Distribution Optimization for Acoustic Design of Porous Layer by the Boundary Element Method

Xu, Yanming; Zhao, Wenchang; Chen, Leilei; Chen, Haibo

doi:10.1007/s40857-020-00181-7

Cited by 5 publications

(3 citation statements)

References 46 publications

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“…At the time of writing this article, topology optimisation has been performed on a variety of acoustic applications, including horns, mu✏ers, rooms and sound barriers [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] . A majority of these applications use the gradient-based SIMP method or its variants, while a small fraction of them use BESO or level-set methods.…”

Section: Acoustic Topology Optimisationmentioning

confidence: 99%

Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials

Ramamoorthy

Özcan

Parkes

et al. 2021

The Journal of the Acoustical Society of America

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When designing sound packages, often fully filling the available space with acoustic materials is not the most absorbing solution. Better solutions can be obtained by creating cavities of air pockets, but determining the most optimal shape and topology that maximises sound absorption is a computationally challenging task. Many recent topology optimisation applications in acoustics use heuristic methods such as solid-isotropic-material-with-penalisation (SIMP) to quickly find near-optimal solutions. This study investigates seven heuristic and metaheuristic optimisation approaches including SIMP applied to topology optimisation of acoustic porous materials for absorption maximisation. The approaches tested are hill climbing, constructive heuristics, SIMP, genetic algorithm, tabu search, covariance-matrix-adaptation evolution strategy (CMA-ES), and di↵erential evolution. All the algorithms are tested on seven benchmark problems varying in material properties, target frequencies, and dimensions. The empirical results show that hill climbing, constructive heuristics, and a discrete variant of CMA-ES outperform the other algorithms in terms of the average quality of solutions over the di↵erent problem instances. Though gradient-based SIMP algorithms converge to local optima in some problem instances, they are computationally more e cient. One of the general lessons is that di↵erent strategies explore di↵erent regions of the search space producing unique sets of solutions.

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Section: Acoustic Topology Optimisationmentioning

confidence: 99%

Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials

Ramamoorthy

Özcan

Parkes

et al. 2021

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

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“…In order to verify the reliability of genetic algorithm optimization, the optimal noise reduction experiment of one chamber plug inlet muffler was carried out [34,35]. Xu et al used the boundary element method to optimize the distribution of porous material layer in the cavity to improve the absorption effect of porous material, reduce the noise level or increase the dissipated sound energy of porous material [36]. To sum up, the previously reported literature mainly focuses on the structural optimization design of cavity or multi-cavity materials, but does not study the structural optimization of the exhaust tailpipe of a tractor.…”

Section: Introductionmentioning

confidence: 99%

Structural Design and Parameter Optimization of Bionic Exhaust Tailpipe of Tractors

et al. 2022

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The exhaust tailpipe of a certain type of tractor was improved from the perspective of bionics, and bionic triangular convex texture was added to the inner surface of the exhaust tailpipe. The bionic tailpipe was proposed to improve noise reduction performance without changing the overall size parameters of the prototype tailpipe. Acoustics simulation software was used to predict the aeroacoustics noise and transmission loss of the exhaust tailpipe. Bionic exhaust tailpipes with triangular textures of different numbers of circumferential columns, height, and top angles were analyzed to study the noise reduction performance. The results showed that the proposed bionic exhaust tailpipes with triangular convex textures reduced the total sound pressure level and improved the transmission loss of the prototype exhaust tailpipe. To increase the transmission loss, a genetic algorithms (GA) optimized back-propagation neural network (BP) was used to optimize the bionic triangular convex texture parameters. By studying the aerodynamic noise reduction mechanism of bionic tailpipes, the research suggested that a secondary vortex appeared near the bionic texture and reduced aerodynamic drag and aeroacoustics noise. In addition, the sound pressure level amplitude nephogram, velocity vector nephogram, and velocity amplitude nephogram of the exhaust tailpipes were analyzed to study the vibration noise reduction mechanism of the bionic tailpipes. Then, the noise reduction performance was experimentally evaluated. The experimental results of the bionics exhaust tailpipes with triangular convex textures were analyzed and compared to that of the prototype tailpipe. The results demonstrated that the bionic exhaust tailpipes were able to attenuate noise.

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“…Lagarrigue et al [ 23 ] came with the idea of incorporating the rigid inclusions in a porous material to be tunable and for it to be possible to improve their sound absorption properties at the low-frequency scope. Cellular materials with several types of inclusions differing in shape was studied by Groby et al [ 24 ], while Xu et al [ 25 ] dealt with an optimum design for the propagation of acoustics in the exact material layer inside the cavity using the bounded element method.…”

Section: Introductionmentioning

confidence: 99%

Effect of the Pore Shape and Size of 3D-Printed Open-Porous ABS Materials on Sound Absorption Performance

et al. 2020

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Noise has a negative impact on our environment and human health. For this reason, it is necessary to eliminate excessive noise levels. This paper is focused on the study of the sound absorption properties of materials with open-porous structures, which were made of acrylonitrile butadiene styrene (ABS) material using additive technology. Four types of structures (Cartesian, Octagonal, Rhomboid, and Starlit) were evaluated in this work, and every structure was prepared in three different volume ratios of the porosity and three different thicknesses. The sound absorption properties of the investigated ABS specimens were examined utilizing the normal incidence sound absorption and noise reduction coefficients, which were experimentally determined by the transfer function method using a two-microphone acoustic impedance tube. This work deals with various factors that influence the sound absorption performance of four different types of investigated ABS material’s structures. It was found, in this study, that the sound absorption performance of the investigated ABS specimens is strongly affected by different factors, specifically by the structure geometry, material volume ratio, excitation frequency of an acoustic wave, material’s thickness, and air space size behind the tested sound-absorbing materials.

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Distribution Optimization for Acoustic Design of Porous Layer by the Boundary Element Method

Cited by 5 publications

References 46 publications

Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials

Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials

Structural Design and Parameter Optimization of Bionic Exhaust Tailpipe of Tractors

Effect of the Pore Shape and Size of 3D-Printed Open-Porous ABS Materials on Sound Absorption Performance

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