Understanding the RK Derivation Intuitively

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In summary, the RK derivation shows that the second derivative of a function y is equal to the sum of the two partial derivatives of the function f with respect to t and y, multiplied by the first derivative of y. This is derived using the total derivative of a differentiable function g and the relationship between the first and second derivatives of a function y.
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bangthatdrum
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Im looking at the RK derivation and as part of that I know it is the case that:

y'' = partial f / partial x + partial f / partial y * y'

But at an intuitive level I cannnot understand why. How does the second derivative equal the sum of the two partial derivatives times the first?
 
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Please ignore this.
 
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Numerical initial value techniques such as Runge-Kutta address the problem of approximating y(t) where the value of y(t) is known at some initial point t0 and where time derivative of y(t) is a function of the variable of interest and time:

[tex]\aligned
y'(t) &\equiv \frac{dy(t)}{dt} = f(t,y(t)) \\[4pt]
y(t_0) &= y_0
\endaligned[/tex]


Suppose some function g(t,y) is a differentiable function of t and y, by which I mean that the partial derivatives of g with respect to t and to y exist at all points where g is defined. Now suppose that y is a function of t. The total derivative of g with respect to t is given by

[tex]\frac{dg(t,y(t))}{dt} = \frac{\partial g(t,y)}{\partial t} + \frac{\partial g(t,y)}{\partial y}\frac{dy}{dt}[/tex]

With this, the second time derivative of y is

[tex]y''(t) = \frac{dy'}{dt} = \frac{df(t,y(t))}{dt} = \frac{\partial f(t,y)}{\partial t} + \frac{\partial f(t,y)}{\partial y}\frac{dy}{dt}[/tex]

But we already know dy/dt: It is f(t,y). Thus

[tex]y''(t) = \frac{\partial f(t,y)}{\partial t} + \frac{\partial f(t,y)}{\partial y}f(t,y)[/tex]
 
  • #4


bangthatdrum said:
Please ignore this.
Too late.
 
  • #5


Thank you D H. This is wonderful.
 

FAQ: Understanding the RK Derivation Intuitively

What is the RK Derivation?

The RK Derivation, also known as the Runge-Kutta Derivation, is a method used to solve ordinary differential equations numerically. It is a mathematical algorithm that approximates the solution to a differential equation by breaking it down into smaller steps.

How does the RK Derivation work?

The RK Derivation works by using a set of equations to calculate the slope of the solution at different points. It then uses this slope to estimate the value of the solution at the next point. This process is repeated until the desired accuracy is achieved.

What is the intuition behind the RK Derivation?

The RK Derivation is based on the idea of using a weighted average of several estimates of the slope at each step. This allows for a more accurate approximation of the solution compared to using only one estimate of the slope.

What are the advantages of using the RK Derivation?

The RK Derivation is a versatile method that can be used for a wide range of differential equations. It also offers a high degree of accuracy and stability, making it a popular choice for solving differential equations numerically.

Are there any limitations to the RK Derivation?

While the RK Derivation is a powerful method, it can become computationally expensive for complex differential equations. It also relies on the accuracy of the initial conditions and may not be suitable for stiff equations where the solution changes rapidly.

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