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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Integrated Noise Model Accuracy for General Aviation Aircraft. Washington, DC: The National Academies Press. doi: 10.17226/22269.
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Page 1
Page 2
Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Integrated Noise Model Accuracy for General Aviation Aircraft. Washington, DC: The National Academies Press. doi: 10.17226/22269.
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Page 2
Page 3
Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Integrated Noise Model Accuracy for General Aviation Aircraft. Washington, DC: The National Academies Press. doi: 10.17226/22269.
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Page 3
Page 4
Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Integrated Noise Model Accuracy for General Aviation Aircraft. Washington, DC: The National Academies Press. doi: 10.17226/22269.
×
Page 4
Page 5
Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Integrated Noise Model Accuracy for General Aviation Aircraft. Washington, DC: The National Academies Press. doi: 10.17226/22269.
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Table 7 Aircraft selected for detailed departure analysis, see Figure 5. ..................................................... 32 Table 8 Aircraft selected for detailed arrival analysis, see Figure 6 ........................................................... 33 Table 9 LJ35 sample size of database by airport ........................................................................................ 35 Table 10 LJ35 measured and modeled departure results summarized ........................................................ 35 Table 11 GLF4 sample size of database by airport ..................................................................................... 38 Table 12 GLF4 measured and modeled departure results summarized ...................................................... 39 Table 13 EA50 sample size of database by airport ..................................................................................... 42 Table 14 EA50 measured and modeled departure results summarized ...................................................... 42 Table 15 C56X sample size of database by airport ..................................................................................... 45 Table 16 C56X measured and modeled arrival results summarized ........................................................... 45 Table 17 GLF5 sample size of database by airport ..................................................................................... 47 Table 18 GLF5 measured and modeled arrival results summarized ........................................................... 47 Table 19 F900 sample size of database by airport ...................................................................................... 49 Table 20 F900 measured and modeled arrival results summarized ............................................................ 49 Table 21 Relative discrepancy due to speed coefficients ............................................................................ 54 Table 22 Standard vs. ATM1 thrust general coefficients ........................................................................... 54 Table 23 Lear35 surrogate aircraft N1 comparisons ................................................................................... 56 Table 24 Lear35 thrust jet coefficients ....................................................................................................... 56 Table 25 GIV noise measured vs. modeled noise levels ............................................................................. 58 Table 26 Lear35 noise measured vs. modeled noise levels ........................................................................ 58 Table 27 CNA560E noise measured vs. modeled noise levels ................................................................... 59 Table 28 INM case.dbf example for standard vs. Initial ATM2 profile ..................................................... 62 Table 29 INM calc_prof_pts.dbf for standard profile ................................................................................. 62 Table 30 INM calc_prof_pts.dbf for ATM2 profile.................................................................................... 63 Table 31 INM prof_pts.dbf data for final ATM2 profile using profile graphs export ............................... 63 Table 32 INM profile.dbf data for final ATM2 profile ............................................................................... 63 Table 33 INM flight.txt data for example ATM2 profile............................................................................ 65 Table 34 INM flight.txt to prof_pts.dbf data mapping................................................................................ 65 Table 35 prof_pts.dbf data for final ATM2 profile using flight path report ............................................... 66 Table 36 GIV Standard Profile ................................................................................................................. H-1 Table 37 GIV ATM1 Profile ..................................................................................................................... H-1 Table 38 GIV ATM Profile Points Profile ................................................................................................. I-1 Table 39 Lear35 ATM Profile Points Profile ............................................................................................. I-1 Table 40 CNA560E ATM Profile Points Profile ....................................................................................... I-2 iv

1 Study Overview and Conclusions Goals 1.1 The original goals of the project were four:  Assess INM Accuracy for General Aviation (GA) Aircraft – How well do INM calculated values of GA aircraft SEL values match measured SEL for selected types of GA aircraft? 1  Identify Causes of Discrepancies – When INM calculated SEL do not agree with measured values, what are the likely causes of these discrepancies?  Identify Potential Solutions – Having identified likely causes of discrepancies, what solutions can be developed generally for GA aircraft that will minimize inaccuracies of modeled results?  Identify Implementation Steps – How should the solutions be implemented Approach 1.2 This final report addresses all goals. Section 3 identifies the total sample of aircraft from which specific aircraft would be selected for detailed analysis. Section 4 uses national flight operations data and aircraft certification levels to compute the discrepancies for each aircraft of the total sample – how much the INM computed Sound Exposure Level of each aircraft differed from that measured by permanent noise monitoring systems at six airports. Section 5 uses the discrepancies to rank-order the aircraft and to identify those that, if realistically modeled in the INM would most improve DNL computations across most airports. Section 6 selected the most important aircraft to examine in detail, and Section 7 described the analysis that identified the causes of error. Section 8 offers and tests two solutions that will correct the GA jet departure profiles and, for the tests, eliminates the errors of the INM modeling. Section 9 describes two approaches that could be used to apply the findings of this study to the GA jet INM database and suggests a single approach. Section 9 also describes approaches and estimated costs for the two approaches. Section 2 describes the state of the practice of modeling GA aircraft through a literature search and a survey of INM users. Results 1.3 1.3.1 General The analysis focused on INM accuracy in modeling operations of GA jets. The study compared INM produced sound exposure levels and climb profiles with measured sound exposure levels and radar reported climb profiles. Modeled jet departures have discrepancies much more significant the modeled arrivals. The over-riding source of error in the INM modeling of GA jet aircraft departures is use of maximum takeoff thrust in the INM rather than the commonly used derated thrust, generally referred to as the “Assumed Temperature Method,” ATM. The report offers in Section 8 two primary solutions to producing the ATM departure for a jet aircraft. A first (called ATM1) is to use manufacturer provided reduced thrust departure data, possibly supplemented with operator information. The preferred data are revised coefficients for the INM-internal performance computation equation (see Equation 1, page 53). Alternative data would include start of takeoff thrust, together with altitudes and amount of changes to 1 SEL is a measure of the total sound energy of a single flyover. It is the basis for computation of DNL. Hence, if the modeled SELs for important aircraft types equal, on average, the SEL of the measurements, then modeled DNL will be an accurate representation of the actual noise exposure, assuming other variables, such as number of operations, flight tracks and runway utilization are realistic. 1

climb thrust which are then used to modify INM departure data. With this approach, it is desirable to have empirical radar climb data and, if possible, noise monitoring data to verify correct modeling of these changed profiles. Section 8 describes this process in detail and successfully applies it to two aircraft: GIV and LEAR35. A second approach (ATM2) is to use the INM directly to develop the ATM departure profile. The approach mimics that used by pilots to select a derated thrust appropriate for a given airport and runway and uses the physics built into the INM. For a specific aircraft, the INM is run at a higher temperature (the assumed temperature) than that used for modeling the airport. (The pilot uses the runway length to determine a derated thrust that produces the maximum safe length of takeoff roll for the runway; the INM uses the assumed temperature to compute the length of takeoff roll.) The resulting fixed profile point procedure is then run again in the INM as a user defined profile at the airport’s modeled temperature (usually an annual average). Radar data would be useful here as well for verification. For modeling, absent radar data, the actual length of takeoff roll used at the airport can be used to compare with the length computed at the assumed temperature. Iterations of the assumed temperature will be required until the modeled takeoff roll matches the actual roll length. This approach was applied successfully to three aircraft: GIV, LEAR35, and the CNA560E. 1.3.2 Specific Sources of discrepancies in INM modeled GA jet departure sound levels are of two related types. The discrepancy is due to INM thrust values that are significantly different from thrust used, and this incorrect thrust in turn not only causes the noise produced to be incorrect, but creates an altitude climb profile that is, for almost all GA jets analyzed, higher than the reality as reported by radar data. These two effects of too high sound levels and too high altitudes interact, and result in the INM produced sound level generally being higher than measured, but it may also be equal to or lower than measured. Higher INM thrust means higher sound level while higher altitude means lower sound level. Thus correcting discrepancies is a balance between lowering thrust and lowering altitude in the INM to match measured data. In this study, GA aircraft were first selected for determining discrepancies using the contribution of each aircraft type to total fleet noise. Aircraft that contributed at least 1% of the total fleet noise were identified, Section 3.4. Section 4 describes how discrepancies were determined and Section 5 gives the discrepancies in decibel effect relative to measured results. Section 6 rank-orders the aircraft in terms of contribution to fleet-wide discrepancies and identifies the ten jet aircraft types most important to correct for modeling accurate departure fleet noise (Figure 5) and for modeling accurate arrival fleet noise (Figure 6). Correcting the ten jet aircraft departures would improve fleet departure noise accuracy by up to 2.5 dB and correcting the 5 arrival aircraft would improve fleet arrival noise by up to 1 dB. Section 7 examines three of the ten jet departure aircraft types and three of the five arrival aircraft to determine the details of the causes of the errors, and to suggest solutions. Because the departures result in the most significant errors, and have the greatest potential for improving INM accuracy, the remainder of the analysis focuses on solutions for the departure types. Through conversations and information from pilots and working with Gulfstream staff, incorporation of Assumed Temperature Method (ATM) departures was identified as the proper solution for correcting the departure discrepancies. Sufficient information was collected on the Gulfstream 4, the Lear 35 and the Cessna Citation 5502 to test two ATM methods that could be used to provide corrected input into the 2 The report notes that both Cessna pilot data and communications with the Cessna manufacturer indicated that Cessna does not use reduced power departures. The radar data however, when compared with the INM standard maximum power takeoff profile, show a more gradual climb profile. The ATM procedure as tested with the INM in Section 8 and shown in Figure 30 resulted in a match of both profile and noise levels with the measured data. 2

INM. The two ATM methods, ATM1 and ATM2, described briefly above in Section 1.3.1and in detail in Section 8 both show promise, but this study recommends that ATM2 be implemented as a modeling procedure for INM users, Section 9. It requires less information than ATM1, uses the strengths of the INM (proper physics including aircraft departure performance response to changes in temperature and altitude), and the information that is required (typical length of takeoff roll at the airport) can be acquired at the airport being modeled. ATM1 requires a detailed and lengthy effort, contacting the manufacturers of each of the ten important aircraft types, six of which are no longer manufactured, or surveying pilots of each aircraft type to determine use of thrust settings on departure, locations / altitudes of cutbacks, and generally full development of either the INM equation coefficients, or a universal standard profile to be applied nationally to all GA jet operations of the ten aircraft types. The most efficient would be if manufacturers could provide the necessary equation coefficients. Then modeling the derated thrust departures would be a process similar to modeling the standard maximum thrust departures. This study’s experience of developing and applying ATM1 leads to the conclusion that the costs of development including the need to find methods for validating the profiles suggest the simpler ATM2 is the best method to implement. ATM2 implementation is recommended to be a procedure followed by an INM modeler. The procedure will guide the modeler through the steps of using the INM to produce the assumed temperature (derated thrust) takeoff procedure. The procedure will reference specific files in the INM that provide the data for input into the final modeling of the airport. As suggested above, the procedure will direct the user to choose an assumed temperature for the aircraft, run the INM for that temperature, identify the resultant profile points, input them into the INM and run at the temperature appropriate for the airport. In the INM files from this second run, the modeler will find the takeoff roll length that results and compare that length with actual lengths of takeoffs at the airport. If the INM length is not within an identified margin of error of the actual length, the user will change the temperature (increase if the modeled length is too short, decrease if the modeled length is too long) and repeat the process until an acceptable modeled takeoff roll length is found. Development of the ATM2 procedure will first require testing that procedure on the remaining seven identified aircraft types, the other three having been tested as described in Section 8.2.2. In these tests, altitude and sound level will be compared with the radar and sound monitoring data available from the present study. The goal is to further validate the procedure and, most importantly, identify any issues with the noise database for each aircraft. As described in Section 8.3, the ATM tests on the Lear 35 showed that, almost certainly, the incorrect engine type was being used for that aircraft in the INM database. If such is the case for any of the other aircraft types, the issue needs to be corrected if a viable ATM2 procedure is to be provided to INM users. 1.3.3 Conclusions Discrepancies in INM modeling of GA jets result of over-estimation of average fleet departure noise exposure by about 3 dB and of arrival noise exposure by about 1 ¼ dB. Correction of the INM inputs of ten jet departures will eliminate about 2 ½ dB of the departure discrepancy and correction of five jet arrivals will eliminate about 1 dB of the arrival discrepancy. The analysis focuses on correcting the GA jet departure procedures. Two identified methods, ATM1 and ATM2, based on actual pilot procedures for conducting reduced thrust departures, are described and tested. Though both result in realistic departure profiles and sound levels, ATM1 requires involvement with manufacturers and possibly pilots and will be time consuming to develop, the other, ATM2, uses the INM to produce the best departure profile by choosing a correct temperature adjustment. 3

Though many factors other than use of thrust can affect aircraft departure operations and hence climb rates and sound levels, it is the use of thrust that has the most effect in performance. Use of flaps, drag coefficient, airspeed, aircraft weight and pressure altitude all can affect performance. However, these factors have generally been included in the INM computations, and using the ATM2 procedure takes full advantage of these factors to the extent they are included in the INM. Further, errors in these other factors have minimal effect on computed results.3 A final note is that commercial jet departure operations commonly use reduced or derated thrust. Two other ACRP studies, 02-55, Enhanced AEDT Modeling of Aircraft Arrival and Departure Profiles, and 02-41, Estimating Takeoff Thrust Settings for Airport Emissions Inventories, are examining current takeoff thrust procedures. Eventually, some standardization across all jet aircraft reduced thrust departures could be thought desirable, though from the findings of this study, the possibility of consistency is judged remote. Commercial jet aircraft continuously record all engine and flight parameters, providing the types of data pursued in this study. GA jets rarely have on-board equipment to record such data, and hence the techniques for developing appropriate departure profiles will for the foreseeable future be very different for GA jets and commercial jets. 3 A sensitivity analysis of Equation 1 showed possible variations in the speed and altitude had little effect on total thrust. 4

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TRB’s Airport Cooperative Research Program (ACRP) Web-Only Document 19: Integrated Noise Model Accuracy for General Aviation Aircraft assesses the predictive accuracy of the Integrated Noise Model, identifies causes for deviations between actual and predicted values, identifies potential solutions to improve the model’s accuracy, and describes the steps needed for implementation

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