How Do You Calculate the Angle Between Two Surfaces at a Given Point?

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In summary, To solve the first problem, find the normal vectors to the surfaces r^2=9 and x+y+z^2=1 at the given point and then find the angle between them. For the second problem, find the maximum of the given function to determine the location and height of the top of the hill, and then find a vector perpendicular to the surface using the gradient vector. The angle between this vector and the z axis can be found by taking the dot product with a vector along the z axis.
  • #1
don_anon25
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If someone could gtive me a general idea about how to approach these problems, I would be very grateful! Our class time was devoted to derivation rather than application.

1) Find the angle between the surfaces defined by r^2=9 and x+y+z^2=1 at the point (2,-2,1).

2) The height of a hill is given by z = 2xy - 3x^2 - 4y^2 - 18x +28y +12. x is the distance east and y is the distance north of the origin. i) Where is the top of the hill and how high is it? ii) What is the angle between a vector perpendicular to the hill and the z axis? I really have no idea where to start with this one!
 
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  • #2
don_anon25 said:
If someone could gtive me a general idea about how to approach these problems, I would be very grateful! Our class time was devoted to derivation rather than application.

1) Find the angle between the surfaces defined by r^2=9 and x+y+z^2=1 at the point (2,-2,1).

Find the angle between the normal vectors. Since you labled this "gradients" I presume you know how to find those normal vectors!

2) The height of a hill is given by z = 2xy - 3x^2 - 4y^2 - 18x +28y +12. x is the distance east and y is the distance north of the origin. i) Where is the top of the hill and how high is it? ii) What is the angle between a vector perpendicular to the hill and the z axis? I really have no idea where to start with this one!
i) Do you know how to find the maximum of a function of two variables? Do you remember how to find the maximum of y= f(x) from Calculus I? (Find the derivative and set it equal to 0. Same here!)
ii) A vector along the z-axis is 0i+ 0j+ 0k. Do you know how to find a vector perpendicular (normal) to a surface? (Think "gradient vector". {3 dimensional, not 2!})
 
  • #3
I understand 2a now! But could you elaborate a little more on the first problem? How do I start?
 
  • #4
1) Find the angle between the surfaces defined by r^2=9 and x+y+z^2=1 at the point (2,-2,1).

r2= 9? Is that in polar coordinates? The sphere of radius 3? Must be since (2, -2, 1)satisfy that. In that case, a normal vector is easy! Any radius is perpendicular to a sphere so 2i- 2j+ k is normal to the sphere at (2, -2, 1).

To find a normal vector to x+y-z2= 1, think of it as a level surface of the function F(x,y,z)= x+ y- z2. The gradient of F, i+ j- 2zk, is normal to that suface at each point. In particular, taking z= 1, i+ j- 2k is normal to that surface at (2, -2, 1). Now, what is the angle between the vectors 2i- 2j+ k and i+ j- k?
 

Related to How Do You Calculate the Angle Between Two Surfaces at a Given Point?

What is the definition of gradient?

The gradient is a mathematical concept that represents the rate of change of a function. It is a vector that points in the direction of the steepest increase of the function at a given point.

How is gradient calculated?

The gradient is calculated by taking the partial derivatives of a function with respect to each input variable and combining them into a vector. The resulting vector represents the direction and magnitude of the steepest increase of the function at a given point.

What is the significance of gradient in optimization?

The gradient is a crucial concept in optimization as it indicates the direction in which a function has the steepest increase. This information is used to iteratively improve the value of a function in order to find its maximum or minimum value.

What is a gradient descent algorithm?

A gradient descent algorithm is an iterative optimization method that uses the gradient to update the parameters of a function in order to find its minimum value. It is commonly used in machine learning and other optimization problems to find the best values for a set of parameters.

What are some applications of gradient in real life?

Gradient has various applications in fields such as physics, engineering, and economics. It is used to calculate the velocity and acceleration of moving objects, determine the flow of heat and fluids, and optimize processes and systems. In everyday life, it can be used to find the most efficient route between two points or to determine the best investment strategies.

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