Investigation of parallel computing for jet-surface interaction noise calculations

The canonical problem of a jet flow interacting with a plate positioned parallel to the level curves of the streamwise mean flow has received much attention in Aero-acoustics research community as a representation of jet installation effects. Goldstein et al [1] find that the acoustic spectrum for the round jet scattering problem is given a formula that involves the computation of4integrals. However, we found that to achieve a good representation of the turbulence structure this formula should be amended such that a numerical Fourier transform is required. Therefore, the acoustic spectrum now involves the calculation of5 nested integrals, one of which requires a small step size. Naturally, this is computationally expensive on standard desktop computers. Therefore, we investigate the use of parallel computing in order to speed up the calculations. We compare the use of multiple cores on a CPU to offloading the calculation to a GPU. We investigate the most efficient way to offload to the GPU taking into consideration the cost of data movement between CPU and GPU. Since more accurate representations of the turbulence will require a finer spatial grid, we also consider the effect on speed up as the step size of the integrals is reduced (by increasing the number of iterations). In general, our calculations using the GPU algorithm show a considerable reduction in computational time and a much larger reduction than using multiple cores on the CPU. This is particularly evident as the step size is reduced, increasing the utilisation of the GPU to full capacity, and reaching the maximum speed-up of 130. Therefore, this approach is a viable option for design/optimization calculations aimed at characterizing the acoustic signature, especially when using models which accurately represent turbulence and thus require a fine spatial grid

Modeling supersonic heated jet noise at fixed jet Mach number using an asymptotic approach for the acoustic analogy Green’s function and an optimized turbulence model

In this study we show how accurate jet noise predictions can be achieved within Goldstein’s generalized acoustic analogy formulation for heated and un-heated supersonic jets using a previously developed asymptotic theory for the adjoint vector Green’s function and a turbulence model whose independent parameters are determined using an optimization algorithm . In this approach, mean flow non-parallelism enters the lowest order dominant balance producing enhanced amplification at low frequencies, which we believe corresponds to the peak sound at small polar observation angles. The novel aspect of this paper is that we exploit both mean flow and turbulence structure from existent Large Eddy Simulations database of two axi-symmetric round jets at fixed jet Mach number and different nozzle temperature ratios to show (broadly speaking) the efficacy of the asymptotic approach. The empirical parameters that enter via local turbulence length scales within the algebraic-exponential turbulence model are determined by optimizing against near field turbulence data post-processed from the LES calculation. Our results indicate that accurate jet noise predictions are obtained with this approach up to a Strouhal number of 0.5 for both jets without introducing significant empiricism

Using Large Eddy Simulation within an Acoustic Analogy Approach for Jet Noise Modelling

A novel approach to the development of a hybrid prediction methodology for jet noise is described. Modelling details and numerical techniques are optimised for each of the three components of the model individually. Far field propagation is modelled via solution of a system of adjoint Linear Euler Equations, capturing convective and refraction effects via use of a spatially developing jet mean flow provided by a RANS CFD solution. Sound generation is modelled following Goldstein's acoustic analogy, including a Gaussian function model for the two-point cross-correlation of the 4th order velocity fluctuations in the acoustic source. Parameters in this model describing turbulent length- and time-scales are assumed to be proportional to turbulence information taken also from the RANS CFD prediction. The constants of proportionality are, however, not determined empirically, but extracted via comparison with turbulence length- and time-scales obtained from an LES prediction. The LES results are shown to be in good agreement with experimental data for the 4th order two-point cross-correlation functions. The LES solution is then used to determine the amplitude parameter and also to examine which components of the cross-correlation are largest, enabling inclusion of all identified dominant terms in the Gaussian source model. The acoustic source description in the present approach is therefore determined with no direct input from experimental data. The paper also examines the accuracy of various commonly made simplifications, for example: the inclusion of an evolving jet flow and scattering from the nozzle, the assumption of small variation in Green's function over the correlation length, the application of the far-field approximation in the Green's function, and the impact of isotropic assumptions made in previous acoustic source models. The final optimised model is applied to prediction of experimental data from the JEAN project, and gives excellent agreement across a wide spectral range and for both sideline and peak noise angles