Blade Shape Optimization of Marine Propeller via Genetic Algorithm for Efficiency Improvement

2012 ◽  
Author(s):  
Ramin Taheri ◽  
Karim Mazaheri
Keyword(s):  
Genetic Algorithm ◽  
Parallel Processing ◽  
Thickness Distribution ◽  
Processing System ◽  
Optimization Method ◽  
Initial Guess ◽  
Hydrodynamic Performance ◽  
Local Optimum ◽  
Lattice Method ◽  
Gradient Based

In this paper, a numerical optimization method has been carried out to optimize the shape and efficiency of a propeller. For analysis of the hydrodynamic performance parameters, an extended vortex lattice method was used by implementing an open-source code which is called OpenProp. The method of optimization is a non-gradient based algorithm. After a trade-off between a few gradient-based and non-gradient based algorithms, it is found that the problem of being trapped in local optimum solutions can be easily solved by choosing nongradient based ones. Hence, modified Genetic algorithm is used to implement the so-called hydrodynamic performance analyzer code. The objective function is to maximize efficiency by considering the design variables as non-dimensional blade’s chord and thickness distribution along the blade. For initial guess data of the DTRC 4119 propeller which are radially distributed along the blade is used. The hydrodynamic performance analyzer code is modified by a higher order QuasiNewton scheme. Also hybrid function is used to accurate the convergence. Finally, parallel processing implementation on the codes has been done successfully. To improve the computation speed, the algorithm is improved to be extended on a parallel processing system. The process of parallelizing has been done simplicity by Matlab M-code and the number of cores has been chosen as 4. The final results verify both fast convergence in comparison with common methods and nearly 10% improvement in propeller efficiency (mechanical efficiency of the system) which is significant for these kinds of problems. Therefore, the algorithm starts with geometry arrived at by other researchers and improves it to a more efficient propeller.

A Kind of New Immune Genetic Algorithm and its Application

2011 ◽  
Vol 48-49 ◽  
pp. 25-28
Author(s):  
Wei Jian Ren ◽  
Yuan Jun Qi ◽  
Wei Lv ◽  
Cheng Da Li
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Optimization Problems ◽  
Logistic Map ◽  
Optimal Solution ◽  
Optimization Method ◽  
Local Optimum ◽  
Immune Genetic Algorithm ◽  
Chaos Optimization ◽  
Scale Optimization

According to the phenomenon of falling into local optimum during solving large-scale optimization problems and the shortcomings of poor convergence of Immune Genetic Algorithm, a new kind of probability selection method based on the concentration for the genetic operation is presented. Considering the features of chaos optimization method, such like not requiring the solved problems with continuity or differentiability, which is unlike the conventional method, and also with a solving process within a certain range traverse in order to find the global optimal solution, a kind of Chaos Immune Genetic Algorithm based on Logistic map and Hénon map is proposed. Through the application to TSP problem, the results have showed the superior to other algorithms.

A Genetic Algorithm Based Method for Product Family Design Optimization

2002 ◽  
Author(s):  
Brayan S. D’Souza ◽  
Timothy W. Simpson
Keyword(s):  
Genetic Algorithm ◽  
Product Family ◽  
Product Variety ◽  
Optimization Method ◽  
General Aviation ◽  
Product Performance ◽  
Individual Product ◽  
The Family ◽  
Gradient Based ◽  
The Individual

Increased commonality in a family of products can simplify manufacturing and reduce the associated costs and lead-times. There is a tradeoff, however, between commonality and individual product performance within a product family, and in this paper we introduce a genetic algorithm based method to help find an acceptable balance between commonality in the product family and desired performance of the individual products in the family. The method uses Design of Experiments to help screen unimportant factors and identify factors of interest to the product family and a multiobjective genetic algorithm, the non-dominated sorting genetic algorithm, to optimize the performance of the products in the resulting family. To demonstrate implementation of the proposed method, the design of a family of three General Aviation Aircraft is presented along with a product variety tradeoff study to determine the extent of the tradeoff between commonality and individual product performance within the aircraft family. The efficiency and effectiveness of the proposed method is illustrated by comparing the family of aircraft against individually optimized designs and designs obtained from an alternate gradient-based multiobjective optimization method.

scholarly journals Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1452
Author(s):  
Cristian Mateo Castiblanco-Pérez ◽  
David Esteban Toro-Rodríguez ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Power Balance ◽  
Continuous Version ◽  
Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

scholarly journals Optimization of a 3D-Printed Permanent Magnet Coupling Using Genetic Algorithm and Taguchi Method

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 494
Author(s):  
Ekaterina Andriushchenko ◽  
Ants Kallaste ◽  
Anouar Belahcen ◽  
Toomas Vaimann ◽  
Anton Rassõlkin ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Taguchi Method ◽  
Permanent Magnet ◽  
Optimization Problems ◽  
Optimization Method ◽  
Taguchi Optimization ◽  
Torque Density ◽  
Electromagnetic Devices ◽  
3D Printed ◽  
Manufacturing Techniques

In recent decades, the genetic algorithm (GA) has been extensively used in the design optimization of electromagnetic devices. Despite the great merits possessed by the GA, its processing procedure is highly time-consuming. On the contrary, the widely applied Taguchi optimization method is faster with comparable effectiveness in certain optimization problems. This study explores the abilities of both methods within the optimization of a permanent magnet coupling, where the optimization objectives are the minimization of coupling volume and maximization of transmitted torque. The optimal geometry of the coupling and the obtained characteristics achieved by both methods are nearly identical. The magnetic torque density is enhanced by more than 20%, while the volume is reduced by 17%. Yet, the Taguchi method is found to be more time-efficient and effective within the considered optimization problem. Thanks to the additive manufacturing techniques, the initial design and the sophisticated geometry of the Taguchi optimal designs are precisely fabricated. The performances of the coupling designs are validated using an experimental setup.

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