In
mathematics, the
directional derivative of a multivariate
differentiable function along a given
vector V at a given point P intuitively represents the instantaneous rate of change of the function, moving through P, in the direction of V. It therefore generalizes the notion of a
partial derivative, in which the direction is always taken parallel to one of the
coordinate axes.
The directional derivative is a special case of the Gâteaux derivative.
Definition
The directional derivative of a
scalar function along a vector
is the
function defined by the
limit
Sometimes authors write Dv instead of . If the function is differentiable at , then the directional derivative exists along any vector and one has
where the on the right denotes the gradient and is the Euclidean inner product. At any point , the directional derivative of intuitively represents the rate of change in along at the point . Usually directions are taken to be normalized, so is a unit vector, although the definition above works for arbitrary (even zero) vectors.
Properties
Many of the familiar properties of the ordinary
derivative hold for the directional derivative. These include, for any functions
f and
g defined in a
neighborhood of, and
differentiable at,
p:
In differential geometry
Let
M be a
differentiable manifold and
p a point of
M. Suppose that
f is function defined in a neighborhood of
p, and
differentiable at
p. If
v is a
tangent vector to
M at
p, then the
directional derivative of
f along
v, denoted variously as
(see
covariant derivative),
(see
Lie derivative), or
(see
Tangent space#Definition via derivations), can be defined as follows. Let γ : [-1,1] →
M be a differentiable curve with γ(0) =
p and γ
′(0) =
v. Then the directional derivative is defined by
This definition can be proven independent of the choice of γ, provided γ is selected in the prescribed manner so that γ'(0) =
v.
Normal derivative
A normal derivative is a directional derivative taken in the direction normal (that is, orthogonal) to some surface in space, or more generally along a normal vector field orthogonal to some hypersurface. See for example Neumann boundary condition. If the normal direction is denoted by , then the directional derivative of a function ƒ is sometimes denoted as .
In the continuum mechanics of solids
Several important results in continuum mechanics require the derivatives of vectors with respect to vectors and of tensors with respect to vectors and tensors. The
directional directive provides a systematic way of finding these derivatives.
The definitions of directional derivatives for various situations are given below. It is assumed that the functions are sufficiently smooth that derivatives can be taken.
Derivatives of scalar valued functions of vectors
Let
be a real valued function of the vector
. Then the derivative of
with respect to
(or at
) in the direction
is the
vector defined as
frac{partial f}{partial mathbf{v}}cdotmathbf{u} = Df(mathbf{v})[mathbf{u}]
= left[frac{d }{d alpha}~f(mathbf{v} + alpha~mathbf{u})right]_{alpha = 0}
for all vectors
.
Properties:
1) If then
2) If then
3) If then
Derivatives of vector valued functions of vectors
Let
be a vector valued function of the vector
. Then the derivative of
with respect to
(or at
) in the direction
is the
second order tensor defined as
frac{partial mathbf{f}}{partial mathbf{v}}cdotmathbf{u} = Dmathbf{f}(mathbf{v})[mathbf{u}]
= left[frac{d }{d alpha}~mathbf{f}(mathbf{v} + alpha~mathbf{u})right]_{alpha = 0}
for all vectors
.
Properties:
1) If then
2) If then
3) If then
Derivatives of scalar valued functions of second-order tensors
Let
be a real valued function of the second order tensor
. Then the derivative of
with respect to
(or at
) in the direction
is the
second order tensor defined as
frac{partial f}{partial boldsymbol{S}}:boldsymbol{T} = Df(boldsymbol{S})[boldsymbol{T}]
= left[frac{d }{d alpha}~f(boldsymbol{S} + alpha~boldsymbol{T})right]_{alpha = 0}
for all second order tensors
.
Properties:
1) If then
2) If then
3) If then
Derivatives of tensor valued functions of second-order tensors
Let
be a second order tensor valued function of the second order tensor
. Then the derivative of
with respect to
(or at
) in the direction
is the
fourth order tensor defined as
frac{partial boldsymbol{F}}{partial boldsymbol{S}}:boldsymbol{T} = Dboldsymbol{F}(boldsymbol{S})[boldsymbol{T}]
= left[frac{d }{d alpha}~boldsymbol{F}(boldsymbol{S} + alpha~boldsymbol{T})right]_{alpha = 0}
for all second order tensors
.
Properties:
1) If then
2) If then
3) If then
4) If then
References
See also