Multi-objective shape optimization of a hydraulic turbine runner using efficiency, strength and weight criteria Full article
Journal |
Structural and Multidisciplinary Optimization
ISSN: 1615-147X , E-ISSN: 1615-1488 |
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Output data | Year: 2018, Volume: 58, Number: 2, Pages: 627-640 Pages count : 14 DOI: 10.1007/s00158-018-1914-6 | ||||||
Tags | Finite element analysis; Genetic algorithm; Hydraulic turbine runner; Thickness function; Three-dimensional flow simulation | ||||||
Authors |
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Abstract:
An approach for multi-discipline automatic optimization of the hydraulic turbine runner shape is presented. The approach
accounts hydraulic efficiency, mechanical strength and the weight of the runner. In order to effectively control the strength
and weight of the runner, a new parameterization of the blade thickness function is suggested. Turbine efficiency is evaluated
through numerical solution of Reynolds-averaged Navier-Stokes equations, while the finite element method is used to evaluate
the von Mises stress in the runner. An objective function, being the weighted sum of maximal stress and the blade volume, is
suggested to account for both the strength and weight of the runner. Multi-objective genetic algorithm is used to solve the
optimization problem. The suggested approach has been applied to automatic design of a Francis turbine runner. Series of threeobjective
optimization runs have been carried out. The obtained results clearly indicate that simultaneous account of stress and
weight objectives accompanied by thickness variation allows obtaining high efficiency, light and durable turbine runners.
Cite:
Chirkov D.V.
, Ankudinova A.S.
, Kryukov A.E.
, Cherny S.G.
, Skorospelov V.A.
Multi-objective shape optimization of a hydraulic turbine runner using efficiency, strength and weight criteria
Structural and Multidisciplinary Optimization. 2018. V.58. N2. P.627-640. DOI: 10.1007/s00158-018-1914-6 WOS Scopus OpenAlex
Multi-objective shape optimization of a hydraulic turbine runner using efficiency, strength and weight criteria
Structural and Multidisciplinary Optimization. 2018. V.58. N2. P.627-640. DOI: 10.1007/s00158-018-1914-6 WOS Scopus OpenAlex
Identifiers:
Web of science: | WOS:000440107200016 |
Scopus: | 2-s2.0-85044959247 |
OpenAlex: | W2786997757 |