Potential flowIn fluid dynamics, potential flow (or ideal flow) describes the velocity field as the gradient of a scalar function: the velocity potential. As a result, a potential flow is characterized by an irrotational velocity field, which is a valid approximation for several applications. The irrotationality of a potential flow is due to the curl of the gradient of a scalar always being equal to zero. In the case of an incompressible flow the velocity potential satisfies Laplace's equation, and potential theory is applicable.
Boundary layer thicknessThis page describes some of the parameters used to characterize the thickness and shape of boundary layers formed by fluid flowing along a solid surface. The defining characteristic of boundary layer flow is that at the solid walls, the fluid's velocity is reduced to zero. The boundary layer refers to the thin transition layer between the wall and the bulk fluid flow. The boundary layer concept was originally developed by Ludwig Prandtl and is broadly classified into two types, bounded and unbounded.
WindmillA windmill is a structure that converts wind power into rotational energy using vanes called sails or blades, by tradition specifically to mill grain (gristmills), but in some parts of the English-speaking world the term has also been extended to encompass windpumps, wind turbines, and other applications. The term wind engine is also sometimes used to describe such devices. Windmills were used throughout the high medieval and early modern periods; the horizontal or panemone windmill first appeared in Persia during the 9th century, and the vertical windmill first appeared in northwestern Europe in the 12th century.
Image momentIn , computer vision and related fields, an image moment is a certain particular weighted average (moment) of the image pixels' intensities, or a function of such moments, usually chosen to have some attractive property or interpretation. Image moments are useful to describe objects after . Simple properties of the image which are found via image moments include area (or total intensity), its centroid, and information about its orientation. For a 2D continuous function f(x,y) the moment (sometimes called "raw moment") of order (p + q) is defined as for p,q = 0,1,2,.
