Multivariable calculus -critical points

In summary, the conversation discusses finding the dimensions of a rectangular box with a volume of 96m^3 and a minimum total mass. The critical point is found at (4,4) and the Hessian matrix shows that it is a saddle point, not a minimum. Further analysis is needed to determine if there is a minimum.
  • #1
ultima9999
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A rectangular box is to have a volume of [tex]96m^3[/tex]. The 4 sides and the top are to be made of a material of density [tex]1kg/m^2[/tex] and the flat base is to have a density of [tex]2kg/m^2[/tex]. Suppose that the base is of size x meters by y meters.

It was found in the first question that the mass, M in kg of the box is:
[tex]M(x,y) = 3xy + \frac{192}{x} + \frac{192}{y}[/tex]

Find the dimensions of the box so that the total mass of the box is a minimum.
So, I just find the critical points, which occur at [tex]f_x = f_y = 0[/tex]
[tex]f_x = 3y - \frac{192}{x^2} = 0[tex]
[tex]y = \frac{64}{x^2}[/tex]

[tex]f_y = 3x - \frac{192}{y^2} = 0[/tex]
[tex]x(x^3 - 1) = 0,\ \ x = 0,\ 1[/tex]

So critical points occur at (1, 64) and x = 0. We cannot have a dimension of 0, so minimum mass at x = 1, y = 64. The next question asks to prove that the dimensions found correspond to a minimum value of M(x,y).

So I use second derivatives and the Hessian matrix.
[tex]f_{xx} = \frac{384}{x^3},\ \ f_{xy} = 3,\ \ f_{yy} = \frac{384}{y^3}[/tex]
[tex]\mbox{det(H)} = \frac{384^2}{(xy)^3} - 9[/tex]
At (1, 64), det(H) < 0 which means that it is a saddle point, not a minimum. So, where have I gone wrong, or is the answer simply "there is no minimum"?
 
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  • #2
a little help, too much perhaps

Your critical points aren't right: notice how m(x,y)=m(y,x) so that any critical points will have x=y? well, anyhow up to here it is ok:

[tex]y=\frac{64}{x^2}, x=\frac{64}{y^2}[/tex]​

now assume [tex]x\neq 0,y\neq 0[/tex] (because of just what you said: can't have 0 volume), now simplify them to get

[tex]x^2y=64, xy^2=64[/tex]​

multiply the first equation by y and the second by x to get

[tex]x^2y^2=64y, x^2y^2=64x[/tex]​

since both equations have one side equal to [tex]x^2y^2[/tex] we can set them equal to each other as in [tex]64y=64x[/tex] so x=y, plug this into any previous equation, say [tex]x^2y=64[/tex] to get [tex]x^3=64[/tex] so x=4, but x=y hence x=y=4 is the critical point.
 

1. What are critical points in multivariable calculus?

Critical points are points on a function where the gradient (or derivative) is equal to zero. They can be either local maxima, local minima, or saddle points.

2. How do you find critical points?

To find critical points, you need to take the partial derivatives of the multivariable function with respect to each variable and set them equal to zero. Then, solve the resulting system of equations to find the critical points.

3. What is the significance of critical points in multivariable calculus?

Critical points are important because they can help identify where a function reaches its maximum or minimum values. They also give us information about the behavior of a function around a certain point.

4. Can a function have multiple critical points?

Yes, a function can have multiple critical points. In fact, most functions have multiple critical points in different regions of their domain.

5. How are critical points used in optimization problems?

Critical points are used in optimization problems to determine the maximum or minimum values of a function. By finding the critical points, we can determine where the function is changing the most and find the optimal solution.

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