Optimization of a Draft Tube using Statistical Techniques- DOE and 2D Computational Fluid Dynamic Analysis

Authors

Federal University of Itajuba, Itajuba-MG, 37500-903, Brazil

Abstract

The draft tube is one of the main components that integrate a turbine, since it has the function of recovering the residual kinetic energy after the runner by the pressure energy. The search for a draft tube design that increases the efficiency of the turbine is always an engineering challenge. The hydromechanics components geometry optimization can be accomplished through the integration of optimization methods and CFD tools. In this work, the geometric optimization of a double diffuser draft tube of a Bulb turbine applied to ultra-low heads is presented, with the objectives of maximizing the pressure recovery coefficient, Cp, and increasing the hydraulic efficiency of the turbine, ηh. These improvements would make it possible to reduce the longitudinal length of the draft tube, thereby, making an easier insertion of this kind of turbines in water transport systems, with pressures around 3 [mH2O]. The optimization methodology was performed in the meridional plane, using twelve geometric variables in the draft tube through the integration of optimization methods and computational fluid dynamics. The optimized geometry obtained showed an increase in the Cp value of 0.71516, from the original geometry, to 0.83080. The results were extended to the 3D flow analysis, where the optimized turbine showed efficiency gains of 82% to 84%, when compared to the original turbine considering that its total length was reduced and its geometry simplified, resulting in a more compact and versatile equipment. The study also concluded that the applied methodology can be extended to other similar optimization problems in the design of hydraulic machines‎.

Keywords

Journal of Applied Fluid Mechanics
Volume 14, Issue 6 - Serial Number 62
November 2021
Pages 1617-1633

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History

  • Received: 23 October 2020
  • Revised: 29 April 2021
  • Accepted: 03 May 2021
  • First Publish Date: 31 October 2021

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