An iterative procedure for 3D blade design is presented. The three-dimensional blade shape is modified using a physical algorithm, based on the transpiration model. The transpiration flux is computed by means of a modified Euler solver, in which the target pressure distribution is imposed along the blade surfaces. Only a small number of modifications is needed to obtain the final geometry. The method is based on a high resolution three-dimensional Euler solver. An upwind biased evaluation of the advective fluxes allows for a very low numerical entropy generation, and sharp shock capturing. The method is first validated, by redesigning an existing geometry, starting from a different one. It is further used to redesign a transonic compressor blade, to achieve, for the same mass flow and outlet flow angle, a shock free deceleration along the suction side. The last example concerns the design of a low aspect ratio turbine blade, with a positive compound lean to reduce the intensity of the passage vortices. The final blade is designed for an optimized pressure distribution, taking into account the forces resulting from the blade lean angle.

An iterative procedure for three-dimensional blade design is presented, in which the three-dimensional blade shape is modified using a physical algorithm, based on the transpiration model. The transpiration flux is computed by means of a modified Euler solver, in which the target pressure distribution is imposed along the blade surfaces. Only a small number of modifications is needed to obtain the final geometry. The method is based on a high-resolution three-dimensional Euler solver. An upwind biased evaluation of the advective fluxes allows for a very low numerical entropy generation, and sharp shock capturing. Non-reflecting boundary conditions are applied along the inlet/outlet boundaries. The capabilities of the method are illustrated by redesigning a transonic compressor rotor blade, to achieve, for the same mass flow and outlet flow angle, a shock-free deceleration along the suction side. The second example concerns the design of a low aspect ratio turbine blade, with a positive compound lean to reduce the intensity of the passage vortices. The final blade is designed for an optimized pressure distribution, taking into account the forces resulting from the blade lean angle.

This paper presents a new integrated environment FINE™/Design3D developed for the optimization of turbomachinery compressor and turbine blade shapes. The methodology relies on the interaction between a genetic algorithm, an artificial neural network, a database and user generated objective functions and constraints. The optimization is coupled to the FINE™/Turbo environment of NUMECA. The present paper focuses on multipoint optimization. The generality of the formulation of the FINE™/Design3D optimization techniques allows the objective function to be based on the evaluation of the performance at different working conditions. The examples presented in the paper illustrate this new capability, showing the application of multipoint optimization to a turbine rotor and to a re-design of the NASA Rotor 37 transonic compressor rotor.

This paper presents an integrated environment FINETM/Design3D developed for the optimization of turbomachinery blade shapes. The methodology relies on the interaction between a genetic algorithm, an artificial neural network, a database and user generated objective functions and constraints. The optimization is coupled to the FINETM/Turbo environment of NUMECA. The present paper focuses on the application of the multipoint optimization algorithm to the design of an industrial pump. The large range of mass flow over which the pump should operate motivates the use of multipoint optimization. The optimization exercise focuses on the efficiency, the head and the NPSH at two operating conditions characterized by largely different mass flows.

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