What is the Last Term in the Expression for \nabla\cdot(\phi\vec{A})?

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In summary: So in summary, the problem involves verifying the equation \nabla\cdot(\phi \vec{A}) = \vec{A}\cdot\nabla \phi + \phi\nabla\cdot\vec{A}, where \phi= xy^{2}, A=xzi-z^{2}j+xy^{2}k, and B=zi+xj+yk. The first two parts of the problem have already been worked out, but the last part, \phi\nabla\cdot\vec{A}, is still being calculated. The expression should actually be \phi\nabla\cdot\vec{A} = xy^{2}z, and this can be verified by computing \nabla
  • #1
SAMSAM12
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Homework Statement


If [itex]\phi[/itex]= xy[itex]^{2}[/itex]
A=xzi-z[itex]^{2}[/itex]j+xy[itex]^{2}[/itex]k
B=zi+xj+yk

Verify that
[itex]\nabla[/itex].([itex]\phi[/itex]A)=A.[itex]\nabla[/itex][itex]\phi[/itex]+[itex]\phi[/itex].[itex]\nabla[/itex]A

Homework Equations


The Attempt at a Solution


I have worked out the first two parts of the question:
[itex]\phi[/itex]A = (x[itex]^{2}[/itex]y[itex]^{2}[/itex]z, -xy[itex]^{2}[/itex]z[itex]^{2}[/itex],x[itex]^{2}[/itex]y[itex]^{4}[/itex])
div([itex]\phi[/itex]A) = 2xy[itex]^{2}[/itex]z-2xyz[itex]^{2}[/itex]

A.grad([itex]\phi[/itex]) = (xy[itex]^{2}[/itex]z-2xyz[itex]^{2}[/itex])

I'm struggling to work out the last part:
[itex]\phi[/itex].[itex]\nabla[/itex]A

I tried working out [itex]\phi[/itex].grad(A)? but the answer sheet has
div(A) = z
[itex]\phi[/itex]div(A) = xy[itex]^{2}[/itex]z

why?
Any help appreciated.

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  • #2
Ok, so to start compute [itex]\nabla A[/itex] which will just be [itex] (\frac{\partial}{\partial x}\vec{A},\frac{\partial}{\partial y}\vec{A},\frac{\partial}{\partial z}\vec{A})[/itex]
You will end up with a scalar, which you can multiply by your scalar [itex]\phi[/itex] and you should end up with [itex]xy^2z[/itex].
 
Last edited:
  • #3
SAMSAM12 said:

Homework Statement


If [itex]\phi[/itex]= xy[itex]^{2}[/itex]
A=xzi-z[itex]^{2}[/itex]j+xy[itex]^{2}[/itex]k
B=zi+xj+yk

Verify that
[itex]\nabla[/itex].([itex]\phi[/itex]A)=A.[itex]\nabla[/itex][itex]\phi[/itex]+[itex]\phi[/itex].[itex]\nabla[/itex]A
The last term of the expression doesn't make sense. You can't dot a scalar into anything. It should be
$$\nabla\cdot(\phi \vec{A}) = \vec{A}\cdot\nabla \phi + \phi\nabla\cdot\vec{A}$$
 
  • #4
vela said:
The last term of the expression doesn't make sense. You can't dot a scalar into anything. It should be
$$\nabla\cdot(\phi \vec{A}) = \vec{A}\cdot\nabla \phi + \phi\nabla\cdot\vec{A}$$

Thank you.
 

Related to What is the Last Term in the Expression for \nabla\cdot(\phi\vec{A})?

1. What is the concept of GRAD DIV CURL?

GRAD DIV CURL is a mathematical concept used in vector calculus to describe the behavior of vector fields. It is also known as the vector derivative and is used to analyze the changes in a vector field at a specific point.

2. What are the three components of GRAD DIV CURL?

The three components of GRAD DIV CURL are gradient (GRAD), divergence (DIV), and curl (CURL). These components represent the change in a vector field in the x, y, and z directions respectively.

3. How is GRAD DIV CURL used in physics?

GRAD DIV CURL has various applications in physics, such as in the study of fluid dynamics, electromagnetism, and heat transfer. It helps to understand the behavior of these systems and predict their future states.

4. What is the relationship between GRAD DIV CURL and the Laplacian operator?

The Laplacian operator is the sum of the divergences of the gradient and the curl of a vector field. In other words, it is the scalar version of GRAD DIV CURL. This relationship is often used in solving differential equations in physics and engineering problems.

5. How is GRAD DIV CURL represented mathematically?

GRAD DIV CURL is represented using the del operator (∇) in vector calculus. The gradient is represented as (∇f), where f is the scalar function of the vector field. The divergence is represented as (∇ · F), and the curl is represented as (∇ x F), where F is the vector field.

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