scholarly journals Optimization of thrust propeller design for an ROV (Remotely Operated Vehicle) consideration by Genetic Algorithms

2017 ◽  
Vol 138 ◽  
pp. 07003 ◽  
Author(s):  
Aldias Bahatmaka ◽  
Dong-Joon Kim ◽  
Deddy Chrismianto ◽  
Nguyen Hai ◽  
Aditya Rio Prabowo
2014 ◽  
Vol 21 (3) ◽  
pp. 40-45 ◽  
Author(s):  
Tadeusz Chruściel ◽  
Ewelina Ciba ◽  
Julita Dopke

Abstract Within the framework of the project for design and optimization of the Remotely Operated Vehicle (ROV), research on its propulsion has been carried out. Te entire project was supported by CFD and FEM calculations taking into account the characteristics of the underwater vehicle. One of the tasks was to optimize the semi-open duct for horizontal propellers, which provided propulsion and controllability in horizontal plane. In order to create a measurable model of this task it was necessary to analyze numerical methodology of propeller design, along with the structure of a propellers with nozzles and contra-rotating propellers. It was confronted with theoretical solutions which included running of the analyzed propeller near an underwater vehicle. Also preliminary qualitative analyses of a simplified system with contra-rotating propellers and a semi-open duct were carried out. Te obtained results enabled to make a decision about the ROVs duct form. Te rapid prototyping SLS (Selective Laser Sintering) method was used to fabricate a physical model of the propeller. As a consequence of this, it was necessary to verify the FEM model of the propeller, which based on the load obtained from the CFD model. Te article contains characteristics of the examined ROV, a theoretical basis of propeller design for the analyzed cases, and the results of CFD and FEM simulations.


1996 ◽  
Vol 47 (4) ◽  
pp. 550-561 ◽  
Author(s):  
Kathryn A Dowsland
Keyword(s):  

2018 ◽  
Vol 1 (1) ◽  
pp. 2-19
Author(s):  
Mahmood Sh. Majeed ◽  
Raid W. Daoud

A new method proposed in this paper to compute the fitness in Genetic Algorithms (GAs). In this new method the number of regions, which assigned for the population, divides the time. The fitness computation here differ from the previous methods, by compute it for each portion of the population as first pass, then the second pass begin to compute the fitness for population that lye in the portion which have bigger fitness value. The crossover and mutation and other GAs operator will do its work only for biggest fitness portion of the population. In this method, we can get a suitable and accurate group of proper solution for indexed profile of the photonic crystal fiber (PCF).


2011 ◽  
Vol 3 (6) ◽  
pp. 87-90
Author(s):  
O. H. Abdelwahed O. H. Abdelwahed ◽  
◽  
M. El-Sayed Wahed ◽  
O. Mohamed Eldaken

2011 ◽  
Vol 2 (3) ◽  
pp. 56-58
Author(s):  
Roshni .V Patel ◽  
◽  
Jignesh. S Patel

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