3D shape optimisation of a low-pressure turbine stage

The possibility of reducing the flow losses in low-pressure turbine stage has been investigated in an iterative process using a novel hybrid optimisation algorithm. Values of the maximised objective func- tion that is isentropic efficiency are found from 3D RANS computation of the flowpath geometry,...

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Bibliographic Details
Published in:International journal of energy production and management Vol. 3; no. 1; pp. 10 - 21
Main Authors: Witanowski, L., Klonowicz, P., Lampart, P.
Format: Journal Article
Language:English
Published: Southampton W I T Press 01.01.2018
Subjects:
Algorithms
Angles (geometry)
Iterative methods
Low pressure
Mass flow rate
Optimization
Stators
Turbines
ISSN:2056-3272, 2056-3280
Online Access:Get full text
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Summary:The possibility of reducing the flow losses in low-pressure turbine stage has been investigated in an iterative process using a novel hybrid optimisation algorithm. Values of the maximised objective func- tion that is isentropic efficiency are found from 3D RANS computation of the flowpath geometry, which was being changed during the optimisation process. To secure the global flow conditions, the constraints have been imposed on the mass flow rate and reaction. Among the optimised parameters are stator and rotor twist angles, stator sweep and lean, both straight and compound. Blade profiles remained unchanged during the optimisation. A new hybrid stochastic-deterministic algorithm was used for the optimisation of the flowpath. In the proposed algorithm, the bat algorithm was combined with the direct search method of Nelder-Mead in order to refine the best obtained solution from the standard bat algorithm. The method was tested on a wide variety of well-known test functions. Also, the results of the optimisation of the other stochastic and deterministic methods were compared and discussed. The optimisation gives new 3D-stage designs with increased efficiency comparing to the original design.
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ISSN:2056-3272
2056-3280
DOI:10.2495/EQ-V3-N1-10-21