Calculating Gradient of u(r,θ)

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In summary, the conversation discusses finding the gradient of a scalar field in spherical coordinates, specifically for the function $u(r, \theta) = r\cos(\theta)\left[1 - \left(\frac{1}{r}\right)^2\right]$. It is obtained by calculating the partial derivatives and converting them into Cartesian coordinates. An alternative method is suggested, which involves switching the function to be in terms of Cartesian coordinates.
  • #1
Dustinsfl
2,281
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I have
$$
u(r,\theta) = r\cos(\theta)\left[1 - \left(\frac{1}{r}\right)^2\right]
$$
and the gradient is
$$
1 + \frac{2 x^2}{(x^2 + y^2)^2} - \frac{1}{x^2 + y^2}, \frac{2 x y}{(x^2 + y^2)^2}
$$
How was this obtained?
 
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  • #2
dwsmith said:
I have
$$
u(r,\theta) = r\cos(\theta)\left[1 - \left(\frac{1}{r}\right)^2\right]
$$
and the gradient is
$$
1 + \frac{2 x^2}{(x^2 + y^2)^2} - \frac{1}{x^2 + y^2}, \frac{2 x y}{(x^2 + y^2)^2}
$$
How was this obtained?

Hi dwsmith, :)

The gradient of a scalar field \(f\) in spherical coordinates is given by,

\[\nabla f(r, \theta, \phi) = \frac{\partial f}{\partial r}\mathbf{e}_r+\frac{1}{r}\frac{\partial f}{\partial \theta}\mathbf{e}_\theta+\frac{1}{r \sin\theta}\frac{\partial f}{\partial \phi}\mathbf{e}_\phi=\left(\frac{\partial f}{\partial r},\,\frac{1}{r}\frac{\partial f}{\partial \theta},\,\frac{1}{r \sin\theta}\frac{\partial f}{\partial \phi}\right)\]

Therefore,

\[\nabla u(r, \theta)=\left(\frac{\partial u}{\partial r},\,\frac{1}{r}\frac{\partial u}{\partial \theta},\,0\right)\]

Calculate the partial derivatives and convert them into Cartesian coordinates. Hope you can continue.

Kind Regards,
Sudharaka.
 
  • #3
Probably the easiest way is to switch u in terms of x and y, $\it{ i.e.}$

$u = x \left( 1 - \dfrac{1}{x^2+y^2}\right)$,

then calculate the gradient the usual way.
 

Related to Calculating Gradient of u(r,θ)

What is the concept of gradient in the context of u(r,θ)?

Gradient is a mathematical concept that represents the rate of change of a function with respect to its variables. In the context of u(r,θ), gradient measures how the function changes as we move in the directions of r and θ.

How is the gradient of u(r,θ) calculated?

The gradient of u(r,θ) is calculated using partial derivatives. For a function with two variables, r and θ, the gradient is calculated as the vector [∂u/∂r, (1/r)∂u/∂θ].

What is the physical significance of calculating gradient in u(r,θ)?

Calculating gradient in u(r,θ) is important in various scientific fields, such as physics and engineering. It helps us understand how a physical quantity, represented by u(r,θ), changes in different directions, which is crucial for predicting and analyzing phenomena.

How does the value of gradient affect the behavior of u(r,θ)?

The value of gradient affects the behavior of u(r,θ) in the sense that it determines the direction and magnitude of the steepest change in the function. A larger gradient indicates a steeper change, while a smaller gradient indicates a gentler change.

Can the gradient of u(r,θ) be negative?

Yes, the gradient of u(r,θ) can be negative. This indicates that the function is decreasing in the direction of the gradient. However, the magnitude of the gradient is more important than its sign, as it determines the rate of change in a specific direction.

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