Aircraft Noise Prediction Research Articles

The consideration of a simplified method for predicting aircraft noise

The Japanese segment model focuses on understanding noise impacts in the surrounding areas relatively close to the airport. The basic data to be prepared for predicting are usually the results of measurements and analysis in the area near the airport. In areas farther away from airports, the altitude of aircraft is higher, there is an issue that prediction results based on the basic data collected near airports accurately reflect the reality. Often, areas far from airports get complaints even if noise exposure was not high. There is a desire for a model that can predict with relatively high accuracy and ease even in locations far from airports like this. Based on this background, we have developed a simple prediction model based on actual observation results of noise and flight paths, which can be used as basic data for aircraft noise prediction. In this approach, a database is created using noise measurements obtained from unattended noise monitoring and short-term survey results and aircraft position information from the ADSB. In noise propagation calculations, predictions are made considering factors such as lateral attenuation of ground surfaces, air absorption, and variability in flight paths by a simple method.

Environmental Impact by Air Traffic: Assessing aircraft noise nearby Hong Kong International Airport

As part of a more global research effort towards a greener aviation, the present study focuses on the noise impact by aircraft operations around a major airport, namely the Hong Kong International Airport (HKIA). To assess a pre-existing aircraft noise prediction platform vis-à-vis the specificities of the local aviation scene, the ground noise impacts of 70+ aircraft flying in and out of HKIA are live-measured in two locations of Hong Kong city. This is achieved through in-situ audio recordings of aircraft during take-off/landing flight phases, along with a real-time tracking of their characteristics (aircraft and engine types, flightpaths, atmospheric conditions, etc.). Once suitably post-processed, the measurements are analyzed to characterize better the noise impacts by these various flights in regard to their specificities (e.g., aircraft types, flight operations). In a second stage, these noise impacts are compared against their digital twins, which are simulated via the noise prediction platform, using the actual flight characteristics (aircraft types, flightpaths, thrust, airspeed, etc.). This comparative assessment is achieved for a total of 60 flights consisting of 37 departures (resp. 23 arrivals) and involving 6 (resp. 5) aircraft types. Overall, the comparison between the field tests and their digital twins proves to be reasonably good, with both measured and predicted noise levels falling within a range of a few decibels across all flights, on average. Finally, specific analyses are conducted to explore the uncertainties weighing on the predictions, possibly explaining some of the mismatches observed between the experimental and computational results. Overall, the study further demonstrates that aircraft noise prediction methods such as the present one constitute a valuable means to assess the environmental impacts of air traffic operations, including when the latter are highly specific — as in Hong Kong city, owing to its complex airspace and meteorological conditions.

Assessing the influence of street canyon shape on aircraft noise: Results from measurements in courtyards near Amsterdam Schiphol Airport

Aircraft noise is a major stressor for communities in the vicinity of airports. Aircraft noise prediction models omit the built environment, based on an implicit assumption that the impact of buildings on the propagation of aircraft noise is neglectable. In this article a study is presented in which aircraft noise levels were measured near walls facing towards and away from aircraft flyovers in an urban test environment near Amsterdam Schiphol Airport. The test environment comprises three adjacent courtyards, each enclosed by stacked shipping containers. To examine the influence of street geometry on aircraft noise, specifically for slanted roofs and building insets, the shipping containers were stacked in a different pattern around each courtyard. In total, sound levels for 2383 aircraft flyovers were analysed across five months at ten microphone positions within the courtyards, for both arrivals and departures. Depending on the geometry of the courtyards, mean differences (LA,max) between facades with- and without a line of sight towards the aircraft ranged between −1,3dBA and 5,0dBA for arrivals, and 8,7dBA and 13,6dBA for departures. SEL values ranged between between −0,8dBA and 4,3dBA for arrivals, and 8,1dBA and 11,6dBA for departures. The results suggest that slanted roofs perpendicular to the flight direction deflect incident sound, substantially reducing the sounds levels inside courtyards. Contrarily, building insets at building sides facing away from the flight paths did not reduce sound levels underneath the overhangs significantly. The findings stress the importance of architectural and urban design to mitigate aircraft noise.

Developing the algorithm for aircraft noise prediction on building façade

Although the COVID-19 pandemic has now become an endemic, working remotely for certain days of the week remains adopted in many companies as the norm. As the air traffic is heavier during office hours, residents staying near to an airport may suffer the adverse effects of aircraft noise exposure relating to productivity and health. As this problem is present in many cities, aircraft noise prediction is important in aiding urban planning processes to identify and manage the problem accordingly. This paper presents our recent work on adding a new feature-important for interior acoustic comfort evaluation-to predict aircraft noise on building façade. The computational procedure involves processing the façade geometry from the 3D model, determining the line of sight between the façade and the aircraft, and generating the noise map. Eventually, this new feature will be integrated to a unified urban environmental modelling tool for the design of highly liveable and sustainable residential towns.

Component-wise regression sound source models for the aircraft noise prediction framework J-FRAIN

In this study, we created sound source models for a newly developed simulation framework named 'J-FRAIN' that can accurately predict the time histories of noises from each major aircraft noise-generating component at ground observation points during the landing approach phase. Sound source distributions of more than twenty types of jet transport aircraft have been measured in flight using a microphone array deployed under the final approach path to an airport. In this paper, the Boeing 787-8 is presented as an example for modeling. The sound powers of each aircraft component - engines, landing gear, and high-lift devices - were calculated quantitatively from the domain integration of the measured acoustic maps. Then, component-wise regression sound source models were created based on the relationship between engine rotational speed, airspeed, and deployment angle of high-lift devices. The models were implemented in the 'J-FRAIN' simulation framework that integrates a sound propagation model. The predicted time histories of ground noise were compared with measurement results from a single microphone placed at the center of the microphone array, and were found to be in good agreement.

Aircraft noise impact prediction with incorporation of meteorological effects

As part of a research effort towards greener aviation, this study focuses on the noise impact of aircraft operations around major airports. First, a pre-existing aircraft noise prediction platform based on a simplified (semi-empirical) approach is refined, to account for all refraction effects inherited from realistic (e.g., heterogeneous) atmospheres. To do so, the platform is enhanced with a more advanced noise propagation kernel relying on Ray Tracing, which combines state-of-the-art functionalities and novel refinements (e.g., to account for the three-dimensional nature of winds). This improved prediction platform is then validated against various benchmark cases, delivering outcomes of both phenomenological and methodological natures (e.g., the importance of accounting for 3D wind patterns whilst numerically handling them with care). Finally, the platform is applied to real-life situations involving representative aircraft operations and actual meteorological conditions, revealing how weather variations can significantly alter the propagation − and thus impact − of aircraft noise.

Assessment of an Open-Source Aircraft Noise Prediction Model Using Approach Phase Measurements

An open-source simulation model for aircraft noise prediction is presented and validated using backpropagated noise measurements for a state-of-the-art engine and aircraft. The validation is focused on approach procedures and was performed using ground-based noise measurements that were taken at 17 recording stations for a total of 18 consecutive flights carried out during the morning of 8 April 2021. The flights were performed using two A321neo aircraft with LEAP-1A engines. It is demonstrated that the presented noise model provides a satisfactory estimation of the source noise for varying approach configurations and flight conditions. Configurations using a greater number of high-lift devices are particularly well predicted in the mid- and high-frequency regions, whereas the lower configuration settings show greater spectral deviations, which are partly attributed to measurement uncertainties caused by the increased aircraft–microphone distance. The model can predict the overall mean total sound intensity level within a 2 dB accuracy for all configurations, while the average predicted level at each microphone differs by less than 3 dB from the measurement average, for all cases except one. Variation in aircraft speed showed to have a strong impact on the predicted total noise, which matches the well-recognized sixth-power Mach number far-field sound intensity scaling law for airframe noise models, while the measurements indicated a less significant dependency. This is mainly due to installation effects and noise reduction measures that are not included in the models. Nevertheless, the variations in the spectra of the predicted and measured noise showed similar patterns.

Assessing the influence of street canyon shape on aircraft noise: results from measurements in courtyards near Amsterdam Schiphol Airport.

Aircraft noise prediction models traditionally omit buildings to optimize speed. Buildings and vertical surfaces scatter and reflect incident sound, affecting sound levels around buildings and within streets. Previous studies showed the impact of buildings on aircraft noise, based on a small number of measurements. Based on additional numerical models, it was found that the shape of buildings, i.e. a slanted or overhanging roof, lead to lower sound levels compared to streets comprised of vertical and flat surfaces. To examine these findings, a full-scale field lab was built near Amsterdam Schiphol Airport, comprised of shipping containers. The experiment consists of three courtyards, in which ten microphones measure sound levels from aircraft flyovers, near facades facing towards and away from the sound source (airplanes). Measurements are matched with meteorological and radar data, which gives information about the position of aircraft and the local weather conditions. The measurements show substantial differences depending on the position, ranging between 11dB(A) for a courtyard with straight facades, up to 14dB(A) for facades in a courtyard with a slanted roof and a roof overhang. Results can be used to rethink the way areas near airports are designed.

Challenges and opportunities for low noise electric aircraft

A new class of electric aircraft is being developed to transport people and goods as a part of the urban and regional transportation infrastructure. To gain public acceptance of these operations, these aircraft need to be much quieter than conventional airplanes and helicopters. This article seeks to review and summarize the aeroacoustic research relevant to this new category of aircraft. First, a brief review of the history of electric aircraft is provided, with an emphasis on how these aircraft differ from conventional aircraft. Next, the physics of rotor noise generation are reviewed, and the noise sources most likely to be of concern for electric aircraft are highlighted. These are divided into deterministic and nondeterministic sources of noise. Deterministic noise is expected to be dominated by the unsteady loading noise caused by the aerodynamic interactions between components. Nondeterministic noise will be generated by the interaction of the rotor or propeller blades with turbulence from ingested wakes, the atmosphere, and self-generated in the boundary layer. The literature for these noise sources is reviewed with a focus on applicability to electric aircraft. Challenges faced by the aeroacoustician in understanding the noise generation of electric aircraft are then identified, as well as the new opportunities for the prediction and reduction of electric aircraft noise that may be enabled by advances in computational aeroacoustics, flight simulation, and autonomy.

Constructing a physics-guided machine learning neural network to predict tonal noise emitted by a propeller

Artificial neural networks offer a highly nonlinear and adaptive model for predicting complex interactions between input-output parameters. However, these networks require large datasets which often exceed practical considerations in modeling experimental results. To alleviate the dataset size requirement, a method known as physics-guided machine learning has been applied to construct several neural networks for predicting propeller tonal noise in the time domain over a broad range of flight conditions. Three space-filling designs, namely, Latin-Hypercube, Sphere-Packing, and Grid-Space, were used to distribute points throughout the input parameter space encompassing nondimensional flight conditions and observer geometry. Each neural network's performance was validated by conditions outside of the training set and compared to the Propeller Analysis System tool from the NASA Aircraft Noise Prediction Program. The Latin-Hypercube and the Sphere-Packing designs provided a uniform representation of the domain, which improved the tonal noise prediction in comparison to the Grid design. The black-box nature of these neural networks was explored, and post-network functions were developed to remove discontinuities in the acoustic signal. Overall, the methods herein show a notable improvement in prediction performance in comparison to a multilayer perceptron. Additional loss functions are necessary for ensuring reasonable accuracy of predictive networks on small datasets and will be investigated for the final paper.

Systematic validation of the PAAShA shielding prediction method

Based on classical diffraction theories with modifications and extensions in analytical formulations and numerical implementations, a new code has been developed at NASA for the prediction of aircraft noise shielding, named as Propulsion Airframe Aeroacoustic Shielding Attenuation (PAAShA). The code is developed primarily for aircraft system noise predictions, although it may also be useable in other applications with acoustic shielding. The requirements for this code are driven by the need for a robust, capable code to use with NASA’s Aircraft Noise Prediction Program (ANOPP) for aircraft integration and system noise research. The requirements are met and include capabilities to use a wide range of aircraft geometries, rapid calculation times consistent with aircraft system noise problems, and the flexibility to model realistic noise source characteristics and distributions. The accuracy and robustness of the method are demonstrated in this paper with a set of problems, including a cylinder, a finite plate, a symmetrical two-dimensional airfoil, and a full three-dimensional hybrid wing body aircraft model tested in a wind tunnel. This range of problems demonstrates both smooth and sharp edge diffraction capabilities for a wide range of frequencies and low Mach number flow effects at low angles of attack. Predictions are shown to be accurate to within 1–4 dB over a wide range of the most significant frequencies and directivity angles. This is determined by comparing with data, which have experimental uncertainties, particularly at high frequencies, high angles, and source characteristics. The accuracy diminishes for geometries that include a significant reflection component, which is not calculated by the code. Accuracy can also be somewhat diminished for high azimuthal angles. Accurate modeling of the noise source, particularly its frequency and directivity characteristics, is essential to obtaining accurate results.

Comparative assessment of measured and modelled aircraft noise around Amsterdam Airport Schiphol

The impressive growth of the aviation industry and the number of flights entail several environmental repercussions, such as increased aircraft noise emissions. With the worrying number of complaints from the communities around airports comes also the distrust in numerical models used for aircraft noise prediction. In this study, we compare the ‘Dutch aircraft noise model’ predictions to measured values from the NOise MOnitoring System (NOMOS) around Amsterdam Airport Schiphol between 2012 and 2018. While the model underestimates aircraft noise in 2012, the model prediction improved throughout the years. We observe a decreasing trend of measured aircraft-related L d e n values of 0.6 dB(A)/year (a total of 3.6 dB(A) over the investigation period), although the total number of flight movements increased during the observation time. We propose that a change in fleet mix, as well as the implementation of Noise Abatement Procedures at Schiphol Airport, fuelled this trend.

Guidelines for the LTO Noise Assessment of Future Civil Supersonic Aircraft in Conceptual Design

One of the most critical regulatory issues related to supersonic flight arises from limitations imposed by community noise acceptability. The most efficient way to ensure that future supersonic aircraft will meet low-noise requirements is the verification of noise emissions from the early stages of the design process. Therefore, this paper suggests guidelines for the Landing and Take-Off (LTO) noise assessment of future civil supersonic aircraft in conceptual design. The supersonic aircraft noise model is based on the semi-empirical equations employed in the early versions of the Aircraft NOise Prediction Program (ANOPP) developed by NASA, whereas sound attenuation due to atmospheric absorption has been considered in accordance with SAE ARP 866 B. The simulation of the trajectory leads to the prediction of the aircraft noise level on ground in terms of several acoustic metrics (LAmax, SEL, PNLTM and EPNL). Therefore, a dedicated validation has been performed, selecting the only available supersonic aircraft of the Aircraft Noise and Performance database (ANP), that is, the Concorde, through the matching with Noise Power Distance (NPD) curves for LAmax and SEL, obtaining a maximum prediction error of ±2.19%. At least, an application to departure and approach procedures is reported to verify the first noise estimations with current noise requirements defined by ICAO at the three certification measurement points (sideline, flyover, approach) and to draw preliminary considerations for future low-noise supersonic aircraft design.

Prediction of Aircraft Noise Impact with Application to Hong Kong International Airport

As part of a collective research effort towards greener aviation, the present study focuses on the noise impact of aircraft operations around major airports. To this end, an aircraft noise prediction platform is developed, which relies on state-of-the-art functionalities as well as more specific, innovative features. Originally built upon the Aircraft Noise and Performance (ANP) database and its Noise–Power–Distance (NPD) table, the method is further refined to alleviate most of their inherent limitations (e.g., standardized and simplified aircraft noise scenarios). The resulting aircraft noise prediction platform is validated against benchmark cases of increasing complexity, being then applied to real-life situations involving actual aircraft operations around Hong Kong International Airport (HKIA). Specific comparative analyses are conducted, which allow highlighting the variability of the noise impact by aircraft, depending on their type (A330, B777) and/or operational conditions (power settings, meteorological conditions, routes, banks, etc.). The study delivers insightful outcomes, whether phenomenological (aircraft noise impact) or methodological (aircraft noise prediction). As a by-product, it illustrates how noise prediction methods/platforms such as the present one may help in guiding the further expansion of airport operations and/or infrastructures (as is currently the case with HKIA).

Aircraft System Noise of the NASA D8 Subsonic Transport Concept

A vehicle-level noise assessment has been performed for the NASA D8 (ND8) concept aircraft in the NASA Advanced Air Transport Technology Project portfolio. The NASA research-level Aircraft Noise Prediction Program was used to predict the noise from each source component on the ND8 to build up a noise estimate for the full aircraft. The propulsion airframe aeroacoustic effects of the ND8 (namely, boundary-layer ingestion, with its influence on fan noise; and the noise shielding, reflection, and diffraction mechanisms of the unconventional airframe) were empirically modeled using experimental data. Far-term noise reduction technology concepts were modeled and added to the noise prediction to evaluate the low-noise potential of the ND8 in the far-term timeframe. Results indicate that the increase in fan noise due to boundary-layer ingestion, as well as the lack of aft shielding, prevents the aircraft from approaching NASA’s noise goals for either the midterm or far term. The aircraft achieves margins to Stage 4 of only 9.4 and 17.3 effective perceived noise in decibels (EPNdB) in the midterm and far-term configurations, respectively, compared with goals of 32–42 EPNdB in the midterm and 42-52 EPNdB in the far term.

Prediction and simulation of aircraft noise in the international Eskisehir Hasan Polatkan airport (LTBY)

PurposeIn recent years, in parallel with the increasing air traffic and the number of passengers in air transport, the number of people exposed to aircraft-induced noise has increased significantly. Especially people living in the areas close to the airports are affected by noise emission during the landing, take-off, taxi and ground operations. Negative effects of noise such as sleep disturbance, lack of concentration, anxiety and high blood pressure cardiac diseases were determined directly or indirectly for human health. For this reason, examining the noise effect caused by aircraft and determining the necessary measures to be taken is very important for the sustainable development of aviation. In the International Eskisehir Hasan Polatkan Airport (LTBY), this paper aims to calculate a noise mapping following international standards in line with the directives of the International Civil Aviation Organization (ICAO). Also, Annex 8, “Airworthiness of Aircrafts” and Annex 16, “Environmental Protection Volume 1 Aircraft Noise”, which were taken at the International Civil Aviation Convention, were proposed to determine the exposure caused by aircraft noise.Design/methodology/approachIn this paper, noise levels for the day (07.00–19.00), evening (19.00–23.00) and night (23.00–07.00) period around LTBY were predicted and calculated by the use of the IMMI software according to the “ECAC Doc. 29-Interim” method for the prediction and computation of the aircraft noise.FindingsAccording to the calculated/mapped values, in the 24 hours (Lden), the noise level is 65 dB (A) and above. In the day time zone, the noise level is 63 dB (A) and above. When the calculations for the evening time zone are examined, the noise level is above 58 dB (A). When the calculations for the night time frame are examined, it is calculated that there is no dwelling that is affected by the noise level above 53 dB (A).Practical implicationsAlong with future improvements, it is recommended to be applied to other civil airports.Originality/valueTo the best of the authors’ knowledge, there is no previous research in the literature on aircraft noise mapping of LTBY. Also, unlike the software commonly used in other works in the literature, IMMI software was used in this study. Such investigations should be carried out in other civil airports in the coming years to struggle with noise emissions and noise control. If noise boundary values are exceeded, action plans should be developed for a sustainable aviation concept. Along with future improvements, it is recommended to be applied to other civil airports.

Doppler's shift on aircraft noise propagation in modern aircraft noise prediction tools

Doppler’s effect is an important factor in the prediction of the noise levels caused by en-route aircrafts. This study is focused on the influence of Doppler’s effect on the propagation of aircraft noise. The received sound pressure can be increased/decreased by Doppler’s effect depending on the relative location of the sound source and receiver. At the same time, the spectral shape of the noise is shifted by this effect which has an impact on the measured A-weighted noise levels. This influence is largely due to the fact that A-weighted correction factors of mid-frequency range are much larger than that those in the low-frequency regime. In this paper, a series of field trial was used to study the propagation effect of noise generated by a propeller-driven aircraft. Aviation Environment Design Tool (AEDT), a widely accepted noise prediction model of aircraft noise, is used to compare with the predictions according to a ray-based numerical model. The inclusion of Doppler’s effect in the noise prediction model has shown to have a better agreement with the field measurement results. The influence of Doppler’s effect on the noise-power-distance (NPD) curves of several different aircrafts is also presented. [Work sponsored by ASCENT, FAA Center of Excellence for Alternative Jet Fuels and Environment.]

Robust Acoustic Objective Functions and Sensitivities in Adjoint-Based Design Optimizations

The multidisciplinary design of aircraft typically includes considerations of performance, weight, fuel burn, and noise, among other factors. Objective functions and constraints reflect these considerations to weigh the tradeoff between different designs. Higher-fidelity optimization exercises have used an adjoint approach to reach an optimal set of aerodynamic objective functions, such as increased lift and reduced drag. The adjoint approach significantly reduces the computational time required to find an optimal configuration when there are many design parameters and few objective functions and constraints. Including acoustics in an adjoint-based design optimization requires the sensitivity of acoustic objective functions with respect to design parameters. This paper presents an approach for defining the sensitivity of several acoustic objective functions, including time-integrated metrics, such as effective perceived noise level, and frequency-integrated metrics, such as overall sound-pressure level. A demonstration, validation, and details on the sensitivity analysis implementation in the second-generation Aircraft Noise Prediction Program are also shown.

Far-Term Noise Reduction Roadmap for the Midfuselage Nacelle Subsonic Transport

A noise reduction technology roadmap study is presented to determine the feasibility for the midfuselage nacelle (MFN) aircraft concept to achieve the noise goal set by NASA for the far-term timeframe, which is beyond 2035. The study starts with updating the noise prediction of the MFN configuration modeled for the timeframe between 2025 and 2035, with a prediction of 34.3 dB cumulative effective perceived noise level below the stage 4 regulation. A suite of technologies that are deemed feasible to mature for practical implementation in the far term and for which the potentials for noise reduction have been demonstrated is selected for analysis. For each technology, component noise reduction is modeled either by available experimental data or by physics-based modeling with aircraft system-level methods. The noise reduction is then applied to the corresponding component predicted by advanced aircraft noise prediction tools. It is shown that the far-term MFN aircraft has the potential to achieve a cumulative effective perceived noise level up to 40.2 dB below stage 4 if all noise reductions are fully realizable. The key technologies to achieve this low noise level are assessed by the impact of each technology on the aircraft system noise.

10 years of joint research at DLR and TU Braunschweig toward low-noise aircraft design-what did we achieve?

This review article is based on an invited keynote presentation at the 22ndWorkshop of the Aero acoustics Specialists Committee of the CEAS. The event was held in September 2018 in Amsterdam with the main focus on the relation between aircraft design and noise impact. This article reviews the last years of joint research activities between the German Aerospace Center (DLR) and the Technical University of Braunschweig (TU BS) in the field of low-noise aircraft design. The joint research was initiated around 2008 between the DLR Institute of Aerodynamics and Flow Technology and the Institute of Aircraft Design and Lightweight Structures at TU BS. Around that time, DLR was developing a first version of an aircraft noise prediction tool. This tool has then consequently been implemented as a module into the aircraft design synthesis code of the TU BS. In 2012, for the first time, a fully automated and fully parametric aircraft design process with integrated noise prediction capabilities was established, i.e., including a full approach and departure flight simulation. The main focus lies on conventional tube-and-wing aircraft with turbofan or turboprop engine concepts. Ever since 2012, the tools have been under constant development and the simulation chain for low-noise aircraft design has been applied to various aircraft concepts. This article is comprised of a description of the tool development from 2008 until early 2018 and a selected application example. Some lessons learned and a brief outlook on future developments and applications conclude this review.