Archives of Acoustics, 43, 3, pp. 517–529, 2018
10.24425/123923

Numerical Assessment of Automotive Mufflers Using FEM, Neural Networks, and a Genetic Algorithm

Ying-Chun CHANG
Tatung University
Taiwan, Province of China

Min-Chie CHIU
Chung Chou University of Science and Technology
Taiwan, Province of China

Meng-Ru WU
Tatung University
Taiwan, Province of China

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.
Keywords: acoustics; finite element method; genetic algorithm; muffler optimization; polynomial neural network model
Full Text: PDF

References

Bies D.A., Hansen C.H. (1988), Engineering noise control, Unwin Hyman, New York.

Chang Y.C., Chiu M.C., Cheng M.M. (2009), Optimum design of perforated plug mufflers using neural network and genetic algorithm, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 223, 4, 935–952.

Chang Y.C., Yeh L.J., Chiu M.C. (2004), Numerical studies on constrained venting system with side inlet/outlet mufflers by GA optimization, Acta Acustica united with Acustica, 90, 6, 1159–1169.

Chen J., Shi X. (2011), CFD numerical simulation of exhaust muffler, 2011 Seventh International Conference on Computational Intelligence and Security, pp. 1438–1441.

Chiu M.C. (2013), Shape optimization of multi-chamber tube-extended mufflers within specified back pressures using a particle swarm method, Noise & Vibration Worldwide, 44, 3, 10–23.

Chiu M.C., Chang Y.C. (2009), Application of neural network and genetic algorithm to the optimum design of perforated tube mufflers, Journal of Mechanics, 25, 3, N7–N16.

Chiu M.C., Chang Y.C., Huang C.L., Cheng H.C. (2016), Venting noise abatement using a cylindrical dissipative muffler and genetic method, Sylwan Journal, 160, 3, 271–299.

Fang J., Zhou Y., Jiao P., Ling Z. (2009), Study on pressure loss for a muffler based on CFD and experiment, 2009 International Conference on Measuring Technology and Mechatronics Automation ICMTMA'09, Vol. 3, pp. 887–890.

Galphade A., Patil A.V. (2015), Design and analysis of muffler for 800 cc car, International Journal of Advance Research in Engineering, Science & Technology, 2, 7, 72–76.

Holland J. (1975), Adaptation in natural and artificial system, Ann Arbor: University of Michigan Press.

Ih J.G. (1992), The reactive attenuation of rectangular plenum chambers, Journal of Sound and Vibration, 157, 1, 93–122.

Ivakhnenko A.G. (1971), Polynomial theory of complex system, IEEE transactions on Systems, Man, and Cybernetics, 1, 4, 364-368.

Jong D. (1975), An analysis of the behavior of a class of genetic adaptive systems, Doctoral thesis, Dept. Computer and Communication Sciences, Ann Arbor, University of Michigan.

Kore S., Aman A., Direbsa E. (2011), Performance evaluation of a reactive muffler using CFD, Journal of EEA, 28, 83–89.

Lyu B.H (2005), An Investigation in design and performance of reactive muffler for dry pump, Master degree, Chung Yuan Christian University.

Mo J.Y., Huh M.S. (1994), A study on the analysis and improvement of the acoustic characteristics of the muffler with complex geometry, International Compressor Engineering Conference.

Mohiuddin A.K.M., Rahman Ataur, Gazali Y.B. (2007), Simulation and experimental investigation of muffler performance, International Journal of Mechanical and Materials Engineering (IJMME), 2, 2, 118–124.

Panigrahi S.N., Munjal M.L. (2007), Backpressure considerations in designing of cross flow perforated-element reactive silencer, Noise Control Engineering Journal, 55, 6, 504–515.

Patrikar A., Provence J. (1996), Nonlinear system identification and adaptive control using polynomial networks, Mathematical and Computer Modelling, 23, 1/2, 159–173.

Potente D. (2005), General design principles for an automotive muffler, Proceedings of Acoustics, pp. 153–158.

Rajadurai S., Ananth S. (2014), Muffler development for diesel hybrid vehicle, International Journal of Innovative Science, Engineering & Technology, 1, 9, 513–519.

Reddy M.R., Reddy K.M. (2012), Design and optimization of exhaust muffler in automobiles, International Journal of Engineering Research and Applications, 2, 5, 395–398.

Somashekar G., Prakasha A.M., Ahamd N., Badrinarayan K.S. (2015), Modal analysis of muffler of an automobile by experimental and numerical approach, International Journal of Recent Research in Civil and Mechanical Engineering, 2, 1, 309–314.

Tajane A., Jadhav M., Rathod R., Elavande V. (2014), Design and testing of automobile exhaust system, International Journal of Research in Engineering and Technology, 3, 11, 164–168.

Vasile O., Gillich G. (2012), Finite element analysis of acoustic pressure levels and transmission loss of a muffler, [in:] Advances in Remote Sensing, Finite Differences and Information Security, Scutelnicu E., Lazic L., de Arroyabe P.F. (Eds.), Wseas LLC, pp. 43–48.

Yeh L.J., Chang Y.C., Chiu M.C. (2006), Numerical studies on constrained venting system with reactive mufflers by GA optimization, International Journal for Numerical Methods in Engineering, 65, 8, 1165–1185.




DOI: 10.24425/123923

Copyright © Polish Academy of Sciences & Institute of Fundamental Technological Research (IPPT PAN)