Blade geometry

Abstract: This paper describes a knowledge-based method for the automatic design of more efficient turbine blades. An Artificial Neural Network (ANN) is used to construct an approximate model (response surface) using a database containing Navier-Stokes solutions for all previous designs. This approximate model is used for the optimization, by means of Simulated Annealing (SA), of the blade geometry, which is then analyzed by a Navier-Stokes solver. This procedure results in a considerable speed-up of the design process by reducing both the interventions of the operator and the computational effort. It is also shown how such a method allows the design of more efficient blades while satisfying both the aerodynamic and mechanical constraints. The method has been applied to different types of two-dimensional turbine blades, of which three examples are presented in this paper.

Abstract: An ultrasonic clamp coagulator assembly embodying the principles of the present invention is configured to permit selective cutting, coagulation, and clamping of tissue during surgical procedures. In an ultrasonic blade according to the present invention, the blade is constructed such that the cross-sectional area of the blade is smaller at the proximal end of the compression zone than at the distal end. This performance-enhancing feature creates a more consistent cutting and coagulation of the tissue along the length of the blade reducing the time the blade is in operation and reducing overall heat generation.

Abstract: Previous studies of the Rushton turbine have shown that the power number is sensitive to the details of impeller geometry, and in particular to the blade thickness, but is independent of the impeller diameter to tank diameter ratio. In this paper, a similar study is reported for the pitched blade impeller. The results show that the power number is independent of blade thickness, but dependent on the impeller to tank diameter ratio. This is exactly the opposite result to that observed for the Rushton turbine. Physical explanations are given for the differences in behaviour between the two impellers. For the Rushton turbine, power consumption is dominated by form drag, so details of the blade geometry and flow separation have a significant impact (30%) on the power number. For the pitched blade impeller, form drag is not as important, but the flow at the impeller interacts strongly with the proximity of the tank walls, so changes in the position of the impeller in the tank can have a significant impact on the power number.