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Technical Brief

Surrogate Model Based Liner Optimization for Aeroengines and Comparison With Finite Elements

[+] Author and Article Information
Hanbo Jiang

Department of Mechanical and Aerospace Engineering,
The Hong Kong University of Science and
Technology Clear Water Bay,
Kowloon 999077, Hong Kong, China
e-mail: hb.jiang@connect.ust.hk

Alex Siu Hong Lau

Department of Mechanical and Aerospace Engineering,
The Hong Kong University of Science and
Technology Clear Water Bay,
Kowloon 999077, Hong Kong, China
e-mail: alexshlau@ust.hk

Xun Huang

State Key Laboratory of Turbulence and Complex System,
Department of Aeronautics and Astronautics,
College of Engineering Peking University,
Beijing 100871, China;
Department of Mechanical and Aerospace Engineering,
The Hong Kong University of Science and
Technology Clear Water Bay,
Kowloon 999077, Hong Kong, China
e-mails: huangxun@pku.edu.cn; huangxun@ust.hk

1Corresponding author.

Contributed by the Noise Control and Acoustics Division of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received June 9, 2017; final manuscript received September 25, 2017; published online January 25, 2018. Assoc. Editor: Sheryl M. Grace.

J. Vib. Acoust 140(3), 034501 (Jan 25, 2018) (8 pages) Paper No: VIB-17-1249; doi: 10.1115/1.4038680 History: Received June 09, 2017; Revised September 25, 2017

Numerical optimizations are very useful in liner designs for low-noise aeroengines. Although modern computational tools are already very efficient for a single aeroengine noise propagation simulation run, the prohibitively high computational cost of a broadband liner optimization process which requires hundreds of thousands of runs renders these tools unsuitable for such task. To enable rapid optimization using a desktop computer, an efficient analytical solver based on the Wiener–Hopf method is proposed in the current study. Although a Wiener–Hopf-based solver can produce predictions very quickly (order of a second), it usually assumes an idealized straight duct configuration with a uniform background flow that makes it arguable for practical applications. In the current study, we employ the Wiener–Hopf method in our solver to produce an optimized liner design for a semi-infinite annular duct setup and compare its noise-reduction effect with an optimized liner designed by the direct application of a numerical finite element solver for a practical aeroengine intake configuration with an inhomogeneous background flow. The near-identical near- and far-field solutions by the Wiener–Hopf-based method and the finite element solvers clearly demonstrate the accuracy and high efficiency of the proposed optimization strategy. Therefore, the current Wiener–Hopf solver is highly effective for liner optimizations with practical setups and is very useful to the preliminary design process of low-noise aeroengines.

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Figures

Grahic Jump Location
Fig. 1

The model setup and the cylindrical coordinate. Here we consider a straight annular duct with semi-infinitely long hard wall (left) and semi-infinitely long lined wall (right).

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Fig. 2

The case setup used for the numerical simulations. Here, the liner covers the inside wall of the inlet duct with a normalized unit length.

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Fig. 3

Flowchart for the surrogate-based liner optimization

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Fig. 4

The dimensional axial velocity field (m/s) for the practical aeroengine intake case

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Fig. 5

Normalized cost function values with respect to liner impedance values. Other parameters are the same as Table 1: (a) numerical, 1 kHz, (b) numerical, 1.5 kHz, (c) numerical, 2 kHz, (d) numerical, 2.5 kHz, (e) Wiener–Hopf, 1 kHz, (f) Wiener–Hopf, 1.5 kHz, (g) Wiener–Hopf, 2 kHz, and (h) Wiener–Hopf, 2.5 kHz.

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Fig. 6

The near-field sound pressure solutions (11 contour levels between 65 dB and 90 dB) at f = 1 kHz, (m, n) = (4, 1) and the amplitude of the incident wave is set to 1: (a) hard wall, (b) optimized liner design with Z = 1.1283–1.4071i based on the numerical solver, and (c) optimized liner design with Z = 1.2140–1.6681i based on the analytical Wiener–Hopf solver

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Fig. 7

The far-field directivity patterns for four frequencies between 1.0 kHz and 2.5 kHz with (m, n) = (4, 1). The impedance values can be found in Table 1. The dotted lines represent the results without acoustic liner. The dashed-dot (with ○) and solid lines show the directivity patterns with the optimized liner designs from the numerical solver and the Wiener–Hopf-based solver, respectively: (a) f = 1 kHz, (b) f = 1.5 kHz, (c) f = 2 kHz, and (d) f = 2.5 kHz.

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