Find Directional Derivative at Given Point in Direction of Given Vector

In summary, the directional derivative of the function g(s,t)=s√t at the point (2,4) in the direction of the vector v=2i−j is 7/(2√5). The dot product of the gradient vector and the directional vector is 5/(2√5), but the correct answer is 7/(2√5) after taking into account the denominator in the second fraction.
  • #1
betamu
12
3

Homework Statement


[/B]
Find the directional derivative of the function at the given point in the direction of the vector v.

$$g(s,t)=s\sqrt t, (2,4), \vec{v}=2\hat{i} - \hat{j}$$

Homework Equations



$$\nabla g(s,t) = <g_s(s,t), g_t(s,t)>\\
\vec{u} = \vec{v}/|\vec{v}|\\
D_u g(s,t) = \nabla g(s, t) \cdot \vec{u}$$

The Attempt at a Solution


I found $$\nabla g(s, t) =<\sqrt{t}, s/(2\sqrt{t})>$$ which gives $$\nabla g(2,4) = <2, 1/2>$$ and the directional vector to be $$<2/\sqrt{5}, -1/\sqrt{5}>$$ Which gives a dot product of $$5/2\sqrt{5}$$ but my book says that it should be $$7/2\sqrt{5}$$.
 
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  • #2
betamu said:

Homework Statement


[/B]
Find the directional derivative of the function at the given point in the direction of the vector v.

$$g(s,t)=s\sqrt t, (2,4), \vec{v}=2\hat{i} - \hat{j}$$

Homework Equations



$$\nabla g(s,t) = <g_s(s,t), g_t(s,t)>\\
\vec{u} = \vec{v}/|\vec{v}|\\
D_u g(s,t) = \nabla g(s, t) \cdot \vec{u}$$

The Attempt at a Solution


I found $$\nabla g(s, t) =<\sqrt{t}, s/(2\sqrt{t})>$$ which gives $$\nabla g(2,4) = <2, 1/2>$$ and the directional vector to be $$<2/\sqrt{5}, -1/\sqrt{5}>$$ Which gives a dot product of $$5/2\sqrt{5}$$ but my book says that it should be $$7/2\sqrt{5}$$.
What is ##\langle (2,1/2)\,,\,(2,-1)\rangle \,?##
 
  • #3
betamu said:

Homework Statement


[/B]
Find the directional derivative of the function at the given point in the direction of the vector v.

$$g(s,t)=s\sqrt t, (2,4), \vec{v}=2\hat{i} - \hat{j}$$

Homework Equations



$$\nabla g(s,t) = <g_s(s,t), g_t(s,t)>\\
\vec{u} = \vec{v}/|\vec{v}|\\
D_u g(s,t) = \nabla g(s, t) \cdot \vec{u}$$

The Attempt at a Solution


I found $$\nabla g(s, t) =<\sqrt{t}, s/(2\sqrt{t})>$$ which gives $$\nabla g(2,4) = <2, 1/2>$$ and the directional vector to be $$<2/\sqrt{5}, -1/\sqrt{5}>$$ Which gives a dot product of $$5/2\sqrt{5}$$
Check your work on the dot product. I think you missed that the second fraction has a 2 in the denominator.
betamu said:
but my book says that it should be $$7/2\sqrt{5}$$.
I get this, as well, but it should be written as ##.7/(2\sqrt{5})## or better, as $$\frac 7 {2\sqrt 5}$$
 
  • #4
fresh_42 said:
What is ##\langle (2,1/2)\,,\,(2,-1)\rangle \,?##
I'm unsure what you mean. You're putting the gradient vector and v into one vector together?
 
  • #5
Mark44 said:
Check your work on the dot product. I think you missed that the second fraction has a 2 in the denominator. I get this, as well, but it should be written as ##.7/(2\sqrt{5})## or better, as $$\frac 7 {2\sqrt 5}$$
Haha wow. Yeah you're right. Well at least I gained some experience in writing out latex code in posting this. Thanks!
 
  • #6
betamu said:
I'm unsure what you mean. You're putting the gradient vector and v into one vector together?
Yes, it is ##\nabla f \cdot \vec{v}##, I simply left out the norm ##\sqrt{5}## since your mistake was the dot product, not the factor.
 
  • #7
betamu said:
I'm unsure what you mean. You're putting the gradient vector and v into one vector together?
That should be the dot product of two vectors. fresh_42's notation might be for the inner product, a generalization of the dot product.
 
  • #8
Oh alright, I'd never seen that notation before. Thank you both!
 

1. What is a directional derivative?

A directional derivative is a measure of the rate at which a function changes with respect to a particular direction or vector in space. It gives information about how a function changes as you move along a specific direction in space.

2. How is a directional derivative calculated?

The directional derivative is calculated by taking the dot product of the gradient of the function and the unit vector in the direction of interest. This can be represented mathematically as Duf(x,y) = ∇f(x,y) · u, where ∇f(x,y) is the gradient of the function and u is the unit vector in the desired direction.

3. What is the significance of the directional derivative?

The directional derivative is useful in understanding the behavior of a function at a specific point in space. It gives information about the rate of change of the function in a particular direction, which can be helpful in optimization problems, determining the slope of a surface, and predicting the movement of a particle in a field.

4. Can the directional derivative be negative?

Yes, the directional derivative can be negative. The sign of the directional derivative depends on the angle between the gradient vector and the direction of interest. If the angle is obtuse, the directional derivative will be negative, indicating that the function is decreasing in that direction.

5. How is the directional derivative used in real-life applications?

The directional derivative has many real-life applications, such as in physics, engineering, and economics. It is used to analyze the behavior of various systems and predict their future state. For example, it can be used to calculate the rate of change of temperature in a specific direction in a heat transfer problem or to determine the rate of change of cost in a business optimization problem.

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