Journal articles: 'Flight noise'

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Mahseredjian, Ara, Jacqueline Thomas, and R. John Hansman. "Advanced procedure noise model validation using Seattle International Airport noise monitor networks." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 2 (2021): 4787–98. http://dx.doi.org/10.3397/in-2021-2842.

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Advanced operational flight procedures that utilize modifications to thrust, airspeed, altitude, and configuration can be implemented to mitigate noise impacts for communities surrounding airports. Evaluating and designing such procedures requires accurate modeling of the aircraft performance, source noise, and atmospheric propagation of the source noise to the ground. Modeling frameworks to assess advanced procedures have been developed but must be validated to ensure their results are reasonable. This paper presents validation of such noise models using a network of ground noise monitoring data at Seattle-Tacoma International airport and ADS-B operational radar flight profiles from the OpenSky database. Modeled noise from operational flights of several aircraft types are shown to be consistent with noise monitor data when reasonable flap settings and atmospheric corrections for the actual weather at the time of flight are used. Discrepancies that exist between the modeled and measured noise results are identified to determine where current noise modeling methods must be improved to accurately represent all relevant noise sources.

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Hübner, Josephin, and Christoph Strümpfel. "Aircraft Noise Modeling of Departure Flights based on Flight Track Data and Actual Aircraft Performance Parameters." Lärmbekämpfung 15, no. 06 (2020): 188–93. http://dx.doi.org/10.37544/1863-4672-2020-06-18.

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Abstract The improvement of existing and the development of new operational noise abatement departure procedures (NADP) requires precise knowledge of the current aircraft noise situation in the vicinity of an airport. While the current noise situation is recorded using aircraft noise measurements, the estimation of future aircraft noise in the vicinity of airports must be calculated using suitable modeling methods (e. g. ECAC Doc 29). So far, the methods for estimating aircraft noise have been based on generic departure profiles and assumptions about flight operations procedures that do not match the real departure profiles, flight performance statuses and operational flight operations procedures sufficiently. In this article a method is presented that enables the calculation of aircraft noise contours of real departures using the aircraft noise modeling software Aviation Environmental Design Tool (AEDT). The exact calculation of aircraft noise contours from departures is based on a data set of flight history data (radar data), including the detailed estimation of aircraft performance parameters (including aircraft mass and engine thrust) and flight operations procedures (cutback and acceleration heights, flap schedule) along the departure trajectory. Then the data set is implemented in the modeling software and the calculated noise metrics (LA,MAX) are validated with real aircraft noise measurements of the corresponding flights.

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Tuân, Lê Đình, Anh Trần Tiến, and Hải Nguyễn. "On the airport environmental noise monitoring and control system." Science & Technology Development Journal - Engineering and Technology 3, SI2 (2021): first. http://dx.doi.org/10.32508/stdjet.v3isi2.622.

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Most major airports use permanent noise and operations monitoring systems to reduce the noise of flight operations in the surrounding community. This paper aims at a technical proposal for a permanent environmental noise monitoring and control system to provide solutions to reduce the noise of flying activities for communities around the airport. Airport noise monitoring is often used to evaluate noise abatement programs and to improve the aircraft's take-off / landing procedures, to minimize the impact of aircraft noise based on altitude, flight path and time of day. Noise monitoring is usually linked to the tracking radar to determine which aircraft is in particular when the noise limit is exceeded and thus provides immediate operational requirements to meet. The airport noise enviromental monitoring and control system is often structured with fixed permanent noise monitoring stations, mobile noise monitoring stations, multi-parameter wheather stations, radar tracks and flights information to automatically evaluate the noise impact due to operation of aircrafts in the surrounds of airport, near and on residential areas. The entire system is operated by a software platform proposed as a cloud configuration available on the internet. The platform provides all the modules required to manage data such as noise and flight information monitoring and control, live data, reports, noise and flight information in public disclosure, complaints management, alarms and warnings, etc.

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Zaporozhets, Oleksandr, and Alexandras Jagniatinskis. "Improving single flyover noise prediction for subsonic aircraft." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 3 (2021): 3259–70. http://dx.doi.org/10.3397/in-2021-2352.

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Current ICAO Doc 9911 provides the algorithm to calculate aircraft noise levels for any kind of airport flight scenario. The essential difference exists between the measured and calculated sound levels, especially for single flight noise events. Doc 9911 recommends using this method for equivalent sound levels L and noise indices L first of all. A number of national noise regulations still require for single noise event assessment. An article analyzes a number of reasons to explain the inaccuracy of noise event calculations. For example, the differences between calculated balanced flight parameters (thrust and velocity first of all) and supervised in real flights may influence the accuracy first of all. Statistical data was gathered to make more general view on these differences and some proposal to use them in calculations has being proved. Also, the assumptions of the ICAO Doc 9911 method may contribute to the inaccuracy of calculations. Among them are the homogeneous atmosphere for sound propagation, generalized for overall fleet noise directivity pattern, etc. Ground effect model defines the values for aircraft absent in operation currently. The first assumption provides a conflict with flight path calculations for varied atmosphere parameters with height over the surface.

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Makino, Koichi, and Naoaki Shinohara. "Daily fluctuations in aircraft noise exposure around civil airports and military airfields in Japan." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 1 (2021): 5154–60. http://dx.doi.org/10.3397/in-2021-2984.

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In Japan, yearly average of (day-evening-night sound level) as cumulative noise index has been adopted in national noise guideline of "Environmental Quality Standards for Aircraft Noise." Daily flight movements at civil airports are almost stable because of scheduled airline flight. On the other, daily total flight movements at military airfields greatly change day to day because of training flights, etc. Thus, noise exposure around the airport may change significantly from day to day due to change of flight movement. This paper shows examples of fluctuations, frequency distribution and deviation of daily using aircraft noise monitoring data around civil airports and military airfields. In the case of civil airports, standard deviation of daily was less than 5 dB at the monitoring stations where the yearly average of were about 55 dB or more. However, the standard deviation of daily increased 10 dB or more in some cases at points where yearly average of less than 55 dB. Furthermore, in the case of military airfields, the standard deviation of daily were 5 dB or more for all monitoring stations.

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Moberg, Bengt, Anders Johansson, Johan Rignér, and Per Näsman. "Operational noise optimization of aircraft approaches - Initial findings." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 6 (2021): 499–507. http://dx.doi.org/10.3397/in-2021-1494.

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As the pilots slow the aircraft down and extend flaps and landing gear in preparation for landing the characteristics of the aircraft as a noise source changes. In the OPNOP project, the possibility to use this variation in noise generation to minimize noise at a specified location is examined. Such analysis requires an increased understanding about aircraft noise generation as the aircraft changes configuration and speed during the approach, where theoretical models available can be overly simplistic and of little use for this purpose. Using flight data from 113 actual Airbus A321 flights, and corresponding noise measurements on the ground, this study reports on the initial findings forming the foundation on which further analysis will be conducted. Intermediary findings relate to: a comparison between models and actual measurements, the distance variability to the runway for various flap selections and extension of the landing gear as well as a comparison between flight data and on-ground noise measurements. Captured data suggest that it should be possible to use speed and configuration recommendations to reduce noise over selected approach areas. Future research will include scenario generation and incorporate flight data from an earlier study to increase validity.

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Jaworski, Justin W., and N. Peake. "Aeroacoustics of Silent Owl Flight." Annual Review of Fluid Mechanics 52, no. 1 (2020): 395–420. http://dx.doi.org/10.1146/annurev-fluid-010518-040436.

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The ability of some species of owl to fly in effective silence is unique among birds and provides a distinct hunting advantage, but it remains a mystery as to exactly what aspects of the owl and its flight are responsible for this dramatic noise reduction. Crucially, this mystery extends to how the flow physics may be leveraged to generate noise-reduction strategies for wider technological application. We review current knowledge of aerodynamic noise from owls, ranging from live owl noise measurements to mathematical modeling and experiments focused on how owls may disrupt the standard routes of noise generation. Specialized adaptations and foraging strategies are not uniform across all owl species: Some species may not have need for silent flight, or their evolutionary adaptations may not be effective for useful noise reduction for certain species. This hypothesis is examined using mathematical models and borne out where possible by noise measurements and morphological observations of owl feathers and wings.

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Zhi, Yongfeng, Gaoshang Li, Qun Song, Ke Yu, and Jun Zhang. "Flight control law of unmanned aerial vehicles based on robust servo linear quadratic regulator and Kalman filtering." International Journal of Advanced Robotic Systems 14, no. 1 (2017): 172988141668695. http://dx.doi.org/10.1177/1729881416686952.

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A new flight control law for unmanned aerial vehicles based on robust servo linear quadratic regulator control and Kalman filtering is proposed. This flight control law has a simple structure with high dependability in engineering. The pitch angle controller, which is designed based on the robust servo linear quadratic regulator control, is given to show the flight control law. Simulation results show that the pitch angle controller works well under noise-free conditions. Finally, Kalman filtering is applied to the pitch angle controller under noisy conditions, and the simulation results show that the proposed method reduces the influence of noise.

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LePiane, Krista, and Christopher J. Clark. "Evidence that the Dorsal Velvet of Barn Owl Wing Feathers Decreases Rubbing Sounds during Flapping Flight." Integrative and Comparative Biology 60, no. 5 (2020): 1068–79. http://dx.doi.org/10.1093/icb/icaa045.

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Synopsis Owls have specialized feather features hypothesized to reduce sound produced during flight. One of these features is the velvet, a structure composed of elongated filaments termed pennulae that project dorsally from the upper surface of wing and tail feathers. There are two hypotheses of how the velvet functions to reduce sound. According to the aerodynamic noise hypothesis, the velvet reduces sound produced by aerodynamic processes, such as turbulence development on the surface of the wing. Alternatively, under the structural noise hypothesis, the velvet reduces frictional noise produced when two feathers rub together. The aerodynamic noise hypothesis predicts impairing the velvet will increase aerodynamic flight sounds predominantly at low frequency, since turbulence formation predominantly generates low frequency sound; and that changes in sound levels will occur predominantly during the downstroke, when aerodynamic forces are greatest. Conversely, the frictional noise hypothesis predicts impairing the velvet will cause a broadband (i.e., across all frequencies) increase in flight sounds, since frictional sounds are broadband; and that changes in sound levels will occur during the upstroke, when the wing feathers rub against each other the most. Here, we tested these hypotheses by impairing with hairspray the velvet on inner wing feathers (P1-S4) of 13 live barn owls (Tyto alba) and measuring the sound produced between 0.1 and 16 kHz during flapping flight. Relative to control flights, impairing the velvet increased sound produced across the entire frequency range (i.e., the effect was broadband) and the upstroke increased more than the downstroke, such that the upstroke of manipulated birds was louder than the downstroke, supporting the frictional noise hypothesis. Our results suggest that a substantial amount of bird flight sound is produced by feathers rubbing against feathers during flapping flight.

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Giladi, Ran, and Eliav Menachi. "Validating Aircraft Noise Models." Proceedings 59, no. 1 (2020): 12. http://dx.doi.org/10.3390/proceedings2020059012.

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Aircraft noise, especially at takeoffs and landings, became a major environmental nuisance and a health hazard for the population around metropolitan airports. In the battle for a better quality of life, wellbeing, and health, aircraft noise models are essential for noise abatement, control, enforcement, evaluation, policy-making, and shaping the entire aviation industry. Aircraft noise models calculate noise and exposure levels based on aircraft types, engines and airframes, aircraft flight paths, environment factors, and more. Validating the aircraft noise model is a mandatory step towards the model credibility, especially when these models play such a key role with a huge impact on society, economy, and public health. Yet, no validation procedure was offered, and it turns out to be a challenging task. The actual, measured, aircraft noise level is known to be subject to statistical variation, even for the same aircraft type at the same situation and flight phase, executing the same flight procedure, with similar environmental factors and at the same place. This study tries to validate the FAA’s AEDT aircraft noise model, by trying to correlate the specific flight path of an aircraft with its measured noise level. The results show that the AEDT noise model underestimates the actual noise level, and four validation steps should be performed to correct or tune aircraft noise databases and flight profiles.

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Georgieva, Hristina. "Aircraft noise level calculation during take-off." Aerospace Research in Bulgaria 32 (2020): 75–87. http://dx.doi.org/10.3897/arb.v32.e07.

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A mathematical model with 4 degree of freedom created in Matlab for aircraft departure trajectory is described in this article. As a reference aircraft a midsize commercial passenger aircraft similar to an Airbus A320 has been chosen. The aircraft is represented by the rigid body and the parameters of model are collected from Airbus and the simulated departure trajectory at the Munich airport is based on a Standard Instrumental Departure. A semi-empirical model of Stone for predicting the jet noise has been used. The proposed model is validated against 10 real flights obtained from aircraft noise and flight track monitoring system at Munich airport. The computed error between the real data and modelling is reported on. Obtained results are presented numerical and graphically. The observed effects of flight operational parameters affecting the aircraft noise emission level during take-off represent subjects of discussions in the paper.

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Feng, Xia, Fangli Sun, and Min Lu. "Noise Reduction-Oriented Flight Aircraft Type." International Journal of Database Theory and Application 8, no. 5 (2015): 255–64. http://dx.doi.org/10.14257/ijdta.2015.8.5.22.

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Maccone, Claudio. "Relativistic interstellar flight and Gaussian noise." Acta Astronautica 17, no. 9 (1988): 1019–27. http://dx.doi.org/10.1016/0094-5765(88)90070-7.

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Tengzelius, Ulf, Anders Johansson, Mats Åbom, and Karl Bolin. "Next generation aircraft noise-mapping." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 4 (2021): 2064–75. http://dx.doi.org/10.3397/in-2021-2043.

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At CSA, Centre for Sustainable Aviation at KTH Stockholm, several projects have run during the last 4 years. One outcome from this research is the SAFT-program for prediction of aircraft noise contours (noise-mapping) and time-histories in receiving points on ground. SAFT is a versatile and comprehensive tool already including several computational methods such as standard ECACdoc.29 method and more accurate time-stepping simulation-based representations of aircraft sound sources (frequency and direction dependent). The program allows for input of "general aircraft trajectory input" in the sense that either the trajectory data of concern is fitted to the current pre-defined formats or SAFT is easily updated to read a "new" format. Among the pre-defined formats of current version is csv-files prepared from OpenSky Historical database. From these kinds of data thrust and other noise-predictor variables are extracted and applied for noise-mapping. Moreover, SAFT allows for studies of aggregated air-traffic in defined areas as well as of single event flight-trajectories. And for these almost any metric (L, L, L, L, ...) might be extracted together with differences in dB, "Delta-dB", between any two scenarios or individual flights. Could be routing, runway-use, individual flight procedures etc. Anticipated future implementations involve drone trajectories and sound-source representations.

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Gabrielian, Ana, Tejas Puranik, Mayank Bendarkar, Michelle Kirby, and Dimitri Marvis. "Validation of the aviation environmental design tool's noise model using high fidelity weather." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 2 (2021): 4810–22. http://dx.doi.org/10.3397/in-2021-2846.

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To enable sustainable aviation growth, mitigation of environmental effects must be developed in parallel. To further this effort, these effects are modeled using capabilities such as the Aviation Environmental Design Tool (AEDT), a program that is able to model aircraft performance, fuel burn, emissions, and noise. Past and current projects are performed with the intent of improving the accuracy of the models within AEDT to capture various real-world effects. This paper targets the sensitivity of the noise prediction and propagation by varying multiple assumptions within AEDT. To validate the noise capabilities, multiple streams of real-world data will be used to accurately model actual flights to and from SFO airport. This data includes High-Fidelity weather data,detailed flight performance characteristics from airline flight data records and noise monitoring data obtained from stations around the airport. The results from this study are expected to offer recommendations and help users prioritize and more accurately quantify community noise exposure using AEDT.

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Zaporozhets, Oleksandr, and Larisa Levchenko. "Accuracy of Noise-Power-Distance Definition on Results of Single Aircraft Noise Event Calculation." Aerospace 8, no. 5 (2021): 121. http://dx.doi.org/10.3390/aerospace8050121.

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Aircraft performance and noise database together with operational weights (depending on flight distances) and operational procedures (including low noise procedures) significantly influence results of noise exposure contour maps assessment in conditions of real atmosphere. Current recommendations of the Standard SAE-AIR1845A allow the definition of flight profiles via solutions of balanced motion equations. However, differences are still supervised between the measured sound level data and calculated ones, especially in assessing the single flight noise events. Some of them are well explained by differences between balanced flight parameters (thrust and velocity first of all) and monitored ones by the traffic control system. Statistical data were gathered to make more general view on these differences and some proposal to use them in calculations has been proven. Besides, the real meteorological parameters provide inhomogeneous atmosphere conditions always, which are quite different from the main assumptions of the SAE-AIR1845A, stipulating inaccuracies of sound level calculations.

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Tian, Yong, Dawei Xing, Lili Wan, and Bojia Ye. "Study on the Optimization Method of Point Merge Procedure Based on Benefit in the Terminal Area." Mathematical Problems in Engineering 2020 (April 6, 2020): 1–12. http://dx.doi.org/10.1155/2020/5757948.

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With the rapid development of the air transport industry, the problem of airspace congestion and flight delay in the terminal area (TMA) becomes more and more serious. In order to improve the efficiency of flight operations in TMA, point merge procedure had been devised. This paper takes the approach routes in TMA as the research object, taking into account such conditions as obstacle clearance, flight interval, and procedure area. Based on the flight time, fuel consumption, pollutant emission, and noise impact, an optimization model of point merge procedure is constructed. Genetic algorithm is used to optimize the structure of procedure. The Shanghai Hongqiao International Airport is selected for simulation verification, and the actual flow distribution of the airport is analyzed as an example. The results show that the average flight time was reduced by 0.26 min, the average fuel consumption was reduced by 1,240.64 kg, the average NOx emissions were reduced by 1.09 kg, and the noise impact range was contracted by 55 km2 after optimization. The point merge procedure optimization method can be expected to reduce the flight time, fuel consumption, and environmental impact of flights in TMA, so as to optimize the aircraft approach trajectory.

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Asakura, T., and Y. Takagi. "Case study: Effect of acoustic characteristics of interior aircraft noise on pilot." Noise Control Engineering Journal 68, no. 2 (2020): 125–36. http://dx.doi.org/10.3397/1/376811.

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The influence of acoustic characteristics of in-flight noise on airplane operations and sound impression has been investigated through objective and subjective measure including the flight simulation. The authors verified the influence of the noise conditions including seven conditions, in which the sound pressure levels and frequency characteristics of them were parametrically changed, on the airplane operations using shortterm flight simulation. Resultantly, the change of the sound pressure levels of the in-flight noise did not greatly affect the operation accuracy although clearly affected the subjective impressions. On the other hand, it has been suggested that the change of the frequency characteristics of in-flight noise affected not only the subjective impressions but also the operation accuracy.

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Jäger, David, Christoph Zellmann, Felix Schlatter, and Jean Marc Wunderli. "Validation of the sonAIR aircraft noise simulation model." Noise Mapping 8, no. 1 (2021): 95–107. http://dx.doi.org/10.1515/noise-2021-0007.

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Abstract sonAIR is a recently developed aircraft noise simulation model designed for single flight simulation while still being applicable for calculation of entire airport scenarios. This paper presents a rigorous validation exercise, wherein roughly 20’000 single flights were simulated using the 22 currently available sonAIR emission models of turbofan aircraft and compared against noise measurements. The measurements were recorded with the noise monitoring terminals at Zurich and Geneva airport, Switzerland, and with additional microphones installed by the author’s institution. Data from 22 measurement positions were analyzed, covering all departure and approach routes at distances from 1.8 to 53 kilometers from the airports. sonAIR was found to be accurate for departures and approaches under different operating conditions and aircraft configuration. The mean overall differences between simulation and measurements were well below ±1 dB in terms of noise event levels, with standard deviations of ±1.7 dB respectively ±2.4 dB, depending on the model type. A few aircraft types that displayed larger deviations are discussed individually. A sensitivity analysis on the input data found the quality and level of detail of the land cover data to be critical for the simulation accuracy. Changes in other input data such as atmospheric profiles and buildings had non-significant impacts.

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Oh, Soo Hee, and Kyoungwon Lee. "Aircraft Noise of Airport Community in Korea." Audiology and Speech Research 16, no. 1 (2020): 1–10. http://dx.doi.org/10.21848/asr.200001.

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Aircraft noise is one of the serious environmental noises with the increased use of flight traffic. The purpose of this study is to understand aircraft noise levels of airport communities in Korea using baseline data for audiologic management. Aircraft noise levels were retrieved from the National Noise Information System every month between 2004 and 2018. We reviewed aircraft noise levels obtained from total of 111 airport communities across 14 airports. In order to understand aircraft noise levels of civil and military airports, the aircraft noise levels measured in civil and military airport communities compared with the noise levels from civil airport communities. The data showed average 71-73 weight equivalent continuous perceived noise level (WECPNL) for fifteen years across airport cities and the average noise levels did not increase over time between 2004 and 2018 years. The civil and military airports showed about 12 WECPNLs of increased noise levels compared to the civil airports. The most civil and military airport communities, including Gwangju, Gunsan, Daegu, Wonju, and Cheongju generated the maximum noise levels and ranked as the highest airport for aircraft noise levels. Although aircraft noise levels in airport communities were similar over the past decade, civil and military airports generated increased noised levels compared to civil airports due to jet plane noises and other military-related noises. Careful consideration is necessary to implement noise reduction policy for civil and military airport communities. Ongoing noise control, hearing monitoring, education, and relevant policies are required to improve the quality of life in the airport community residences.

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Chen, Yong, Sebastian Ghinet, Andrew Price, Viresh Wickramasinghe, and Anant Grewal. "Investigation of aircrew noise exposure levels and hearing protection solutions in helicopter cabin." Journal of Intelligent Material Systems and Structures 28, no. 8 (2016): 1050–58. http://dx.doi.org/10.1177/1045389x16667553.

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High noise levels in the helicopter cabin adversely affect aircrew communication and reduce comfort in the short-term and may lead to hearing loss in the long-term if flight helmets cannot provide sufficient protection to the aircrew. A cabin noise exposure survey has been performed on a Royal Canadian Air Force CH-147F Chinook heavy lift helicopter to evaluate the noise environment and noise protection performance of the flight helmet. Investigation results showed that the low-frequency noise attenuation provided by the Royal Canadian Air Force flight helmet was marginal in high-speed flight conditions that generate loud cabin noise. Therefore, in-canal earphone integrated with active noise cancellation capability was investigated to provide enhanced noise protection and improve clarity in voice communication. Simulation and proof-of-concept test results verified that active noise cancellation in-canal earphones can serve as a feasible technical solution to provide enhanced noise attenuation to mitigate the low-frequency N/rev tonal noise generated by the aerodynamic pressure from the helicopter rotor blades.

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Centracchio, Francesco, Lorenzo Burghignoli, and Umberto Iemma. "Multiobjective optimisation of flight paths for noise level mitigation and sound quality improvement." Noise Mapping 8, no. 1 (2021): 268–80. http://dx.doi.org/10.1515/noise-2021-0022.

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Abstract The present work deals with the multiobjective, multidisciplinary optimisation of takeoff and approach operations of a commercial aircraft aimed at the mitigation of the impact of aviation noise on the population. The innovative approach used here couples the minimisation of the aircraft noise level at the certification points with the improvement of the sound quality. The latter objective represents the main novelty of the present work and is addressed using a spectral–matching approach to make the aircraft noise as close as possible to a target sound. The rationale underlying the research is the development of a community–oriented approach to the assessment airport operations in view of the complete redefinition of the future airport scenarios. Indeed, the air traffic growth, the rapid expansion of urban areas around airports, and the expected advent of urban air mobility, are transforming the aviation noise into a serious hazard to the sustainable development of society. The sound–quality–based objective imposes a comprehensive multidisciplinary approach also in the procedural optimisation, due to the detail required to estimate the noise spectrum composition. Two merit factors are minimised, specifically the EPNL at the noise certification points and the Lp –norm of the difference between the noise produced by the configuration under analysis and a target sound. The target sounds are obtained by using sound engineering techniques aimed at the sound quality improvement, on the basis of the results of the psychometric tests campaigns performed within the projects SEFA and COSMA. The minimisation is achieved adopting a global evolution method, and the results are presented in terms of approximated Pareto frontiers for a single–aisle aircraft in both takeoff and landing conditions.

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KOBAYAHI, Hiroshi, Tadao TORISAKI, and Mitsuo MORITA. "Experimental Study of Flight Effect on Fan Noise : 2nd, Report, Fan Noise Variations due to Flight Effect." Bulletin of JSME 29, no. 255 (1986): 2909–16. http://dx.doi.org/10.1299/jsme1958.29.2909.

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Robinson, Remigius, Pujianti Bejahida Donuata, Agustinus Angelaus Ete, and Muhamad Epi Rusdin. "Effect of Noise Intensity of Aviation Activities on Student Learning Concentrations." Indonesian Review of Physics 3, no. 2 (2020): 47. http://dx.doi.org/10.12928/irip.v3i2.2632.

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This study aims to determine the effect of flight activity noise intensity on student learning concentration. This study involved 48 students (male = 24 and female = 24) who were randomly selected in the Islamic elementary school Waioti, Maumere. The intensity of flight activity noise during classroom learning activities is measured using a Sound Level Meter (SLM), and students' concentration levels were measured using a 5-level Likert scale learning concentration questionnaire. The effect of flight noise intensity on student learning concentration was determined using linear regression analysis. The results showed that the noise level due to flight activities in the Waioti Islamic Elementary School was 58.92 dB, exceeding the set threshold value. The intensity level of students' learning concentration disorders reached 71.43%, including frequent disturbance. The level of flight activity noise significantly affects student learning concentration with the regression model: Y = 49.972 + 0.834X with R2 of 0.635.

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Bergen, Thomas, Harry Himelblau, and Dennis Kern. "Development of Acoustic Test Criteria for the Cassini Spacecraft." Journal of the IEST 41, no. 1 (1998): 26–38. http://dx.doi.org/10.17764/jiet.41.1.77v54517021l5941.

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Acoustic measurements from eight Titan IV flights, and an acoustic test of a Cassini simulator and Titan payload fairing (PLF), were used to derive acoustic flight and test criteria for the Cassini spacecraft. The flight and laboratory data were used or modified to account for the following factors: (a) noise-spike contamination of flight data, (b) spatial and flight-to-flight variations of flight data, (c) application of a thicker barrier-blanket to the PLF for the Cassini mission, (d) effects of locating two Cassini assemblies, the Huygens Probe (HP), and the High Gain Antenna (HGA), near the PLF, and (e) higher thrust of upgraded Titan solid rocket motors (SRMs) for the Cassini mission. An overall sound pressure level of 145 dB was verified for the protoflight acoustic test criteria for the Cassini spacecraft.

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Lee, Incheol. "Empirical prediction of flight effect on subsonic coaxial-jet noise by introducing an adjusted flight velocity term." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 2 (2021): 4495–501. http://dx.doi.org/10.3397/in-2021-2719.

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The effect of forward flight on jet noise is difficult to quantify through flyover tests since only the total noise is measured in a full-scale flyover test, and the contribution of the jet noise is difficult and sometimes nearly impossible to identify. Thus, most studies on the flight effect have been carried out through model-scale experiments with a single-stream jet simulator in a free jet facility. In this paper, the effect of forward flight was captured by using an adjusted flight velocity term (αV) to describe jet velocity in a new prediction of coaxial-jet noise. The new jet noise prediction method assumes that there are three components: primary, secondary, and mixed components with no filter functions. The coefficient α is determined by a thorough investigation of the model-scale data gained from an experiment in the anechoic wind tunnel of ONERA. The value of α is 1 for the primary component, 0.5 for the secondary component, and a linear function of the angle for the mixed component. The simple adjustment of the flight velocity successfully embodied the effect of forward flight at all angles, with no separate velocity exponent or an additional term.

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Zein, Karman, and Safrudin Sagaf. "Analisis Paparan Kebisingan Pesawat Terbang di Bandara Babullah Ternate." UNM Environmental Journals 1, no. 2 (2018): 39. http://dx.doi.org/10.26858/uej.v1i2.8062.

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This study aims to measure exposure to aircraft noise levels in the Babullah Airport area of Ternate. Data collection in this study is observation (observation), which aims to obtain preliminary data relating to the problems studied, besides that data collection also uses noise level measurements carried out at the 0 meter point from the runway to 500 meters at 5 points. The results of the research show that the activities of airplanes at Babullah Ternate Airport began to experience an increase, as indicated by the type of airlines that competed in serving flights at national and domestic levels.Domestic and national flight activities, airplanes at Babullah Ternate Airport greatly affect the environment. The results of this study indicate that the kebanganangan level in the airport area reaches an average of 78.8 db (A) with other environmental parameters such as wind speed and air humidity 12.6 m / s and 81.23%. If the size of the environmental parameters no longer affect noise exposure, the area has noise that exceeds the threshold. To reduce the noise level due to the flight activities at Babullah Ternate Airport, a barrier is needed as well as socializing the danger of noise for humans.

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Tan, Qichen, Haoyu Bian, Siyang Zhong, and Xin Zhang. "Simulation of multi-rotor powered urban aerial mobility noise for environmental assessment." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 3 (2021): 3854–60. http://dx.doi.org/10.3397/in-2021-2541.

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The operation of the rapidly growing unmanned aerial vehicles (UAV) and the promising urban aerial mobility (UAM) could have a significant noise impact on the environment. In this work, we developed a cloud-based noise simulator to efficiently assess the environmental impact of UAM and UAV. The noise sources and long-distance propagation are computed by the propeller noise prediction models and an advanced Gaussian beam tracing method, respectively, in local high-performance computers. Users can define the working conditions and vehicle layer through a platform with a user-friendly graphical interface. In addition, the noise level distribution at the observers of interest such as the buildings can be visualized. By employing advanced interpolation methods or autonomous learning algorithms, the computations are efficiently accelerated such that the noise distributions are simultaneously displayed during flights of the vehicles. To better measure the noise impact on human perception, various noise metrics will be output for further analysis. By conducting the virtual flights using the simulator, the noise impact in each flight state and atmospheric condition of different vehicles can be predicted, which will then facilitate the low-noise flights for both UAV and UAM.

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Xie, Rukuan, Shengqing Xiong, Shuling Duan, et al. "Noise estimation in vector magnetic data derived from airborne vector magnetic system." GEOPHYSICS 85, no. 4 (2020): J71—J83. http://dx.doi.org/10.1190/geo2019-0663.1.

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The accuracy of the airborne vector magnetic (VM) survey mainly depends on the attitude measurement precision of the aircraft. An orientation change of 0.001° can produce an error of approximately 1 nT in VM components for a geomagnetic field of 50,000 nT. Therefore, noise estimation or accurate understanding of noise characteristics of measured airborne VM data plays an important role in geophysical applications. A new airborne VM system with high-precision attitude measurement (0.003°–0.007° root-mean square [rms]) for geophysical prospecting was developed. We have analyzed the results from test flights, compared the difference between measured and calculated VM data, and we developed two methods to estimate the noise in VM data derived from the new system, which include (1) VM noise, that is, the rms error of the difference between the total magnetic intensity calculated from the measured VM data and measured by the scalar sensor, to mainly estimate the error of calibration and compensation, and (2) rms error of the difference between the data from repeat flight lines, to mainly estimate the error of multiple measurements. The noise estimation results of the two methods based on data from test flights in the Qixin area of the East Tianshan Mountains in China indicate that the new system has high accuracy: VM noise is 2.32 nT; the error of the repeat flight lines is 4.86, 6.08, and 2.80 nT for the [Formula: see text], [Formula: see text], and [Formula: see text] components, respectively.

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Sarradj, Ennes, Christoph Fritzsche, and Thomas Geyer. "Silent Owl Flight: Bird Flyover Noise Measurements." AIAA Journal 49, no. 4 (2011): 769–79. http://dx.doi.org/10.2514/1.j050703.

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Zaporozhets, Oleksander I., and Vadim I. Tokarev. "Predicted flight procedures for minimum noise impact." Applied Acoustics 55, no. 2 (1998): 129–43. http://dx.doi.org/10.1016/s0003-682x(97)00108-4.

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Snell, Andrew, and Darren Wallis. "The Flight Path of Aircraft Noise Measurement." Measurement and Control 34, no. 3 (2001): 69–71. http://dx.doi.org/10.1177/002029400103400302.

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Maccone, Claudio. "Relativistic interstellar flight and instantaneous noise energy." Acta Astronautica 21, no. 3 (1990): 155–59. http://dx.doi.org/10.1016/0094-5765(90)90107-v.

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KOBAYASHI, Hiroshi, Tadao TORISAKI, Mitsuo MORITA, and Hiroharu TAKAGI. "The experimental study of flight effect on fan noise. 2nd report Fan noise variations due to flight effect." Transactions of the Japan Society of Mechanical Engineers Series B 52, no. 473 (1986): 334–44. http://dx.doi.org/10.1299/kikaib.52.334.

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Fujita, Etsushi, Taichi Higashioka, Manabu Sugiura, and Osamu Kohashi. "Evaluation method of military aircraft noise using AI analysis of aircraft images." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 6 (2021): 854–62. http://dx.doi.org/10.3397/in-2021-1668.

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In recent aircraft noise survey in Japan, noise data is associated with each aircraft by flight log or by radio information including transponder signals. Especially, above Tokyo metropolitan area, flight tracks are tangled extremely each other, therefore assessments from various perspectives such as departure / arrival airport, used runway, aircraft model, and operator have been demanded for determining noise policies. However, for military aircrafts, it is not easy to identify their information with the same way as commercial aircrafts, because their flight logs are not disclosed and many of them do not emit transponder signals like commercial aircrafts. Therefore, manned 24 hours survey around air bases have been necessary to obtain flight information of military aircrafts. In this paper, we propose an AI-based analysis using captured aircraft images for obtaining actual flight data of military aircrafts. In the past trials, we could determine the takeoff/landing time and the aircraft model by the above method. Associating these information and noise data measured at monitoring stations, details of noise characteristics around the air base can be clearly grasped. Advanced analysis of the causes of noise impact will lead effective and concrete countermeasures.

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Page, Juliet, Amanda Rapoza, and Eric Jacobs. "Development of Fly Neighborly helicopter model specific operational noise abatement guidance from acoustic flight test data." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 1 (2021): 5671–77. http://dx.doi.org/10.3397/in-2021-3210.

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Improved helicopter noise abatement guidance has been developed based on acoustic test data acquired by NASA, FAA and Volpe in support of the Helicopter Association International (HAI)'s Fly Neighborly Program. This higher fidelity material was developed to supplement previous training programs based on pilot and operator feedback. The manner of presentation allows pilots to readily interpret the directional noise emission of their vehicle at different operating conditions. Flight path, airspeed, approach descent rate, and deceleration rate can be assessed to optimize flight patterns both during the pre-flight planning stage and in real time during flight operations in response to local conditions and events. The resultant sound directivity would be displayed as colored noise exposure contours overlaid onto a map of the area in the vicinity of the helicopter. New Fly Neighborly training modules have been developed utilizing directional operational noise plots based on Volpe's Advanced Acoustic Model (AAM) modeling with empirical sound sphere data from dedicated US Government helicopter flight tests. This paper will describe the acoustic analyses and will present the updated noise guidance for the AS350, AS365, AW139, Bell 205, Bell 206, Bell 407, R-44, R-66 and S-76D helicopters.

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Yin, Jianping, and Heino Buchholz. "Toward Noise Abatement Flight Procedure Design: DLR Rotorcraft Noise Ground Footprints Model." Journal of the American Helicopter Society 52, no. 2 (2007): 90–98. http://dx.doi.org/10.4050/jahs.52.90.

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Wagner, Hermann, Matthias Weger, Michael Klaas, and Wolfgang Schröder. "Features of owl wings that promote silent flight." Interface Focus 7, no. 1 (2017): 20160078. http://dx.doi.org/10.1098/rsfs.2016.0078.

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Owls are an order of birds of prey that are known for the development of a silent flight. We review here the morphological adaptations of owls leading to silent flight and discuss also aerodynamic properties of owl wings. We start with early observations (until 2005), and then turn to recent advances. The large wings of these birds, resulting in low wing loading and a low aspect ratio, contribute to noise reduction by allowing slow flight. The serrations on the leading edge of the wing and the velvet-like surface have an effect on noise reduction and also lead to an improvement of aerodynamic performance. The fringes at the inner feather vanes reduce noise by gliding into the grooves at the lower wing surface that are formed by barb shafts. The fringed trailing edge of the wing has been shown to reduce trailing edge noise. These adaptations to silent flight have been an inspiration for biologists and engineers for the development of devices with reduced noise production. Today several biomimetic applications such as a serrated pantograph or a fringed ventilator are available. Finally, we discuss unresolved questions and possible future directions.

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Hu, Jun. "Aviation Flight Attitude Control Technology." Applied Mechanics and Materials 716-717 (December 2014): 1567–71. http://dx.doi.org/10.4028/www.scientific.net/amm.716-717.1567.

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This paper presents a range of two miniature spacecraft attitude Fuzzy Neural Network Sliding adaptive controller, using a weighting factor to combine indirect and direct fuzzy neural network controller fuzzy neural network controller. Interval two free parameters of fuzzy neural network adaptive sliding mode controller via output feedback control law and adaptive law be adjusted online. Simulation results show that after joining 10db Gaussian white noise, and in order to reduce the impact of external interference and noise training data, a controller with respect to the range of large amount of control type II generated by the controller. Overall adaptive scheme guarantees the global stability of the closed-loop system, all signals involved are bounded in some way, and also showed a high level of tracking performance.

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Zhang, Li Jun, Xiao Jiao Chen, Min Li, Yue Fan, and Qiang Fu. "Research on Numerical Calculation Method to Aerodynamic Noise in High Velocity Environment." Advanced Materials Research 655-657 (January 2013): 809–12. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.809.

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At present, the flight velocity and flight performance of an aircraft are higher, so that aerodynamic noise caused by an engine jet in the take-off and flight processes can reach 160 dB. The high strength of the jet aerodynamic noise is very harmful to vehicle drivers, vehicle structures and airborne equipments. Two numerical calculation methods to aerodynamic noise, the FW-H acoustic analogy method and the FW-H acoustic analogy and boundary element combining method, were introduced. These two methods were used to predict the aerodynamic noise, and the numerical calculation results were compared with the physical experimental results. Results show that the FW-H acoustic analogy method can predict aerodynamic noise. However, it cannot predict the sound field distribution. The FW-H acoustic analogy and boundary element combining method is able to predict the sound field distribution with sound reflection.

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Nur, Mulyadi. "Pengaruh Kebisingan Dalam Ruang Control Tower Terhadap Pelayanan Lalulintas Penerbangan Di Bandara Sentani Jayapura." Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) 6, no. 1 (2019): 75–90. http://dx.doi.org/10.46447/ktj.v6i1.43.

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In the provision of air traffic services, ATC (Air Traffic Controller) officers are requiredto ensure safety and smoothness in accordance with the procedures for flight safety can beachieved. The case of Kelas I Khusus Sentani Jayapura Airport is the noise caused by theapron building which is quite close to the tower building and the propeller type plane thatpasses the bravo taxiway causing quite disturbing noise. The purpose of this research is toprovide optimal air traffic service related to controller comfort in providing flight trafficservice, using qualitative deskriktif method based on field observation and related documenton air transport service provision in order to create flight safety and security. The results ofthis paper indicate that noise can affect the convenience of the controller when providing airtraffic services in terms of safety and regularity of the flight. It is suggested to AIRNAV andKelas I Khusus Sentani Jayapura Airport managers should install carpet and rubber silencerin tower building to reduce noise.

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Koehler, Mark, Frank Baader, and Peter Brandstätt. "Noise prediction for urban air taxi operation." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 3 (2021): 2984–95. http://dx.doi.org/10.3397/in-2021-2278.

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Solutions to escape crowded streets are increasingly taking up new forms of mobility. This also includes air taxis or VTOLs. In addition to passenger traffic, suggestions, such as parcel delivery by drones, are also regularly part of future visions. Air taxis pose additional safety requirements due to the transport of people and they also represent a major potential source of noise. A challenge that urban planners, pollution control officers and decision-makers have to face. Using the concrete example of an urban landing place for air taxis at the main train station in the city of Ingolstadt, possible problems, issues related to noise protection and their legal basis were examined. This presentation is a summary of the projects results. The examinations include the creation of noise mapping in order to simulate the impact to the already existing noise situation. Those were based on current flight noise regulations with necessary alterations regarding VTOLs. Because air taxi noise is expected to be more annoying than regular traffic noise, the possible application of flight noise indexes such as the "Frankfurt flight noise index FFI 2.0" shall be reviewed. Based on the results of the previous examinations, possible noise protection measures shall be developed.

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Ikelheimer, Bruce, Kenneth Plotkin, and Timothy Lavallee. "Prediction of aircraft flight tracks from noise measurements." Journal of the Acoustical Society of America 110, no. 5 (2001): 2731. http://dx.doi.org/10.1121/1.4777464.

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Yamamoto, Kazuomi, Kenji Hayama, Toshiyuki Kumada, and Kensuke Hayashi. "A flight demonstration for airframe noise reduction technology." CEAS Aeronautical Journal 10, no. 1 (2019): 77–92. http://dx.doi.org/10.1007/s13272-019-00376-3.

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Falcão, Taiana Pacheco, Ronir Raggio Luiz, Gabriel Eduardo Schütz, Márcia Gomide da Silva Mello, and Volney de Magalhães Câmara. "Audiometric profile of civilian pilots according to noise exposure." Revista de Saúde Pública 48, no. 5 (2014): 790–96. http://dx.doi.org/10.1590/s0034-8910.2014048005256.

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OBJECTIVE To evaluate the audiometric profile of civilian pilots according to the noise exposure level. METHODS This observational cross-sectional study evaluated 3,130 male civilian pilots aged between 17 and 59 years. These pilots were subjected to audiometric examinations for obtaining or revalidating the functional capacity certificate in 2011. The degree of hearing loss was classified as normal, suspected noise-induced hearing loss, and no suspected hearing loss with other associated complications. Pure-tone air-conduction audiometry was performed using supra-aural headphones and acoustic stimulus of the pure-tone type, containing tone thresholds of frequencies between 250 Hz and 6,000 Hz. The independent variables were professional categories, length of service, hours of flight, and right or left ear. The dependent variable was pilots with suspected noise-induced hearing loss. The noise exposure level was considered low/medium or high, and the latter involved periods > 5,000 flight hours and > 10 years of flight service. RESULTS A total of 29.3% pilots had suspected noise-induced hearing loss, which was bilateral in 12.8% and predominant in the left ear (23.7%). The number of pilots with suspected hearing loss increased as the noise exposure level increased. CONCLUSIONS Hearing loss in civilian pilots may be associated with noise exposure during the period of service and hours of flight.

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Feng, Bing, Ji-feng Zhang, Peng-ju Gao, Jie Li, and Yang Bai. "Nonlinear Noise Reduction for the Airborne Transient Electromagnetic Method based on Kernel Minimum Noise Fraction." Journal of Environmental and Engineering Geophysics 26, no. 2 (2021): 165–75. http://dx.doi.org/10.32389/jeeg20-020.

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The airborne transient electromagnetic method has become a powerful tool to explore deep resource and tectonic structures. However, aircraft vibrations and flight environments produce very strong and complex nonlinear noise and result in poor data quality compared to ground transient electromagnetic methods. Consequently, the reduction of airborne electromagnetic noises is of vital importance to data inversion and imaging. To suppress and remove the nonlinear noise, we propose using kernel minimum noise fraction (KMNF), which is a nonlinear generalized method of minimum noise fraction. First, an adaptive variable window-width filtering algorithm is used to evaluate the noises and perform the preliminary denoising. Then, we adopt the two filter methods, which are minimum noise fraction (MNF) and KMNF to suppress the noise. The results show that these two methods can both suppress noise and make the decay curves smooth, but kernel MNF is more effective for the nonlinear characteristics of noise and it does not weaken the anomaly. Finally, field data from the Qinling mine area is processed, using the MNF and KMNF methods. The results show that nonlinear noise is suppressed by both methods but the results of KMNF are better than those of the linear MNF method.

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Takaishi, Takehisa, Hiroki Ura, Kenichiro Nagai, et al. "Airframe noise measurements on JAXA Jet Flying Test Bed “Hisho” using a phased microphone array." International Journal of Aeroacoustics 16, no. 4-5 (2017): 255–73. http://dx.doi.org/10.1177/1475472x17718725.

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In 2015, the Japan Aerospace Exploration Agency launched the Flight demonstration of QUiet technology to Reduce nOise from High-lift configurations project to verify by flight demonstration the feasibility of practical noise-reducing aircraft modification concepts. In order to serve as a baseline for comparison before modification, airframe noise sources of the JAXA Jet Flying Test Bed “Hisho” were measured with a 30 m diameter array of 195 microphones mounted on a wooden platform built temporary beside the runway of Noto Satoyama Airport in Japan. A classical Delay and Sum in the time domain beamforming algorithm was adapted for the present study, with weight factors introduced to improve the low-frequency resolution and autocorrelations eliminated to suppress wind noise at high frequencies. In the landing configuration at idle thrust, the main landing gear, nose landing gear, and side edges of the six extended flap panels were found to be the dominant “Hisho” airframe noise sources. Deconvolution by the DAMAS and CLEAN-SC algorithms provided clearer positions of these sound sources at low frequencies. Integration of acoustical maps agreed well with the sound pressure level measured by a microphone placed at the center of the microphone array and gave detailed information about the contribution of each noise source.

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Gross, Daniel A. "Calculating total daily noise exposure using aircrew flight equipment noise attenuation and fight segment noise data." Journal of the Acoustical Society of America 138, no. 3 (2015): 1804. http://dx.doi.org/10.1121/1.4933722.

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Zafari, Zafar, Boshen Jiao, Brian Will, Shukai Li, and Peter Muennig. "The Trade-Off between Optimizing Flight Patterns and Human Health: A Case Study of Aircraft Noise in Queens, NY, USA." International Journal of Environmental Research and Public Health 15, no. 8 (2018): 1753. http://dx.doi.org/10.3390/ijerph15081753.

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Objectives: Airports in the U.S. have gradually been transitioning to automated flight systems. These systems generate new flight paths over populated areas. While they can improve flight efficiency, the increased noise associated with these novel flight patterns potentially pose serious health threats to the overflown communities. In this case study, we estimated the monetary benefits relative to health losses associated with one significant change in flight patterns at LaGuardia Airport, year-round use of “TNNIS Climb”, which happened in 2012 as a result of flight automation in New York City. Prior to that, the use of the TNNIS Climb was limited to the U.S. Open tennis matches. Methods: We developed a decision-analytic model using Markov health states to compare the costs and quality-adjusted life years (QALYs) gained associated with the limited use of TNNIS (old status quo) and the year-round use of TNNIS (current status quo). The TNNIS Climb increases airplane noise to above 60 decibels (dB) over some of the most densely populated areas of the city. We used this increased exposure to noise as the basis for estimating ground-level health using data from sound monitors. The total costs (including both direct and indirect costs), QALYs, and the incremental cost-effectiveness ratio (ICER) were estimated for the limited versus the year-round use of the TNNIS Climb. Results: The incremental lifetime costs and QALYs per person exposed to noise associated with the limited versus the year-round use of TNNIS was $11,288, and 1.13, respectively. Therefore, the limited use of TNNIS had an ICER of $10,006/QALY gained relative to the year-round of TNNIS. Our analyses were robust to changes in assumptions and data inputs. Conclusions: Despite increases in efficiency, flight automation systems without a careful assessment of noise might generate flight paths over densely populated areas and cause serious health conditions for the overflown communities.

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Luo, Yun Lin, and Hong Qiang Sun. "Study of Method of Denoising for Triaxial Flight Simulation Turntable Based on Generalized Minimum Variance." Advanced Engineering Forum 2-3 (December 2011): 156–61. http://dx.doi.org/10.4028/www.scientific.net/aef.2-3.156.

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Aiming at dealing with the existing noise of triaxial flight simulation turntable, the paper design digital filter low-pass transmitters and generalized minimum variance control filter to process signal for random disturbance, and have test study based on outside box control system of triaxial flight simulation turntable. The test results show that we can get better control effect by adopting generalized minimum variance control rates to denoise for measured signal on triaxial flight simulation turntable, and that is much helpful to improve the noise control accuracy.

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Journal articles on the topic 'Flight noise'

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