Some vector calculus questions

In summary: I'm still not sure where to go from there... I'll keep thinking on it though.Thanks!In summary, the problem asks for the gradient of a given height function and the maximum slope at a specific point. It also asks for the slope of a path in a certain direction and for a vector in that direction that remains at the same height. To find the vector, one can use the first order approximation of the change in height with respect to small changes in x and y.
  • #1
sa1988
222
23

Homework Statement



2. The shape of a hill is described by the height function h(x,y) = (2 + x2 + y4)-1/2

(a) Find the gradient ∇h(x,y)

(b) What is the maximum slope of the hill at the point r0 = i+j [or (x,y) = (1,1)]?

(c) If you walk north-east (in the direction of the vector i+j) from the point r0, what
is the slope of your path? Are you going uphill or downhill?

(d) Find a vector in the direction of a path through the point r0 that remains at the
same height.

Homework Equations

The Attempt at a Solution



For parts a), b) and c) I think I'm okay.

a) ∇h(x,y) = ([-x(2 + x2 + y4)-3/2], [-y3(2 + x2 + y4)-3/2])

b) At point (1,1) just plug x and y into ∇h(x,y) to get (-1/8 , -1/4)

c) Along path of vector (i+j) you will be going in a downhill direction since it is in a direction 'away' from the maximum slope found in the previous question. But is there a way I can mathematically prove this?

d) This is the part I'm unsure of. It's been a while since I did work with vectors. I'm guessing I need to find a vector such that infinitesimal change in the x-y direction gives no change in height. So that would mean d(h(x,y)) = 0...? Since this would signify no change in the value of h(x,y). Overall I'm a bit lost.

Thanks.
 
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  • #2
sa1988 said:

Homework Statement



2. The shape of a hill is described by the height function h(x,y) = (2 + x2 + y4)-1/2

(a) Find the gradient ∇h(x,y)

(b) What is the maximum slope of the hill at the point r0 = i+j [or (x,y) = (1,1)]?

(c) If you walk north-east (in the direction of the vector i+j) from the point r0, what
is the slope of your path? Are you going uphill or downhill?

(d) Find a vector in the direction of a path through the point r0 that remains at the
same height.

Homework Equations

The Attempt at a Solution



For parts a), b) and c) I think I'm okay.

a) ∇h(x,y) = ([-x(2 + x2 + y4)-3/2], [-y3(2 + x2 + y4)-3/2])


You might want to recheck your calculation of ∂h / ∂y.
 
  • #3
SteamKing said:

You might want to recheck your calculation of ∂h / ∂y.
Sorry, typo... should be -2y3 there.
 
  • #4
sa1988 said:
Sorry, typo... should be -2y3 there.
Good. Recalculate your results from that point on.
 
  • #5
SteamKing said:
Good. Recalculate your results from that point on.

No need. I'll get the same result. I've already done all of this on paper.The mistake you saw was purely a typing error.

The only bit I'm stumped on is part d)
 
  • #6
sa1988 said:

Homework Statement



2. The shape of a hill is described by the height function h(x,y) = (2 + x2 + y4)-1/2

(a) Find the gradient ∇h(x,y)

(b) What is the maximum slope of the hill at the point r0 = i+j [or (x,y) = (1,1)]?

(c) If you walk north-east (in the direction of the vector i+j) from the point r0, what
is the slope of your path? Are you going uphill or downhill?

(d) Find a vector in the direction of a path through the point r0 that remains at the
same height.

Homework Equations

The Attempt at a Solution



For parts a), b) and c) I think I'm okay.

a) ∇h(x,y) = ([-x(2 + x2 + y4)-3/2], [-y3(2 + x2 + y4)-3/2])

b) At point (1,1) just plug x and y into ∇h(x,y) to get (-1/8 , -1/4)

c) Along path of vector (i+j) you will be going in a downhill direction since it is in a direction 'away' from the maximum slope found in the previous question. But is there a way I can mathematically prove this?

d) This is the part I'm unsure of. It's been a while since I did work with vectors. I'm guessing I need to find a vector such that infinitesimal change in the x-y direction gives no change in height. So that would mean d(h(x,y)) = 0...? Since this would signify no change in the value of h(x,y). Overall I'm a bit lost.

Thanks.

If you go along the surface ##z = h(x,y)## a short distance from a point with ##x\,y## coordinates ##(x_0,y_0)## to a neighboring point with ##x\,y## coordinates ##(x_0+ \Delta x , y_0 + \Delta y)##, the change in "height" ##z## is given as
[tex] \Delta z = h_x(x_0,y_0) \Delta x + h_y(x_0,y_0) \Delta y [/tex]
to first order in the small step sizes ##\Delta x, \Delta y##. Here, ##h_x = \partial h/\partial x## and ##h_y = \partial h/ \partial y##. The equation above is standard Calculus II material.
 
  • #7
Ray Vickson said:
If you go along the surface ##z = h(x,y)## a short distance from a point with ##x\,y## coordinates ##(x_0,y_0)## to a neighboring point with ##x\,y## coordinates ##(x_0+ \Delta x , y_0 + \Delta y)##, the change in "height" ##z## is given as
[tex] \Delta z = h_x(x_0,y_0) \Delta x + h_y(x_0,y_0) \Delta y [/tex]
to first order in the small step sizes ##\Delta x, \Delta y##. Here, ##h_x = \partial h/\partial x## and ##h_y = \partial h/ \partial y##. The equation above is standard Calculus II material.

Sure, I get that, but how does it apply to part d) of the question?

Thanks.
 
  • #8
sa1988 said:
Sure, I get that, but how does it apply to part d) of the question?

Thanks.

PF Rules forbid us from telling you that.
 
  • #9
Ray Vickson said:
PF Rules forbid us from telling you that.

:oldeek: If it's not possible to get even a single nudge in the right direction, then it must mean that single nudge would give the whole answer, so I assume the whole thing must be far easier than I've been anticipating!

For what it's worth, I've actually gone beyond even Calc IV at this point. I'm just rusty with vectors as I took a year out of university.

I'll mull things over and try to see the glaringly obvious thing that I've missed.

Thanks! :oldsmile:
 
  • #10
sa1988 said:
:oldeek: If it's not possible to get even a single nudge in the right direction, then it must mean that single nudge would give the whole answer, so I assume the whole thing must be far easier than I've been anticipating!

For what it's worth, I've actually gone beyond even Calc IV at this point. I'm just rusty with vectors as I took a year out of university.

I'll mull things over and try to see the glaringly obvious thing that I've missed.

Thanks! :oldsmile:

Hint: what is ##\Delta z## when you stay at the same level?
 
  • #11
Ray Vickson said:
Hint: what is ##\Delta z## when you stay at the same level?

Well it's 0, however I have no idea how that relates to finding a vector pointing in a direction such that its change in the z-direction is 0

Intuitively it seems to be that a vector that is orthogonal to ∇h(x,y) will be at that point moving in a direction such that it has no change in z-position.

... which in the case of my given answer would be (1/4 i - 1/8 j ) ...?

However I've done no calculus to get to that, which seems to go against the advice you're giving regarding ##\Delta z## etc. However I did work out ∇h(x,y) and the direction of steepest slope in the previous parts of the question, if that's what you were referring to.
 
  • #12
sa1988 said:
Well it's 0, however I have no idea how that relates to finding a vector pointing in a direction such that its change in the z-direction is 0

Intuitively it seems to be that a vector that is orthogonal to ∇h(x,y) will be at that point moving in a direction such that it has no change in z-position.

... which in the case of my given answer would be (1/4 i - 1/8 j ) ...?

However I've done no calculus to get to that, which seems to go against the advice you're giving regarding ##\Delta z## etc. However I did work out ∇h(x,y) and the direction of steepest slope in the previous parts of the question, if that's what you were referring to.

I don't get why you are having a problem. Saying that ##\Delta z = 0## is saying that ##z## (the height) does not change. And, since we already have a formula for ##\Delta z## in terms of ##\Delta x, \Delta y## and the partial derivatives of ##h(x,y)##, we have everything we need. Of course, that only determines the direction (the ratio of ##\Delta y## to ##\Delta x##) and not the absolute magnitudes of ##\Delta x, \Delta y##, so we are free to "scale" the results however we like.
 
  • #13
Ray Vickson said:
. Of course, that only determines the direction (the ratio of ##\Delta y## to ##\Delta x##) and not the absolute magnitudes of ##\Delta x, \Delta y##, so we are free to "scale" the results however we like.

Sure but does ∇h(x,y) not determine the direction of x and y such that the resultant vector is pointing in the direction of the steepest slope at that point of the function? Whereas my challenge is to find the vector which has no steepness at that point. Hence me intuitively suggesting it must be orthogonal to the gradient vector. Was I wrong?

Thanks
 
  • #14
sa1988 said:
Sure but does ∇h(x,y) not determine the direction of x and y such that the resultant vector is pointing in the direction of the steepest slope at that point of the function? Whereas my challenge is to find the vector which has no steepness at that point. Hence me intuitively suggesting it must be orthogonal to the gradient vector. Was I wrong?

Thanks

Why are you arguing with me? I said exactly the same as what you have said, except that I gave reasons instead of just writing down a prescription without explanation.
 
  • #15
Ray Vickson said:
Why are you arguing with me? I said exactly the same as what you have said, except that I gave reasons instead of just writing down a prescription without explanation.

Oh wow no I wasn't arguing, sorry if it came across that way. It was just the first line of your previous post seemed to infer that I was still wrong overall, so I remained confused.

If all is good then that's fine, thanks.
 
  • #16
simple calculate here and answer it.
Read more
 

Related to Some vector calculus questions

What is vector calculus?

Vector calculus is a branch of mathematics that deals with vector fields and their derivatives, such as gradients, divergences, and curls. It is used to study the properties of vector fields and their behavior in space.

What are the basic operations in vector calculus?

The basic operations in vector calculus include addition, subtraction, scalar multiplication, dot product, cross product, and differentiation and integration of vector functions.

What is the difference between a scalar and a vector in vector calculus?

A scalar is a quantity that has only magnitude, while a vector has both magnitude and direction. In vector calculus, scalars are represented by real numbers, while vectors are represented by arrows.

What are some real-world applications of vector calculus?

Vector calculus has various applications in physics, engineering, and computer graphics. Some examples include analyzing the flow of fluids, determining electric and magnetic fields, and modeling motion and forces in 3D space.

What are the prerequisites for learning vector calculus?

To understand vector calculus, one should have a strong foundation in algebra, trigonometry, and calculus. It is also helpful to have a basic understanding of vectors and vector operations.

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