On the modelling of wavepacket scattering noise with coherence effects

Silva, Filipe D. da; Jordan, Peter; Cavalieri, André V. G.

doi:10.1121/1.5140190

Cited by 6 publications

(6 citation statements)

References 26 publications

(29 reference statements)

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“…When projecting the RESPOD modes onto the forcing modes, the radially thin supersonic wavepackets observed in figure 8 are integrated in the radial direction without any modulation by the optimal forcing mode. This implies that the forcing modes of figure 8 can be replaced by a line source obtained by radial integration, justifying the use of line-source models in the literature (Michalke 1970;Michel 2009;Lesshafft, Huerre & Sagaut 2010;Cavalieri et al 2011;Cavalieri & Agarwal 2014;Maia et al 2019;da Silva et al 2019). The resulting line sources at different frequencies are shown in figure 11 for the case M04Mc00.…”

Section: Empirical Modelling Of the Acoustically Efficient Forcing Co...mentioning

confidence: 75%

“…2019; da Silva et al. 2019). The resulting line sources at different frequencies are shown in figure 11 for the case M04Mc00.…”

Section: Empirical Modelling Of the Acoustically Efficient Forcing Co...mentioning

confidence: 99%

“…2019; da Silva et al. 2019) have shown that the noise generated by a wavepacket in a subsonic jet is highly sensitive to the coherence decay rate embedded in the source model. Indeed, a source model based on a wavepacket with unit coherence, although matching the near-field wavepacket obtained experimentally, generates an acoustic field that is off by up to 40 dB when compared with the experimental data (Baqui et al.…”

Section: Empirical Modelling Of the Acoustically Efficient Forcing Co...mentioning

confidence: 99%

“…This way, they leveraged the linear mechanisms embedded in the resolvent operator associated with noise generation and modelled only the remaining nonlinearities coming from the forcing. Other studies have used a wavepacket source model for the near-field velocity correlations paired with Lighthill's analogy to predict jet noise (Huerre & Crighton 1983;Cavalieri et al 2011Cavalieri et al , 2012Cavalieri & Agarwal 2014;Maia et al 2019;da Silva, Jordan & Cavalieri 2019).…”

Section: Introductionmentioning

confidence: 99%

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An empirical model of noise sources in subsonic jets

Karban

Bugeat²,

Towne

et al. 2023

J. Fluid Mech.

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Modelling the noise emitted by turbulent jets is made difficult by their acoustic inefficiency: only a tiny fraction of the near-field turbulent kinetic energy is propagated to the far field as acoustic waves. As a result, jet-noise models must accurately capture this small, acoustically efficient component hidden among comparatively inefficient fluctuations. In this paper, we identify this acoustically efficient near-field source from large-eddy simulation data and use it to inform a predictive model. Our approach uses the resolvent framework, in which the source takes the form of nonlinear fluctuation terms that act as a forcing on the linearised Navier–Stokes equations. First, we identify the forcing that, when acted on by the resolvent operator, produces the leading spectral proper orthogonal decomposition modes in the acoustic field for a Mach 0.4 jet. Second, the radiating components of this forcing are isolated by retaining only portions with a supersonic phase speed. This component makes up less than 0.05 % of the total forcing energy but generates most of the acoustic response, especially at peak (downstream) radiation angles. Finally, we propose an empirical model for the identified acoustically efficient forcing components. The model is tested at other Mach numbers and flight-stream conditions and predicts noise within 2 dB accuracy for a range of frequencies, downstream angles and flight conditions.

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Section: Empirical Modelling Of the Acoustically Efficient Forcing Co...mentioning

confidence: 75%

“…2019; da Silva et al. 2019). The resulting line sources at different frequencies are shown in figure 11 for the case M04Mc00.…”

Section: Empirical Modelling Of the Acoustically Efficient Forcing Co...mentioning

confidence: 99%

Section: Empirical Modelling Of the Acoustically Efficient Forcing Co...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An empirical model of noise sources in subsonic jets

Karban

Bugeat²,

Towne

et al. 2023

J. Fluid Mech.

View full text Add to dashboard Cite

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“…Ffowcs Williams and Hall (1970) introduced a tailored Green's function (TGF), which can account for the scattered acoustic field due to a source near a semi-infinite plate using Curle's analogy (Curle, 1955). There exist many studies Nogueira et al, 2016;Piantanida et al, 2016;da Silva et al, 2019) showing that the TGF for semiinfinite plates can be used for accurate prediction of the acoustic field in an installed jet configuration.…”

Section: Introductionmentioning

confidence: 99%

Modeling closed-loop control of installation noise using Ginzburg-Landau equation

Karban¹,

Martini²,

Jordan³

2023

Preprint

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Installation noise is a dominant source associated with aircraft jet engines. Recent studies show that linear wavepacket models can be employed for prediction of installation noise, which suggests that linear control strategies can also be adopted for mitigation of it. We present here a simple model to test different control approaches and highlight the potential restrictions on a successful noise control in an actual jet. The model contains all the essential elements for a realistic representation of the actual control problem: a stochastic wavepacket is obtained via a linear Ginzburg-Landau model; the effect of the wing trailing edge is accounted for by introducing a semi-infinite half plane near the wavepacket; and the actuation is achieved by placing a dipolar point source at the trailing edge, which models a piezoelectric actuator. An optimal causal resolvent-based control method is compared against the classical wave-cancellation method. The effect of the causality constraint on the control performance is tested by placing the sensor at different positions. We demonstrate that when the sensor is not positioned sufficiently upstream of the trailing edge, which can be the case for the actual control problem due to geometric restrictions, causality reduces the control performance. We also show that this limitation can be moderated using the optimal causal control together with modelling of the forcing.

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