Sebastien Guerin

Airframe noise characteristics from flyover measurements and prediction

Aircraft noise impact around airports will increase corresponding to the predicted growth in air-traffic if no measures for aircraft source noise reduction are taken or noise abatement flight procedures are developed. During the final approach phase engine noise and airframe noise are comparable in level, the latter being governed by flow noise originating from landing gears and high lift devices. Based on the results of dedicated wind tunnel studies semi-empirical/empirical airframe noise prediction schemes were developed for both high lift devices’ and landing gear noise to support the calculation of noise impact in the vicinity of airports. Within an ongoing German national research project on the development of noise abatement procedures, co-financed by the German Ministry of Education and Research (BMBF), flyover noise measurements were conducted on an Airbus A319 aiming at the validation of DLR’s airframe noise prediction schemes. In order to distinguish between airframe and engine noise sources flyovers were performed for different aircraft configurations and operational conditions.

Airbus A319 Database from Dedicated Flyover Measurements to Investigate Noise Abatement Procedures

A series of flyover noise tests on the Airbus A319 performed in the framework of the German project ”Noise Optimized Approach and Departure Procedures (LAnAb)” took place at Parchim airport (Germany) in June 2004. A noise database was created that will be a support for the validation of aircraft noise prediction models dedicated to investigate noise abatement procedures. In all, 37 take-off and 82 approach conditions were simulated. Depending on the simulated flight phase, different values of engine power, airspeed, position of the high-lift devices, and also of the landing gears were tested. The aim of this paper is to show the different possibilities of using the signals recorded by a phased-array of microphones installed on the ground to analyse aircraft noise and confront some prediction models to the results.

The Parametric Aircraft Noise Analysis Module - status overview and recent applications

The German Aerospace Center (DLR) is investigating aircraft noise prediction and noise reduction capabilities. The Parametric Aircraft Noise Analysis Module (PANAM) is a fast prediction tool by the DLR Institute of Aerodynamics and Flow Technology to address overall aircraft noise. It was initially developed to (1) enable comparative design studies with respect to overall aircraft ground noise and to (2) indentify promising low-noise technologies at early aircraft design stages. A brief survey of available and established fast noise prediction codes is provided in order to rank and classify PANAM among existing tools. PANAM predicts aircraft noise generated during arbitrary 3D approach and take-off flight procedures. Noise generation of an operating aircraft is determined by its design, the relative observer position, configuration settings, and operating condition along the flight path. Feasible noise analysis requires a detailed simulation of all these dominating effects. Major aircraft noise components are simulated with individual models and interactions are neglected. Each component is simulated with a separate semi-empirical and parametric noise source model. These models capture major physical effects and correlations yet allow for fast and accurate noise prediction. Sound propagation and convection effects are applied to the emitting noise source in order to transfer static emission into aircraft ground noise impact with respect to the actual flight operating conditions. Recent developments and process interfaces are presented and prediction results are compared with experimental data recorded during DLR flyover noise campaigns with an Airbus A319 (2006), a VFW-614 (2009), and a Boeing B737-700 (2010). Overall, dominating airframe and engine noise sources are adequately modeled and overall aircraft ground noise levels can sufficiently be predicted. The paper concludes with a brief overview on current code applications towards selected noise reduction technologies.

Simultaneous Computation of Surface and Volume Sources for Fan Broadband Noise with the Random-Particle-Mesh Method

The relative contribution of broadband noise has steadily increased over the last decades as the mechanisms creating tones are now well understood and can be efficiently reduced. For fan-design capabilities an interim or intermediate solution is needed between restrictive analytical models and full-resolved costly simulations. Ewert et al.1 proposed an affordable way to simulate broadband noise with a CAA solver in the time domain while accounting for the complex geometry and background flow. The Random-Particle-Mesh (RPM) method reconstructs the turbulent fluctuations based on a RANS calculation. Turbulence source is coupled to the Acoustic Perturbation Equations solved by a CAA solver. The approach was applied sucessfully for slat noise and generic trailing-edge noise problems. Our investigations showed that this coupling method does not work sufficiently for lead- ing edge noise of generic airfoil configurations if the vortex sound sources are determined from an incident vorticity field that does not include the additional effect of scattered vorticity shed from the trailing edge of the airfoil due to the presence of a Kutta condition. The objective of this article is to extend and validate the coupling between the RPM and the CAA domain to explicitly include the enforcement of the Kutta condition into the CAA model for homogeneous and potential flow. This is achieved by adding another domain which computes the vorticity–wall interaction. Theoretically the approach should be sufficient to separate the surface from the volu- metric sources. This works very well for a flat plate. But we apply this on a NACA0012 airfoil in potential flow which gives unreasonable results. We discuss the issue and offer ideas for this cause.

CFD/CAA Coupling Applied to the DLR UHBR-Fan: Comparison to Experimental Data

A CFD-CAA hybrid method for fan noise prediction is presented and compared to experimental data. The study shows a very good agreement between numerical simulations and experimental measurements regarding the level of the rotor-stator interaction tones generated by a Ultra-High Bypass Ratio Fan designed by DLR. The comparison is done at a single approach condition for which the blade passing frequency (BPF 1) is cut-off. For the BPF 2, the sound pressure level measured in the inlet is in agreement within 1 or 2 dB with the experimental results. The agreement in terms of radial mode amplitudes is also very satisfying. The discrepancies are slightly higher for the BPF 3 and 4. Nevertheless the trends of the results, for instance the fact that the tone is higher at BPF 4 than BPF 3, are all well predicted. Most of the discrepancies are of the order of the amplitude variations measured between the two investigated experimental runs. The boundary layer influence on the sound propagation is shown to increase with the frequency as stated in literature. Some numerical results from the bypass duct are also presented.

A Hybrid Time-Frequency Approach for the Noise Localization Analysis of Aircraft Fly-overs

A hybrid time-frequency approach based on acoustic beamforming has been successfully developed in order to determine the absolute contribution of the aircraft noise components measured during fly-overs. The method, derived from DAMAS, 1 accounts for the fact that the sources move relative to the microphones. Indeed, the motion is responsible for a frequency shift of the sidelobes and a strong modification of the point-spread functions compared to the static case. The method developed is hybrid in the sense that the beamforming algorithm is applied in the time domain while the point-spread functions are approximated in the frequency domain. When the sound sources are characterized by broadband spectra, it becomes possible to discard the frequency coupling between the sources and the sidelobes. This enables to reduce the computing time considerably. In the present publication, the method is applied to AIRBUS A340 fly-overs with the high-lift devices deployed, landing gear up, and the engines running at idle. The study is focused on the influence of some processing parameters (grid spacing, number of iterations, cut of the focusing grid, and frequency bandwidth) on the source breakdown. It turns out that the noise spectra of the aircraft components are almost independent of reasonable variations of these parameters. This indicates that the method is relatively robust. A detailed investigation of the noise sources (flaps, slats, and engines) with respect to the variations of the airspeed, the ECAM position, the engine rating, etc. is not part of this work.

A robust extension to the triple plane pressure mode matching method by filtering convective perturbations

Time-periodic computational fluid dynamics simulations are widely used to investigate turbomachinery components. The triple plane pressure mode matching method developed by Ovenden and Rienstra extracts the acoustic part in such simulations. Experience shows that this method is subject to significant errors when the amplitude of pseudo-sound is high compared to sound. Pseudo-sounds are unsteady pressure fluctuations with a convective character. The presented extension to the triple plane pressure improves the splitting between acoustics and the rest of the unsteady flow field. The method is simple: (i) the acoustic eigenmodes are analytically determined for a uniform mean flow as in the original triple plane pressure mode matching method; (ii) the suggested model for convective pressure perturbations uses the convective wavenumber as axial wavenumber and the same orthogonal radial shape functions as for the acoustic modes. The reliability is demonstrated on the simulation data of a low-pressure fan. As acoustic and convective perturbations are separated, the accuracy of the results increases close to sources, allowing a reduction of the computational costs by shortening the simulation domain. The extended method is as robust as the original one–giving the same results for the acoustic modes in absence of convective perturbations.

Analytical reconstruction of isotropic turbulence spectra based on the Gaussian transform

Abstract The field of application of the Random Particle Mesh (RPM) method used to simulate turbulence-induced broadband noise in several aeroacoustic applications is improved to realise isotropic turbulence spectra. With this method turbulent fluctuations are synthesised by filtering white noise with a Gaussian filter kernel that in turn gives a Gaussian spectrum. The Gaussian filter is efficient and finds wide-spread applications in stochastic signal processing. However Gaussian spectra do not correspond to real turbulence spectra. Thus in turbo-machines the von Karman, Liepmann , and modified von Karman spectra are more realistic model spectra. In this note we analytically derive weighting functions to realise arbitrary isotropic solenoidal spectra using a superposition of weighted Gaussian spectra of different length scales. The analytic weighting functions for the von Karman , the Liepmann , and the modified von Karman spectra are derived subsequently. Finally a method is proposed to discretise the problem using a limited number of Gaussian spectra. The effectivity of this approach is demonstrated by realising a von Karman velocity spectrum using the RPM method.

Open-rotor noise prediction with a RANS informed analytical method

Analytical models are informed by a steady-state RANS calculation with mixing plane in order to predict turbomachinery noise with a short computing time; the method is tested on the example of a contra-rotating open-rotor propulsion system at take-off condition; the results are compared to these of an unsteady RANS calculation with the pressure far field given by the Ffowcs Williams–Hawkings solution for a porous integration surface. Regarding the rotor-alone tones, the sound power level agrees within 0.5 dB between the two methods; for the interaction tones, the discrepancy is around 2 dB reaching up to 10 dB locally on the directivity. So far the sound-generating mechanisms considered by the acoustical models are the steady loading and thickness tonal components and the unsteady periodic loading of the aft rotor due to the interaction with the front-rotor wakes. Inherently, the prediction of interaction noise with the RANS-informed analytical approach lacks accuracy for two main reasons. First, the determination of the unsteady lift relies on a gust response function, the prediction of which ist not commonplace for real loaded blades; the analytical solution for a flat plate is applied in the present study. Second, the wake velocity profiles used as input for the gust response function are mixed out at the interface between the two rotors typically located in the middle of the rotor interval; ideally the values at the aft-rotor leading edge should be used. An evaluation of these two problems shall be undertaken before using the RANS-informed analytical method for aeroacoustic design optimisation.

Similarities of the free-field and in-duct formulations in rotor noise problems

This paper deals with the comparison between open rotor and ducted fan noise. Similar theoretical formulations for the freeeld and in-duct noise problems are derived from the original equation for noise generation given by Goldstein. The form of the nal equations enables to separate the terms related to noise propagation from those representing the acoustic source. Among the similarities shared by the freeeld and in-duct cases, the possibility to de ne a common cut-o ratio for the spinning modes provides some insight in the relation between the position of the sources and the excited modes in a way more general than that already proposed by the authors. With help of this formalism we hope to reach a better understanding of the di erences in noise levels to be expected on contrarotating open rotor (CROR) and contra-rotating turbofan (CRTF) concepts.