17
QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. • Need to extend idea of a gradient (df/dx) to 2D/3D functions • Example: 2D scalar function h(x,y) • Need “dh/dl” but dh depends on direction of dl (greatest up hill), define dl max as short distance in this direction • Define • Direction, that of steepest slope CP3 Revision: Vector Calculus

Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Embed Size (px)

Citation preview

Page 1: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

• Need to extend idea of a gradient (df/dx) to 2D/3D functions

• Example: 2D scalar function h(x,y)

• Need “dh/dl” but dh depends on direction of dl (greatest up hill), define dlmax as short distance in this direction

• Define

• Direction, that of steepest slope

CP3 Revision: Vector Calculus

Page 2: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

So if is along a contour line

Is perpendicular to contours, ie up lines of steepest slope

And if is along this direction

The vector field shown is of

Vectors always perpendicular to contours

Magnitudes of vectors greatest where slope is steepest

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Page 3: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Del

Page 4: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Grad

“Vector operator acts on a scalar field to generate a vector field”

Example:

Page 5: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Grad Example: Tangent Planes

• Since is perpendicular to contours, it locally defines direction of normal to surface

• Defines a family of surfaces (for different values of A)

• defines normals to these surfaces

• At a specific point

tangent plane has equation

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Page 6: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Conservative Fields

In a Conservative Vector Field

Which gives an easy way of evaluating line integrals: regardless of path, it is difference of potentials at points 1 and 2.

Obvious provided potential is single-valued at the start and end point of the closed loop.

Page 7: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Div

“Vector operator acts on a vector field to generate a scalar field”

Example

Page 8: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Divergence Theorem

V

S

Oover closed outer surface S enclosing V

Page 9: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Divergence Theorem as aid to doing complicated surface

integrals• Example

y

z

x

• Evaluate Directly

• Tedious integral over and (exercise for student!) gives

Page 10: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Using the Divergence Theorem

• So integral depends only on rim: so do easy integral over circle

• as always beware of signs

Page 11: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Curl

“Vector operator acts on a vector field to generate a vector field”Example

Magnitude

Direction: normal to plane which maximises the line integral.

Can evaluate 3 components by taking

areas with normals in xyz directions

Page 12: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Key Equations

Page 13: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Simple Examples

Radial fields have zero curl

Rotating fields have curl in direction of rotation

Page 14: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Example

•So this is a conservative field, so we should be able to find a potential

• All can be made consistent if

• Irrotational and conservative are synonymous becauseby Stokes Theorem

Page 15: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Stokes Theorem• Consider a surface S, embedded in a

vector field

• Assume it is bounded by a rim (not necessarily planar)

OUTER RIM SURFACE INTEGRAL OVER ANY

SURFACE WHICH SPANS RIM

Page 16: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

Example

quarter circle

(0,1,0) yx

z

(0,0,1)

C1

C3

C2

• Check via direct integration

Page 17: Need to extend idea of a gradient (df/dx) to 2D/3D functions Example: 2D scalar function h(x,y) Need “dh/dl” but dh depends on direction of dl (greatest

2nd-order Vector Operators

Lecture 11

meaningless

Laplace’s Equation is one of the most important in physics