How to find the surface density for a given linear density

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Discussion Overview

The discussion revolves around the relationship between linear mass density and surface mass density, particularly in the context of a square with a linear mass density defined as λ(x) = a * x. Participants explore how to derive the surface mass density from the given linear density, addressing the implications of translational invariance and dimensional analysis.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant suggests that the surface mass density should depend on x due to the variation in linear density, questioning why it wouldn't change as well.
  • Another participant argues against dividing by the height coordinate y, stating that the density is translationally invariant in that direction.
  • A different participant proposes that if the total mass of a square sheet is known, the uniform areal density can be calculated by dividing the total mass by the total area.
  • One participant expresses confusion about the appropriate length to divide by in the context of a one-dimensional density variation.
  • Another participant emphasizes the need to find a length to divide by to obtain the areal density, suggesting that the total mass can be expressed as an integral involving the surface density.
  • There is a suggestion that the length l could be related to the y coordinate or an infinitesimal dy, as it relates to the integration process.

Areas of Agreement / Disagreement

Participants express differing views on how to approach the relationship between linear and surface mass densities. There is no consensus on the correct method to derive the surface mass density from the linear density, and the discussion remains unresolved.

Contextual Notes

Participants highlight the complexity of determining the appropriate length to divide by, with some suggesting that the translational invariance in the y direction complicates the analysis. The discussion involves various assumptions about the nature of the densities and their relationships.

Inquisitive Student
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Given a square with a linear mass density of:

λ(x) = a * x (see image below where black is high density and white is low density)

200px-XO-4-test-display-5-black-vs-white-horizontal-gradient.png

how would you deduce what the surface mass density is?

I get confused for the following reason:

To me it seems that the surface mass density should depend on x, because the further left or right you go the linear density changes, so why wouldn't the surface density change as well. A surface mass density must have units of $$\frac{m}{L^2}$$ so since λ(x) has units of $$\frac{m}{L}$$ I would think I need to divide λ(x) by some length. I don't think you would divide by y (the height coordinate) because the density is translationally invariant in y. But that means you have to divide by x to get the right units, and that would mean that the surface mass density is a constant, which doesn't make physical sense to me.
 

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Inquisitive Student said:
I don't think you would divide by y (the height coordinate) because the density is translationally invariant in y.
Seems to me that's pretty much why you should divide by the linear mass density by y. The linear mass element (a point) is getting smeared up and down a surface mass element (a vertical line) of length y.
 
If I told you that the total mass of a square sheet was m and that it had uniform areal density, how would you get that density?
 
Ibix said:
If I told you that the total mass of a square sheet was m and that it had uniform areal density, how would you get that density?
I would divide the total mass m by the total area A:
$$\sigma = \frac{m_{tot}}{A}$$
 
Inquisitive Student said:
I would divide the total mass m by the total area A:
$$\sigma = \frac{m_{tot}}{A}$$
And the area is the square of the side length, ##A=L^2##. But now you've got a 1d density variation. What's the appropriate length you were looking for?
 
Ibix said:
And the area is the square of the side length. But now you've got a 1d density variation. What's the appropriate length you were looking for?
Is this what you mean:

$$\sigma = \frac{m_{tot}}{L^2}$$

but the total mass is equal to the masses of the infinitely thin lines that you stack up together to create a square:

$$\frac{\int_0^L {\lambda(x) dx} * L}{L^2} = \frac{\int_0^L {a*x dx} * L}{L^2} = \frac{a *\frac{L^2}{2}* L}{L^2} = \frac{aL}{2} $$
 
That seems over-complex. My point was that you were correct to say you need to find a length to divide by.

In the simple uniform density case the linear density is ##m/L##. The areal density is ##m/L^2##. What is the length I divided by to get the areal density? Given that your density is uniform in the y direction, should your approach be different?

Another way to look at it is that the total mass is ##m=\iint\sigma(x,y)dxdy##. But you know that ##\sigma(x,y)=\lambda(x)/l##, where ##l## is this length that's confusing you. So you have ##m=\iint(\lambda(x)/l)dxdy##. But from the definition of linear density you know that ##m=\int\lambda(x)dx##. What's ##l##?
 
Ibix said:
That seems over-complex. My point was that you were correct to say you need to find a length to divide by.

In the simple uniform density case the linear density is ##m/L##. The areal density is ##m/L^2##. What is the length I divided by to get the areal density? Given that your density is uniform in the y direction, should your approach be different?

Another way to look at it is that the total mass is ##m=\iint\sigma(x,y)dxdy##. But you know that ##\sigma(x,y)=\lambda(x)/l##, where ##l## is this length that's confusing you. So you have ##m=\iint(\lambda(x)/l)dxdy##. But from the definition of linear density you know that ##m=\int\lambda(x)dx##. What's ##l##?

In the uniform density case you had $$\lambda = \frac{m}{L}$$ where in this case L is the distance in x. Then you divide by the y coordinate to get the area density.

So then it looks like it should be l = y (or maybe l = dy because you have $$\iint (\lambda(x) / l) dxdy = \int \lambda(x) dx$$)
 

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