Help with intuition of divergence, gradient, and curl

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Discussion Overview

The discussion revolves around the physical intuition behind the mathematical concepts of divergence, gradient, and curl in vector fields. Participants explore definitions, interpretations, and the implications of these concepts in various contexts, including their relationships to physical phenomena such as flow and slope.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant defines divergence, curl, and gradient using limits and integrals, suggesting that divergence represents the expansion or contraction of a vector field.
  • Another participant describes curl as the degree of "circulation" in a vector field and reiterates that gradient represents "slope."
  • A question is raised about whether "slope" is an appropriate description for the gradient of a vector, given that it results in a tensor.
  • Some participants clarify that the gradient of a scalar function yields a vector, while the gradient of a vector function results in a second rank tensor.
  • There is a suggestion that the gradient can be viewed as an extension of the concept of "slope," prompting further inquiry into its implications for velocity fields.
  • Participants express uncertainty about the physical interpretation of the dyadic product in the gradient of a vector.

Areas of Agreement / Disagreement

Participants generally agree on the definitions of divergence, curl, and gradient, but there is disagreement regarding the appropriateness of the term "slope" for the gradient of a vector and the physical interpretation of certain mathematical constructs.

Contextual Notes

The discussion includes limitations in understanding the physical implications of the dyadic product in the gradient of a vector and the relationship between different mathematical representations of these concepts.

member 428835
hey pf!

i have a few question about the physical intuition for divergence, gradient, and curl. before asking, i'll define these as i have seen them (an intuitive definition).

\text{Divergence} \:\: \nabla \cdot \vec{v} \equiv \lim_{V \to 0} \frac{1}{V} \oint_A \hat{n} \cdot \vec{v} da

\text{Curl} \:\: \nabla \times \vec{v} \equiv \lim_{V \to 0} \frac{1}{V} \oint_A \hat{n} \times \vec{v} da

\text{Gradient} \:\: \nabla \vec{v} \equiv \lim_{V \to 0} \frac{1}{V} \oint_A \hat{n} \vec{v} da

where ##V## is the volume, ##\vec{v}## is a vector field and the rest (i think) is evident.

as for the divergence, i understand that ##\hat{n} \cdot \vec{v} da## is a volumetric flow rate through a differential surface element. thus the integral is the total volumetric flow rate, and dividing by volume and the limit gives us a nice understanding that divergence is expansion/contraction of a vector field.

my understanding is predicated on the understanding of the dot product, namely ##\hat{n} \cdot \vec{v} da##. however, the curl uses a cross product. i understand a cross product to be a vector orthogonal to two given vectors. thus, ##\hat{n} \times \vec{v} da## seems to be some new vector in a field such that it is tangent to the surface at any point. if we add all these vectors ##\hat{n} \times \vec{v} da## up we should get some kind of body rotation about a point, which i think parallels the general understanding of curl.

however, what on Earth do we do about the dyadic product ##\hat{n} \vec{v}## embedded in the definition of gradient? i really don't have a physical interpretation of what is happening here, and thus i really don't physically understand ##\nabla \vec{v}##.

please help!
 
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The curl is the degree of "circulation" in the vector field.
The gradient is the "slope".

You should get your intuition from using the definitions and not so much from the definitions themselves.
 
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Simon Bridge said:
The gradient is the "slope".

but the gradient of a vector is a tensor. is slope still an appropriate description?

thanks for the response.
 
electricspit said:
The vector points in the direction of maximum increase/decrease of the function. The magnitude of the vector gives the traditional "slope".

http://demonstrations.wolfram.com/VisualizingTheGradientVector/

EDIT: The slope in each direction is given by the component values.

i think you're referring to the gradient of a scalar, ##\nabla f##, which returns a vector. but what i am referring to is the gradient of a vector ##\nabla \vec{f}##, which returns a 2nd rank tensor (a matrix).
 
You're right my mistake, sorry I didn't see the vector symbol there!
 
electricspit said:
You're right my mistake, sorry I didn't see the vector symbol there!
no need to be sorry. i appreciate your interest.
 
I thought you were after a conceptual understanding ... you can think of grad as an extension of the concept of "slope".
 
Simon Bridge said:
I thought you were after a conceptual understanding ... you can think of grad as an extension of the concept of "slope".
so if ##\vec{v}## is a velocity field would ##\nabla \vec{v}## be some sort velocity flux? but then what is ##\hat{n} \vec{v}##? is it the same?
 

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