Is Taking the Gradient of a Vector Possible?

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In summary, the conversation discusses the mathematical expression (\vec A\cdot\nabla)\vec B and its interpretation as the Advective or Convective operator in Fluid Mechanics. The equation is shown to be equivalent to \left(a_x \frac{\partial}{\partial x} + a_y \frac{\partial}{\partial y} + a_z \frac{\partial}{\partial z}\right) \vec B=a_x \frac{\partial\vec B}{\partial x} + a_y \frac{\partial\vec B}{\partial y} + a_z \frac{\partial\vec B}{\partial z}, where \vec A=(a_x,a_y,a_z). It is noted that, while the notation may
  • #1
Henry Morton
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What does this mean?

[itex](\vec A\cdot\nabla)\vec B[/itex]

I read somewhere that

[itex](\vec A\cdot\nabla)\vec B=\vec A\cdot\nabla\vec B[/itex]

but this must be nonsense since you can't take the gradient of a vector.
 
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  • #2
Well, you could try extending it out by components. Assuming three-space, we have as such:

[tex]\left(a_x \frac{\partial}{\partial x} + a_y \frac{\partial}{\partial y} + a_z \frac{\partial}{\partial z}\right) \left(b_x \hat{i} + b_y \hat{j} + b_z \hat{k}\right)[/tex]

Which would be the interpretation I'd go with. What that means, on the other hand, is harder to determine.

EDIT: Should probably say that I assumed [itex]\vec{A} = a_x \hat{i} + a_y \hat{j} + a_z \hat{k}[/itex], and same with B.
 
  • #3
What you're talking about is called the Advective or Convective operator and describes the change in a property due to flow of continuous media (in Fluid Mechanics anyway).

Char limit is correct. Don't worry about whether it makes sense or not the way it's written because it is essentially taking notation abuse to the next level (similarly to the way curl and divergence are written as cross and dot products of the gradient with the vector!). This is what the thing actually looks like:

[tex]
(\vec A\cdot\nabla)\vec B=\vec A\cdot\nabla\vec B=\left(a_x \frac{\partial}{\partial x} + a_y \frac{\partial}{\partial y} + a_z \frac{\partial}{\partial z}\right) \vec B=a_x \frac{\partial\vec B}{\partial x} + a_y \frac{\partial\vec B}{\partial y} + a_z \frac{\partial\vec B}{\partial z}[/tex]
where
[tex] \vec A=(a_x,a_y,a_z) [/tex]

Does that help? Can you see how it can be written both ways? You can think of the gradient of a vector as a vector of vectors, but as I said, don't worry about doing that. You should use the formula you wrote initially only as a sort of mnemonic device for what it actually is (the final formula I wrote). You should note, however, that when you're actually doing the calculations (I'm assuming you're seeing this in the Navier-Stoke's Equations), you won't do this as one big vector, but rather you'll have separate equations for the x, y, and z components of B.
 
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  • #4
schliere said:
What you're talking about is called the Advective or Convective operator and describes the change in a property due to flow of continuous media (in Fluid Mechanics anyway).

Char limit is correct. Don't worry about whether it makes sense or not the way it's written because it is essentially taking notation abuse to the next level (similarly to the way curl and divergence are written as cross and dot products of the gradient with the vector!). This is what the thing actually looks like:

[tex]
(\vec A\cdot\nabla)\vec B=\vec A\cdot\nabla\vec B=\left(a_x \frac{\partial}{\partial x} + a_y \frac{\partial}{\partial y} + a_z \frac{\partial}{\partial z}\right) \vec B=a_x \frac{\partial\vec B}{\partial x} + a_y \frac{\partial\vec B}{\partial y} + a_z \frac{\partial\vec B}{\partial z}[/tex]
where
[tex] \vec A=(a_x,a_y,a_z) [/tex]

Does that help? Can you see how it can be written both ways? You can think of the gradient of a vector as a vector of vectors, but as I said, don't worry about doing that. You should use the formula you wrote initially only as a sort of mnemonic device for what it actually is (the final formula I wrote). You should note, however, that when you're actually doing the calculations (I'm assuming you're seeing this in the Navier-Stoke's Equations), you won't do this as one big vector, but rather you'll have separate equations for the x, y, and z components of B.

Yes, thanks a bunch.
 
  • #5
You SURE can take the gradient of a vector!
What you end up with is a matrix, and your left-hand side in your identity is a scalar operator on a vector, yielding a vector C, whereas your right hand side is a vector-matrix product, yielding a vector D..
The equality sign means that C=D
 

1. What is the meaning of (A dot nabla)B?

The expression (A dot nabla)B represents the dot product between the vector A and the nabla operator applied to the vector B. In other words, it is a mathematical operation used to calculate the directional derivative of B in the direction of A.

2. How is (A dot nabla)B used in physics?

In physics, (A dot nabla)B is used to calculate the rate of change of a physical quantity B in the direction of a given vector A. This is particularly useful in studying fluid dynamics, electromagnetism, and other fields where directional changes are important.

3. Can (A dot nabla)B be simplified?

Yes, (A dot nabla)B can be simplified using the product rule of differentiation. This allows us to expand the expression and rewrite it in terms of partial derivatives of A and B.

4. What is the physical significance of (A dot nabla)B?

The physical significance of (A dot nabla)B is that it represents the change in a physical quantity B as we move in the direction of the vector A. This can help us understand how a system or process changes as we move in different directions.

5. How is (A dot nabla)B related to the gradient of a scalar field?

The expression (A dot nabla)B is closely related to the gradient of a scalar field. In fact, the gradient of a scalar field can be thought of as a special case of (A dot nabla)B, where A is a unit vector in the direction of the gradient of the scalar field. This allows us to use (A dot nabla)B to calculate the gradient of a scalar field in any given direction.

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