Calculating the dot Product of \nabla and Vector Identity

In summary, the conversation discusses the vector identity ##\nabla •fA=f(\nabla • A)+A•\nabla f## where f is a scalar and A is a vector. It then explores how the formula changes when f is an operator acting on A, specifically looking at ##\nabla •[(v•\nabla)v]## where v is a vector. Through some calculations in Cartesian coordinates, it is determined that the formula becomes ## \nabla \cdot [(\vec{v} \cdot \nabla) \vec{v}]=\frac{1}{2} \nabla^2 (\vec{v}\cdot \vec{v})
  • #1
Apashanka
429
15
From the vector identity ##\nabla •fA=f(\nabla • A)+A•\nabla f## where f is a scalar and A is a vector.
Now if f is an operator acting on A how does this formula change??
Like ##\nabla •[(v•\nabla)v]## where v is a vector
 
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  • #2
The most sure way of getting the answer would be to write out all of the terms in Cartesian coordinates... I will try to work on it a little and see what I get...## \\ ## Edit: With about 10 minutes of work on the above, I believe I get ## \nabla \cdot [(\vec{v} \cdot \nabla) \vec{v}]=\frac{1}{2} \nabla^2 (\vec{v}\cdot \vec{v}) ##. ## \\ ## I'll be happy to show more detail, but basically, I just worked with Cartesian coordinates.
 
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  • #3
A check on my above work shows## \nabla \cdot [(\vec{v} \cdot \nabla) \vec{v}]=\frac{1}{2}\nabla^2 (\vec{v} \cdot \vec{v})-\nabla \cdot (\vec{v} \times \nabla \times \vec{v}) ##. ## \\ ## I think the second expression on the right side is zero, but I haven't proven it yet. If the expression in post 2 is not correct, then post 3 contains your answer. I do think post 2 is correct. ## \\ ## Edit: I made an error in post 2. I believe post 3 is correct. ## \\ ## To see how I got the result of this post, begin with ## \nabla (\vec{v} \cdot \vec{v}) ## and use ## \nabla (\vec{a} \cdot \vec{b})=(\vec{a} \cdot \nabla ) \vec{b}+(\vec{b} \cdot \nabla )\vec{a}+\vec{a} \times \nabla \times \vec{b}+\vec{b} \times \nabla \times \vec{a} ##. ## \\ ## Next take ## \nabla \cdot ## on the expression, to give ## \nabla^2 (\vec{v} \cdot \vec{v}) ##.
 
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1. What is the dot product of the gradient and vector identity?

The dot product of the gradient and vector identity is a mathematical operation that results in a scalar value. It is used to calculate the directional derivative of a vector field in a specific direction.

2. How is the dot product of the gradient and vector identity calculated?

The dot product is calculated by multiplying the corresponding components of the two vectors and then summing the products. In the case of the gradient and vector identity, the vectors are represented as nabla (∇) and the vector identity (I), respectively.

3. What is the significance of calculating the dot product of the gradient and vector identity?

The dot product of the gradient and vector identity is significant in vector calculus as it allows for the calculation of the directional derivative, which is useful in determining the rate of change of a vector field in a specific direction.

4. Can the dot product of the gradient and vector identity be negative?

Yes, the dot product can be negative if the two vectors are pointing in opposite directions. This indicates that the rate of change of the vector field is decreasing in the specified direction.

5. Are there any real-world applications of calculating the dot product of the gradient and vector identity?

Yes, the dot product is used in various fields such as physics, engineering, and computer graphics. It is used to calculate the work done by a force, the flux of a vector field, and the shading of 3D objects, among other applications.

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