A Vector Calculus Identity for Characteristic Projections in PDEs

Click For Summary

Homework Help Overview

The discussion revolves around a vector calculus identity related to characteristic projections in partial differential equations (PDEs). The original poster questions the relationship between the dot product of a vector and the gradient of a scalar field, specifically in the context of understanding the arclength and its implications in the derivation of a first-order linear PDE.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the meaning of the arclength in the context of the vector and gradient relationship, questioning the definitions of the variables involved. Some provide derivations related to the rate of change of a scalar field along a curve, drawing parallels to the original identity.

Discussion Status

The discussion is active, with participants sharing insights and derivations that relate to the original question. There is an exchange of ideas regarding parameterization and its relevance to the context of PDEs, though no consensus has been reached on the original poster's query.

Contextual Notes

Participants note the lack of clarity regarding the definitions of the scalar field and the vector, as well as the specific context of the arclength in the discussion. This highlights the need for further clarification on these foundational elements.

Gregg
Messages
452
Reaction score
0
In the notes it says that

\text{v}\cdot \nabla \text{u} = |\text{v}|\frac{du}{dl}

\text{v} = (a(x,y), b(x,y))

l is the arclength in the v-direction.

Why is this?

The LHS is the projection of v onto the gradient of u, the other thing is the magnitude of v, multiplied by the du/dl.
 
Physics news on Phys.org
Gregg said:
In the notes it says that

\text{v}\cdot \nabla \text{u} = |\text{v}|\frac{du}{dl}

\text{v} = (a(x,y), b(x,y))

l is the arclength in the v-direction.

Why is this?

The LHS is the projection of v onto the gradient of u, the other thing is the magnitude of v, multiplied by the du/dl.

l is the arclength of what in the v direction? And you haven't told us what u is. Nor what v represents. What we have here is an example of "guess the question". Since I have a bit of time on my hands, I will expound a bit about a question I think might be relevant.

Let ##u(x,y)## be a scalar field, perhaps the temperature at ##(x,y)##. Let a curve ##C## be given by ##\vec R(t) = \langle x(t), y(t)\rangle## represent the location of a moving particle. What if we want the rate of change of ##u## as the particle moves along ##C##? Well we have$$
\frac{du}{ds}=\frac{du}{dt}\frac{dt}{ds}=
(u_x\frac {dx}{dt}+ u_y\frac{dy}{dt})\frac{dt}{ds}$$Multiply both sides by$$
\frac{ds}{dt}=\frac 1 {\frac{dt}{ds}}$$to get$$
\frac{du}{ds}\frac{ds}{dt}=u_x\frac {dx}{dt}+ u_y\frac{dy}{dt}=
\nabla u\cdot \frac {d\vec R}{dt}= \nabla u\cdot \vec V$$

where ##\vec V## is the velocity of the particle. Since ##v = \frac{ds}{dt}=|\vec V|## is its speed, this can be written$$
|\vec V|\frac{du}{ds}=\nabla u\cdot \vec V$$This looks a lot like your result, using ##s## instead of ##l## for arc length. There may be a more direct way of getting the result but, hey, I'm not even sure I worked the problem you were thinking about.
 
Last edited:
It is the derivation for characteristic projections in PDEs. First order linear PDE with the form

## a(x,y) u_x + b(x,y) u_y + c(x,y) u = d(x,y) ##

##v \cdot \nabla u + c u = d \Rightarrow |v| \frac{du}{dl} + cu = d ##

So I have looked at what you wrote, you have parameterised it so that s is the position or arc length along some curve C?
 
Gregg said:
It is the derivation for characteristic projections in PDEs. First order linear PDE with the form

## a(x,y) u_x + b(x,y) u_y + c(x,y) u = d(x,y) ##

##v \cdot \nabla u + c u = d \Rightarrow |v| \frac{du}{dl} + cu = d ##

So I have looked at what you wrote, you have parameterised it so that s is the position or arc length along some curve C?

Yes. Now, I am not a PDE expert so I'm not going to comment directly on your PDE question. I do suspect, though, that if you look at and understand what I have done, it will likely apply to your context. Good luck with it.
 

Similar threads

  • · Replies 9 ·
Replies
9
Views
2K
  • · Replies 9 ·
Replies
9
Views
3K
Replies
5
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 1 ·
Replies
1
Views
1K
Replies
10
Views
3K
Replies
7
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K