Fast Random Particle-Mesh Method Research Articles

Stochastic Noise Sources for Computational Aeroacoustics of a Vehicle Side Mirror

<div>The broadband aeroacoustics of a side mirror is investigated with a stochastic noise source method and compared to scale-resolving simulations. The setup based on an already existing work includes two geometrical variants with a plain series side mirror and a modified mirror with a forward-facing step mounted on the inner side. The aeroacoustic near- and farfield is computed by a hydrodynamic–acoustic splitting approach by means of a perturbed convective wave equation. Aeroacoustic source terms are computed by the Fast Random Particle-Mesh method, a stochastic noise source method modeling velocity fluctuations in time domain based on time-averaged turbulence statistics. Three RANS models are used to provide input data for the Fast Random Particle-Mesh method with fundamental differences in local flow phenomena. Results of aeroacoustics simulations excited by the Fast Random Particle-Mesh method based on well-matching RANS data are in good agreement to the scale-resolving simulations in the integral acoustic Delta on the side window induced by the different side mirror geometries. For relative levels in between the variations, the robustness of the Fast Random Particle-Mesh method can be shown with secondary influences on the choice of the integral length scale. Absolute levels are only achieved with an adaptation of the length scale from literature. Two different RANS models with a missing separation bubble on the mirror or an overestimated wake flow show a good agreement with the plain series side mirror. However, they fail at computing the Delta to the step variant due to the missing amplification of the local turbulent kinetic energy interacting with the step and downstream mirror surfaces. Computational aeroacoustics simulations excited by the Fast Random Particle-Mesh method method based on RANS data only needs 14% of the computational effort compared to the conventional hybrid RANS-LES approach. This reveals its enormous potential for aeroacoustic broadband noise optimization purposes.</div>

Trailing-edge noise reduction of a wing by a surface modification

There is an increased emphasis on reducing airframe noise in the last decades. Airframe noise is sound generated by the interaction of a turbulent flow with the aircraft geometry, and significantly contributes to the overall noise production during the landing phase. One examples of airframe noise is the noise generated at a wing's trailing edge, i.e., trailing-edge noise. In this contribution, we numerically explore the local application of riblets for the purpose of trailing-edge noise reduction. Two configurations are studied: i) a clean NACA0012 wing section as a reference, and ii) the same configuration with riblets installed at the wing's aft part. The numerical investigation follows a hybrid computational aeroacoustics approach, where the time-average flow is studied by means of RANS. Noise sources are generated by means of a stochastic approach called Fast Random Particle Mesh method. The results show a deceleration of the flow behind the riblets. Furthermore, the turbulent kinetic energy indicates increased unsteadiness behind the riblets which is shifted away from the wall due to the presence of the riblets. Lastly, the sound sources are investigated by means of the 3D Lamb-vector, which indicates a slight reduction in magnitude near the trailing edge.

Comparison of predicted fan broadband noise using a two- versus a three-dimensional synthetic turbulence method

Fan broadband noise - in particular broadband rotor-stator-interaction noise - is a significant noise source of modern aircraft. However, its accurate prediction remains a challenge. RANS-informed synthetic turbulence methods are increasingly applied for these types of noise predictions as they present a compromise between accuracy and computational effort. Two-dimensional simulations are especially inexpensive but their results are not necessarily representative for the entire fan stage. To investigate this issue, the authors present the expansion of an approach based on the fast Random Particle Mesh method to three-dimensional space and apply it to the AneCom AeroTest Rotor 1 fan stage. The three-dimensional simulations are compared in detail to two-dimensional simulations to quantify and analyze observed differences between the results. As a consequence, a correction technique for the two-dimensional simulation results is proposed.

Simulation of Surface Pressure Fluctuations on an Airbus-A320 Fuselage at Cruise Conditions

The fuselage surface pressure fluctuations on an Airbus-A320 aircraft at cruise conditions are simulated by solving a Poisson equation. The right-hand-side source terms of the Poisson equation, including both the mean-shear term and the turbulence–turbulence term, are realized with synthetic turbulence generated by the fast random particle-mesh method. The stochastic realization is based on time-averaged turbulence statistics derived from a Reynolds averaged Navier–Stokes simulation under the same condition as in the flight tests conducted with DLR, German Aerospace Center’s Airbus-A320 research aircraft. The fuselage surface pressure fluctuations are calculated at three streamwise positions from front to rear, corresponding to the measurement positions in the flight tests. Features of the pressure fluctuations relevant to the fuselage surface excitation are obtained and analyzed. A good agreement for one- and two-point spectral characteristics of the surface pressure fluctuations is found between the simulation and flight-test results.

Numerical prediction of passenger cabin noise due to jet noise by an ultra–high–bypass ratio engine

Within the framework of the Collaborative Research Center 880, future civil transportation aircraft are investigated. One major aim is a drastic reduction of the noise emission to the ground and an appropriate noise immission into the passenger cabin. The latter forms the focus of this contribution with the aim to ensure an equal or lower noise level in the cabin for new aircraft configurations. Numerical methods are applied to establish a multidisciplinary modeling chain resulting in a prediction of cabin noise due to jet noise by two different engine configurations. An ultra–high–bypass ratio engine is compared to a conventional engine on the basis of a preliminary aircraft design used for both configurations. On the basis of flow calculations in cruise flight as operation point, the hybrid Computational Aeroacoustics solver PIANO combined with the Fast Random Particle Mesh method is applied to compute the pressure fluctuations due to jet noise on the outer skin of the fuselage. These loads are applied to a finite element model considering the structure and the fluid of the aircraft cabin. The acoustic model resolving the structure-borne and airborne sound waves is derived from the design data. The results show a lower sound pressure level induced by the ultra–high–bypass ratio engine in the entire frequency range on the outer skin. Within the cabin, the modern engine is still much quieter, though this fact is not generally valid for the entire frequency range as transmission effects of the double wall occur.

Zonal Overset-LES with stochastic volume forcing

In this contribution, a hybrid Zonal LES tool is presented that uses a stochastic volume forcing for “inflow” turbulence generation. The here used hybrid approach is based on an implementation of the Non-Linear Perturbation Equations extended with fluctuating viscous terms, denoted as “Overset” since a perturbation analysis is performed on top of a background flow. A turbulent flat plate is considered to investigate the generation of inflow turbulence and how this artificial turbulence is seeded into the computational domain. At the inflow region, turbulence is stochastically generated (in three-dimensional space and time) with the Fast Random Particle-Mesh method and subsequently injected in the Overset-LES domain with the eddy-relaxation source term. This eddy-relaxation source term is shown to pilot the hydrodynamics while leaving the acoustics untouched (i.e., transparent for acoustic). The application of the Overset-LES method to a NACA0012 trailing edge at zero angle-of-attack is furthermore presented. Mean flow and turbulence characteristics in the wake show a good agreement with experimental data. Finally, a possible way to couple the turbulent sound sources into a CAA simulation is described. Comparison between directivities obtained with this method and reference data revealed good agreement.

Simulation of turbulent boundary layer wall pressure fluctuations via Poisson equation and synthetic turbulence

Flat plate turbulent boundary layers under zero pressure gradient are simulated using synthetic turbulence generated by the fast random particle–mesh method. The stochastic realisation is based on time-averaged turbulence statistics derived from Reynolds-averaged Navier–Stokes simulation of flat plate turbulent boundary layers at Reynolds numbers $\mathit{Re}_{\unicode[STIX]{x1D70F}}=2513$ and $\mathit{Re}_{\unicode[STIX]{x1D70F}}=4357$. To determine fluctuating pressure, a Poisson equation is solved with an unsteady right-hand side source term derived from the synthetic turbulence realisation. The Poisson equation is solved via fast Fourier transform using Hockney’s method. Due to its efficiency, the applied procedure enables us to study, for high Reynolds number flow, the effect of variations of the modelled turbulence characteristics on the resulting wall pressure spectrum. The contributions to wall pressure fluctuations from the mean-shear turbulence interaction term and the turbulence–turbulence interaction term are studied separately. The results show that both contributions have the same order of magnitude. Simulated one-point spectra and two-point cross-correlations of wall pressure fluctuations are analysed in detail. Convective features of the fluctuating pressure field are well determined. Good agreement for the characteristics of the wall pressure fluctuations is found between the present results and databases from other investigators.

Efficient Prediction of Broadband Noise of a Centrifugal Fan Using U-FRPM Technique

ABSTRACT: Recently, a lot of studies have been made about the methods used to generate turbulent velocity fields stochastically in order to effectively predict broadband flow noise. Among them, the FRPM (Fast Random Particle Mesh) method which generates turbulence with specific statistical properties using turbulence kinetic energy and dissipation obtained from the steady solution of the RANS (Reynolds Averaged Navier-Stokes) equations has been successfully applied. However, the FRPM method cannot be applied to the flow noise problems involving intrinsic unsteady characteristics such as centrifugal fan. In this paper, to effectively predict the broadband noise generated by centrifugal fan, U-FR PM (unsteady FRPM) method is developed by extending the FRPM method to be combined with the unsteady numerical solutions of the unsteady RANS equations to generate the turbulence considered as broadband noise sources. Firstly, an unsteady flow field is obtained from the unsteady RANS equations through CFD (Computational Fluid Dynamics). Then, noise sources are generated using the U-FRPM method combined with acoustic analogy. Finally, the linear propagation model which is realized through BEM (Boundary Element Method) is combin ed with the generated sources to predict broadband noise at the listeners' position. The proposed technique is validated to compare its prediction result with the measured data.