Aircraft noise level prediction in the vicinity of Lisbon Airport

Transcription

1 1 Aircraft noise level prediction in the vicinity of Lisbon Airport Gonçalo S. D. Correia Departamento de Engenharia Aeroespacial; IST - Instituto Superior Técnico, Lisbon, September 2011 Abstract Aircraft noise is one of the main contributors for the population s discomfort, as its occurrence is directly linked with diverse health hazards. It is therefore imperative to find reliable and low cost methods of noise mitigation, preserving the amount of aircraft operations needed from a normal acting airport. Being so, the current thesis objective is the prediction of noise levels from the aeronautical sector in the vicinity of Lisbon s Airport. Following the conclusions of the european projects Harmonoise and Imagine, which relies in a new methodology of noise assessment, separating the noise s source description from its propagation, a computational model was implemented which allowed the sound levels prognosis of an Airbus A320 landing in two distinct locations in the airport s proximity. Terrain topography and meteorological events also play an important role in the noise s quantification. In order to be possible to establish a comparison between the values from the theoretical model and reality, an experimental validation was undertaken where sound measurements were obtained with the help of a sound analyzer. The results from the model stood at levels close to those achieved through the measurements, implying the method s reliability in the evaluation of noise from aeronautical origins. Fundamentally, the effectiveness of this new approach to the problem has been verified, since there is no need for much technical resources nor unlimited processing time to estimate noise levels. Last but not least, some new routes of improvement are explicited regarding a facilitation in the prediction of these values. Key Words: Imagine, Noise, Lisbon Airport, Landing, A320, Source and propagation separation I. INTRODUCTION Air traffic has been increasing in the last decades and it is expected to continue to do so throughout the next twenty years. In order to achieve sustainability in this growth, it is necessary to reduce the impact that air traffic holds on the surrounding population, being CO 2 emissions or excessive noise, just to name a few examples. This objective can be reached by restricting the number of airborne operations, executing a change in the type of aircrafts, or modifying the operational procedures. The two former points are harder to accomplish since it is not desirable to decrease the frequency of aircrafts operations to a profitable market, nor it is possible to substitute airships without having a revolutionary breakthrough in the construction methods - at an aerodynamical level or in new engines design. Therefore, the latter option presents itself as the best one. To fulfill this goal it is necessary to possess a correct description of the nature of an event, in this case, the noise levels produced by an aircraft landing or taking off. Nowadays, aircraft noise poses as one of the main contributors to the population s discomfort. There are studies that relate the intensification of cardiovascular diseases with an exposure to aircraft and automobile noise. Local communities also tend to report their annoyance towards this type of noise, for example, by asking for route alterations in the aproximation corridors, the exclusion of certain aircrafts or even the settlement of curfew hours in which no airplane can operate. Thus, it has become essential to devise new noise mitigation techniques, where the correct noise levels are predicted in a simple, efficient and non-time consuming way. The work developed aims to predict the noise levels originated from the aeronautical sector in the vicinity of Lisbon s Airport. Following the results of the European projects Harmonoise and Imagine, the source s noise description is separated from its propagation allowing for a different characterization of an aircraft event, be it a landing or a take-off. Real life measurements taken in two different locations in the Lisbon area are compared with simulated ones in order to perceive the new model s quality in the noise assessment. Finally, some recommendations are provided regarding future studies in this field. This article is divided in six sections. In section II, a detailed explanation of the main conclusions and breakthroughs of the European models is provided. section III shows the computacional construction of the theoretical model : explaining the equations behind the flighpath segmentation, the source s noise description and the different factors that interact with it, the importance of the meteorological conditions and the new approach to noise propagation. In section IV, the results from the measurements are explicited and discussed. Next, section V presents the results from the computational model and a comparison is carried out with those from the previous section. Finally, in section VI, conclusions are taken and

2 2 further work on this subject in proposed. II. ACOUSTIC SOURCES AND SOUND ATMOSPHERE PROPAGATION According to directive 2002/49/EC 1, European State Members are obliged to produced noise maps of certain important locations until This way, the projects Harmonoise and Imagine were developed; the former aims to create a consistent method for noise prediction and quantification from different sources, mainly roads and railroads and the latter extends its findings to a different type of sources - aviation and industry related. Basically, the methods consist in a detachment between the source s and propagation descriptions. Separating these concepts allows for the creation of a generic model of sound propagation, thus enabling the easiness of sound mitigation by modifying the source or altering the propagation path. R. Bütikofer [1] describes the Imagine project as follows : This model calls for a detailed source description, for instance using 1/3 octave band sound levels in function of longitudinal and lateral angles for various power settings for departure as well as for approach. Another topic is to adapt the propagation algorithms established in the EC5 program HARMONOISE for propagation from earth bound sources to high elevation angles of sound incidence up to the vertical sound incidence of a flyover situation. A. Source description and characterisation In an aircraft, the noise is not originated from a single souce; instead, it is linked with a combination of different mechanisms (fans, fuselage, turbines) where each one has a specific directivity and power spectrum. As most of the instalation effects are not yet fully understood, there is no difference (in the project context) between the source region and the region outside the immediate vicinity of the source. Hence, phenomena like diffraction or reflexion are considered to be an intrisic property of the aircraft. B. Source strength Usually, aircraft noise is determined through a series of measurements directly under the flightpath and at a fixed lateral distance considering reference conditions, constant flight speed and plain terrains. Afterwards, these measurements are transformed in NPD tables which take 1 Directive 2002/49/EC from the European Parliament and Counsil, June , regardind the ambient noise evaluation and management, JO L 189, into account the effect of atmospheric attenuation and receiver-source distance. One has to bear in mind that these relationships may lead to erroneous results since they are established using specific engine configurations at a given moment. In a flight phase, when the main contributor for noise does not involve the engines, the flight speed, flap position and landing gear assume a significative importance that are not mentioned in these calculations. C. Source directivity Sound radiation is not uniform, as it varies in intensity and frequency, essentially due to: Each entity responsible for sound generation possess a frequency dependent directivity - there is a clear difference between low and high frequencies in jets, where the latter exhibit no noise creation at downstream and the former exhibit a maximum in this direction. The importance of the different sources in sound generation is strongly linked with the flight phase (take-off, landing, etc) and the combination of all the mechanisms. It is also important to comprehend that there is a gap between the directivity measured when the aircraft is airborne versus stationary. The flight speed and the air flux all contribute to this problem. D. Source position Obviously, the source is not static. As the flightpath construction was based in theoretical operational procedures, it is normal that the actual flightpath flown by the aircraft differs from the previous; security limitations, meteorological conditions or air space restrictions are the reasons for this condition to occur. Despite this fact, the model can always be adapted to fit reality better. E. Topography The topography between the noise s source and the receiver s position has a direct effect in the intensity of the measured sound, as it affects the propagation attenuation between both. The introduction of small hills and mounts, as well as the type of soil/ground travelled by the sound rays, produces a substantial attenuation in the sound measurement. One must not forget the consequences of building induced phenomena, such as shielding and reflection effects, in the final results. Finally, meteorological conditions also play a key role, since they are responsible for the definition of sound profiles. Special care must be taken when executing the measurements in order to comply with the project demands.

3 3 The composition of the Imagine project [2] is as follows: 1) Construction of an adequate flighpath to the airport and aircraft in study 2) Data colection, namely from: a) Noise source description: i) Speed estimation throughout the flightpath ii) Engine thrust evaluation iii) Flight phase determination (landing / take-off) iv) Directivity b) Meteorology i) Simplified model relating the meteorological conditions with pre-establisehed values c) Topography i) Analysis for substancial topological variations in the study area ii) Resistivity/ground impedance, based in classes for a limited number of soils type 3) Propagation model a) Derived from flightpath segmentation theories and an estimation model for the speed gradient effects in sound propagation The model structure was elaborated according to the norm ISO and employs the spectral emission for a frequency band f : L p,i (r)=l W,i ( f )+D c ( f ) 10log(4πr 2 ) A i ( f,r) (1) = L W,i ( f )+D c ( f ) 11 20log(r) a lu,i r A excess (r, f ) where L W,i ( f ): corresponds to the source power level measured in the receiver for a frequency band f L p,i (r) : corresponds to the sound pressure level for a frequency band f D c ( f ) : is the directivity correction for a frequency band f. It describes the angular variation of the sound emission 10log(4πr 2 ) : is the geometrical attenuation due to the spherical sound emission A i (r, f ): corresponds to a frequency band f attenuation measured from the point source to the receiver. Here it is included: A excess (r i, f ): is the excess attenuation for a source at the position i in the frequency band f. It includes the ground reflexions perceived in the receiver for a determined source height, the diffraction suffered by the sound rays and the scattering effect. The excess attenuation is calculated using the previous engineering model for a point source in the beginning of each segment. In order to achieve reliable results, the excess attenuation must vary slowly regarding the source s position in the trajectory. a lu,i : corresponds to the air absorption for a distance r i and a frequency band f, intended for a specific temperature and humidity. In this work, the norm Air Absorption SAE 1845 was applied. In the Imagine project, the intermediate term L W,dir = L W + D c is used and called sound power including directivity. It is derived from the previous equation and employed for all 1/3 octave frequencies. Simply, it refers to the sound power spectrum from a specified direction of emission and for well defined operational conditions. III. MODEL CONSTRUCTION AND INTEGRATION The work follows the principles described in the 2nd volume of 29 document ECAC.CEAC [3]. It uses a segmentation method (instead of simulation one, mainly for computational time) that relies on an exaustive database of noise and performance for aeronautical vehicles (ANP - Aircraft Noise and Performance [4]), compiled by the industrie and noise regulators, available online. Segmentation can be described as the model s adaptation process to an ideal infinite path of NPD 2 relationships, aiming to calculate the noise levels for a receiver observing a flightpath where the aircraft configurations are constantly mutating. In order to the sound evaluation to be possible, the flightpath is represented by a series of continuous straight segments, that can be seen as finite parts of an infinite path. Each segment is described by the geometrical coordinates of its final points, speed and engine parameters. A. Flightpath construction The tridimensional path of an aircraft determines the radiation and propagation geometrical aspects between it and an observer. The flightpath is divided in two different stages: horizontally, it s defined by straight lines with specific distances to the next curve, these being described by the angle and radius - ground track; vertically, the segments are caracterized by the required distance to achieve predetermined speed configurations or altitude, according to the power supplied and flap positioning - flight profile. The vertical coordinates are called profile points. Local coordinate system: The local coordinate system (x,y,z) is a Cartesian one and has its origin in the landing strip beginning at the point (0,0,0). The axis Z concerns with the reference altitude, being z=0 the ground soil. The receiver is defined in local coordinates. 2 NPD - Noise Power Distance

4 4 n TO = int(1 +V TO /10) (4) where the chance in velocity along a segment is V = V TO /n TO (5) and the t on each segment Figure 1. Local coordinate system Aircraft coordinate system: The aircraft coordinate system is also a Cartesian one and has its origin in the actual flight position of the aircraft. It is define by: γ- climb angle, ξ -flight direction, and εbank angle. Figure 2. Aircraft coordinate system Takeoff ground roll segmentation: When taking off, as an aircraft accelerates between the point of brake release and the point of lift-off, the speed varies intensively. The real take-off distance is aproximated by a distance s TO8, which assumes frontal wind velocity of 8 knots and it s define by: s TO8 = B 8 θ (W/δ) 2 (2) N (F n /δ) where B 8 is a coefficient appropriate to a specific aeroplane/flap-deflection combination for the ISA reference conditions (ft/lbf), W is the aeroplane gross weight at brake release (lbf) and N is the number of engines supplying thrust. Net thrust represents the component of engine gross thrust that is available for propulsion. For acoustical calculations, the net thrust is referred to standard air pressure at mean sea level - corrected net thrust (F n /δ) Fn δ = E + F V C + G A h + G B h 2 + H T (3) where F n is the net thrust per engine (lbf), δ is the ratio of the ambient air pressure at the aeroplane to the stardard air pressure at mean sea level, V C is the calibrated airspeed (kt), T is the ambient air temperature in which the aeroplane is operating (ºC), and E, F, G A, G B, H are engine thrust coefficients for the temperatures below the engine flat rating temperature at the thrust rating in use (lb.s/ft, lb/ft, lb/ft 2, lb/ºc). Having S TO8, the segmentation is trivial. Assuming V TO = 85m/s, the segment number n TO is: t = 2 s TO V TO n TO (6) The length s TO,k of segment k (1 k n TO ) of the takeoff roll is then s TO,k =(k 0,5) V t (7) Initial climb segmentation: After takeoff, the geometry changes rapidly. Studies show that a single climb segment results in a poor aproximation in the perceived noise levels. Being so, the initial climb segment must be sub-segmented based on the following set of height values: z = {18.9, 41.5, 68.3, 102.1, 147.5, 214.9, 334.9, 609.6, } Using the ANP database, the final segment of the initial climb is located at z = 1000 ft, thus using, z i = z[z i /z N ](i = 1...N) (8) where z is the original segment end height, z i is the i th member of the set of height values and z N is the closest upper bound to height z, is possible to produce reliable results without the manipulation of short segments. The average geometrical climb angle is found by : γ = arcsin K N FN/δ W/δ R cosε where K is a speed-dependent constant equal to 1.01 when V C 200kt or 0.95 otherwise. It accounts for the effects of climbing with an 8-knot headwind and the acceleration inherent in climbing at constant CAS. The distance the aircraft travels since the runway s end until the last segment is expressed by: s = (h 2 h 1 ) tanγ (9) (10) Landing segmentation: The ANP database supplies default landing points, where the aircraft speed, power configuration, height and distance travelled are explicited in table I.

5 5 we are concerned with the Airbus A320, the directivity was catalogued in d4 classe and is as follows: Table I DEFAULT POINTS PROFILE FOR LANDING Table II DIRECTIVITY CLASS An equation based landing was also developed, where the descent angle γ is considered constant and equal to -3º, for jet airplanes. The horizontal distance is given by: As = h descent tanγ (11) where h descent = m, as seen in ANP database. The descent segments are formed by reversing the previous equations, creating symmetrical points to those found. Both modeling form different sets of flightpaths. B. Noise source definition There are two coordinate systems regardind the noise s source: one fixed to the aircraft and another fixed to the ground. Figure 3. Aircraft coordinates for sound s emission Aircraft coordinates: The longitudinal angle θ and the lateral angle ϕ are defined in relation to the aircraft. The origin is at the centre of gravity of the aircraft. θ is define from the axis of flight to the vector pointing towards the receiver. It varies from 0º to 180º. ϕ is defined between two planes: Plane a) is defined by the axis of flight and the vector pointing out of the bottom of the aircraft, perpendicular to the wing-plane; Plane b) is defined by the axis of flight and the vector from the aircraft to receiver. Ground coordinates: The parameters in ground coodinates are the distance r, the elevation angle β and the corresponding height of the aircraft. Directivity: One understands directivity as a measurement of a source s noise radiation pattern that indicates the amount of energy discharged in a determined direction. Measurements made by Empa [5] allowed for the classification of directivity into classes. As in this work, Reverse engineering from NPD relations: NPD relationships can be found in the ANP database. For different power configurations, these relations indicate an event noise level for ten pre-established propagation distances - 200, 400, 630, 1000, 4000, 6300, 10000, 16000, ft. Each combination of engine/aircraft is associated with a spectral class for landing and takeoff. The high frequencies are strongly attenuated for long distances, opposed of what happens for the low ones. Knowing the spectral class of a determined aircraft, it is possible to reconstruct its A-weighted spectrum. In order to estimate the sound power s spherical spectrum, L w,dir, one carries out the following steps: 1) Using the Excel file Tool to estimate the source emission spectrum (Sound power Lw) for the vertical flyover, based on NPD-SEL data provided by the authors of the Imagine project, the leveltime history of a flyover is calculated (caution must be exerted, using variable length segments that are seen from the receiver under constant angle increments of 2,5º, for 10º<θ < 160º). After this estimation, the longitudinal directivity is added. 2) In an iterative loop, the spectrum is optimised to produce the best fit for the SEL values for all the 10 distances of the NPD. The user also works with a variable in db, using it to shift the standard deviation towards zero. 3) After having found the optimal spectrum, it is converted to a linear spectrum by removing the A-filter. 4) Aiming the conversion to free field conditions, the ground interference is subtracted from the source spectrum. 5) The spectrum is converted to sound power L w,dir adding 11 db. 6) Finally, the number of engines N is accounted for by adding 10log(N) to the final result. In sum, the calculus is : FinalSpectrum = EstimatedSpectrum + constant A f ilter Grounde f f ect log(enginenumber) The final spectrum exhibits the average sound emission Lmax. Noise variations from the fan and jet, as well as the Doppler effect, are not accounted for. It is

6 6 also assumed, for simplification reasons, that the final spectrum is applicable to all longitudinal directions; despite the wrongness of this assumption, it is tolerable since it produces valid results. C. Propagation The point-to-point (P2P) propagation model [6] describes the sound s propagation through a pre-defined path from a point source to a receiver, in which meteorological conditions play an important role. The model accounts for reflexions in barriers/buildings, obstacle diffraction that blocks LOS, incertainty in heights (both from the source and receiver), turbulence, and sound speed variation. In this work, the Harmonoise Demonstration Software was made availabe by the authors. Meteorological effects: Noise from high sources propagates through a vast atmosphere layer - here only the last 1000 meters are considered [7]. As this is an engineering model, it is expected that the aproximations to speed and temperature profiles are of simple use, sufficient accuracy and great computational speed. To start, meteorological parameters are put in predefined tables [8] and consist in: hence in the flight profiles, e.g. as the temperature rises, the aircraft will climb slower than otherwise. To account for this effect and the consequent curving of sound rays, the model shifts the curvature for the ground, considering the ray path propagation as being straight. This also reduces computational resources without damaging the final results. The sound speed profile are assumed being lin-log type, defined by: c(z)=c 0 + A z + B log(1 + z z 0 ) (12) The constants A and B are expressed by; which in turn, are found using: A W = kl u A T =( 1 c 0 2 T 0 )(0.74 T A = A T + A W (13) B = B T + B W (14) kl g c p ) day(stability classes S1, S2, S3) (15) Table III WIND SPEED AND OKTA LEVEL CLASSIFICATION A W = 4.7 kl u A T =( 1 c 0 2 T 0 )(4.7 T kl g night (stability classes S4, S5) c p ) (16) B W = u cosϕ k B T =( 1 c 0 2 T 0 )(0.74 T k ) (17) Table IV MONIN-OBUKHOV INVERSE DISTANCE AND TEMPERATURE SCALE BOTH ESTIMATED IN FUNCTION OF WIND SPEED AND STABILITY CLASS The following parameters are : k=0.4 - Von-Karman constant, g = 9.81m/s 2 - gravity acceleration, c p = 1005Jkg 1 K 1 - air specific heat at constant pressure, T 0 = 273K, c 0 = 331.4m/s - sound speed at T 0 = 273K. The ground curving radius, which simulates the effects of sound propagation is expressed by: If B > 0: 1 R A = A c 0 (18) 1 = 8 B (19) R B D sr 2πc 0 Table V FRICTION SPEED ESTIMATED IN FUNCTION OF WIND SPEED CLASSES Meteorological parameters influence the aircraft s noise received on the ground not only through propagation effects; Temperature, amospheric pressure or wind speed have an influence on the aircraft s performance, Otherwise: Which results in: 1 = B (20) R B c 0 Z sr 1 R = 1 R A + 1 R B (21)

7 7 where D sr is the distance between the source and the receiver, measured in the horizontal plane, and Z sr = (Z s+z r ) 2 represents the medium height of the path s propagation above ground. Ground impedance: In order to describe the accoustic impedance of the ground, it was used the model developed by Delany and Bazley [9], where σ corresponds to the effective flow resistivty. Default values are presented in table VI. the probability of an event s ocurrence from this aircraft is significantly larger than others. The objective was to quantify the parameter L AE Sound ExposureLevel in each landing event. Using data from ANA - Aeroportos de Portugal 3, that provided a list of pre established slots for the scheduled days, and with the help of the website flightradar24, where one can track the aircrafts navigating through the national territory in real time, an elaboration of a landing calendar was made possible. Here, the flights are discriminated - aircraft type, flight number, air company and flight schedule - and so are the measurements results - L AE. Since not all the flights matter for the calculation, only those that correspond to an Airbus A320 are exhibited. Table VI GROUND IMPEDANCE IV. MEASUREMENTS RESULTS Measurements were undertaken in two different Lisbon locations with the help of a Hand-helf Analyzer Type 2250 device. The first location, in a top of a building on the Duque de Ávila Avenue, was used for test measurements and the second one, closer to the landing strip, was used for model validation. The former were measured on June 24th and the latter, on June 26th. Table IX FLIGHT SCHEDULE AND SEL MEASUREMENTS JUNE 24TH Table X FLIGHT SCHEDULE AND SEL MEASUREMENTS JUNE 26TH Table VII EXACT LOCATION OF THE MEASUREMENT POINTS The measurements spectrum are also interesting and can be seen at Figure 4 and 5. Using information from the portuguese website of Instituto de Meterologia de Portugal [10], one was able to extract the following information, regarding meteorological conditions: Table VIII ATMOSPHERIC CONDITIONS PRESENT AT THE MEASUREMENTS TIME Figure 4. Spectrum for the measurements of day 26 According to a study from Universidade do Minho, the Airbus A320 is the most representative airship in terms of air traffic usage for the Lisbon s Airport. This way, the study was focused in this particular airplane since 3 ANA - Public portuguese company which primary goal is the effective management of the aeronautical infrastructures given

8 8 Figure 5. Spectrum for the measurements of day 24 Figure 7. Graphic representation of an A320 s landing using the equations modeling It is observable in figure 4 the steadiness of standard measurements; i.e., the standard measurements are very similar throughout the entirety of the spectrum, except for a small discrepancy (± 5dB) for higher frequencies. The landing measurements are also quite alike, varying about 5 db among one another, but towards higher frequencies their behaviour tends to become erratic, as can be seen in measurement nº 10, that acts like an averaging spectrum between the other two. A. Meteorological effects and ground impedance Given the conditions established in table XI and bearing in mind the equations defined in III-C, the two locations were classified as : V. MODEL RESULTS Table XI METEOROLOGICAL CHARACTERISTICS CLASSIFICATION FOR THE DIFFERENTE LOCATIONS As mentioned before, two different landings were simulated: one that takes into account the default profile points contained in the ANP database for the A320 aircraft, and the other that uses mathematical equations intended for creating a flightpath. Although both exhibit a rather long route, one limited the revelant segments to those included in a 10.5 km radius area which has its origin in the landing strip. Where the distance between the segments was found to be superior to 2500 meters, an extra segment was included in order to present a more realistic and coherent flightpath. The difference in the classification resides in the fact that the building s top was mainly constituted from asphalt, whereas in the ISCTE location one was situated on a parking lot. Knowing the preponderant effect that meteorology has in the sound profile s definition (through A and B constants), one was able to characterize the segments as: Table XII CONSTANTS A AND B QUANTIFICATION DEPENDING ON THE OBSERVER S LOCATION Figure 6. Graphic representation of an A320 s landing using the default profile points modeling Constant s B variation is to be expected, since its genesis is related to the angle ϕ, whose diversity is strictly linked with the aircraft movement in relation to the observer.

9 9 B. Propagation The propagation s results were obtained with the Harmonoise Demonstration Software and the data from previous sections. One tried to replicate the most relevant topographical conditions with obvious limitations. C. Source s Spectrum The source s spectrum was acquired using the provided file Tool to estimate the source emission spectrum (Sound power Lw) for the vertical flyover, based on NPD-SEL data. While trying to comply with the methods process described in III-B, one notes the inclusion of a constant that can be manipulated by the modeler. It aims to adjust the estimated spectrum, in order to minimize the difference between the original NPD relations and the calculated ones. One tried to diminish the standard deviation of these relations. The achieved spectrum is below. Figure 8. A-filter Source s spectrum obtained with (blue) and without (red) D. Model concatenation The sound spectrum of each segment is computed the following way: 1. Bearing in mind the contribution from the noise s source, it is added the excess attenuation described before (the A-filter is taken from as it is already included in the demo) 2. The attenuation from the different propagation distances is subtracted using the inverse square law. A suppression of 11 db is also applied since the source is considered omnidirectional 3. The attenuation from the air absorption is also subtracted using the SAE 1845 norm 4. Finally, the decibel level per segment is expressed by L i = 10lg (L i,k+w k ) k where L i,k represents the db level for a specific segment i of spectral level k, W k represents the A-filter weigth for the k frequency and L i represents the total db of a segment i, considering the A-filter This way, extending the calculation method to the two distinct locations and different flightpaths, one gathered the following results: Table XIII SEL FROM THE RESULTS REGARDING THE DIFFERENT LOCATIONS AND FLIGHTPATHS Table XIV SEL FROM THE MEASUREMENTS According to the Imagine s project reports [11][12][13][14], the obtained results are satisfactory, as it is usual to occur discrepancies among the measurements and the predictions, tipically around 5 db for distances superior to 1000 meters. The flightpath modeling that uses the default profile points provides noise levels a bit lower (about 2,5 db) than the equation s modeling. As there is not a substantial differente amidst the two simulations, it is unquestionable easier to access the pre-established data present in the ANP database. Yet, one needs to be careful doing so; Lisbon s Airport is a type of airport where its main conditions and characteristics are effortless to reply. In other airports, namely the Aeroporto International de El Alto in Bolivia, this may not be the case. The disparity between results may have its origin in the fact that the parameter Thrust in the file provided Tool to estimate the source emission spectrum (Sound power Lw) for the vertical flyover, based on NPD-SEL data does not modify the source s spectrum in any way, which is known to be incorrect. Evidently, a change in the thrust the aircraft produces during landing has an effect in the noise s production, either increasing or decreasing. Despite this, the error is assumed to be small since the theoretical results match the measurements. Other possible source of error may be related to the deficient topographical definition from the locations where measurementes were made. In the time available to compile this work, it was not feasible to perfectly assess the topography in the propagation s planes, as it would require special authorizations for measurements that were not defined as well as an extensive crew able to perform those measurements. Finally, it is interesting to observe the spectrum that compares the theoretical results and the measurements made. At first glance, it is easy to evaluate the obvious

10 10 imbalance between the two. For higher frequencies, the difference can be explained resorting to the ambiance noise, that increases the registered noise level despite not having its origin in the airship. As for the lower frequencies, the model overshoots the measurements by more than 20 db, thus making them unreliable for data extraction. It is concluded that the model must be used strictly has a tool to find the sound exposure level of an event, being it a landing or a takeoff. The merit of both projects is clear; with reasonable ease in the landing s modeling (as it is thoroughly available in the ANP database) and few effort required it is possible to obtain correct data about the sound level in a region encompassing the Lisbon Airport. With the correct motivation, the entire city s mapping is desirable; not only the aeronautical noise but also the one whose origin is linked with automobiles and industry. It is also recommended that all the files and programs be compiled together, always looking for their expansion and inclusion of more detailed aspects such as unusual building facades, different grounds topography or specific construction materials - this way the noise calculation can be facilitated while speeding the process. Figure 9. Simulation spectrum obtained with the default profile points and the receiver positioned in the ISCTE s parking lot VI. CONCLUSIONS AND RECOMMENDATIONS This work main objective was to predict the noise levels originated from the aeronautical area in the vicinity of Lisbon s Airport. In order to do so, the main conclusions from the European projects Harmonoise and Imagine were applied. Through the Eurocontrol Experimental Centre, which contains the ANP database previously mentioned, it was possible to extract the majority of the data required to develop the project. Two distinct landing s models of the aircraft A320 were created aiming to observe the sound levels variation between each other. Afterwards, post processing the data was expected, concentrating in : the distance between source and receiver, atmospheric absorption and the excess attenuation calculated with the aid of the demo Harmonoise Demonstration Software. In two different occasions, measurements were recorded with the aid of the Hand-held Analyzer Type 2250, where one tried to obtain relevant information regarding the aircrafts circling the airport and waiting to land, in a given moment. Although both measurements were included, one should consider the measurements from June 26th as more reliable ones, since they were taken carefully on the weekend (implying a lower noise ambiance which does not have its origin on the aircraft). The two different simulations yielded good results, according to the Imagine project, as they were able to predict with relative accuracy the noise levels in the airport s vicinity. There is pratically no distinction between the modeling type used, as this decision can be ultimately be left for the modeler. REFERENCES [1] R. Bütikofer. Concepts of aircraft noise calculations. Acta Acustica United with Acustica, Vol 93 (2007) [2] R. Parchen, F. de Roo, E. Salomons : IMAGINE WP 4- Aircraft sound sources, Task Modelling principles and lay-out, IMAGINE report no. IMA41TR TNO10, January 2006 [3] European Civil Aviation Conference (ECAC): Report on Standard Method of Computing Noise Contours around Civil Airports. Volume 2: Technical Guide. ECAC.CEAC Doc.29, 3rd Edition, December 2005 [4] Aircraft Noise and Performance (ANP) database : [5] R. Bütikofer: IMAGINE - Default aircraft source description and methods to assess source data Deliverable 10 of the IMAGINE project, IMAGINE report no. IMA4DR EMPA-10, December 2006 [6] D. van Maercke, J. Defrance. Development of an Analytical Model for Outdoor Sound Propagation Within the Harmonoise Project. Acta Acustica United with Acustica, Vol 93 (2007) [7] D. Heimann, F. de Roo, E. Salomons, P. Hullah : IMAG- INE - Reference and Engineering Models for Aircraft Noise Sources, Volume 1, IMAGINE report no. IMA4DR EEC- 10, March 2007 [8] B. Hemsworth : IMAGINE - Determination of Lden by calculation - definition of meteorogical classes - extra document, IMAGINE report no. IMA010TR DeltaRail10, January 2007 [9] M. Delany, E. Bazley :Acoustical properties of fibrous absorbant materials, Applied Acoustics. 3, (1970) [10] Instituto de Metereologia, IP Portugal: (6 de Julho 2011) [11] D. Heimann, F. de Roo, E. Salomons, P. Hullah : IMAGINE - Reference and Engineering Models for Aircraft Noise Sources, Volume 2 - Validation, IMAGINE report no. IMA4DR EEC-10, March 2007 [12] D. Heimann, F. de Roo, E. Salomons, P. Hullah : IMAGINE - Reference and Engineering Models for Aircraft Noise Sources, Volume 3a - Appendix 1, IMAGINE report no. IMA4DR EEC-10, March 2007 [13] D. Heimann, F. de Roo, E. Salomons, P. Hullah : IMAGINE - Reference and Engineering Models for Aircraft Noise Sources, Volume 3b - Appendix 2, IMAGINE report no. IMA4DR EEC-10, March 2007 [14] D. Heimann, F. de Roo, E. Salomons, P. Hullah : IMAGINE - Reference and Engineering Models for Aircraft Noise Sources, Volume 3c - Appendix 3, IMAGINE report no. IMA4DR EEC-10, March 2007