Open AccessDesign Optimization of B-series Marine Propeller using NSGA-II, Iterative and Gekko Algorithm
Author(s) -
SM Munawar Mahtab,
Debasish Roy,
M.S. Rabbi,
Md. Iftekharul Alam
Publication year - 2021
Publication title -
journal of engineering advancements
Language(s) - English
Resource type - Journals
eISSN - 2708-6437
pISSN - 2708-6429
DOI - 10.38032/jea.2021.03.006
Subject(s) - sorting , propeller , thrust , series (stratigraphy) , genetic algorithm , mathematical optimization , python (programming language) , multi objective optimization , sorting algorithm , algorithm , iterative method , computer science , engineering , mathematics , marine engineering , aerospace engineering , paleontology , biology , operating system
The design of a propeller plays a significant role in naval architecture. Optimization of various design factors is the primary concern for effective and efficient propulsion. This study investigates the optimization of the B-series marine propellers using three different methods, i.e. (i) a non-linear constrained single-objective optimization approach using the Non-Dominated Sorting Genetic Algorithm (NSGA-II), (ii) a python package for dynamic optimization based optimization software ‘Gekko’, (iii) an iterative approach and results were compared with each other. Efficiency is considered as the single objective function whereas three constraints are imposed: cavitation, thrust and strength. Analogous characteristics have been found in the comparison of results from all three methods. Comparing the various factors, this study suggests that, Gekko can be used as the optimization algorithm.