Optimization of multiple-layer microperforated panels by simulated annealing

Ruiz, Heidi; Cobo, Pedro; Jacobsen, Finn

doi:10.1016/j.apacoust.2011.04.010

Cited by 93 publications

(57 citation statements)

References 20 publications

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“…In metallurgy, for instance, annealing alters the microstructure of a material producing changes in properties such as strength, hardness and ductility. When the metals are slowly cooled from a high temperature state, atoms rearrange themselves to reach minimum energy following the Boltzmann law [16]. Let ∆E be the energy change from one state to another at a temperature T. The Boltzmann law establishes that the probability that the system change from one state to another is…”

Section: Optimization By Samentioning

confidence: 99%

“…Some authors have used a microstructural model combined with genetic [12][13], non-lineal best fitting algorithms [13], or sequential linear programming [14], to estimate the five non-acoustical parameters of porous fibrous materials. Others, have used impedance models for graded cellular metals [15] or multilayered microperforated panels [16] combined with simulating annealing algorithms to maximise the mean absorption within a prescribed frequency band.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Inverse estimation of the non-acoustical parameters of loose granular absorbers by Simulated Annealing

Cobo

Moraes²,

Simón

2015

Building and Environment

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Section: Optimization By Samentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Inverse estimation of the non-acoustical parameters of loose granular absorbers by Simulated Annealing

Cobo

Moraes²,

Simón

2015

Building and Environment

Self Cite

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“…Genetic algorithm (GA), simulated annealing (SA), and Topology methods have been widely used as optimizing tools for sound absorption and transmission loss (Bolton, Shiau, & Kang, 1996;Chang, Yeh, Chiu, & Lai, 2005;Dühring, Jensen, & Sigmund, 2008;Krynkin & Tyutekin, 2002;Lee, Kim, Kim, Kim, & Kang, 2007;Meng, Wen, Zhao, & Wen, 2012;Ruiz, Cobo, & Jacobsen, 2011;Thamburaj & Sun, 2002;Tyutekin, 1998;Yoon, 2013;. The goal of maximizing the absorption property of single-layer sound absorbers using GA and SA methods was previously addressed by and .…”

Section: Introductionmentioning

confidence: 98%

Application of evolution strategy algorithm for optimization of a single-layer sound absorber

et al. 2014

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Depending on different design parameters and limitations, optimization of sound absorbers has always been a challenge in the field of acoustic engineering. Various methods of optimization have evolved in the past decades with innovative method of evolution strategy gaining more attention in the recent years. Based on their simplicity and straightforward mathematical representations, single-layer absorbers have been widely used in both engineering and industrial applications and an optimized design for these absorbers has become vital. In the present study, the method of evolution strategy algorithm is used for optimization of a single-layer absorber at both a particular frequency and an arbitrary frequency band. Results of the optimization have been compared against different methods of genetic algorithm and penalty functions which are proved to be favorable in both effectiveness and accuracy. Finally, a single-layer absorber is optimized in a desired range of frequencies that is the main goal of an industrial and engineering optimization process. Subjects: Acoustical Engineering, Mechanical Engineering, TechnologyKeywords: evolution strategy algorithm, single-layer sound absorber, one-fifth success rule, frequency band (range)

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“…Ng and Hui (2008) proposed a new honeycomb core design by increasing the stiffness and damping to improve TL in the low-frequency range. Finite element method and shape optimization method were combined to optimize the solid-void layout of a sandwich panel for higher TL (Onen and Caliskan 2010;Chang et al 2005;Ruiz et al 2011). Hudson et al (2010 applied an ant-colony optimization algorithm to the multiple-objective optimization of a railway vehicle's floor sandwich panel.…”

Section: Introductionmentioning

confidence: 99%

Optimum core design to improve noise attenuation performance and stiffness of sandwich panels used for high-speed railway vehicles

Yoon

Lee

2016

Struct Multidisc Optim

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In this study, we optimally design the core of a metal sandwich panel used in high-speed railway vehicles to minimize the amount of metal solid in the core and subsequently reduce its weight. The optimum core must satisfy constraints regarding sound transmission class (STC) and compliance. Because the solid-void layout in the core strongly affects the acoustic and static characteristics of sandwich panels, the core layout should be carefully designed when reducing the amount of metal solid. To this end, three topology-optimization problems and one size-optimization problem are formulated and sequentially solved. A single unit cell is periodically repeated in the core. Thus, structural and acoustic topology-optimization problems are first formulated and solved for the unit cell. Based on the optimal topologies obtained for the unit cell, a moderate initial solid-void layout in the unit cell is determined for the size-optimization problem to optimally design core. The effectiveness of the current design approach for the core of the sandwich panel is validated by comparing the STC and compliance values of the optimal core design and a reference design. Nomenclature A N n¼1 finite element assembly operator Bmatrix relating the element strain vector to its nodal displacement vector C m e a nc o m p l i a n c e C ini initial mean compliance c speed of sound in air D constitutive matrix d 1 thickness of thin flat plates at both ends in a sandwich panel d 2 thickness of the bar inside a sandwich panel dis (r,m) distance between the centers of the r th and m th elements E r (χ r ) Young's modulus of the r th element

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Optimization of multiple-layer microperforated panels by simulated annealing

Cited by 93 publications

References 20 publications

Inverse estimation of the non-acoustical parameters of loose granular absorbers by Simulated Annealing

Inverse estimation of the non-acoustical parameters of loose granular absorbers by Simulated Annealing

Application of evolution strategy algorithm for optimization of a single-layer sound absorber

Optimum core design to improve noise attenuation performance and stiffness of sandwich panels used for high-speed railway vehicles

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