TY - JOUR N2 - The locally resonant sonic material (LRSM) is an artificial metamaterial that can block underwater sound. The low-frequency insulation performance of LRSM can be enhanced by coupling local resonance and Bragg scattering effects. However, such method is hard to be experimentally proven as the best optimizing method. Hence, this paper proposes a statistical optimization method, which first finds a group of optimal solutions of an object function by utilizing genetic algorithm multiple times, and then analyzes the distribution of the fitness and the Euclidean distance of the obtained solutions, in order to verify whether the result is the global optimum. By using this method, we obtain the global optimal solution of the low-frequency insulation of LRSM. By varying parameters of the optimum, it can be found that the optimized insulation performance of the LRSM is contributed by the coupling of local resonance with Bragg scattering effect, as well as a distinct impedance mismatch between the matrix of LRSM and the surrounding water. This indicates coupling different effects with impedance mismatches is the best method to enhance the low-frequency insulation performance of LRSM. L1 - http://www.czasopisma.pan.pl/Content/112100/PDF/aoa.2019.128500.pdf L2 - http://www.czasopisma.pan.pl/Content/112100 PY - 2019 IS - No 2 EP - 374 DO - 10.24425/aoa.2019.128500 KW - underwater acoustic KW - sound insulation KW - local resonance KW - statistical optimization KW - global optimum A1 - Yuan, Bo A1 - Chen, Yong A1 - Tan, Bilian A1 - Li, Bo PB - Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics VL - vol. 44 DA - 2019.06.13 T1 - Statistical Optimization of Underwater Lower-Frequency Sound Insulation for Locally Resonant Sonic Material Using Genetic Algorithm SP - 365 UR - http://www.czasopisma.pan.pl/dlibra/publication/edition/112100 T2 - Archives of Acoustics ER -