Gradient and curvilinear coordinates

In summary, the goal is to show that the gradient is orthogonal to the other two partial derivatives, and the expression can be written as a sum involving the unit vectors and the partial derivatives of the generalized coordinates. By substituting the expression for the partial derivative of the position vector, it can be simplified to the partial derivative of the generalized coordinate with respect to itself, which is 1 for when the indices are the same and 0 when they are different. This is because the partial derivative is defined such that the other generalized coordinates are held constant.
  • #1
Incand
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Homework Statement


Show that ##\nabla u_i \cdot \frac{\partial \vec r}{\partial u_i} = \delta_{ij}##.

(##u_i## is assumed to be a generalized coordinate.)

Homework Equations


Gradient in curvilinear coordinates
##\nabla \phi = \sum_{i=1}^3 \vec e_i \frac{1}{h_i} \frac{\partial \phi}{\partial u_i}##

The Attempt at a Solution


So what I need to show is that the gradient is orthogonal to the (other two) partial derivatives (but it doesn't have to be parallel to the third since the system doesn't have to be orthogonal!).
The expression can then be written as
##\sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k} \frac{\partial u_i}{\partial u_k} \right) \cdot \frac{\partial \vec r}{\partial u_j} = \sum_{k=1}^3 \frac{1}{h_k}\frac{\partial u_i}{\partial u_k}\frac{\partial r_k}{\partial u_j} ##.
I'm thinking I could use the chain rule here but I don't seem to get anywhere. Another thing of note is that ##\frac{1}{h_k}\frac{\partial \vec r}{\partial u_k} = \vec e_k## which may be of use somewhere.
 
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  • #2
You can substitue ##\partial \vec{r}/\partial u_j = h_j \vec{e}_j## in your expression.
 
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  • #3
fzero said:
You can substitue ##\partial \vec{r}/\partial u_j = h_j \vec{e}_j## in your expression.
Thanks!
##\sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k}\frac{\partial u_i}{\partial u_k} \right) \cdot \frac{h_j}{h_j} \frac{\partial \vec r}{\partial u_j} = \sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k}\frac{\partial u_i}{\partial u_k} \right) \cdot h_j \vec e_j = \frac{\partial u_i}{\partial u_j}##.
Which is obviously ##1## for ##i=j## but how do I know that it's zero when ##i\ne j##? For me this isn't obvious. In a cylindrical coordinate system the unit vector ##\hat \rho## is dependent on ##\hat \phi## and the other way around so I don't see why the coordinates them self can't be dependent.
 
  • #4
Incand said:
Thanks!
##\sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k}\frac{\partial u_i}{\partial u_k} \right) \cdot \frac{h_j}{h_j} \frac{\partial \vec r}{\partial u_j} = \sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k}\frac{\partial u_i}{\partial u_k} \right) \cdot h_j \vec e_j = \frac{\partial u_i}{\partial u_j}##.
Which is obviously ##1## for ##i=j## but how do I know that it's zero when ##i\ne j##? For me this isn't obvious. In a cylindrical coordinate system the unit vector ##\hat \rho## is dependent on ##\hat \phi## and the other way around so I don't see why the coordinates them self can't be dependent.

The partial derivative ##\partial/\partial u_j## is defined so that ##u_{i\neq j}## are treated as constants for the purpose of taking the derivative.
 
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  • #5
fzero said:
The partial derivative ##\partial/\partial u_j## is defined so that ##u_{i\neq j}## are treated as constants for the purpose of taking the derivative.
Right, I wasn't thinking clearly, Thanks!
 

Related to Gradient and curvilinear coordinates

1. What is the difference between gradient and curvilinear coordinates?

Gradient coordinates are a type of cartesian coordinates, where the axes are perpendicular to each other and remain constant throughout space. Curvilinear coordinates, on the other hand, are a type of non-cartesian coordinates where the axes can be curved and vary in magnitude and direction throughout space.

2. How are gradient and curvilinear coordinates used in physics and engineering?

Gradient coordinates are commonly used to describe physical quantities such as force, velocity, and acceleration in a constant direction. Curvilinear coordinates, on the other hand, are useful in describing the motion of objects in non-uniformly curved spaces, such as the Earth's surface.

3. What are some examples of gradient and curvilinear coordinates?

Some common examples of gradient coordinates include the Cartesian (x, y, z) coordinates, cylindrical coordinates (r, θ, z), and spherical coordinates (r, θ, φ). Examples of curvilinear coordinates include polar coordinates (r, θ), elliptic coordinates (u, v), and parabolic coordinates (η, χ).

4. How are gradients and curvilinear coordinates related?

Gradients can be used to describe the rate of change of a function in any coordinate system, including curvilinear coordinates. In fact, the gradient in curvilinear coordinates is often expressed using a set of partial differential equations, known as the covariant derivative, which takes into account the varying axes and their derivatives.

5. What are some applications of using gradient and curvilinear coordinates?

Gradient and curvilinear coordinates are used in many fields, including physics, engineering, and computer graphics. They are particularly useful in solving problems involving motion and forces in non-uniformly curved spaces, such as fluid dynamics, electromagnetism, and general relativity.

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