Find that this partial differentiation is equal to 0

In summary, the equation $$\sum_i (\frac{\partial}{\partial q_i}(\frac{\partial T}{\partial q_j}\dot{q}_i)+\frac{\partial}{\partial q_i}(\frac{\partial T}{\partial q_j})\ddot{q}_i)+\frac{\partial}{\partial t}(\frac{\partial T}{\partial \dot{q}_j})$$ is equal to ##\dfrac{d}{dt}(\dfrac{\partial T}{\partial \dot{q}_j})##, which is the chain rule for ##\dfrac{\partial T}{\partial \dot{q}_j}(q,\dot{q},
  • #1
Istiak
158
12
Homework Statement
find a partial differentiation is equal to 0
Relevant Equations
Partial Differentiation
$$\sum_i (\frac{\partial}{\partial q_i}(\frac{\partial T}{\partial q_j}\dot{q}_i)+\frac{\partial}{\partial q_i}(\frac{\partial T}{\partial q_j})\ddot{q}_i)+\frac{\partial}{\partial t}(\frac{\partial T}{\partial \dot{q}_j})$$

They wrote that above equation is equal to $$\frac{d}{dt}(\frac{\partial T}{\partial \dot{q}_j})$$ hiwhc means differentiation of other functions are ##0##. But, I was thinking if my explanation was correct. I thought that while differentiating respect to ##q_i## in the function ##\sum_i \frac{\partial}{\partial q_i}(\frac{\partial T}{\partial q_j}\dot{q}_i)## there's no variable ##q## so, while differentiating respect to that it will become ##0##. I was thinking the same thing had happened to second one also.

But, actually ##T=T(q_i,\dot{q}_i,t)##. So, T has q variable but although why it will be ##0##? Is there something else I am missing?
 
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  • #2
Istiakshovon said:
$$\sum_i (\frac{\partial}{\partial q_i}(\frac{\partial T}{\partial q_j}\dot{q}_i)+\frac{\partial}{\partial q_i}(\frac{\partial T}{\partial q_j})\ddot{q}_i)+\frac{\partial}{\partial t}(\frac{\partial T}{\partial \dot{q}_j})$$They wrote that above equation is equal to ##\dfrac{d}{dt}(\dfrac{\partial T}{\partial \dot{q}_j})##.
Did you make a typo? Ought to be ##\dfrac{d}{dt} \dfrac{\partial T}{\partial \dot{q}_j} = \dfrac{\partial^2 T}{\partial q_i \partial \dot{q}_j} \dot{q}_i + \dfrac{\partial^2 T}{\partial \dot{q}_i \partial \dot{q}_j} \ddot{q}_i + \dfrac{\partial^2 T}{ \partial t\partial \dot{q}_j}##.
 
  • #3
Screenshot from 2021-09-02 01-38-51.png
that's what author wrote. I don't think I made typo.
 
  • #4
You did make a few typos, but the picture in #3 is right. It's the chain rule for ##\dfrac{\partial T}{\partial \dot q_j}(q,\dot{q}, t)##.
 
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Likes Delta2 and Istiak
  • #5
Since, my another thread was deleted mod was saying it's dup of that so adding info here.
Screenshot from 2021-09-02 13-43-40.png

In the last second line they wrote that,

$$\frac{d}{dt}(\frac{\partial T}{\partial \dot{q}_j})-\frac{\partial T}{\partial q_j}=\frac{\partial \dot{T}}{\partial \dot{q}_j}-\frac{\partial T}{\partial q_j}-\frac{\partial T}{\partial q_j}$$

which isn't looking correct to me. Cause, we know that ##\frac{d}{dt}(\frac{\partial T}{\partial \dot{q}_j})=\frac{\partial \dot{T}}{\partial \dot{q}_j}##
 
  • #6
ergospherical said:
It's the chain rule for ##\dfrac{\partial T}{\partial \dot q_j}(q,\dot{q}, t)##.
$$\frac{\partial T}{\partial \dot{q}_j}=\frac{\partial T}{\partial q_j}\frac{\partial q_j}{\partial \dot{q}_j}+\frac{\partial T}{\partial \dot{q}_j}+\frac{\partial T}{\partial t}\frac{\partial t}{\partial \dot{q}_j}$$ I found it. I think something is wrong. Cause, I still can't make them ##0## (after putting that in the main equation).
 

FAQ: Find that this partial differentiation is equal to 0

What is partial differentiation?

Partial differentiation is a mathematical concept used to find the rate of change of a function with respect to one of its variables while holding all other variables constant.

Why is it important to find when partial differentiation is equal to 0?

When partial differentiation is equal to 0, it indicates that the function has reached a critical point, which could be a maximum, minimum, or saddle point. This information is crucial in optimization problems and can help determine the behavior of a function.

How do you find when partial differentiation is equal to 0?

To find when partial differentiation is equal to 0, you need to take the partial derivatives of the function with respect to each variable, set them equal to 0, and solve for the variables. This will give you the critical points of the function.

Can partial differentiation be used for any type of function?

Yes, partial differentiation can be used for any type of function, including multivariable functions. However, the function must be differentiable, meaning it must have continuous partial derivatives.

What is the significance of the value of partial differentiation at a critical point?

The value of partial differentiation at a critical point can tell us the type of critical point it is. If the value is positive, it is a minimum point, if it is negative, it is a maximum point, and if it is 0, it is a saddle point. This information can help us understand the behavior of the function at that point.

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