Reliability Based Design Optimization of Shape Memory Alloy

"Smart Materials" become more and more used due to their physical properties compared to other materials. Shape memory alloys (SMA) could be classified as one of them. Such material is characterized by the ability to remember its original shape after deformation. SMA provides high structural performance. However, this kind of material increases the cost of structures. Thus, optimization techniques have been applied in order to obtain minimum the volume structure. As SMA requires a global optimization tool, the evolutionary algorithms such as particle swarm optimization (PSO) is well suited. In deterministic optimization, the uncertainties of the system parameters are not taken into consideration. As a result, the optimal design obtained does not ensure the target reliability level. Thus, reliability based design optimization (RBDO) method was applied to provide an enhanced design. However, classical RBDO leads to high computational time. So, the purpose of this paper is to optimize SMA structure taking into consideration uncertainties in the structural dimensions. Therefore, a proposed RBDO methodology based on safety factors derived from Karush Kuhn Tucker (KKT) methodology coupled with PSO is developed. Compared to deterministic optimization, the proposed method guarantees the target reliability level of the structure but requires little extra computational effort.