Comparing Optimized Sound Absorption Coefficient of Aluminum Foam with Local Search Algorithm, Genetic Algorithm, and Particle Swarm Optimization

  • سال انتشار: 1403
  • محل انتشار: فصلنامه بهداشت محیط و توسعه پایدار، دوره: 9، شماره: 2
  • کد COI اختصاصی: JR_JEHSD-9-2_004
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 214
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نویسندگان

Rohollah Fallah Madvari

Industrial Diseases Research Center, Department of Occupational Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Mohsen Niknam Sharak

PhD Graduate in Mechanical Engineering, University of Birjand, Birjand, Iran

Mohammad Javad Jafari

Department of Occupational Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Faezeh Abbasi Balochkhaneh

Department of Occupational Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

چکیده

Introduction: The principle of passive sound control is based on the phenomenon of sound absorption by absorbers. The factors affecting sound absorption include porosity, pore size, pore opening size, thickness, and air flow resistance. Materials and Methods: In this study, the authors compared the optimization results of the effective parameters on sound absorption coefficient (AC) using the three optimization methods: Guided Local Search (GLS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The programming was done in MATLAB software. Thicknesses of ۵, ۱۰, ۲۰, ۳۰ and ۴۰ mm were chosen for optimization at frequencies of ۵۰۰ to ۳۰۰۰ Hz. Results: In frequencies above ۲ kHz (thickness ۵ to ۴۰ mm), the three optimal methods had the same performance and estimated AC of ۱. At low frequencies of ۲ kHz and thicknesses of ۳۰ and ۴۰ mm, GA and PSO methods obtained an AC of ۱. Conclusion: It seems that the GA and PSO optimization algorithm are suitable methods to optimize the AC of metal foam in low and high frequencies.

کلیدواژه ها

Sound Absorption, High-Frequency, Low-Frequency, Optimization Algorithm.

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