Engineering Math: Lecture Notes on Gradient, Divergence, and Surface Normals, Lecture notes of Engineering Mathematics

A portion of lecture notes from a university course in engineering mathematics (mat 247) taught by hakkı ulaş unal at anadolu university, turkey. The notes cover topics such as the gradient operator, properties of gradients, directional derivatives, surface normals, and the divergence of a vector field.

Typology: Lecture notes

2018/2019

Uploaded on 04/13/2019

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MAT 247 Engineering Mathematics
Hakkı Ula¸s ¨
Unal
Dept. of Electrical-Electronics Eng.
Anadolu University, Turkey
October 3, 2018
MAT 247 Eng. Math. October 3, 2018 1 / 12
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MAT 247 Engineering Mathematics

Hakkı Ula¸s Unal¨ Dept. of Electrical-Electronics Eng. Anadolu University, Turkey

October 3, 2018

Today

1 Gradient Operator:Review

(^2) Properties of gradient

(^3) Divergence of a Vector field

Some Review on Gradient Operator:

Difference between scalar and vector fields:

-14.5562 -42.

-14.

-14.

12.^

(^00 1 2 3 )

1

2

B A^ A

gradf = ∂f ∂x

i + ∂f ∂y

j,

∂f ∂x ∂f : Rate of change along^ x^ direction for fixed^ y: ∂y : Rate of change along^ y^ direction for fixed^ x: What about moving from A to B, say A is fixed and B varying, however, it is parallel to unit vector?

Example

Find the directional derivative of f (x, y, z) = 2x^2 + 3y^2 + z^2 at the point A in the direction of b = i − 2 k.

Direction of maximum increase

Let f (P ) = f (x, y, z) be a scalar function having continuos partial derivatives in some domain in the space

∇f = ∂f ∂x

i + ∂f ∂y

j + ∂f ∂z

k,

Direction of maximum increase

Let f (P ) = f (x, y, z) be a scalar function having continuos partial derivatives in some domain in the space

∇f = ∂f ∂x

i + ∂f ∂y

j + ∂f ∂z

k,

Then, the directional derivative

Dbf = (^) ds df (x(s), y(s), z(s)) = b·∇f = |b||∇f | cos θ,

where θ is a positive angle btw ∇f and b. Then, Dbf = |gradf |

Gradients as a surface normal vector

Lemma

Suppose f (x, y, z) is a scalar field and let f (x, y, z) = c, where c is constant, and let P (x, y, z) be a particular point on the surface. Then, gradf , if it is non-zero at P , is a normal vector to the level surface f = c at P.

Gradients as a surface normal vector

Lemma

Suppose f (x, y, z) is a scalar field and let f (x, y, z) = c, where c is constant, and let P (x, y, z) be a particular point on the surface. Then, gradf , if it is non-zero at P , is a normal vector to the level surface f = c at P.

Proof

Suppose that r(t) = [x(t), y(t), z(t)] represents a curve C passing through P and lying on the level surface f = c. Then, r(t) must satisfy

f (x(t), y(t), z(t)) = c.

Example

Find a unit normal vector for the curve described as

log(x^2 + y^2 ) − 4 = 0,

at P = (2, 0).

Divergence of a Vector field

Let v(x, y, z) be a differentiable vector function, where x, y, z are Coordinates and let v 1 , v 2 , v 3 are components of v.

div v = ∂v^1 ∂x

  • ∂v^2 ∂y

  • ∂v^3 ∂z

is called the divergence of v.

Curl of a Vector field

Let v(x, y, z) = [v 1 , v 2 , v 3 ] = v 1 i + v 2 j + v 3 k be a differentiable vector function, where x, y, z are Coordinates, and v 1 , v 2 , v 3 are components of v. Then the curl of the vector function v is defined as

curlv = ∇ × v =

i j k ∂ ∂x

∂ ∂y

∂ ∂z v 1 v 2 v 3

∂v 3 ∂y

− ∂v^2 ∂z

i +

∂v 1 ∂z

− ∂v^3 ∂x

j +

∂v 2 ∂x

− ∂v^1 ∂y

k.

Example

Find curlv and curl curlv, where v = (x + z, x + y, y + z).