Can the Chain Rule be Applied to Simplify Divergence in Entropy Equation?

In summary, the conversation discusses the derivation of the Entropy equation for a Newtonian Fluid with Fourier Conduction law. The use of the chain rule is mentioned in relation to the middle term in the equation, and the relevant product and chain rules are suggested to simplify the expression.
  • #1
BeeKay
16
0
I am looking at the derivation for the Entropy equation for a Newtonian Fluid with Fourier Conduction law. At some point in the derivation I see

[tex] \frac{1}{T} \nabla \cdot (-\kappa \nabla T) = - \nabla \cdot (\frac{\kappa \nabla T}{T}) - \frac{\kappa}{T^2}(\nabla T)^2 [/tex]

K is a constant and T is a scalar field. It seems obvious that there is some way to use the chain rule on the middle term to get the left and right terms, but I frankly don't exactly understand the "rules" of how to use it with the divergence. I know you can't just factor out [tex] \frac{1}{T} [/tex] from the middle term, but I'm not sure how to actually simplify that middle expression. Any help is appreciated.
 
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  • #2
I think the relevant product rule is ##\nabla\cdot (fV)=(\nabla f)\cdot V+f (\nabla\cdot V)##. Try applying this with ##f=1/T## and ##V=\nabla T##.

You will also want to use the chain rule for ##\nabla (1/T)=-\frac{\nabla T}{T^2}##.
 

What is "Divergence with Chain Rule"?

"Divergence with Chain Rule" is a mathematical concept used in vector calculus to calculate the rate of change of a vector field in a given direction. It involves taking the dot product of the gradient of a scalar field with the vector field.

How is "Divergence with Chain Rule" different from regular divergence?

Regular divergence is a scalar quantity that measures the net flow of a vector field out of a given region. "Divergence with Chain Rule" is a vector quantity that takes into account the direction of the flow.

What is the formula for calculating "Divergence with Chain Rule"?

The formula for "Divergence with Chain Rule" is div F = ∇ · (F ∘ φ), where div F is the divergence of the vector field F, ∇ is the gradient operator, and φ is the scalar field.

Why is "Divergence with Chain Rule" important in science?

"Divergence with Chain Rule" is important in science because it allows us to understand the behavior of vector fields in a given direction. It is used in many fields such as fluid mechanics, electromagnetism, and quantum mechanics.

Are there any real-world applications of "Divergence with Chain Rule"?

Yes, "Divergence with Chain Rule" has many real-world applications. It is used in weather forecasting to predict the movement of air masses, in computer graphics to create realistic fluid simulations, and in medical imaging to analyze blood flow in the body.

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