Is this use of the grad function correct?

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Discussion Overview

The discussion revolves around the application of the gradient function in vector calculus, specifically in modeling how temperature varies in relation to a heat source. Participants explore the mathematical formulation of temperature change as a function of distance from the source, including the correct differentiation of temperature equations and the implications of the gradient's direction.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant proposes a model for temperature variation based on distance from a heat source, suggesting that temperature decreases as one moves away from the source.
  • Another participant points out that the gradient should be taken as negative due to the decreasing temperature, and corrects the differentiation of the temperature function.
  • A later reply acknowledges the differentiation error and discusses the implications of the gradient's direction, emphasizing the need for the negative sign to reflect the decrease in temperature away from the source.
  • Participants discuss the concept of the gradient, noting its role in indicating the direction of greatest increase and how this relates to the behavior of temperature in the given scenario.

Areas of Agreement / Disagreement

There is no consensus on the correct application of the gradient function, as participants express differing views on the differentiation process and the necessity of the negative sign in the gradient. The discussion remains unresolved regarding the correct interpretation and application of these concepts.

Contextual Notes

Participants highlight limitations in understanding the implications of the gradient's direction and the correct differentiation of temperature functions. There are unresolved mathematical steps related to the differentiation process and the application of the gradient in this context.

CraigH
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Hi,
I am currently studying vector calculus, and to try and understand it I have created a question for myself, and it would be greatly appreciated if someone could verify that I have answered my question correctly, and I have done everything right.

Okay here it is; Point Q in the room is a heat source, how does the temperature vary as you move away from the origin (0,0,0)

http://img571.imageshack.us/img571/4250/gascube.png
http://imageshack.us/a/img841/4250/gascube.png

.The further away from point Q you are the less heat there is. This can be modeled by:

[itex]dt = \nabla t .dr[/itex]

.(dt) is a scalar, it is a change in temperature
.(dr) is a vector, it is a change in distance of x, y and z [itex](dr=dx\hat{x} +dy\hat{y} +dz\hat{z} )[/itex]
.(del t) is a vector, it is the amount t changes for x, y, and z, for a change in distance of x,y,and z

For the purposes of this example I am going to say that the heat at any point equals 1 divided by the square of the distance from q.

In the x direction
[itex]t = \frac{1}{(xq-x)^{2}}[/itex]

In the y direction
[itex]t = \frac{1}{(yq-y)^{2}}[/itex]

In the z direction
[itex]t = \frac{1}{(zq-z)^{2}}[/itex]

Where (xq,yq,zq)=(0,2.5,2.5) And (x,y,z) is the point you are at

So, [itex]\frac{dt}{dx} = 2(xq-x)^{-1}, \frac{dt}{dy} = 2(yq-y)^{-1}, \frac{dt}{dz} = 2(zq-z)^{-1}[/itex]

And the final answer is:

[itex]dt =(2(xq-x)^{-1}\hat{x} + 2(yq-y)^{-1}\hat{y} + 2(zq-z)^{-1}\hat{z}) . dr[/itex]

Is this correct?

Thank you
 
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The gradient points in the direction of greatest increase. Since temperature is decreasing, you will want to take the negative gradient of your function. You also differentiated incorrectly. The derivative of x^(-2) is not 2^(-1). It's -2^(-3). Remember: d/dx(x^n) = nx^(n-1).
 
Ah yes I can see I have differentiated incorrectly, although I think it would be 2(xq-x)^-3 and not -2(xq-x)^-3 because of the chain rule:
derivative of (xq-x) with repect to x = -1, so the whole thing will be multiplied by -1.

And can you explain exactly what I did wrong apart from this, I do not really understand why I should have to take the negative gradient, or what this actually even means.

When you say:
Mmm_Pasta said:
The gradient points in the direction of greatest increase

I've always thought that this just meant that if you plot the gradient vector it would point in the direction of greatest increase, but that was just a property of the gradient function, and the true reason you would use the gradient function is to see how much change one variable would change (dt) as three other variables are changing (dr)
[itex]dt = \nabla .dr[/itex]
 
I totally missed that -x part. Thanks!

The fact that the gradient points in the direction of greatest increase is the reasons for the negative sign in your case. The temperature is decreasing as you go away from the source. Without this negative sign, the resulting vector field would be pointing away from the source which implies that temperature is increasing.

By multiplying the gradient by -1, the resulting vector field would be pointing towards the source which means that temperature increases towards the source. Gradients are not only used for seeing *how much* a variable changes, but we are also interested in *which direction* the greatest increase/decrease occurs (for other directions we use directional derivatives). In your case, you specified that temperature drops away from the source.

It's a subtle point, but it's important.
 

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