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Each packing problem has a dual covering problem, which asks how many of the same objects are required to completely cover every region of the container, where objects are allowed to overlap. In a bin packing problem, people are given: A container, usually a two- or three-dimensional convex region, possibly of infinite size. Multiple containers ...
Python supports most object oriented programming (OOP) techniques. It allows polymorphism, not only within a class hierarchy but also by duck typing. Any object can be used for any type, and it will work so long as it has the proper methods and attributes. And everything in Python is an object, including classes, functions, numbers and modules.
Blood flow in brain ~ 1 × 10 2; Blood flow in aorta ~ 1 × 10 3; Onset of turbulent flow ~ 2.3 × 10 3 to 5.0 × 10 4 for pipe flow to 10 6 for boundary layers; Typical pitch in Major League Baseball ~ 2 × 10 5; Person swimming ~ 4 × 10 6; Fastest fish ~ 1 × 10 8; Blue whale ~ 4 × 10 8; A large ship (Queen Elizabeth 2) ~ 5 × 10 9 ...
When the smaller sphere has a radius greater than 0.41421 of the radius of the larger sphere, it is no longer possible to fit into even the octahedral holes of the close-packed structure. Thus, beyond this point, either the host structure must expand to accommodate the interstitials (which compromises the overall density), or rearrange into a ...
An object immersed in a liquid displaces an amount of fluid equal to the object's volume. Thus, buoyancy is expressed through Archimedes' principle, which states that the weight of the object is reduced by its volume multiplied by the density of the fluid. If the weight of the object is less than this displaced quantity, the object floats; if ...
The volume flux, through a tube bounded by a surface of some constant value ψ, is equal to 2πψ and is constant. [9] For this case of an axisymmetric flow, the only non-zero component of the vorticity vector ω is the azimuthal φ –component ω φ [11] [12]
A simple example is fitting a line in two dimensions to a set of observations. Assuming that this set contains both inliers, i.e., points which approximately can be fitted to a line, and outliers, points which cannot be fitted to this line, a simple least squares method for line fitting will generally produce a line with a bad fit to the data including inliers and outliers.
Depending on the type of surrogate used and the complexity of the problem, the process may converge on a local or global optimum, or perhaps none at all. [9] In design space approximation, one is not interested in finding the optimal parameter vector, but rather in the global behavior of the system.