Shape optimization of mufflers hybridized with multiple connected tubes using the boundary element method, neural networks, and genetic algorithm

2010 ◽  
Vol 224 (4) ◽  
pp. 901-913 ◽  
Author(s):  
Y-C Chang ◽  
M-C Chiu ◽  
L-W Wu
Keyword(s):  
Genetic Algorithm ◽  
Noise Reduction ◽  
Boundary Element ◽  
Matrix Method ◽  
Transmission Loss ◽  
Real Data ◽  
Element Model ◽  
Design Data ◽  
Phase Cancellation ◽  
Input Design

Recently, research on new mufflers hybridized with connected curved tubes using phase cancellation techniques has been well addressed in the industrial field. Most researchers have explored noise reduction effects based on the transfer matrix method and the stiffness matrix method. However, the maximum noise reduction of a silencer within a constrained space, which frequently occurs in engineering problems, has been neglected. Therefore, the optimum design of mufflers becomes an essential issue. In this article, two kinds of phase-cancellation mufflers (a two-connected tube and a three-connected tube) within a fixed length are assessed. In order to speed up the assessment of optimal mufflers hybridized with multiple connected curved tubes, a simplified objective function (OBJ) is established by linking the boundary element model (BEM; developed by the commercialized software SYSNOISE) with a polynomial neural network fitted with a series of real data: input design data (muffler dimensions) and output data approximated by BEM data in advance. To assess the optimal mufflers, a genetic algorithm is applied. Optimal results reveal that the maximum value of the sound transmission loss can be improved at the desired frequencies. Consequently, the optimum algorithm proposed in this study can provide an efficient way to develop optimal silencers for industry.

Numerical Assessment of Multi-Splitter Mufflers Using Neural Networks, the Boundary Element Method, and the Genetic Algorithm

2011 ◽  
Vol 58-60 ◽  
pp. 1049-1055 ◽  
Author(s):  
Min Chie Chiu
Keyword(s):  
Genetic Algorithm ◽  
Noise Reduction ◽  
Boundary Element ◽  
Matrix Method ◽  
Transmission Loss ◽  
Real Data ◽  
Element Model ◽  
Design Data ◽  
Input Design ◽  
The Cost

Recently, research on new mufflers lined with sound-absorbing material has been addressed in the industrial field. On the basis of the transfer matrix method and the stiffness matrix method, most researchers have explored noise reduction effects. Yet, the maximum noise reduction of a compact silencer equipped with sound-absorbing splitters within a constrained space, which often occurs in modern industries, has been ignored. Therefore, the optimum design of mufflers becomes essential. In this paper, a one-chamber muffler equipped with multiple sound-absorbing panels within a fixed length is assessed. In order to facilitate the assessment of optimal mufflers having multiple sound-absorbing splitters, an approximated simplified objective function (OBJ) is established in advance by linking the boundary element model (BEM) with a polynomial neural network fitted with a series of real data, input design data (muffler dimensions) and output data obtained by BEM simulation. To assess the optimal mufflers, a genetic algorithm (GA) is applied. Before the GA operation can be carried out, the accuracy of the mathematical models must be checked using the experimental data. On the basis of the fixed total thickness of the splitters, the open area of the flowing channel can be assured. Therefore, not only the influence of the backpressure can be minimized, but also the cost of the sound absorbing splitters can be economically saved. Optimal results reveal that the maximum value of the sound transmission loss (STL) can be improved at the targeted frequencies. Consequently, the optimum algorithm proposed in this study provides an efficient way to find a better silencer for industry.

Shape Optimisation of Multi-Chamber Acoustical Plenums Using BEM, Neural Networks, and GA Method

2016 ◽  
Vol 41 (1) ◽  
pp. 43-53 ◽  
Author(s):  
Ying-Chun Chang ◽  
Ho-Chih Cheng ◽  
Min-Chie Chiu ◽  
Yuan-Hung Chien
Keyword(s):  
Noise Reduction ◽  
Boundary Element ◽  
Transmission Loss ◽  
Real Data ◽  
Element Model ◽  
Shape Optimisation ◽  
Design Data ◽  
Input Design ◽  
Speed Up ◽  
Fixed Space

Abstract Research on plenums partitioned with multiple baffles in the industrial field has been exhaustive. Most researchers have explored noise reduction effects based on the transfer matrix method and the boundary element method. However, maximum noise reduction of a plenum within a constrained space, which frequently occurs in engineering problems, has been neglected. Therefore, the optimum design of multi-chamber plenums becomes essential. In this paper, two kinds of multi-chamber plenums (Case I: a two-chamber plenum that is partitioned with a centre-opening baffle; Case II: a three-chamber plenum that is partitioned with two centre-opening baffles) within a fixed space are assessed. In order to speed up the assessment of optimal plenums hybridized with multiple partitioned baffles, a simplified objective function (OBJ) is established by linking the boundary element model (BEM, developed using SYSNOISE) with a polynomial neural network fit with a series of real data – input design data (baffle dimensions) and output data approximated by BEM data in advance. To assess optimal plenums, a genetic algorithm (GA) is applied. The results reveal that the maximum value of the transmission loss (TL) can be improved at the desired frequencies. Consequently, the algorithm proposed in this study can provide an efficient way to develop optimal multi-chamber plenums for industry.

Optimum design of perforated plug mufflers using a neural network and a genetic algorithm

2008 ◽  
Vol 223 (4) ◽  
pp. 935-952 ◽  
Author(s):  
Y-C Chang ◽  
M-C Chiu ◽  
M-M Cheng
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Mathematical Model ◽  
Noise Reduction ◽  
Optimum Design ◽  
Transmission Loss ◽  
Real Data ◽  
Wave Theory ◽  
Optimum Process ◽  
Design Data

Research on new techniques of perforated plug silencers has been well addressed. Most researchers have explored noise reduction effects based on a pure plane wave theory. However, the maximum noise reduction of a silencer under a space constraint, which frequently occurs in engineering problems, is rarely addressed. Therefore, the optimum design of mufflers becomes an essential issue. In this paper, to save the design time during the flexible optimum process, a simplified mathematical model of a muffler is constructed with a neural network with a series of real data — input design data (muffle dimensions) and output data (theoretical sound transmission loss (STL)) were approximated by a theoretical mathematical model (TMM) in advance. To assess the optimal mufflers, the neural network model (NNM) is used as an objective function in conjunction with a genetic algorithm (GA). Moreover, the numerical cases of sound elimination with respect to various parameter sets and pure tones (500, 1000, and 2000 Hz) are exemplified and discussed. Before the GA operation is carried out, the approximation between TMM and real data is checked. In addition, both the TMM and NNM are compared. It is found that the TMM and the experimental data are in agreement. Moreover, the TMM and NNM conform. Optimal results reveal that the maximum amount of the STL can be optimally obtained at the desired frequencies. Consequently, the optimum algorithm proposed in this study can provide an efficient method to develop optimal silencers in industry.

Optimization of Rectangular Multi-Chamber Plenums Equipped with Multiple Extended Tubes Using the BEM, Neural Networks, and the Genetic Algorithm

2014 ◽  
Vol 30 (6) ◽  
pp. 571-584 ◽  
Author(s):  
Y.-C. Chang ◽  
M.-C. Chiu
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Transmission Loss ◽  
Focal Point ◽  
Analytical Data ◽  
Element Model ◽  
The Neural Network ◽  
Numerical Assessment ◽  
Pure Tones ◽  
Rectangular Tubes

AbstractThe focal point of this paper is to uncover, by analyzing the higher order wave effect, an improved mechanism for space-constrained rectangular plenums using a simplified objective function in conjunction with a genetic (GA). Three kinds of rectangular mufflers hybridized with extended tubes will be assessed: Plenum A: A two-chamber plenum equipped with an extended tube; plenum B: A three-chamber plenum with two extended tubes; and plenum C: A two-chamber plenum equipped with three extended tubes. In order to shorten the numerical assessment, a simplified objective function (OBJ) is established using a boundary element model (BEM) in conjunction with the neural network model (NNM). To expediently approach an optimal plenum, the best OBJ will be numerically searched using a genetic algorithm (GA). However, before the GA operation is performed, the accuracy of the BEM is verified using analytical data. And, because the simplified objective function (OBJ) is seen to be in agreement with the BEM, the numerical cases of sound elimination relative to the various parameter sets and pure tones (300, 750, and 1300Hz) can be carried out.Results reveal that the maximum value of the sound transmission loss (STL) can be accurately obtained at the desired frequencies. Additionally, the acoustical performance of the lower frequencies will be improved if the number of chambers and rectangular tubes are increased. However, the acoustical performance of the higher frequencies will decrease when the number of chambers and rectangular tubes are decreased. Consequently, the algorithms proposed in this study will efficiently develop optimal rectangular plenums with multiple rectangular extended tubes.

scholarly journals Investigation of Low-Sidelobe Beampattern Controlling Methods for Acoustic Transmitting Array of Underwater Vehicles

2017 ◽  
Vol 24 (s2) ◽  
pp. 103-110
Author(s):  
Zhengyao He ◽  
Qiang Shi ◽  
Shaoxuan Wu
Keyword(s):  
Boundary Element ◽  
Element Model ◽  
Optimization Method ◽  
Underwater Vehicles ◽  
Unmanned Vehicles ◽  
Driving Voltage ◽  
Sound Waves ◽  
Low Sidelobe ◽  
Acoustic Transducer ◽  
Weighting Vector

Abstract In underwater unmanned vehicles, complex acoustic transducer arrays are always used to transmitting sound waves to detect and position underwater targets. Two methods of obtaining low-sidelobe transmitting beampatterns for acoustic transmitting arrays of underwater vehicles are investigated. The first method is the boundary element model optimization method which used the boundary element theory together with the optimization method to calculate the driving voltage weighting vector of the array. The second method is the measured receiving array manifold vector optimization method which used the measured receiving array manifold vectors and optimization method to calculate the weighting vector. Both methods can take into account the baffle effect and mutual interactions among elements of complex acoustic arrays. Computer simulation together with experiments are carried out for typical complex arrays. The results agree well and show that the two methods are both able to obtain a lower sidelobe transmitting beampattern than the conventional beamforming method, and the source level for each transmitting beam is maximized in constraint of the maximum driving voltage of array elements being constant. The effect of the second method performs even better than that of the first method, which is more suitable for practical application. The methods are very useful for the improvement of detecting and positioning capability of underwater unmanned vehicles.

Numerical Prediction of Noise Radiated From a Panel Subjected to Boundary Layer Excitation

1999 ◽  
Author(s):  
Michael Allen ◽  
Nickolas Vlahopoulos
Keyword(s):  
Boundary Layer ◽  
Finite Element ◽  
Boundary Element ◽  
Transfer Functions ◽  
Element Model ◽  
Acoustic Response ◽  
Spectral Densities ◽  
Wind Noise ◽  
Element Analysis ◽  
Power Spectral

Abstract In this paper an algorithm is developed for combining finite element analysis and boundary element techniques in order to compute the noise radiated from a panel subjected to boundary layer excitation. The excitation is presented in terms of the auto and cross power spectral densities of the fluctuating wall pressure. The structural finite element model for the panel is divided into a number of sub-panels. A uniform fluctuating pressure is applied as excitation on each sub-panel separately. The corresponding vibration is computed, and is utilized as excitation for an acoustic boundary element analysis. The acoustic response is computed at any data recovery point of interest. The relationships between the acoustic response and the pressure excitation applied at each particular sub-panel constitute a set of transfer functions. They are combined with the spectral densities of the excitation for computing the noise generated from the vibration of the panel subjected to the boundary layer excitation. The development presented in this paper has the potential of computing wind noise in automotive applications, or boundary layer noise in aircraft applications.

Commercial aircraft cabin noise reduction based on SEA and transfer-matrix method

2018 ◽  
Vol 66 (4) ◽  
pp. 362-374 ◽  
Author(s):  
Ying Hu ◽  
Chenxi Li ◽  
Feng Han ◽  
Zixin Feng ◽  
Liyan He
Keyword(s):  
Noise Reduction ◽  
Transfer Matrix ◽  
Transfer Matrix Method ◽  
Matrix Method ◽  
Commercial Aircraft ◽  
Aircraft Cabin ◽  
Cabin Noise
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