Meshless numerical simulation of (full) potential flows in a nozzle by genetic algorithms

Abstract

A new procedure to solve some fluid problems formulated in elliptical partial differential equations is presented. A Genetic Algorithm with a dynamical encoding and a partial grid sampling is proposed for it as the advantages of solving the problem without using all grid nodes at the same time, and of adjusting step grid, without increasing the complexity. The designed method has immediate applications some self‐contained and some in combination with other traditional methods. Also, it provides a method alternative to the existing ones and uses simpler operations. Theoretical mathematical foundations of the problem are easily incorporated and that as a powerful characteristic of the method. In practice, our focus is to obtain an acceptable approximated solution. The method makes it possible to solveproblems with vague boundary conditions since no algebraic equation system is involved in the process. From the solution reached we have good information available to make an appropriate mesh to solve the problem through a traditional method. Comparative results for both linear and non‐linear potential flow problems inside a nozzle are given.