Abstract <p>A numerical approach based on the orthogonal central composite design is proposed. This approach allows one to study the mechanism of acoustic wave scattering on the system of sound-permeable spheres and analyze the sensitivity of this multiparameter system to a small change in several main parameters (factors). The method is implemented for a three-factor computational experiment using the example of systems with strong interaction between scatterers. For the resulting regression equation, the significance of the coefficients and the adequacy of the model are checked for two simple configuration types and three values of the number of spheres in them, as well as optimal values of two objective functions are found. For each case, essential and insignificant factors are established, the parameters at which the objective functions achieve the maximum (minimum) value are determined, and the sensitivity of this function to a small change in the variable parameters is determined.</p>

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Orthogonal Central Composite Design to Study Acoustic Scattering on the System of Sound-Permeable Spheres

  • E. Sh. Nasibullaeva

摘要

Abstract

A numerical approach based on the orthogonal central composite design is proposed. This approach allows one to study the mechanism of acoustic wave scattering on the system of sound-permeable spheres and analyze the sensitivity of this multiparameter system to a small change in several main parameters (factors). The method is implemented for a three-factor computational experiment using the example of systems with strong interaction between scatterers. For the resulting regression equation, the significance of the coefficients and the adequacy of the model are checked for two simple configuration types and three values of the number of spheres in them, as well as optimal values of two objective functions are found. For each case, essential and insignificant factors are established, the parameters at which the objective functions achieve the maximum (minimum) value are determined, and the sensitivity of this function to a small change in the variable parameters is determined.