Calculating direction derivative to a line in 2D

In summary, the question is asking for the computation of ##\partial_n f## where ##n## is normal to ##f##. The curve ##f## lies in the ##x-z## plane and is parameterized by ##x(s) = \frac{1}{c} \sin (c s)## and ##z(s) = \frac{1}{c} (1-\cos (c s))##. The solution involves defining a vector ##\hat f \equiv x(s) \hat i + z(s) \hat k## and finding the unit normal vector ##\hat n## to the surface using the rotational matrix. Then the computation of ##\partial_n f## is done using ##\n
  • #1
member 428835

Homework Statement


Compute ##\partial_n f## where ##n## is normal to ##f##, and ##f## lies in the ##x-z## plane and is parameterized by $$x(s) = \frac{1}{c} \sin (c s);\\
z(s) = \frac{1}{c} (1-\cos (c s))
$$

Homework Equations


##\partial_n f = \nabla f \cdot \hat n##

The Attempt at a Solution


I was thinking of defining vector ##\hat f \equiv x(s) \hat i + z(s) \hat k##. Then tangent would be ##\hat f '(s)##. Now rotate this by ##90^\circ##. We know $$
\begin{bmatrix}
\cos\theta & -\sin \theta\\
\sin\theta & \cos \theta\\
\end{bmatrix}$$
is the rotational matrix where ##\theta = 90^\circ##. Thus the unit normal ##\hat n## to the surface would be $$\hat n = \frac{z'(s) \hat i - x'(s) \hat k}{\sqrt{z'(s)^2+x'(s)^2}}$$
Once we have ##\hat n##, we should be able to construct ##\partial_n f## via ##\nabla f \cdot \hat n##, where I assume ##\nabla f = x'(s) \hat i + z'(s) \hat k##. Then $$
\partial_n f = \frac{z'(s)x'(s) - x'(s)z'(s) }{\sqrt{z'(s)^2+x'(s)^2}} = 0
$$
I think I went wrong in computing ##\nabla f##. Can someone help?
 
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  • #2
joshmccraney said:
Then tangent would be ##\hat f '(s)##.
Why? s is only a parameter. It has no physical meaning in the shape of the curve.

By the way, it is not clear to me whether the answer is expected in terms of x and z or in terms of s.
 
  • #3
haruspex said:
Why? s is only a parameter. It has no physical meaning in the shape of the curve.
I'm not sure, but I know this is correct. I should specify that ##s## is said to be the arclength.
haruspex said:
By the way, it is not clear to me whether the answer is expected in terms of x and z or in terms of s.
I'd like the answer as a function of ##s##, as I'll have to integrate w.r.t ##s##.
 
  • #4
I think I may have misunderstood the question...
Is f a curve in the XZ plane or a function of x and z?
 
  • #5
What is ##f##?
 
  • #6
Oh shoot, thank you both for responding! Okay, by asking the question you've given me the answer! I need to compute ##\int_s \partial_n\phi(x,z)## along a curve in the ##x-z## plane, where ##x = x(s)## and ##z=z(s)##. Since I have an explicit formula for ##\phi(x,z)##, all I need is ##\nabla \phi \cdot \hat n##, where ##\hat n## is above in post 1.
 

FAQ: Calculating direction derivative to a line in 2D

What is the formula for calculating the direction derivative to a line in 2D?

The formula for calculating the direction derivative to a line in 2D is:
d/dt[f(x,y)] = [fx(x,y) * dx/dt] + [fy(x,y) * dy/dt],
where fx(x,y) and fy(x,y) are the partial derivatives of f(x,y) with respect to x and y, and dx/dt and dy/dt are the derivatives of the line's x and y components with respect to t, respectively.

What does the direction derivative to a line in 2D represent?

The direction derivative to a line in 2D represents the rate of change of a function along a specific direction on a 2D plane. It measures how quickly the function changes in the direction of the line at a given point.

How is the direction derivative to a line in 2D used in real-world applications?

The direction derivative to a line in 2D is commonly used in physics and engineering to analyze the motion of objects. It is also used in mathematics to optimize functions and find critical points.

Can the direction derivative to a line in 2D be negative?

Yes, the direction derivative to a line in 2D can be negative. A negative direction derivative indicates that the function is decreasing in the direction of the line, while a positive direction derivative indicates that the function is increasing.

Is the direction derivative to a line in 2D affected by the slope of the line?

Yes, the direction derivative to a line in 2D is affected by the slope of the line. The steeper the slope, the greater the rate of change of the function in the direction of the line. This means that a line with a steeper slope will have a higher direction derivative compared to a line with a shallower slope, assuming all other factors remain constant.

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