Abstract: In this study, the three-dimensional cavitating
turbulent flow in a complete Francis turbine is simulated using
mixture model for cavity/liquid two-phase flows. Numerical analysis
is carried out using ANSYS CFX software release 12, and standard k-ε
turbulence model is adopted for this analysis. The computational
fluid domain consist of spiral casing, stay vanes, guide vanes, runner
and draft tube. The computational domain is discretized with a threedimensional
mesh system of unstructured tetrahedron mesh. The
finite volume method (FVM) is used to solve the governing equations
of the mixture model. Results of cavitation on the runner’s blades
under three different boundary conditions are presented and
discussed. From the numerical results it has been found that the
numerical method was successfully applied to simulate the cavitating
two-phase turbulent flow through a Francis turbine, and also
cavitation is clearly predicted in the form of water vapor formation
inside the turbine. By comparison the numerical prediction results
with a real runner; it’s shown that the region of higher volume
fraction obtained by simulation is consistent with the region of runner
cavitation damage.
Abstract: In this article, a method is presented to effectively
estimate the deformed shape of a thick plate due to line heating. The
method uses a fifth order spline interpolation, with up to C3
continuity at specific points to compute the shape of the deformed
geometry. First and second order derivatives over a surface are the
resulting parameters of a given heating line on a plate. These
parameters are determined through experiments and/or finite element
simulations. Very accurate kriging models are fitted to real or virtual
surfaces to build-up a database of maps. Maps of first and second
order derivatives are then applied on numerical plate models to
evaluate their evolving shapes through a sequence of heating lines.
Adding an optimization process to this approach would allow
determining the trajectories of heating lines needed to shape complex
geometries, such as Francis turbine blades.
Abstract: Nowadays, the challenge in hydraulic turbine design is
the multi-objective design of turbine runner to reach higher
efficiency. The hydraulic performance of a turbine is strictly depends
on runner blades shape. The present paper focuses on the application
of the multi-objective optimization algorithm to the design of a small
Francis turbine runner. The optimization exercise focuses on the
efficiency improvement at the best efficiency operating point (BEP)
of the GAMM Francis turbine. A global optimization method based
on artificial neural networks (ANN) and genetic algorithms (GA)
coupled by 3D Navier-Stokes flow solver has been used to improve
the performance of an initial geometry of a Francis runner. The
results show the good ability of optimization algorithm and the final
geometry has better efficiency with initial geometry. The goal was to
optimize the geometry of the blades of GAMM turbine runner which
leads to maximum total efficiency by changing the design parameters
of camber line in at least 5 sections of a blade. The efficiency of the
optimized geometry is improved from 90.7% to 92.5%. Finally,
design parameters and the way of selection have been considered and
discussed.