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Large Markov Decision Processes Based Management Strategy of Inland Waterways in Uncertain Context Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Combination of a Particle Swarm Optimization and Nelder–Mead Algorithm in a Diffuser Shape Optimization

Authors : Prokop Moravec, Pavel Rudolf

Published in: Advances in Hydroinformatics

Publisher: Springer Singapore

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Abstract

This work focuses on the optimization of a hydraulic turbine diffuser, which is located behind the runner of the swirl turbine. The present paper extends our work in shape optimization using direct methods (namely Nelder–Mead method) and stochastic methods (namely Particle swarm optimization) coupled with CFD simulations. Both methods have their own advantages and disadvantages. Present work focuses on a combination of particle swarm optimization (at the beginning of the algorithm) and Nelder–Mead algorithm (NMA) (at the end of the algorithm). The diffuser will serve as the test case to demonstrate efficient coupling of the mathematical optimization procedure and CFD simulation. The main goal of this test problem is set to maximize the coefficient of pressure recovery c p, which is the main parameter to judge the proper design of the draft tube. Results obtained with this new method will be discussed and their advantages/disadvantages summarized.

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previous chapter New Prototype of a Kinetic Turbine for Artificial Channels
next chapter Multiphase Modeling of Hydrosystems Using OpenFOAM
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Metadata
Title
Combination of a Particle Swarm Optimization and Nelder–Mead Algorithm in a Diffuser Shape Optimization
Authors
Prokop Moravec
Pavel Rudolf
Copyright Year
2018
Publisher
Springer Singapore
Book
Advances in Hydroinformatics

Print ISBN: 978-981-10-7217-8

Electronic ISBN: 978-981-10-7218-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7218-5_70