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Wyszukujesz frazę "Chang, Y. C." wg kryterium: Autor


Wyświetlanie 1-5 z 5
Tytuł:
Acoustical Assessment of Automotive Mufflers Using FEM, Neural Networks, and a Genetic Algorithm
Autorzy:
Chang, Y.-C.
Chiu, M.-C.
Wu, M.-R.
Powiązania:
https://bibliotekanauki.pl/articles/177901.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
acoustics
finite element method
genetic algorithm
muffler optimization
polynomial neural network model
Opis:
In order to enhance the acoustical performance of a traditional straight-path automobile muffler, a multi-chamber muffler having reverse paths is presented. Here, the muffler is composed of two internally parallel/extended tubes and one internally extended outlet. In addition, to prevent noise transmission from the muffler’s casing, the muffler’s shell is also lined with sound absorbing material. Because the geometry of an automotive muffler is complicated, using an analytic method to predict a muffler’s acoustical performance is difficult; therefore, COMSOL, a finite element analysis software, is adopted to estimate the automotive muffler’s sound transmission loss. However, optimizing the shape of a complicated muffler using an optimizer linked to the Finite Element Method (FEM) is time-consuming. Therefore, in order to facilitate the muffler’s optimization, a simplified mathematical model used as an objective function (or fitness function) during the optimization process is presented. Here, the objective function can be established by using Artificial Neural Networks (ANNs) in conjunction with the muffler’s design parameters and related TLs (simulated by FEM). With this, the muffler’s optimization can proceed by linking the objective function to an optimizer, a Genetic Algorithm (GA). Consequently, the discharged muffler which is optimally shaped will improve the automotive exhaust noise.
Źródło:
Archives of Acoustics; 2018, 43, 3; 517-529
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Noise Elimination of Reciprocating Compressors Using FEM, Neural Networks Method, and the GA Method
Autorzy:
Chang, Y.-C.
Chiu, M.-C.
Xie, J.-L.
Powiązania:
https://bibliotekanauki.pl/articles/178126.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
finite element method
polynomial neural network model
genetic algorithm
group method of data handling
reciprocating compressor
optimization
Opis:
Industry often utilizes acoustical hoods to block noise emitted from reciprocating compressors. However, the hoods are large and bulky. Therefore, to diminish the size of the compressor, a compact discharge muffler linked to the compressor outlet is considered. Because the geometry of a reciprocating compressor is irregular, COMSOL, a finite element analysis software, is adopted. In order to explore the acoustical performance, a mathematical model is established using a finite element method via the COMSOL commercialized package. Additionally, to facilitate the shape optimization of the muffler, a polynomial neural network model is adopted to serve as an objective function; also, a Genetic Algorithm (GA) is linked to the OBJ function. During the optimization, various noise abatement strategies such as a reverse expansion chamber at the outlet of the discharge muffler and an inner extended tube inside the discharge muffler, will be assessed by using the artificial neural network in conjunction with the GA optimizer. Consequently, the discharge muffler that is optimally shaped will decrease the noise of the reciprocating compressor.
Źródło:
Archives of Acoustics; 2017, 42, 2; 189-197
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Numerical Assessment of a One-Mass Spring-Based Electromagnetic Energy Harvester on a Vibrating Object
Autorzy:
Chiu, M.-C.
Chang, Y.-C.
Yeh, L.-J.
Chung, C.-H.
Powiązania:
https://bibliotekanauki.pl/articles/177720.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
spring
harvester
generator
permanent magnet
simulated annealing
optimization
buckling
Fatigue
Opis:
The paper is an exploration of the optimal design parameters of a space-constrained electromagnetic vibration-based generator. An electromagnetic energy harvester is composed of a coiled polyoxymethylen circular shell, a cylindrical NdFeB magnet, and a pair of helical springs. The magnet is vertically confined between the helical springs that serve as a vibrator. The electrical power connected to the coil is actuated when the energy harvester is vibrated by an external force causing the vibrator to periodically move through the coil. The primary factors of the electrical power generated from the energy harvester include a magnet, a spring, a coil, an excited frequency, an excited amplitude, and a design space. In order to obtain maximal electrical power during the excitation period, it is necessary to set the system’s natural frequency equal to the external forcing frequency. There are ten design factors of the energy harvester including the magnet diameter (Dm), the magnet height (Hm), the system damping ratio (ζsys), the spring diameter (Ds), the diameter of the spring wire (ds), the spring length (ℓs), the pitch of the spring (ps), the spring’s number of revolutions (Ns), the coil diameter (Dc), the diameter of the coil wire (dc), and the coil’s number of revolutions (Nc). Because of the mutual effects of the above factors, searching for the appropriate design parameters within a constrained space is complicated. Concerning their geometric allocation, the above ten design parameters are reduced to four (Dm, Hm, ζsys, and Nc). In order to search for optimal electrical power, the objective function of the electrical power is maximized by adjusting the four design parameters (Dm, Hm, ζsys, and Nc) via the simulated annealing method. Consequently, the optimal design parameters of Dm, Hm, ζsys, and Nc that produce maximum electrical power for an electromagnetic energy harvester are found.
Źródło:
Archives of Acoustics; 2016, 41, 1; 119-131
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Shape Optimisation of Multi-Chamber Acoustical Plenums Using BEM, Neural Networks, and GA Method
Autorzy:
Chang, Y.-C.
Cheng, H.-C.
Chiu, M.-C.
Chien, Y.-H.
Powiązania:
https://bibliotekanauki.pl/articles/177780.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
boundary element method
plenum
centre-opening baffle
polynomial neural network model
group method of data handling
optimisation
genetic algorithm
Opis:
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.
Źródło:
Archives of Acoustics; 2016, 41, 1; 43-53
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Shape Optimization of Mufflers Composed of Multiple Rectangular Fin-Shaped Chambers Using Differential Evolution Method
Autorzy:
Chiu, M.-C.
Chang, Y.-C.
Cheng, H.-C.
Tai, W.-T.
Powiązania:
https://bibliotekanauki.pl/articles/177237.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
fin
multi-chamber
high-order-mode
differential evolution
Opis:
There has been considerable research done on multi-chamber mufflers used in the elimination of industrial venting noise. However, most research has been restricted to lower frequencies using the plane wave theory. This has led to underestimating acoustical performances at higher frequencies. Additionally, because of the space-constrained problem in most plants, the need for optimization of a compact muffler seems obvious. Therefore, a muffler composed of multiple rectangular fin-shaped chambers is proposed. Based on the eigenfunction theory, a four-pole matrix used to evaluate the acoustic performance of mufflers will be deduced. A numerical case for eliminating pure tones using a three-fin-chamber muffler will also be examined. To delineate the best acoustical performance of a space-constrained muffler, a numerical assessment using the Differential Evolution (DE) method is adopted. Before the DE operation for pure tone elimination can be carried out, the accuracy of the mathematical model must be checked using experimental data. The results reveal that the broadband noise has been efficiently reduced using the three-fin-chamber muffler. Consequently, a successful approach in eliminating a pure tone using optimally shaped three-fin-chamber mufflers and a differential evolution method within a constrained space has been demonstrated.
Źródło:
Archives of Acoustics; 2015, 40, 3; 311-319
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-5 z 5

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