TOPOLOGY OPTIMIZATION ANALYSIS OF ADHESIVE SOUND ABSORBING MATERIALS STRUCTURE WITH SUBDIVISION SURFACE BOUNDARY ELEMENT METHOD

Isogeometric analysis (IGA) realizes the seamless integration of CAD and CAE by using spline basis functions to represent geometric models and implement the numerical analysis, and is widely used in elastic mechanics, electromagnetic field, potential problem and other fields. However, it is difficult to construct directly a complex structure by using IGA. The subdivision surface method can be used to subdivide and fit the discrete mesh of a traditional model in order to construct smooth surfaces. Such a method is suitable for complicated problems. This method has the following advantages: (1) It is suitable for any topological structure; (2) The numerical calculation is stable; (3) It is simple to implement; (4) Local refinement and continuity control. Because of its flexibility and convenience in the construction of complex structural models, this method has been widely used in aerospace, automobile, animation, game making and other modeling fields. The subdivision surface method (SSM) and the boundary element method (BEM) were integrated to perform structural acoustic analysis. The box-spline interpolation of SSM was used for both geometric interpolation and physical interpolation, achieving high-order approximation of the structural surface and physical field. The acoustic scattering of the structure of adhesive sound absorption materials was taken as an example to test the effectiveness of the algorithm. The above analysis was combined with the method of moving asymptotes (MMA) algorithm to conduct a topological optimization of the distribution of sound absorption materials. In this study, the adjoint variable method and the acoustic BEM were used to analyze the sensitivity of the distribution of sound absorption materials on the surface of the structure. Each update of design variables brings small changes in the layout of sound absorbing materials, and ultimately the optimal solution is obtained. The resulting solvers provide an efficient computational tool for topology optimization design. The proposed algorithm is then applied to some numerical examples to illustrate the potential for engineering optimization design.