Use the gradient vector to find out the direction

In summary, to find the direction in which the ant should move to reach the cooler place fastest, one can take the gradient of the function and determine the direction in which the gradient is steepest. This can be done by finding the gradient at the ant's starting point and moving in that direction. The function for this problem is defined as ##\frac k{\sqrt{x^2+y^2}}##, and the direction is (3,2). Calculus is not necessary to solve this problem, as the ant simply needs to move as fast as possible away from the origin.
  • #1
daphnelee-mh
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Homework Statement
Suppose there is a rectangular metal plate in the Oxy-plane with vertices (1,1),(5,1),(1,3) and (5,3). There is a heat source at the origin that heats the plate. Suppose the temperature at a point in the plate is inversely propotional to the distance of this point to the origin. Suppose there is an ant at the point (3.2). In which direction should the ant creep such that it gets to the cooler place fastest?
Relevant Equations
Duf(x,y)=∇f(x,y)⋅u

To Maximizing The Directional Derivative : Duf(x,y)=|∇f(x,y)| , in the direction as ∇f(x,y)
For my understanding, to move to the coolest place, it has to move in direction of -∇f(x,y)
How can I find the value of 'k' to evaluate the directional derivative and what can I do with the vertices given.
1593742216504.png
 
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  • #2
daphnelee-mh said:
In which direction should the ant creep such that it gets to the cooler place fastest?

How can I find the value of 'k'
The question is ambiguous. Is the ant trying to maximise the rate at which the temperature starts to drop (which is what you seem to have assumed in your reference to derivatives) or to reach the coolest point on the plate in the least time (matching your use of "coolest" in your handwritten explanation)?
Either way, the value of k is irrelevant. You seem to be trying to find the temperature where the ant starts, which is also irrelevant.
 
  • #3
It seems have to find out the direction to reach the point which is cooler. I am trying to get k to get the function T then take the derivative . Any other method to find out function ?
 
  • #4
daphnelee-mh said:
It seems have to find out the direction to reach the point which is cooler. I am trying to get k to get the function T then take the derivative . Any other method to find out function ?
But ##\frac k{\sqrt{13}}## is not the function, it is only the value at one point.
And "the point which is cooler" doesn't define it. Lots of points are cooler.
Are you trying to find:
  1. The fastest route to the coolest point, or
  2. The direction in which it gets cooler fastest?
If (1), you first need to identify where the coolest point is.
If (2), taking the derivative (##\nabla##) of the function will tell you how fast it gets cooler in a given direction. You would then need to figure out the direction that maximises it. However, if you think a bit more you may realize the answer is obvious, no calculus needed.
 
  • #5
if (2), but the function f is not defined, what can I do with the given vertices?
 
  • #6
daphnelee-mh said:
if (2), but the function f is not defined, what can I do with the given vertices?
It is defined. As you wrote, it is ##\frac k{\sqrt{x^2+y^2}}##. Don't worry about what k is, just work with that and see what happens.
This is the sequence:
What is the gradient at (x,y)?
In which direction from (x,y) is the gradient steepest?
Which direction is that at the ant's starting point?
 
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  • #7
haruspex said:
It is defined. As you wrote, it is ##\frac k{\sqrt{x^2+y^2}}##. Don't worry about what k is, just work with that and see what happens.
This is the sequence:
What is the gradient at (x,y)?
In which direction from (x,y) is the gradient steepest?
Which direction is that at the ant's starting point?
1593817194548.png

Is it correct? Thank you
 
  • #8
daphnelee-mh said:
View attachment 265797
Is it correct? Thank you
Yes, but since it is only a direction you can just give (3,2) as the answer. Or normalise it to a unit vector if you prefer.
As I posted, calculus was not really needed. The ant just needs to move as fast as possible away from the origin, so that is obviously in the direction (3,2).
 
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  • #9
haruspex said:
Yes, but since it is only a direction you can just give (3,2) as the answer. Or normalise it to a unit vector if you prefer.
As I posted, calculus was not really needed. The ant just needs to move as fast as possible away from the origin, so that is obviously in the direction (3,2).
Okay, Thank you very much
 

1. What is a gradient vector?

A gradient vector is a mathematical concept used in vector calculus to represent the direction and magnitude of the steepest slope of a multi-dimensional function. It is typically denoted by the symbol ∇ (del) and is also known as the "nabla" or "gradient operator".

2. How is the gradient vector used to find direction?

The gradient vector is used to find direction by pointing in the direction of the steepest increase of a function at a given point. This means that if we move in the direction of the gradient vector, we will be moving in the direction of the greatest change in the function's value.

3. Can the gradient vector be used to find the direction of decrease?

Yes, the gradient vector can also be used to find the direction of decrease. This is because the gradient vector always points in the direction of the steepest slope, whether it is increasing or decreasing. To find the direction of decrease, we simply move in the opposite direction of the gradient vector.

4. What is the relationship between the gradient vector and the level curves of a function?

The gradient vector is always perpendicular to the level curves of a function. This means that the gradient vector is always tangent to the level curves and points in the direction of the greatest increase or decrease of the function.

5. How is the gradient vector used in real-world applications?

The gradient vector has various applications in fields such as physics, engineering, economics, and machine learning. It is used to optimize functions and find the most efficient or optimal solution. For example, it can be used to find the direction of steepest descent in a terrain map, or to determine the best route for a delivery truck based on varying terrain and traffic conditions.

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