Shengyin Wang

TL;DR: In this paper, the radial basis functions (RBFs) in scattered data fitting and function approximation are incorporated into the conventional level set methods to construct a more efficient approach for structural topology optimization.

TL;DR: In this article, a parametric level set method was proposed for structural shape and topology optimization using the compactly supported radial basis functions and the optimality criteria (OC) method.

TL;DR: The RBF multiquadric splines are used to construct the implicit level set function with a high level of accuracy and smoothness and to discretize the original initial value problem into an interpolation problem, leading to a rapid convergence to the final design insensitive to initial guesses.

TL;DR: It is highlighted that the present method can not only inherit the merits of the implicit boundary representation, but also avoid some unfavorable features of the conventional discrete level set method, such as the CFL condition restriction, the re-initialization procedure and the velocity extension algorithm.

TL;DR: In this article, a finite element model for the static and dynamic analysis of a piezoelectric bimorph is proposed, which combines a 2D single-layer representation model (finite 2D isoparametric elements) for the mechanical displacement field with a layerwise-like approximation for the electric potential field to achieve the accurate prediction of both mechanical displacement and electric potential fields.