Integrated intelligent Jaya Runge-Kutta method for solving Falkner-Skan equations with various wedge angles
by Hongwei Guo; Xiaoying Zhuang; Timon Rabczuk
International Journal of Hydromechatronics (IJHM), Vol. 5, No. 4, 2022

Abstract: In this work, the hybrid intelligent computing method is developed to solve the Falkner-Skan equations with various wedge angles, which combines efficient Jaya algorithm with classical Runge-Kutta method. Using higher order reduction strategies, the whole problem can be reduced to solving of coupled differential equations with prescribed initial and boundary conditions. The hybrid Jaya Runge-Kutta method is found to yield stable and accurate results and can extract those unknown parameters brought by asymptotic boundary condition in solving the coupled differential equations. In addition, the Jaya algorithm, without the need for tuning the algorithm-specific parameters, is proved to be effective and stable for optimisation problems. By comparing numerical results obtained using the Jaya algorithm with particle swarm optimisation (PSO), genetic algorithm (GA), hyperband, the hybrid Jaya Runge-Kutta method proves to be more stable and accurate, which shows great potential for solving more complicated multifield and multiphase flow problems.

Online publication date: Fri, 18-Nov-2022

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