Definition of the Partial Derivative
∂f/∂x = (ε->0)lim f(x+ε, y, z) - f(x,y,z) / ε
-it is the derivative with respect to one variable whilst treating all other variables as constants
Exact Derivative
Definition
df = ∂f/∂x dx + ∂f/∂y dy + ∂f/∂z dz
The Chain Rule
x, y, z as functions of s
-let x, y, z be continuously differentiable functions of s, then:
df/ds = ∂f/∂x dx/ds + ∂f/∂y dy/ds + ∂f/∂z dz/ds
The Chain Rule
x, y, z as functions of u, v, w
∂f/∂u = ∂f/∂x ∂x/∂u + ∂f/∂y ∂y/∂u + ∂f/∂z ∂z/∂u
∂f/∂v = ∂f/∂x ∂x/∂v + ∂f/∂y ∂y/∂v + ∂f/∂z ∂z/∂v
∂f/∂w = ∂f/∂x ∂x/∂w + ∂f/∂y ∂y/∂w + ∂f/∂z ∂z/∂w
Simple Differentiation of Vectors
-consider a vector |F that is a function of a single variable t:
|F(t) = f1(t)e1 + f2(t)e2 + f3(t)e3
-for fixed cartesian axes {e1/e2/e3} we have:
d|F/dt = df1/dt e1 + df2/dt e2 + df3/dt e3
Simple Differentiation of Vectors - Notes
i) d|F/dt is a vector
ii) the equation for simple differentiation of vectors only applies to constant basis vectors (i.e. fixed axes), if e1, e2, e3 also change with t then they also have to be differentiated
iii) obvious generalisation for higher derivatives
Tangent Vectors
- the curve with position vector |r(s) where s is a parameter increasing along the curve, has tangent vector d|r.ds
- hence the unit tangent vector is (d|r/ds) / | d|r/ds |
Field Definition
- a scalar or vector that is a function of position is called a field
e. g. temperature is a scalar field
Contours
- in 2D, fields can be represented by contours
- contours are curves of equal value of the field
- in 3D contours are curved surfaces defined by T(|r)=T0
- this is a surface that can be written in the form f(x,y,z)=constant
Vector Fields
- an example of a vector field is wind speed which can be written |u(|r)
- vector fields can be represented by arrows with size and direction representing ||u| and |u^
Gradient of a Scalar Field
-if f(x,y,z) is a continuously differentiable scalar field, then its “gradient”, written grad f = ∇f is defined as:
∇f = ∂f/∂x e1 + ∂f/∂y e2 + ∂f/∂z e3
= (∂f/∂x, ∂f/∂y, ∂f,∂z)
Notes on Grad
i) grad f is a vector
ii) ∇(f + g) = ∇f + ∇g
Geometric Interpretation of Grad
Formula
-consider a scalar field f(|r)
-the change in f on moving from |r to (|r+d|r)is found from the exact derivative:
df = ∂f/∂x dx + ∂f/∂y dy + ∂f//∂z dz -> a scalar product
df = (∂f/∂x, ∂f/∂y, ∂f/∂z) . (dx, dy, dz)
df = (∇f) . d|r
Geometric Interpretation of Grad
Case 1: d|r parallel to contour
- consider a contour of f passing through a point at |r, let d|r lie in the tangent plane of the contour
- then df=0 as you move along the contour as f is constant along the contour
- > (∇f) . d|r = 0
- hence d|r is perpendicular to ∇f
- so ∇f is normal to all vectors in the tangent plane of a contour -> ∇f is normal to any surface of constant f
Geometric Interpretation of Grad
Case 2: d|r perpendicular to the contour
-let d|r be perpendicular to the contour of f
-let d|r = n^ds where ds is the magnitude of d|r and n^ is a unit normal to the contour
-> df = (∇f) . n^ ds
-but ∇f is also normal to the contour so (∇f) . n^ = |∇f||n|
-> df = |∇f| ds
|∇f| = df/ds
-so ∇f is the rate of change of f in the direction in which f is changing most rapidly
-the magnitude and direction of ∇f are coordinate invariant
Directional Derivative
Equation
df/ds = u^ . ∇f
Directional Derivative
Derivation
-the directional derivative of a field, f, in the direction of unit vector u^, can be found by substituting into the grad formula: df = (∇f) . d|r -in this case we take d|r = u^ ds -where ds is the magnitude of dr df = (∇f) . u^ ds -the dot product commutes df/ds = u^ . ∇f
Directional Derivative
Notes
-the directional derivative of a scalar field is a scalar field
The Del Operator
-∇ is an operator that operates on functions to produce other functions
∇ = e1 ∂/∂x + e2 ∂/∂y + e3 ∂/∂z
-this is a vector differential operator called ‘del’, and its symbol is called nabla
-the del operator is coordinate invariant
The Del Operator and Grad
-we can interpret grad f as the result of operating with ∇ on s scalar field f ro produce a vector field
Divergence
Definition
-the divergence of a field
|F(|r) = (F1(|r), F2(|r), F3(|r)) is defined:
div F = ∂F1/∂x + ∂F2/∂y + ∂F3/∂z
The Del Operator and Divergence
div F = ∇ . F
Divergence
Derivation
div F = ∇ . F =
(∂/∂x, ∂/∂y, ∂/∂z) . (F1, F2, F3)
=∂F1/∂x + ∂F2/∂y + ∂F3/∂z
Divergence
Notes
- the divergence of a vector field is a scalar field
- ∇ is also a linear operator so ∇.(F+G)=∇.F + ∇.G
- a field |F for which ∇.F=0 is called ‘incompressible’ OR ‘solenoidal’
