CFD Based Stochastic Optimization of Pelton Turbine Bucket in Stationery Condition

Suyesh Bhattarai; Keshav Dahal; Parag Vichare; Bhupesh Mishra

doi:10.1109/ICMAE.2018.8467607

CFD Based Stochastic Optimization of Pelton Turbine Bucket in Stationery Condition

Suyesh Bhattarai, Keshav Dahal, Parag Vichare, Bhupesh Mishra

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Computational fluid dynamics (CFD) and stochastic optimization are both highly computationally expensive processes. These processes may not produce the same unique result every time and demand large computing resources. The outcomes are determined as the final if the results repeat themselves for some predefined number of iterations causing convergence. Due to this expensive and non-deterministic nature, research on CFD optimization using stochastic optimization method such as Genetic Algorithm has been limited. This paper presents a noble method in which the CFD codes can be used together with genetic algorithm to optimize the shape of a responsive surface such as a Pelton turbine bucket. An existing Pelton bucket's model has been acquired and a set of random surfaces have been created as the initial population to optimize the shape of the bucket in stationery condition. The results show that an increase in efficiency by 13.21% to the normalized efficiency of existing design can be obtained by incorporating the changes suggested.

Original language	English
Title of host publication	Proceedings of 2018 9th International Conference on Mechanical and Aerospace Engineering, ICMAE 2018
Publisher	IEEE
Pages	53-57
Number of pages	5
ISBN (Electronic)	9781538672297
ISBN (Print)	978-1-5386-7230-3
DOIs	https://doi.org/10.1109/ICMAE.2018.8467607
Publication status	Published - 20 Sept 2018
Event	9th International Conference on Mechanical and Aerospace Engineering, ICMAE 2018 - Budapest, Hungary Duration: 10 Jul 2018 → 13 Jul 2018

Conference

Conference	9th International Conference on Mechanical and Aerospace Engineering, ICMAE 2018
Country/Territory	Hungary
City	Budapest
Period	10/07/18 → 13/07/18

Keywords

bucket design
Computational fluid dynamics
design optimization
genetic algorithms
Pelton turbine
turbomachinery

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10.1109/ICMAE.2018.8467607

Cite this

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title = "CFD Based Stochastic Optimization of Pelton Turbine Bucket in Stationery Condition",

abstract = "Computational fluid dynamics (CFD) and stochastic optimization are both highly computationally expensive processes. These processes may not produce the same unique result every time and demand large computing resources. The outcomes are determined as the final if the results repeat themselves for some predefined number of iterations causing convergence. Due to this expensive and non-deterministic nature, research on CFD optimization using stochastic optimization method such as Genetic Algorithm has been limited. This paper presents a noble method in which the CFD codes can be used together with genetic algorithm to optimize the shape of a responsive surface such as a Pelton turbine bucket. An existing Pelton bucket's model has been acquired and a set of random surfaces have been created as the initial population to optimize the shape of the bucket in stationery condition. The results show that an increase in efficiency by 13.21% to the normalized efficiency of existing design can be obtained by incorporating the changes suggested.",

keywords = "bucket design, Computational fluid dynamics, design optimization, genetic algorithms, Pelton turbine, turbomachinery",

author = "Suyesh Bhattarai and Keshav Dahal and Parag Vichare and Bhupesh Mishra",

year = "2018",

month = sep,

day = "20",

doi = "10.1109/ICMAE.2018.8467607",

language = "English",

isbn = "978-1-5386-7230-3",

pages = "53--57",

booktitle = "Proceedings of 2018 9th International Conference on Mechanical and Aerospace Engineering, ICMAE 2018",

publisher = "IEEE",

address = "United States",

note = "9th International Conference on Mechanical and Aerospace Engineering, ICMAE 2018 ; Conference date: 10-07-2018 Through 13-07-2018",

}

Bhattarai, S, Dahal, K, Vichare, P & Mishra, B 2018, CFD Based Stochastic Optimization of Pelton Turbine Bucket in Stationery Condition. in Proceedings of 2018 9th International Conference on Mechanical and Aerospace Engineering, ICMAE 2018., 8467607, IEEE, pp. 53-57, 9th International Conference on Mechanical and Aerospace Engineering, ICMAE 2018, Budapest, Hungary, 10/07/18. https://doi.org/10.1109/ICMAE.2018.8467607

TY - GEN

T1 - CFD Based Stochastic Optimization of Pelton Turbine Bucket in Stationery Condition

AU - Bhattarai, Suyesh

AU - Dahal, Keshav

AU - Vichare, Parag

AU - Mishra, Bhupesh

PY - 2018/9/20

Y1 - 2018/9/20

N2 - Computational fluid dynamics (CFD) and stochastic optimization are both highly computationally expensive processes. These processes may not produce the same unique result every time and demand large computing resources. The outcomes are determined as the final if the results repeat themselves for some predefined number of iterations causing convergence. Due to this expensive and non-deterministic nature, research on CFD optimization using stochastic optimization method such as Genetic Algorithm has been limited. This paper presents a noble method in which the CFD codes can be used together with genetic algorithm to optimize the shape of a responsive surface such as a Pelton turbine bucket. An existing Pelton bucket's model has been acquired and a set of random surfaces have been created as the initial population to optimize the shape of the bucket in stationery condition. The results show that an increase in efficiency by 13.21% to the normalized efficiency of existing design can be obtained by incorporating the changes suggested.

AB - Computational fluid dynamics (CFD) and stochastic optimization are both highly computationally expensive processes. These processes may not produce the same unique result every time and demand large computing resources. The outcomes are determined as the final if the results repeat themselves for some predefined number of iterations causing convergence. Due to this expensive and non-deterministic nature, research on CFD optimization using stochastic optimization method such as Genetic Algorithm has been limited. This paper presents a noble method in which the CFD codes can be used together with genetic algorithm to optimize the shape of a responsive surface such as a Pelton turbine bucket. An existing Pelton bucket's model has been acquired and a set of random surfaces have been created as the initial population to optimize the shape of the bucket in stationery condition. The results show that an increase in efficiency by 13.21% to the normalized efficiency of existing design can be obtained by incorporating the changes suggested.

KW - bucket design

KW - Computational fluid dynamics

KW - design optimization

KW - genetic algorithms

KW - Pelton turbine

KW - turbomachinery

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UR - https://ieeexplore.ieee.org/document/8467607

U2 - 10.1109/ICMAE.2018.8467607

DO - 10.1109/ICMAE.2018.8467607

M3 - Conference publication

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SN - 978-1-5386-7230-3

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BT - Proceedings of 2018 9th International Conference on Mechanical and Aerospace Engineering, ICMAE 2018

PB - IEEE

T2 - 9th International Conference on Mechanical and Aerospace Engineering, ICMAE 2018

Y2 - 10 July 2018 through 13 July 2018

ER -

CFD Based Stochastic Optimization of Pelton Turbine Bucket in Stationery Condition

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