Partial Drivative- Inclined Plane Problem

In summary, a partial derivative is a mathematical concept used in multivariable calculus to calculate the rate of change of a function with respect to one of its variables while holding all other variables constant. It is commonly applied to inclined plane problems to analyze the relationship between multiple variables and make predictions about the behavior of objects on inclined surfaces. Partial derivatives can be negative, indicating a decrease in the function as one variable increases, and can be used to optimize inclined plane problems by finding critical points. There are numerous real-world applications of partial derivatives in inclined plane problems, such as designing ramps and analyzing the performance of objects in fields like physics and engineering.
  • #1
ritwik06
580
0

Homework Statement


A ping pong ball is projected (with velocity v)from a foot of an inclined plane with an inclination of [tex]\beta[/tex] . The initial velocity of projection makes an angle [tex]\alpha[/tex] with the surface of th incline. Find the relation beteen [tex]\alpha[/tex] and [tex]\beta[/tex] such that the range is maximum.

The Attempt at a Solution


Time of flight=[tex]\frac{2v sin \alpha}{g cos \beta}[/tex]

Range(R)=[tex]\frac{2 v^{2} sin \alpha cos \alpha}{g cos \beta}-\frac{4 tan \beta v^{2} sin ^{2} \alpha}{g cos \beta}[/tex]

Now the range is a function of both [tex]\alpha[/tex] and [tex]\beta[/tex]. I have been searching how to do the derivative. I learned from mathworld.wolfram that I need to consider one quantity constant and differentiate with respect to the other. and then do the same by keeping the other constant. Then by adding these partial derivatives I can get the complete derivative of the function concerned (which in my case is the range of the projectile).

[tex]\frac{\delta R}{d\alpha}=\frac{2 v^{2} cos 2\alpha}{g cos \beta}-\frac{4 v^{2} tan \beta sin 2\alpha}{g cos \beta}[/tex]


[tex]\frac{\delta R}{d\beta}=\frac{v^{2} sin 2\alpha tan \beta}{g cos \beta}-\frac{4 v^{2} sin^{2} \alpha(2tan^{2}\beta+1)}{g cos \beta}[/tex]

Adding these two and putting them equal to zero does not yield the desired result. I am stuck. Please help me with this.
 
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  • #2
One method is to resolve the velocity in the plane parallel to the incline slope and perpendicular to the inclined slope.

wait while i try it out
 
  • #3
ShellSnail said:
One method is to resolve the velocity in the plane parallel to the incline slope and perpendicular to the inclined slope.

wait while i try it out

I done just that. I have resolved it along the surface of incline and perpendicular to it.

Yup! take your time! :approve:
 
  • #4
x = ucos[tex]\beta[/tex]t - 0.5gsin[tex]\alpha[/tex]t[tex]^{2}[/tex] ----1
y = usin[tex]\beta[/tex]t - 0.5gcos[tex]\alpha[/tex]t[tex]^{2}[/tex] ---- 2
At the point of impact, y = 0
Hence, t = (2usin[tex]\beta[/tex]) / (gcos[tex]\alpha[/tex]) --- 3

put 3 into 1
and differentiate with respect to [tex]\beta[/tex]

you shld end up with

tan 2[tex]\beta[/tex] = cot[tex]\alpha[/tex]

thus, [tex]\beta[/tex] = pi/4 - [tex]\alpha[/tex]/2

EDIT: switch all the alpha with beta and beta with alpha
 
  • #5
You have an error in your Range; you should have

[tex]R=\frac{2 v^{2} sin \alpha cos \alpha}{g cos \beta}+\frac{2 tan \beta v^{2} sin ^{2} \alpha}{g cos \beta} [/tex]

It looks like you forgot to multiply your at^2 term by (1/2), and it should be +(1/2)at^2, not minus. (Assuming your g is -9.8m/s^2)

The total derivative of R is given by:

[tex]dR=\frac{\partial R}{\partial \alpha}d \alpha +\frac{\partial R}{\partial \beta}d \beta [/tex]

At a local max/min the total derivative will be zero, so each partial derivative must also vanish. Compute the partial derivatives and set them equal to zero.
 
  • #6
ShellSnail said:
x = ucos[tex]\beta[/tex]t - 0.5gsin[tex]\alpha[/tex]t[tex]^{2}[/tex] ----1
y = usin[tex]\beta[/tex]t - 0.5gcos[tex]\alpha[/tex]t[tex]^{2}[/tex] ---- 2
At the point of impact, y = 0
Hence, t = (2usin[tex]\beta[/tex]) / (gcos[tex]\alpha[/tex]) --- 3

put 3 into 1
and differentiate with respect to [tex]\beta[/tex]

you shld end up with

tan 2[tex]\beta[/tex] = cot[tex]\alpha[/tex]

thus, [tex]\beta[/tex] = pi/4 - [tex]\alpha[/tex]/2

EDIT: switch all the alpha with beta and beta with alpha
Can you please explain how you got that relation?
 
  • #7
Hmmm...did you understand my last post? Is there anything in there that you don't understand?
 
  • #8
gabbagabbahey said:
Hmmm...did you understand my last post? Is there anything in there that you don't understand?

To an extent...
You were right that i forgot to multiply that by 1/2 but there would be a minus sign there.

I didn't understand how you got the total derivative?
And then is it necessary that if z=x+y and z=0, then how come can we say that x=0, and y=0 are the only solutions?

And I am facing problems in deriving the required relation between alpha and beta!
 
  • #9
The total derivative of a function of two variables, say [itex]f(x,y)[/itex] is by definition:

[tex]df=\left| \frac{\partial f}{\partial x} \right| d x +\left| \frac{\partial f}{\partial y} \right| d y[/tex]

Since [itex]x[/itex] and [itex]y[/itex] are independent variables, so are there total derivatives [itex]dx[/itex] and [itex]dy[/itex]; and so the only way that [itex]df[/itex] can be zero is if each of the partial derivatives [tex]\frac{ \partial f}{\partial x}[/tex] and [tex]\frac{ \partial f}{\partial y}[/tex] are zero.

Do you follow this?
 
  • #10
gabbagabbahey said:
The total derivative of a function of two variables, say [itex]f(x,y)[/itex] is by definition:

[tex]df=\left| \frac{\partial f}{\partial x} \right| d x +\left| \frac{\partial f}{\partial y} \right| d y[/tex]

Since [itex]x[/itex] and [itex]y[/itex] are independent variables, so are there total derivatives [itex]dx[/itex] and [itex]dy[/itex]; and so the only way that [itex]df[/itex] can be zero is if each of the partial derivatives [tex]\frac{ \partial f}{\partial x}[/tex] and [tex]\frac{ \partial f}{\partial y}[/tex] are zero.

Do you follow this?

Yup! I do it now. As x is independent of y at all times, therefore we cannot force it to become a function of y to get the minimum value. right?
just like saying if
x i+ y j=0 i+ 0 j
in vector notation, then x=0 and y=0. right >
 
  • #11
More or less, yes.

So in this case your function is [itex]R(\alpha,\beta)[/itex] and so [tex]\frac{\partial R}{\partial \alpha}[/tex] and [tex]\frac{\partial R}{\partial \beta}[/tex] must both be zero at the local max/min...what do you get when you compute these partial derivatives...where are they zero?
 
  • #12
SOLVED

gabbagabbahey said:
More or less, yes.

So in this case your function is [itex]R(\alpha,\beta)[/itex] and so [tex]\frac{\partial R}{\partial \alpha}[/tex] and [tex]\frac{\partial R}{\partial \beta}[/tex] must both be zero at the local max/min...what do you get when you compute these partial derivatives...where are they zero?

Thanks a lot! I am very grateful to you. I have got my result.
 
  • #13
Congrats! :smile:
 

FAQ: Partial Drivative- Inclined Plane Problem

What is a partial derivative?

A partial derivative is a mathematical concept that calculates the rate of change of a function with respect to one of its variables while holding all other variables constant. It is used in multivariable calculus to analyze how a function changes in one direction while keeping other variables constant.

How is a partial derivative applied to inclined plane problems?

Inclined plane problems often involve multiple variables, such as the angle of inclination and the weight of an object. By taking partial derivatives, we can determine how the weight of the object changes with respect to the angle of inclination, and vice versa. This helps us analyze the relationship between these variables and make predictions about the behavior of the object on an inclined plane.

Can a partial derivative be negative?

Yes, a partial derivative can be negative. This means that as one variable increases, the function is decreasing. In inclined plane problems, this could represent a situation where the weight of an object decreases as the angle of inclination increases, which could be due to a decrease in friction.

How can we use partial derivatives to optimize inclined plane problems?

By taking partial derivatives and setting them equal to zero, we can find critical points where the function reaches its maximum or minimum value. In inclined plane problems, this can help us determine the optimal angle of inclination for an object to reach its maximum speed or for a minimum amount of force to be exerted.

Are there any real-world applications of partial derivatives in inclined plane problems?

Yes, there are many real-world applications of partial derivatives in inclined plane problems. For example, engineers use partial derivatives to design ramps and other inclined surfaces in buildings and wheelchair accessibility. Partial derivatives are also used in fields such as physics and engineering to analyze the motion of objects on inclined planes and optimize their performance.

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