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Page 105
Suggested Citation:"Appendix E - EMAS." National Academies of Sciences, Engineering, and Medicine. 2011. Improved Models for Risk Assessment of Runway Safety Areas. Washington, DC: The National Academies Press. doi: 10.17226/13635.
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Suggested Citation:"Appendix E - EMAS." National Academies of Sciences, Engineering, and Medicine. 2011. Improved Models for Risk Assessment of Runway Safety Areas. Washington, DC: The National Academies Press. doi: 10.17226/13635.
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Suggested Citation:"Appendix E - EMAS." National Academies of Sciences, Engineering, and Medicine. 2011. Improved Models for Risk Assessment of Runway Safety Areas. Washington, DC: The National Academies Press. doi: 10.17226/13635.
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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.

E-1 The Federal Aviation Administration (FAA) requires that standard-size runway safety areas (RSA) be provided to mini- mize the risks associated with aircraft overruns and under- shoots. In some instances, however, natural or manmade obsta- cles, local developments, surface conditions, or environmental constraints make it difficult or impossible to comply with the FAA standards. As part of the study described in ACRP Report 3, historical records of accidents and incidents were compiled and used to develop risk models for overrun and undershoot events. How- ever, the study did not address the evaluation of RSAs when EMAS is used. The models used in the approach developed in this study are based on data provided by ESCO. To evaluate the risk mitigation provided by EMAS, it is nec- essary to normalize the EMAS distance to an equivalent con- ventional RSA distance so that the value can be used directly in the location probability models for landing and takeoff overruns. No adjustments are necessary to the distances en- tered into the location models for landing undershoots. To accomplish this, the length of the conventional RSA is modified by a runway length factor (RLF), which is calculated by taking into account the effectiveness of the EMAS in de- celerating a specific type of aircraft. In other words, the length of the conventional RSA is increased to provide an equivalent distance where the aircraft can stop when entering the EMAS bed at a certain speed. Figure E1 shows the schematics of an RSA with EMAS and its equivalent conventional RSA. The relationship between the aircraft deceleration, a, the aircraft speed when entering the RSA, v, and the RSA length, S, is 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 equivalent conventional RSA, it is established that: a S a SEMAS EMAS RSA RSA= [Eq. 2] a v S = 2 2 [Eq. 1] To estimate aEMAS, data provided by ESCO were used as shown next. For aRSA a maximum runway exit speed of v = 70 knots and a standard RSA dimension of S = 1,000 feet was employed in Eq. 1, resulting in aRSA = 2.156 m/s2. The data included the necessary lengths and estimated air- craft performance in terms of the maximum runway exit speed. The study includes values for a spectrum of aircraft models and maximum takeoff weights (MTOW). Table E1 lists the aircraft manufacturers, models, and MTOW that are included in the ESCO data. Table E2 shows the data provided by ESCO. The maximum runway exit speed for all aircrafts models was combined in a single dataset and employed in a regression analysis to generate the model for the maximum runway exit speed (v) in terms of the EMAS length and aircraft MTOW. A total of 84 data points were included in the regression. A logarithmic transformation was performed on the EMAS length and the aircraft weight before performing the analy- sis. The resulting regression equation is listed next, where W is the MTOW of the aircraft in kg and S the EMAS bed length in meters. The R-squared of the linear regression was 0.89, and the standard error was equal to 2.91m/s. Figure E2 shows the re- lationship between the reported ESCO maximum runway exit speeds and the predicted speed values obtained using Eq. 3. The 45-degree angle dashed line represents the equality line between the values. The maximum runway exit speed estimated using the regres- sion equation (Eq. 3), along with the EMAS bed length (SEMAS), was input in Eq. 1 to estimate the deceleration of the RSA with EMAS bed (aEMAS). The runway length factor was then esti- mated as follows: where aRSA is 2.156 m/s2 as explained before. RLF a a EMAS RSA = [Eq. 4] v W S= − ( )+ ( )3 0057 6 8329 31 1482. . log . log [Eq. 3] A P P E N D I X E EMAS

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

E-3 B767 407,000 54 350 27.8 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 CITATION 560 16,300 80 550 41.2 CITATION 560 16,300 77 350 39.6 CITATION 560 16,300 48 120 24.7 CRJ 200 53,000 80 550 41.2 CRJ 200 53,000 80 350 41.2 CRJ 200 53,000 45 120 23.1 CRJ 700 75,000 80 550 41.2 CRJ 700 75,000 77 350 39.6 CRJ 700 75,000 41 120 21.1 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 Aircraft Weight (lb) Speed(knots) EMAS (feet) Speed (m/s) A319(B737) 141,000 80 550 41.2 A319(B737) 141,000 79 350 40.6 A319(B737) 141,000 40 120 20.6 A320(B737) 162,000 80 550 41.2 A320(B737) 162,000 75 350 38.6 A320(B737) 162,000 37 120 19.0 A340 567,000 70 550 36.0 A340 567,000 50 350 25.7 A340 567,000 28 120 14.4 B747 870,000 66 550 34.0 B747 870,000 47 350 24.2 B747 870,000 29 120 14.9 B757 255,000 80 550 41.2 B757 255,000 58 350 29.8 B757 255,000 31 120 15.9 B767 407,000 75 550 38.6 Table E2. Data provided by ESCO. 0 5 10 15 20 25 30 35 40 45 50 0 10 20 30 40 50 Reported max speed entering EMAS bed (m/s) Pr ed ic te d m ax sp ee d en te rin g EM A S be d (m /s) Figure E2. Relationship between reported and predicted maximum aircraft speeds entering the EMAS bed. Subsequently, based on the relationship established in Eq. 2, RLF was multiplied by the length of the EMAS bed to estimate the equivalent length of the conventional RSA: Note that, depending on the RSA configuration and the type of aircraft, different operations will generate different RLFs. S a a S RLF SRSA EMAS RSA EMAS EMAS= = g [Eq. 5]

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TRB’s Airport Cooperative Research Program (ACRP) Report 50: Improved Models for Risk Assessment of Runway Safety Areas analyzes aircraft veer-offs, the use of declared distances, the implementation of the Engineered Material Arresting System (EMAS), and the incorporation of a risk approach for consideration of obstacles in or in the vicinity of the runway safety area (RSA).

An interactive risk analysis tool, updated in 2017, quantifies risk and support planning and engineering decisions when determining RSA requirements to meet an acceptable level of safety for various types and sizes of airports. The Runway Safety Area Risk Analysis Version 2.0 (RSARA2) can be downloaded as a zip file. View the installation requirements for more information.

ACRP Report 50 expands on the research presented in ACRP Report 3: Analysis of Aircraft Overruns and Undershoots for Runway Safety Areas. View the Impact on Practice related to this report.

Disclaimer - This software is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences or the Transportation Research Board (collectively “TRB’) be liable for any loss or damage caused by the installation or operations of this product. TRB makes no representation or warrant of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.

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