Find the rate of change of temperature

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Homework Help Overview

The problem involves finding the rate of change of temperature at a specific point in three-dimensional space, given a temperature function T(x, y, z). The original poster seeks to determine this rate in the direction of another point, raising questions about their calculations and understanding of directional derivatives.

Discussion Character

  • Exploratory, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • The original poster calculates partial derivatives and the gradient of the temperature function but questions their approach to finding the unit vector in the correct direction. Some participants suggest that the direction vector should be derived from the difference between the two points rather than directly using one of the points.

Discussion Status

Participants are actively discussing the correctness of the calculations related to the directional derivative and the unit vector. There is acknowledgment of potential mistakes in the exponent of the temperature function and the interpretation of the direction vector. Some guidance has been offered regarding the proper method for determining the unit vector.

Contextual Notes

There are indications of confusion regarding the calculations and assumptions made about the direction of the temperature change, as well as the requirements for the unit vector. The problem also includes additional parts that explore related concepts of maximum rate of increase and direction of fastest increase.

tangibleLime
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Homework Statement



The temperature at a point (x, y, z) is given by the following equation where T is measured in °C and x, y, z in meters.

T(x, y, z) = 200e-x2-3y2-9z2

Find the rate of change of temperature at the point P(2, -1, 2) in the direction towards the point (3, -3, 3).

Homework Equations


The Attempt at a Solution



I calculated the partial derivatives of T(x,y,z) as...
T_{x} = -400xe^{-x^{2}-3y^{2}-9z^{2}}
T_{y} = -1200ye^{-x^{2}-3y^{2}-9z^{2}}
T_{z} = -3600ze^{-x^{2}-3y^{2}-9z^{2}}

Giving me the gradient...

\nabla T(x,y,z) = <-400xe^{-x^{2}-3y^{2}-9z^{2}}, -1200ye^{-x^{2}-3y^{2}-9z^{2}}, -3600ze^{-x^{2}-3y^{2}-9z^{2}}>

Plugging in the given values for the gradient, I get...

\nabla T(2,-1,2) = <\frac{-800}{e^{35}},\frac{1200}{e^{35}},\frac{-7200}{e^{35}}>

Meanwhile, I take the point (3,-3,3) and convert it into a direction unit vector (I think this is where I make a mistake).

v = <3,-3,3>

u = \frac{1}{\sqrt{27}} * <3,-3,3>

u = <\frac{1}{\sqrt{3}},-\frac{1}{\sqrt{3}},\frac{1}{\sqrt{3}}>

Combining all of this in DuT...

D_{u}T = \frac{-800}{\sqrt{3}*e^{35}} + \frac{-1200}{\sqrt{3}*e^{35}} + \frac{-7200}{\sqrt{3}*e^{35}}

This gives me a wrong answer of...

\frac{-9200}{\sqrt{3}*e^{35}}

Any help that isn't a purposefully cryptic message that leaves me no closer to solving my problem is appreciated.

Thanks.
 
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tangibleLime said:

Homework Statement



The temperature at a point (x, y, z) is given by the following equation where T is measured in °C and x, y, z in meters.

T(x, y, z) = 200e-x2-3y2-9z2

Find the rate of change of temperature at the point P(2, -1, 2) in the direction towards the point (3, -3, 3).

...

Meanwhile, I take the point (3,-3,3) and convert it into a direction unit vector (I think this is where I make a mistake).

Yes, that is a mistake. You want the direction from (2,-1,2) to (3,-3,3).
 
Thanks, I knew that was a little fishy. But unfortunately I still can't get the right answer.

To get a unit directional vector from those points, this is what I did:

P = (2, -1, 2)

Q = (3, -3, 3)

PQ = (3-2, -3-(-1), 3-2) = <1,-2,1> = v

\frac{<1,-2,1>}{\sqrt{1^2+(-2)^2+1^2}} = \frac{<1,-2,1>}{\sqrt{6}}

u = <\frac{1}{sqrt{6}},\frac{-2}{\sqrt{6}},\frac{1}{\sqrt{6}}>

I then use this directional unit vector u as I did originally, which I believe is the correct method, but it still results in an incorrect answer (all calculations verified by calculator). Am I doing something else wrong?
 
I think the e35 terms are wrong.
 
Ah, yes, got it.

I was, for the first x in the exponent of e, squaring negative x instead of squaring x and taking the negative of that.

Thanks!
 
Hmm, sorry but I have one more question.

This problem had two more parts.

Part B:
In which direction does the temperature increase fastest at P?

Part C:
Find the maximum rate of increase at P.

I was able to calculate part C by simply computing |\nabla T(2,-1,2)|. I thought I knew how to do part B, but apparently I am mistaken. It is my understanding that to maximize the directional derivative (which I believe is what I must do here), I simply take the unit vector in the same direction as my gradient vector, which turns out to be <1,-2,1> from my P-Q calculations a few posts above. However, the first element of the answer is -2... (it's an online system, with the answer set up as <-2, ____, ____> where I will in the second blanks). Shouldn't the answer be <1, -2, 1>? I thought it may just be a scalar of -2 at first, but multiplying that out gave me <-2,4,-2> which was incorrect.
 
tangibleLime said:
Hmm, sorry but I have one more question.

This problem had two more parts.

Part B:
In which direction does the temperature increase fastest at P?

Part C:
Find the maximum rate of increase at P.

I was able to calculate part C by simply computing |\nabla T(2,-1,2)|. I thought I knew how to do part B, but apparently I am mistaken. It is my understanding that to maximize the directional derivative (which I believe is what I must do here), I simply take the unit vector in the same direction as my gradient vector, which turns out to be <1,-2,1> from my P-Q calculations a few posts above.

But the point Q has nothing to do with the gradient vector at P. And <1,-2,1> is not a unit vector, not that that matters.

However, the first element of the answer is -2... (it's an online system, with the answer set up as <-2, ____, ____> where I will in the second blanks). .

Probably the reason they specified a -2 as the first component is that any positive multiple of the correct direction points in the same correct direction. So if you scale it properly to agree with the first component, the other two components will agree, making it easy for the computer to check your answer.
 
The gradient vector itself always points in the direction of fastest increase and it length is that rate of increase.
 

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