Integrated intelligent Jaya Runge-Kutta method for solving Falkner-Skan equations with various wedge angles

Verfasst von

Hongwei Guo, Xiaoying Zhuang, Timon Rabczuk

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.

Details

Organisationseinheit(en)
Institut für Photonik
Externe Organisation(en)
Tongji University
King Saud University
Typ
Artikel
Journal
INTERNATIONAL JOURNAL OF HYDROMECHATRONICS
Band
5
Seiten
311-335
Anzahl der Seiten
25
ISSN
2515-0464
Publikationsdatum
2022
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Fahrzeugbau, Elektrotechnik und Elektronik, Maschinenbau, Werkstoffwissenschaften (sonstige)
Elektronische Version(en)
https://doi.org/10.48550/arXiv.2010.05682 (Zugang: Offen )
https://doi.org/10.1504/ijhm.2022.127047 (Zugang: Geschlossen )
 
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