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John Neulinger (April 26, 1924 - June 20, 1991) was a German-American psychologist and Professor Emeritus of psychology at City College of New York.Neulinger is best known for contributing a social psychological theory of leisure to the field of leisure studies. [1]
A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, [1] [2] [3] which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.
In queueing theory, a discipline within the mathematical theory of probability, a fluid queue (fluid model, [1] fluid flow model [2] or stochastic fluid model [3]) is a mathematical model used to describe the fluid level in a reservoir subject to randomly determined periods of filling and emptying.
This simple model is the basis for the "law of the wall", which is a surprisingly accurate model for wall-bounded, attached (not separated) flow fields with small pressure gradients. More general turbulence models have evolved over time, with most modern turbulence models given by field equations similar to the Navier–Stokes equations .
The one-dimensional (1-D) Saint-Venant equations were derived by Adhémar Jean Claude Barré de Saint-Venant, and are commonly used to model transient open-channel flow and surface runoff. They can be viewed as a contraction of the two-dimensional (2-D) shallow-water equations, which are also known as the two-dimensional Saint-Venant equations.
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In fluid dynamics, the Buckley–Leverett equation is a conservation equation used to model two-phase flow in porous media. [1] The Buckley–Leverett equation or the Buckley–Leverett displacement describes an immiscible displacement process, such as the displacement of oil by water, in a one-dimensional or quasi-one-dimensional reservoir.
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