Star grain optimization and simulation using genetic algorithm based on high speed codes

In this article, the focus is on optimizing solid-fuel grain based on high-speed codes. One of the ways to design a high-performance solid fuel engine is to design the optimal grain for it, so that the highest burning area is provided, and on the other hand other requirements such as mechanical strength and build ability of the grain are provided. One of the most common types of grain is the star shape. To optimize a solid-fuel engine with a star grain, a model is needed to simulate the grain to provide the burning area at any given time. One of the methods of simulating the burning area is modeling it in CAD software and extracting the burning area using cloud points. This method has a high computational volume and its application in optimization algorithm, which is a recurring numerical method, is practically time consuming. To solve this problem, in this paper, a geometric parametric model has been used to calculate the burning area and the Zero-dimensional internal ballistic considering the erosive burning. The distinctive feature of this model is the high speed of its calculations, which is highly efficient in the coupling with optimization algorithms. The results show that this parametric geometric model, in addition to the much lower computational volume than the cloud point model, is also more accurate.