Directional Derivatives and max rate of change

In summary, the conversation is discussing the maximum rate of change and directional derivative of a function and how to calculate it using the gradient and unit vectors. Part (b) involves finding the direction of maximum rate of change in the direction of a given vector, and the conversation discusses the process of solving for this direction using the gradient of the function and a unit vector in the given direction. There may be some missing information or potential simplifications in the given problem.
  • #1
Blkmage
11
0

Homework Statement



See attachment.

2. Homework Equations /solution attempt

Part (a)
Well, the gradient evaluated at (1,2-1) will give the rate of change. If we want the maximum rate of change then we need the directional direction such that the unit vector [tex]\mathbf{u}[/tex] is in the same direction as [tex]\nabla f(1,2,-1)[/tex]. So the unit vector would just be [tex]\frac{\nabla f(1,2,-1)}{\text{norm}(\nabla f(1,2,-1))}[/tex]? And the max rate of change is just the direction derivative at this point and direction?

Anyways, part (b) is what I'm having trouble with:

Since we want it to be in the direction of the vector (1,-1,-1), does that mean that we want [tex]\nabla g(x_{Q},y_{Q},z_{Q}) = (1,-1,-1)[/tex]? Since (1,-1,-1) isn't a unit vector, I didn't divide by the norm of the gradient...
 

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  • #2
the gradient gives the direction of maximum rate of change, its magnitude is the rate of change moving along that direction

the magnitude of the gradient is equivalent to a dot product with a unit vector in the same direction, ie the value of the directional derivative in that direction
 
  • #3
So for part (b), we have

[tex]\text{norm}(\nabla g(x_{Q},y_{Q},z_{Q})) = \nabla g(x_{Q},y_{Q},z_{Q}) \cdot \frac{1}{\sqrt{3}}\left(1,-1,-1\right)[/tex]

This seems so tedious to solve though. It's on a practice exam my teacher gave us and his tests are very reasonable given the time limits, so I'm guessing there is something I'm missing?

edit: not to mention that would give me a single equation of 3 variables, which I wouldn't be able to solve
 
  • #4
[tex]g(x,y,z) = x^2yz [/tex]
[tex]\nabla g(x,y,z) = (2xyz, x^2z, x^2y) [/tex]

and you want to know when is in the direction (1,-1,-1), first clearly this will not be possible if any of the varibales are 0 as it will lead tio .

substituting in gives
2xyz = -x^2z _______(1)
2xyz = -x^2y _______(2)
x^2z = x^2y _______(3)

so you know y=z from (3), as x dne 0, which should simplify things
 

What is a directional derivative?

A directional derivative is a measure of the rate at which a function changes in a specific direction. It is used to determine the slope of a function along a given direction.

How is the directional derivative calculated?

The directional derivative is calculated using the gradient of the function and the unit vector in the desired direction. It is the dot product of the gradient and the unit vector.

What is the significance of the directional derivative?

The directional derivative helps in finding the maximum rate of change of a function in a given direction. It is also useful in optimization problems where we want to find the direction in which the function increases or decreases the most.

How is the maximum rate of change related to directional derivative?

The maximum rate of change is equal to the magnitude of the directional derivative. In other words, the maximum rate of change is the largest possible value of the directional derivative in a given direction.

What are some real-world applications of directional derivatives and maximum rate of change?

Directional derivatives and maximum rate of change are used in fields such as physics, engineering, and economics to analyze the behavior of systems and optimize processes. They are also used in computer graphics to create realistic lighting effects.

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