75,000 41 120 21.1 of aircraft, different operations will generate different RLFs. EMB 120(SAAB340) 28,000 75 550 38.6 EMB 120(SAAB340) 28,000 70 350 36.0 EMB 120(SAAB340) 28,000 41 120 21.1 ERJ 190(ERJ170) 51,800 80 550 41.2 ERJ 190(ERJ170) 51,800 65 350 33.4 ERJ 190(ERJ170) 51,800 37 120 19.0 MD 83(MD 82) 160,000 80 550 41.2 MD 83(MD 82) 160,000 70 350 36.0 MD 83(MD 82) 160,000 35 120 18.0