Broad Band Shock Associated Noise Modelling for High-Area-Ratio Under-Expanded Jets

Broadband Shock Associated Noise (BBSAN) is an important component of supersonic jet noise for jets at off-design conditions when the pressure at the nozzle exit is different from the ambient. Two high area ratio under-expanded supersonic jets at Nozzle Pressure Ratios (NPRs) 3.4 and 4.2 are considered. The jets correspond to conditions of the experiment in the Laboratory for Turbulence Research in Aerospace and Combustion (LTRAC) in the Supersonic Jet Facility of Monash University. Flow solutions are obtained by the Large Eddy Simulation (LES) and Reynolds Averaged Navier-Stokes (RANS) methods. The solutions are validated against the Particle Image Velocimetry (PIV) data. For noise spectra predictions, the LES solution is combined with the time-domain Ffowcs Wiliams -Hawkings method. To probe accuracy of the reduced-order method based on acoustic analogy, the RANS solutions are substituted in the Morris and Miller BBSAN method, where different options for modelling of the acoustic correlation scales are investigated. The noise spectra predictions are compared with the experimental data from the non-anechoic LTRAC facility and the NASA empirical sJet model. Apart from the low-frequencies influenced by the jet mixing noise, the RANS-based acoustic predictions align with those from LES for most frequencies in the range of Strouhal numbers (St) 0.4<St<2 within 1-2 dB

A comparison of the value of viscosity for several water models using Poiseuille flow in a nano-channel

The viscosity-temperature relation is determined for the water models SPC/E, TIP4P, TIP4P/Ew, and TIP4P/2005 by considering Poiseuille flow inside a nano-channel using molecular dynamics. The viscosity is determined by fitting the resulting velocity profile (away from the walls) to the continuum solution for a Newtonian fluid and then compared to experimental values. The results show that the TIP4P/2005 model gives the best prediction of the viscosity for the complete range of temperatures for liquid water, and thus it is the preferred water model of these considered here for simulations where the magnitude of viscosity is crucial. On the other hand, with the TIP4P model, the viscosity is severely underpredicted, and overall the model performed worst, whereas the SPC/E and TIP4P/Ew models perform moderately

Effect of large-scale mixing on the axisymmetric structure of turbulence correlations in complex dual stream jets

Dual-stream flows are a ubiquitous feature of turbofan engines used in civil aviation. In this paper we analyze the spatial structure of turbulence correlations in a high speed round coaxial jet operating at heated conditions. In particular we consider the effect of axisymmetry of a second rank correlation tensor and the usual fourth order Reynolds stress auto-covariance tensor that enters the Goldstein’s generalized acoustic analogy formulation. The invariants of these tensors can be reduced to a simpler form depending on whether isotropy or axisymmetry was assumed. We show that an axisymmetric turbulence approximation remains accurate in the core region but tends to break down in the bypass stream and especially in the interfacial region between both streams where high level of mixing of turbulence takes place. In the paper we present some of our latest results and provide a road map for the future calculations that we have planned

Analysis of the non-parallel flow-based Green's function in the acoustic analogy for complex axisymmetric jets

This paper considers how a complex axisymmetric jet modifies the structure of the propa- gator tensor in Goldstein’s generalized acoustic analogy. The jet flow we consider is in general a dual stream flow that operates either as a single jet or a complex co-axial jet flow. The latter of which is of interest to turbofan engine manufacturers. The form of the acoustic analogy that we use here is based on our recent work on jet noise modeling (Afsar et al. 2019, PhilTrans. A., vol. 377) that highlighted the importance of non-parallel flow effects in the correct calcu- lation of the propagator. The propagator calculation takes advantage of the fact that mean flow non-parallelism enters the lowest order asymptotic expansion of the former at sufficiently low frequencies of the same order as the jet spread rate. Whilst this might seem restrictive, our previously reported calculations at high subsonic and mildly supersonic jets indicate that the subsequent jet noise predictions remain accurate up to the peak frequency (typically at a Strouhal number based on jet velocity and diameter of ≈ 0.5 − 0.6) for the small angle acoustic radiation. One of critical assumptions of this approach is that the mean flow speed of sound squared is given by either the Crocco relation (in unheated jets) or the Crocco-Busemann relation for heated flows. Our analysis for the dual stream complex axisymmetric jet however shows that the latter assumption (in the form of Crocco-Busemann formula) is no longer an accurate representation of the speed of sound variation. We therefore present a more general form of the asymptotic analysis than that used in Afsar et al. (2019a & b). For the complex jet mean flow field, the mean flow speed of sound is otherwise arbitrary but must remain a single-valued function of the streamwise mean flow. The predictions based on this approach are shown to remain accurate up to the peak frequency. We discuss how to extend the range of validity by utilizing a suitable composite asymptotic solution for the Green’s function problem

Statistical analysis of high-speed jet flows

The spatiotemporal dynamics of pressure fluctuations of a turbulent jet flow is examined from the viewpoints of symbolic permutations theory and Kolmogorov-Smirnov statistics. The methods are applied to unveil hidden structures in the near-field of the two jets corresponding to the NASA SHJAR SP3 and SP7 experiments. Large Eddy Simulations (LES) are performed using the high-resolution Compact Accurately Boundary-Adjusting high-REsolution Technique (CABARET) accelerated on Graphics Processing Units (GPUs). It is demonstrated that the decomposition of the LES pressure solutions into symbolic patterns of simpler temporal structure reveals the existence of some orderly structures in the jet flows. To separate the non-linear dynamics of the revealed structures from the linear part, the results based on the pressure signals obtained from LES are compared with the surrogate dataset constructed from the original data

Application of Genetic Programming and Artificial Neural Network Approaches for Reconstruction of Turbulent Jet Flow Fields

Two Machine Learning (ML) methods are considered for reconstruction of turbulet signals corresponding to the Large Eddy Simulation database obtained by application of the high-resolution CABARET method accelerated on GPU cards for flow solutions of NASA Small Hot Jet Acoustic Rig (SHJAR) jets. The first method is the Feedforward Neural Networks technique, which was successfully implemented for a turbulent flow over a plunging aerofoil in (Lui and Wolf, 2019). The second method is based on the application of Genetic Programming, which is well-known in optimisation research, but has not been applied for turbulent flow reconstruction before. The reconstruction of local flow velocity and pressure signals as well as timedependent principle coefficients of the Spectral Proper Orthogonal Decomposition of turbulent pressure fluctuations are considered. Stability and dependency of the ML algorithms on the smoothness property and the sampling rate of the underlying turbulent flow signals are discussed

Effect of tensor representations for high-order turbulence correlations in complex axi-symmetric flow fields

Dual-stream flows are common feature of turbofan engines in civil aviation. For jet flows with a significant (i.e. proportional of total mass flow) bypass stream, transport of momentum through mixing between streams may cause an apparent departure of axi-symmetric turbu- lence conditions. One of the pertinent features of such departure is the difference in amplitude of transverse diagonal components of velocity and Reynolds stress based correlation function– that is correlation tensors of rank 2 and 4 respectively. Since these functions play a direct role in, among other things, the sound generation process, their accurate representation into an irreducible tensor form is vital in Engineering analysis. This paper builds on our previ- ous work (AIAA 2020-2573, [1]) in which we assessed the kinematic structure of generalized auto-covariance tensor using turbulence data obtained by highly resolved Large-Eddy Simu- lations of complex dual stream jets. Now, however, we extend this work further by showing how a generalized form of the axisymmetric representation theory of the appropriate tensor correlation functions can be determined by exploiting the experimental observation that such correlation metrics are localized in small azimuthal separations for axisymmetric jets. The paper summarizes the new theory and shows initial comparisons of an appropriate tensor form using LES data reported in our previous work

Multiscale molecular dynamics/hydrodynamics implementation of two dimensional “Mercedes Benz” water model

A multiscale Molecular Dynamics/Hydrodynamics implementation of the 2D Mercedes Benz (MB or BN2D) [1] water model is developed and investigated. The concept and the governing equations of multiscale coupling together with the results of the two-way coupling implementation are reported. The sensitivity of the multiscale model for obtaining macroscopic and microscopic parameters of the system, such as macroscopic density and velocity fluctuations, radial distribution and velocity autocorrelation functions of MB particles, is evaluated. Critical issues for extending the current model to large systems are discussed