Evolutionary topology optimization for acoustic-structure interaction problems using a mixed u/p formulation

Kook, Junghwan

doi:10.1080/15397734.2018.1557527

Cited by 16 publications

(5 citation statements)

References 32 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

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“…Reducing sound pressure and sound power radiation (SPR) in an acoustic medium is of great interest in environment and engineering applications. This can be achieved by optimal design of the source (Parmee 1996;Shang and Zhao 2016) or receiver using some sorts of isolations for the source or the receiver (Silva and Pavanello 2010;Yin et al 2018;Kook 2019).…”

Section: Introductionmentioning

confidence: 99%

Damping design of harmonically excited flexible structures with graded materials to minimize sound pressure and radiation

Alfouneh

Luo

2020

Engineering Optimization

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Topology optimization is an effective method in design of acoustic media. This article presents optimization for graded damping materials to minimize sound pressure at a reference point or sound power radiation under harmonic excitation. The Helmholtz integral equation is used to calculate an acoustic field to satisfy the Sommerfeld conditions. The equation of motion is solved using a unit dynamic load method. Formulations for the sound pressure or sound power radiation in an integral form are derived in terms of mutual kinetic and strain energy densities. These integrals lead to novel physical response functions for solving the proposed optimization to design graded damping materials. The response function derived for individual frequency is utilized to solve the multi-objective optimization problem of minimizing sound pressure at the reference point for excitations with a range of frequencies. Numerical examples are presented to verify efficiency of the present formulations.

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“…In addition, the interface was defined implicitly using a level-set function [14][15][16] or a binary density function in the case of the solid isotropic material penalization (SIMP) approach. 17,18 In some cases the interface was modeled explicitly by using the level-set function in conjunction with adaptive mesh refinement to accommodate the changing interface boundary. 19 A closely related approach 20 used bidirectional evolutionary structural optimization (BESO) on a finely refined mesh to impose explicit interface constraints.…”

Section: Introductionmentioning

confidence: 99%

“…In most of these problems, the fluid was also treated as a “solid” with negligible shear modulus. In addition, the interface was defined implicitly using a level‐set function 14‐16 or a binary density function in the case of the solid isotropic material penalization (SIMP) approach 17,18 …”

Section: Introductionmentioning

confidence: 99%

Material parameter optimization for interior and exterior fluid‐structure acoustic problems

Ramaswamy

Dey

Oberai

2020

Numerical Meth Engineering

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Summary We present an efficient adjoint‐based framework for computing sensitivities of quantities of interest with respect to material parameters for coupled fluid‐structural acoustic systems with explicit interface coupling. The fluid is modeled using the Helmholtz equation and the structure is modeled using the Navier‐Cauchy equations. Sensitivities are used to drive a gradient based optimization algorithm to solve important problems in structural acoustics, viz noise minimization and vibration isolation. For each problem, we consider two different priors: one where the optimal solution has a smooth variation and another with a bimaterial distribution. These priors are imposed with the help of suitable regularization terms. The effectiveness of this approach is demonstrated on both interior and exterior structural acoustic problems.

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Evolutionary topology optimization for acoustic-structure interaction problems using a mixed u/p formulation

Cited by 16 publications

References 32 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

Damping design of harmonically excited flexible structures with graded materials to minimize sound pressure and radiation

Material parameter optimization for interior and exterior fluid‐structure acoustic problems

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