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  2. Potential gradient - Wikipedia

    en.wikipedia.org/wiki/Potential_gradient

    The simplest definition for a potential gradient F in one dimension is the following: [1] = = where ϕ(x) is some type of scalar potential and x is displacement (not distance) in the x direction, the subscripts label two different positions x 1, x 2, and potentials at those points, ϕ 1 = ϕ(x 1), ϕ 2 = ϕ(x 2).

  3. Gran plot - Wikipedia

    en.wikipedia.org/wiki/Gran_plot

    The Gran plot is based on the Nernst equation which can be written as = + ⁡ {+} where E is a measured electrode potential, E 0 is a standard electrode potential, s is the slope, ideally equal to RT/nF, and {H +} is the activity of the hydrogen ion.

  4. Gradient - Wikipedia

    en.wikipedia.org/wiki/Gradient

    The gradient of a function is called a gradient field. A (continuous) gradient field is always a conservative vector field: its line integral along any path depends only on the endpoints of the path, and can be evaluated by the gradient theorem (the fundamental theorem of calculus for line integrals). Conversely, a (continuous) conservative ...

  5. Vector calculus identities - Wikipedia

    en.wikipedia.org/wiki/Vector_calculus_identities

    In Cartesian coordinates, the divergence of a continuously differentiable vector field = + + is the scalar-valued function: ⁡ = = (, , ) (, , ) = + +.. As the name implies, the divergence is a (local) measure of the degree to which vectors in the field diverge.

  6. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Log–log_plot

    In science and engineering, a log–log graph or log–log plot is a two-dimensional graph of numerical data that uses logarithmic scales on both the horizontal and vertical axes. Power functions – relationships of the form y = a x k {\displaystyle y=ax^{k}} – appear as straight lines in a log–log graph, with the exponent corresponding to ...

  7. Newton's method in optimization - Wikipedia

    en.wikipedia.org/wiki/Newton's_method_in...

    The geometric interpretation of Newton's method is that at each iteration, it amounts to the fitting of a parabola to the graph of () at the trial value , having the same slope and curvature as the graph at that point, and then proceeding to the maximum or minimum of that parabola (in higher dimensions, this may also be a saddle point), see below.

  8. Prandtl–Glauert transformation - Wikipedia

    en.wikipedia.org/wiki/Prandtl–Glauert...

    Plot of the inverse Prandtl–Glauert factor / as a function of freestream Mach number. Notice the infinite limit at Mach 1. Notice the infinite limit at Mach 1. Inviscid compressible flow over slender bodies is governed by linearized compressible small-disturbance potential equation: [ 1 ]

  9. Hazen–Williams equation - Wikipedia

    en.wikipedia.org/wiki/Hazen–Williams_equation

    S is the slope of the energy line (head loss per length of pipe or h f /L) The equation is similar to the Chézy formula but the exponents have been adjusted to better fit data from typical engineering situations. A result of adjusting the exponents is that the value of C appears more like a constant over a wide range of the other parameters. [8]

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