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Shape Optimization of Two-layer Acoustical Hoods Using an Artificial Immune Method

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Research on acoustical hoods used in industry has been widely discussed; however, the assessment of shape optimization on space-constrained close-fitting acoustic hoods by adjusting design parameters has been neglected. Moreover, the acoustical performance for a one-layer acoustic hood used in a high intensity environment seems to be insufficient. Therefore, an assessment of an optimally shaped acoustical hood with two layers will be proposed. In this paper, a numerical case for depressing the noise level of a piece of equipment by optimally designing a shaped two-layer close-fitting acoustic hood under a constrained space will be introduced. Furthermore, to optimally search for a better designed set for the multi-layer acoustical hood, an artificial immune method (AIM) has been adopted as well. Consequently, this paper provides a quick and effective method to reduce equipment noise by optimally designing a shaped multi- layer close-fitting acoustic hood via the AIM searching technique.
Rocznik
Strony
181--188
Opis fizyczny
Bibliogr. 28 poz., tab., wykr.
Twórcy
autor
  • Department of Mechanical and Automation Engineering, Chung Chou University of Science and Technology No. 6, Lane 2, Sec.3, Shanchiao Rd., Yuanlin, Changhua 51003, Taiwan, R.O.C., minchie.chiu@msa.hinet.net
Bibliografia
  • 1. Beranek L.L., Work G.A. (1949), Sound transmission through multiple structures containing flexible blankets, J. Acoust. Soc. Am., 7, 419.
  • 2. Beranek L.L., V큖r I.L. (1992), Noise and vibration control engineering, John Wiley and Sons, New York.
  • 3. Bersini H., Varela F.J. (1994), The immune learning mechanisms: reinforcement, Recruitment and their applications, [in:] Computing with Biological Metaphors, Paton R. [Ed.], Chapman and Hall.
  • 4. Blanks J.E. (1997), Optimal Design of an Enclosure for a Portable Generator, Unpublished Master Thesis, Virginia Polytechnic Institute and State University.
  • 5. Carter J.H. (2000), The immune system as a model for pattern recognition and classification, Journal of the American Medical Information Association, 7, 1, 28-41.
  • 6. Crocker M.J. (1994), A system approach to the transmission of sound and vibration through structures, Noise-Con 94, 525-533.
  • 7. Dasgupta D. (1999), Artificial immune systems and their applications, Springer-Verlag.
  • 8. de Castro L.N., von Zuben F.J. (1999), Artificial immune systems: part I-basic theory and applications, Technical Report, TR-DCA01/99.
  • 9. Fahy F. (1989), Sound and structural vibration, Academic Press, San Diego, Ca.
  • 10. Fukuda T., Mori M., Tsukiyama M. (1993), Immune network genetic algorithm for adaptive production scheduling, Proceeding of the 15th IFAC World Congress, 3, 57-60.
  • 11. Hajela P., Yoo J., Lee J. (1997), GA based simulation of immune networks-application in structural optimization, Engineering Optimization, 29, 131-149.
  • 12. Hine M.J. (1972), Acoustic hood design in theory and practice, Noise-Con, 72, 278-281.
  • 13. Ishida Y., Hirayama H., Fujita H., Ishiguro A., Mori K. (1998), Immunity-based systems-intelligent system by artificial immune systems [in Japanese], Corona Pub. Co. Japan.
  • 14. Jackson R.S. (1962), The performance of acoustic hoods at low frequencies, Acustics, 12, 139-152.
  • 15. Jackson R.S. (1966), Some aspects of acoustic hoods, Journal of Sound and Vibration, 3, 82-94.
  • 16. Junger M.C. (1970), Sound through an elastic enclosure acoustically coupled to a noise source, ASME Paper No - WA/DE - 12.
  • 17. Kephart J.O. (1994), A biological inspired immune system for computers, [in:] Artificial Life IV Proceeding of the Fourth International Workshop on the Synthesis and Simulation of Living Systems, Brooks R.A., Maes P. [Eds.], MIT press.
  • 18. Kim J., Bentley P. (1999), Negative selection and niching by an artificial immune system for network instrusion Detection, Proceeding of Genetic and Evolutionary Computation Conference, 149-158.
  • 19. Kinsler L.E., Frey A.R. (1982), Fundamentals of acoustics, John Wiley and Sons, New York.
  • 20. Knight T., Timmis J. (2001), AINE: an immunological approach to data mining, Proceeding of the IEEE International Conference on Data Mining, 297-304.
  • 21. Ku C.C. (2003), Multimodal Topology Optimization of Structure Using Distributed Artificial Immune Algorithm, Unpublished Master Thesis, Department of Mechanical Engineering, Tatung University.
  • 22. London A. (1950), Transmission of reverberant sound through single wall, J. Acoust. Soc. Am., 22, 270-279.
  • 23. Moreland J.B. (1984), Low frequency noise reduction of acoustic enclosures, Noise Control Engineering Journal, 23, 3, 140-149.
  • 24. Mori M., Tsukiyama M., Fukuda T. (1993), Immune algorithm with searching diversity and its application to allocation problem, Trans. of Institute of Electrical Engineering of Japan, 113-C, 10, 872-878.
  • 25. Oldham D.J., Hilarby S.N. (1991a), The acoustical performance of small close fitting enclosures, part 1: theoretical methods, Journal of Sound and Vibration, 150, 261-281.
  • 26. Oldham D.J., Hilarby S.N. (1991b), The acoustical performance of small close fitting enclosures, part 2: experimental investigation, Journal of Sound and Vibration, 150, 283-300.
  • 27. Roberts J. (1990), The principle of noise control with enclosures, Journal of Electrical and Electronic Engineering, Australia, 10, 3, 151-155.
  • 28. Tomoyuki M. (2003), An application of immune algorithms for job-shop scheduling problems, Proc. of the 5th International Symposium on Assembly and Task Planning, 146-150.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0022-0006
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