The Finite Element Method A Practical Course

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Transcript The Finite Element Method A Practical Course

The Finite Element Method

A Practical Course

CHAPTER 5: FEM FOR 2D SOLIDS

CONTENTS

   INTRODUCTION LINEAR TRIANGULAR ELEMENTS – Field variable interpolation – Shape functions construction – – Using area coordinates Strain matrix – Element matrices LINEAR RECTANGULAR ELEMENTS – – – – – Shape functions construction Strain matrix Element matrices Gauss integration Evaluation of

m

e

CONTENTS

 LINEAR QUADRILATERAL ELEMENTS – – – – Coordinate mapping Strain matrix Element matrices Remarks  HIGHER ORDER ELEMENTS  COMMENTS (GAUSS INTEGRATION)  CASE STUDY

INTRODUCTION

 2D solid elements are applicable for the analysis of plane strain and plane stress problems.

 A 2D solid element can have a rectangular or quadrilateral shape with curved edges.

triangular , straight or  2D solid element can deform only in the plane of the 2D solid.

 At any point, there are two components in

x

and directions for the displacement as well as forces.

y

INTRODUCTION

 For plane strain problems, the thickness of the element is unit , but for plane stress problems, the actual thickness must be used.

 In this course, it is assumed that the element has a uniform thickness

h

.

 Formulating 2-D elements with given variation of thickness is also straightforward, as the procedure is the same as that for a uniform element.

2D solids – plane stress and plane strain Plane stress Plane strain

LINEAR TRIANGULAR ELEMENTS

 Less accurate than quadrilateral elements  Used by most mesh generators for complex geometry  Linear triangular element Triangular elements Nodes

y, v

1 (

x

1

, y

1 ) (

u

1 ,

v

1 ) 3 (

x

3

, y

3 ) (

u

3 ,

v

3 )

f sy A f sx

2 (

x

2

, y

2 ) (

u

2 ,

v

2 )

x, u

Field variable interpolation

U

h

N

( , )

d

e

where

N

  

N

1 0

d

e

     

u v u v

  

u v

2 3 1 1 2 3            displaceme   displaceme displaceme nts nts at node 2 nts at node at node 1 3

y, v

0

N

1

N

0 2 0

N

2

N

0 3 0

N

3   Node 1 Node 2 Node 3 (Shape functions) 1 (

x

1

, y

1 ) (

u

1 ,

v

1 ) 3 (

x

3

, y

3 ) (

u

3 ,

v

3 )

f sy A f sx

2 (

x

2

, y

2 ) (

u

2 ,

v

2 )

x, u

Shape functions construction

Assume,

N

1   1 1  1

N

2 

a

2  2  2

N

3   3 3  3

N i

 

i i

i

or

i

= 1, 2, 3

N i

  1

x

p

T y

a

 

b i

   

p

T

Shape functions construction

Delta function property:

i

( ,

j

Solving,

j

) Therefore, 1 for 0 for

i i

 

j j

1 ( , 1 1 1 ( , 2 2 )  0 3 )  0 1 1 ( , 1 1 ) 1 ( , 2 2 )   1   1

b x

1 1

b x

1 2  

c y

1 1

c y

1 2  1  0 ( , 3 3 )   1

b x

1 3 

c y

1 3  0

a

1 

x y

2 3 

x y

3 2 ,

b

1 2

A e

y

2 

y

3 ,

c

1  2

A e x

3 

x

2 2

A e

Shape functions construction

A e

 1 2

P

 1 1 1 2 1

x

1

x

2

x

3

y

1

y

2

y

3  1 2 [(

x y

2 3 

x y

3 2 Area of triangle Moment matrix

y

2 

y x

3 ) 1  (

x

3  2 ) ] 1 Substitute

a

1 ,

b

1 and

c

1 back into

N

1

= a

1

+ b

1

x + c

1

y

:

N

1  1 2

A e

[(

y

2 

y

3 )(

x

x

2

x

3 

x

2 )(

y

y

2 )]

Shape functions construction

Similarly, 2 ( , 1 1 )  0 2 ( , 2 2 2 ( , 3 3 )  0 3 ( , 2 1 )  0 2 )  0 3 ( , 3 3

N

2  1 2

A e

[(

x y

3 1 

x y

1 3  1 2

A e

[(

y

3 

y

1 )(

x

x

3

y

3 

y x

1 )  (

x

1 

x y

3 ) ]

x

1 

x

3 )(

y

y

3 )]

N

3  1 2

A e

[(

x y

1 2 

x y

1 1  1 2

A e

[(

y

1 

y

2 )(

x

x

1

y

1 

y x

2 )  (

x

2 

x y

1 ) ]

x

2 

x

1 )(

y

y

1 )]

Shape functions construction

N

i

 

i i

i

where

a i

 1 2

A e

(

x y j k

x y k j

)

b i

 1 2

A e

(

y j

y k

)

c i

 1 2

A e

(

x k

x j

)

i J

= 1, 2, 3 ,

k

permutation

k

= 3, 1

k

determined from cyclic

i i

= 1, 2

j j

= 2, 3

Using area coordinates

 Alternative method of constructing shape functions

y i,

1  2-3-P:

P k

, 3

A

1

A

1  1 1 1 2 1

x x

2

y y

2  1 2 [(

x y

2 3 

x y

3 2

x

3

y

3

L

1 

A

1

A e

Similarly,  3-1-P

A

2

y

2 

y x

3 )  (

x

3 

x y

2 ) ]

L

2 

A

2  1-2-P

A

3

A e A

3

j

, 2

L

3 

A e x

Using area coordinates

Partitions of unity:

L

1 

L

2 

L

3  1

L

1 

L

2 

L

3 

A

1 

A e A

2

A e

A

3

A e

A

1 

A

2 

A

3

A e

 1 Delta function property: e.g.

L

1 = 0 at if

P

at nodes 2 or 3 Therefore,

N

1 

L

1 ,

N

2 

L

2 ,

N

3 

L

3

U

h

N

( , )

d

e

Strain matrix

xx

yy

xy

     

x v

u y

 

u y

  

v x

 

LU

 

LU B

LN

          

x

0  

y

LNd

e

Bd

e

0  

y

 

x

       

N

 where

L

          

x

0  

y

 0  

y

x

       

B

   

b

1 0 

c

1 0

c

1

b

1

b

2 0

c

2 0

c

2

b

2

b

3 0

c

3 0

c

3

b

3     (constant strain element)

Element matrices

k

e

 

V e T

B cB

d

V

A e

  0

h T

B cB

d

A

 

A e h T

B cB

d

A

Constant matrix 

k

e

hA e T

B cB m

e

 

V e

T

N N

d

V

A e

  0

h

d

z

T

N N

d

A

 

A e h

T

N N

d

A

Element matrices

For elements with uniform density and thickness,

m

e

h

 

A e

       

N N

1 0

N N

2 1 0

N N

3 1 0 1 0

N N

1 1 0 0

N N

3 1 1

N N

1 2 0

N N

2 2 0

N N

3 2 0 0

N N

1 2 0 0

N N

3 2 2

N N

1 3 0

N N

2 3 0

N N

3 3 0 0

N N

1 3 0 0

N N

3 3 3         d

A

Eisenberg and Malvern (1973): 

A L m

1

L n

2

L

3

p

d

A

 (

m

m

!

n

!

p

!

n

p

 2 )!

2

A

Element matrices

m

e

 

hA

12          2 0 2

sy

.

1 0 2 0 1 0 2 1 0 1 0 2 0   1 0 1     0   2 

y, v

1 (

x

1

, y

1 ) (

u

1 ,

v

1 ) 3 (

x

3

, y

3 ) (

u

3 ,

v

3 )

f sy A f sx

2 (

x

2

, y

2 ) (

u

2 ,

v

2 )

x, u

f

e

l

N

T

f f

    d

l

Uniform distributed load:

f

e

 1 2

l

2  3        

f f f

0 0

f y x y x

       

LINEAR RECTANGULAR ELEMENTS

 Non-constant strain matrix  More accurate representation of stress and strain  Regular shape makes formulation easy

Shape functions construction

Consider a rectangular element

d

e u

 

u

1 2

v u v u

2 3   3    displacements at node 1 displacements at node 2 displacements at node 3  displacements at node 4

y, v

4 (

x

4 ,

y

4 ) (

u

4 ,

v

4 )

2b

1 (

x

1 ,

y

1 ) (

u

1 ,

v

1 )

2a

  3 (

x

3 ,

y

3 ) (

u

3 ,

v

3 )

f sy f sx

2 (

x

2 ,

y

2 ) (

u

2 ,

v

2 )

x, u

Shape functions construction

4 (  1, +1) (

u

4 ,

v

4 )

y, v

 4 (

x

4 ,

y

4 ) (

u

4 ,

v

4 )

2b

1 (

x

1 ,

y

1 ) (

u

1 ,

v

1 )

2a

 3 (

x

3 ,

y

3 ) (

u

3 ,

v

3 )

f sy f sx

2 (

x

2 ,

y

2 ) (

u

2 ,

v

2 )

2

1 (  1,  1)

2

(

u

1 ,

v

1 )

x, u

 

x

 (

x

2

a

x

1 ) / 2 ,  

y

 (

y

2

b

y

1 ) / 2   3 (1, +1) (

u

3 ,

v

3 ) 2 (1,  1) (

u

2 ,

v

2 )

U

h

N

( , )

d

e

where

N

N

1  0 Node 1 0

N

1

N

2 0 Node 2 0

N

2

N

3 0 Node 3 0

N

3

N

4 0 0

N

4    Node 4

Shape functions construction

N

1

N

2

N

3

N

4     1 4 ( 1   )( 1   ) 1 4 ( 1   )( 1   ) 1 4 ( 1   )( 1   ) 1 4 ( 1   )( 1   )

N j

 1 4 ( 1  

j

 )( 1  

j

 ) 4 (  1, +1) (

u

4 ,

v

4 )

N

3 at node 1

N

3 at node 2

N

3 at node 3

N

3 at node 4    1 4 (1   )(1   )     1 1 1 4 (1   )(1   )    1  1  0  0 1 4 (1   )(1   )     1 1  1  1 4 (1   )(1   )     1 1  0 Delta function property

2

1 (  1,  1)

2

(

u

1 ,

v

1 )  

i

4   1

N i

N

1 1 4 [(1   )(1 1 4 [2(1   

N

2   

N

3 

N

4  )(1   )(1    )(1   )]   Partition of unity 3 (1, +1) (

u

3 ,

v

3 ) 2 (1,  1) (

u

2 ,

v

2 )

Strain matrix

B

LN

4     1  

a

 0 1  

b

0   1   1

b

a

 1  

a

 0 1  

b

0  1 1  

b

 

a

1  

a

0 1  

b

0 1   1

b

 

a

 1  

a

0 1  

b

0  1   1

b

 

a

    Note: No longer a constant matrix!

Element matrices

 

x a

,  

y b

 d

x

d

y

=

ab

d  d  Therefore,

k

e

A

h

B

T

cB

d

A

   1   1  1  1

ab h

B

T

cB

d  d 

m

e

V

 

T

N N

d

V

A

 0

h

d

z

T

N N

d

A

A

h

T

N N

d

A

   1   1  1  1

abh

T

N N

 

Element matrices

f

e

l

N

T

f f

    d

l

For uniformly distributed load,

f

e

b

           0 0

f f f f

0 0

x y x y

          

y, v 2b

4 (

x

4 ,

y

4 ) (

u

4 ,

v

4 ) 1 (

x

1 ,

y

1 ) (

u

1 ,

v

1 )

2a

  3 (

x

3 ,

y

3 ) (

u

3 ,

v

3 )

f sy f sx

2 (

x

2 ,

y

2 ) (

u

2 ,

v

2 )

x, u

Gauss integration

 For evaluation of integrals in

k

e

and

m

e

(in practice) In 1 direction:

I

   1  1

f

(  )d  

j m

  1

w j f

( 

j

)

m

gauss points gives exact solution of polynomial integrand of

n

= 2

m

- 1 In 2 directions:

I

   1   1   1 1

f

i n x n

   1

j y

 1

w w f i j

 

i j

)

Gauss integration

m Gauss Point

j Gauss Weight w j

3 4 1 2 5 6 0 -1/  3, 1/  3  0.6, 0,  0.6

2 1, 1 5/9, 8/9, 5/9 -0.861136, -0.339981, 0.339981, 0.861136 -0.906180, -0.538469, 0, 0.538469, 0.906180 -0.932470, -0.661209, -0.238619, 0.238619, 0.661209, 0.932470 0.347855, 0.652145, 0.652145, 0.347855 0.236927, 0.478629, 0.568889, 0.478629, 0.236927 0.171324, 0.360762, 0.467914, 0.467914, 0.360762, 0.171324

Accuracy order

n

1 3 5 7 9 11

Evaluation of

m

e

m

e

 

hab

9             4 0 4

sy

.

2 0 4 0 2 0 4 1 0 2 0 4 2 0 4 0 1 0 0 2 0 4 2 0 1 0   2 0 4     0   2 0 1    

Evaluation of

m

e m ij

   

hab

  1   1  1  1 

hab

 16

hab

  1  1 ( 1  ( 1 1

N i

4 3  

i

N

i

j j d

d

 )( 1  )( 1  1 3 

j

 

i

j

)

d

 )   1  1 ( 1  

i

 )( 1  

j

 )

d

 E.g.

m

33  

hab

( 1  4 1 3  1  1 )( 1  1 3  1  1 )  4  

hab

9 Note: In practice, gauss integration is often used

LINEAR QUADRILATERAL ELEMENTS

 Rectangular elements have limited application  Quadrilateral elements with unparallel edges are more useful  Irregular shape requires coordinate mapping before using Gauss integration

Coordinate mapping

y

4 (

x

4 ,

y

4 ) 3 (

x

3 ,

y

3 ) 4 (  1, +1)  3 (1, +1)   1 (

x

1 ,

y

1 ) 2 (

x

2 ,

y

2 )

x

1 (  1,  1) 2 (1,  1) Physical coordinates Natural coordinates

U

h

N

 

d

e

X

  

N

 

x

e

(Interpolation of displacements) (Interpolation of coordinates)

Coordinate mapping

X

  

N

 

x

e

where

X

N

1

N

2

N

3

N

4     1 4 ( 1   )( 1   ) 1 4 ( 1   )( 1   ) 1 4 ( 1   )( 1   ) 1 4 ( 1   )( 1   ) ,

x

e x y x

1   1  

y

 

y x y

2 3 3 4 4  coordinate at node 1  coordinate at node 2 coordinate at node 3 coordinate at node 4

x

i

4   1

N i

(  ,  )

x i y

i

4   1

N i

(  ,  )

y i

Coordinate mapping

Substitute   1 into

x

i

4   1

x y

  1 2 1 2 (1   )

x

2 (1   )

y

2   1 2 1 2 (1   )

x

3 (1   )

y

3 or

N i

(  ,  )

x i x

y

 1 2 (

x

2 1 2 (

y

2  

x

3 )

y

3 )   1 2  (

x

3 1 2  (

y

3  

x

2

y

2 ) ) Eliminating  ,

y

 (

y

3 (

x

3  

y

2

x

2 ) ) {

x

 1 2 (

x

2 

x

3 )}  1 2 (

y

2 

y

3 )

y

4 (

x

4 ,

y

4 ) 3 (

x

3 ,

y

3 )  4 (  1, +1) 3 (1, +1)  1 (

x

1 ,

y

1 ) 2 (

x

2 ,

y

2 )

x

1 (  1,  1) 2 (1,  1)

Strain matrix

N i

  

N

 

i

  

N

x i

N

x i

x

  

x

    

N i

y

N i

y

y

  

y

  or       

N i

  

N

 

i

      

J

      

N i

x

N i

y

      where

J

     

x

  

x

  Since

X

  

y

  

y

      (Jacobian matrix) 

N

 

x

e

,

J

     

N

1   

N

1   

N

  2 

N

  2 

N

  3 

N

  3 

N

  4 

N

  4         

x x

2

x

1 3

x

4

y y y

3 1 2    

y

4

Strain matrix

Therefore,     

N i

x

N i

y

    

J

 1      

N

 

i

N

 

i

    (Relationship between differentials of shape functions w.r.t. physical coordinates and differentials w.r.t. natural coordinates) Replace differentials of

N i

with differentials of

N i

w.r.t.

x

w.r.t.  and and

y

B

LN

       0 

x

y

  0 

y

x

   

N

Element matrices

Murnaghan (1951) : d

A

=det |

J

| d  d 

k

e

   1   1  1  1

h

T

B cB

det

J m

e

 

V

 

N

T

N

d

V

A

 0

h

d

x

N

T

N

d

A

  1   1  1  1

h

N

T

N

det

J

d  d  

A

h

N

T

N

d

A

Remarks

 Shape functions used for interpolating the coordinates are the same as the shape functions used for the interpolation of the displacement field. Therefore, the element is called

isoparametric element

.

 Note that the shape functions for coordinate interpolation and displacement interpolation do not have to be the same.

 Using the different shape functions for coordinate interpolation and displacement interpolation, respectively, will lead to the development of so-called

superparametric

elements.

subparametric

or

HIGHER ORDER ELEMENTS

(

p

,0,0)  Higher order triangular elements (0,0,

p

)

n d

= (

p

+1)(

p

+2)/2 (1,0,

p

 1) (0,1,

p

 1) Node

i

,

I

(2,0,

p

 2) Argyris, 1968 :

L

1

L

2 (

p

 1,1,0)

i

(

I

,

J

,

K

)

L

3

K p N i

I I l L l

1

J J L l

2 )

K K

(

L

3 ) (0,

p

 1,1)

l

  (

L

 )  ( (

L

L

   

L

 0 )(

L

L

 0 )(

L

   

L

 1 )

L

 1 ) (

L

 (

L

  

L

 1) ) 

L

 (   1) ) (0,

p

,0)

HIGHER ORDER ELEMENTS

 Higher order triangular elements (Cont’d)

y, v

3

N

1

N

4   (2

L

1 4 2  1)

L

1 5 6 2 1 4 Quadratic element

x, u y, v

1 9 8 3 7 4 10 5 6

N

1  1 2 (3

L

1  1)(3

L

1  2)

L

1

N

4

N

 10 9 2 

L L

1 2 27 (3

L

1 

L L L

1 2 3 1) 2

x, u

Cubic element

HIGHER ORDER ELEMENTS

(0,

m

)  Higher order rectangular elements  Lagrange type: (Zienkiewicz et al., 2000) (

n

,

m

)

N i

 1

D N N

1

D J

l I n

l J m

i

(

I

,

J

) 0 

l k n

 (     0 )(  1 (    

k

 0 )(

k

 1 ) ) (   (  

k k k

 1  1 )(   )(  

k

k

 1

k

)  1 ) (   (

k

n

)  

n

) (0,0) (

n

,0)

HIGHER ORDER ELEMENTS

 Higher order rectangular elements(Cont’d) 4 7 3 J=2  J=1 8 9  6 (9 node quadratic element) J=0 1 I=0

N

1 

N

0 1

D N

2 

N

2 1

D N

3 

N

2 1

D N

4 

N

0 1

D N

0 1

D N

0 1

D N

2 1

D N

2 1

D

5 I=1 2 I=2  1 4  (1    1 4  (1   1 4  (1   )(1     1 4  (1   )(1    )  )

N

5 

N

1 1

D N

6 

N

2 1

D N

7 

N

1 1

D N

8 

N

0 1

D N

9 

N

1 1

D N

0 1

D N

1

N

1 2

D

1

D N

1 1

D N

1 1

D

  1 2 (1   )(1   )(1   1 2  (1   )(1   )(1   )  1 2 (1   )(1   )(1    1 2  (1   )(1   2 )(1   2 )

HIGHER ORDER ELEMENTS

  8  Higher order rectangular elements(Cont’d) Serendipity type: 4  =1 7  3 0   6 

N j N j N j

 1 4 (1   

j

)(1 

j j

j

 1)

j

 1, 2, 3, 4  1 2 (1   2 )(1   

j

)

j

 5, 7  1 2 (1   

j

)(1   2 )

j

 6, 8 1  =  1 5 2 (eight node quadratic element)

HIGHER ORDER ELEMENTS

 Higher order rectangular elements(Cont’d) 4 10  9 1 11 12 5 6 2 3 8  7

N j

 1 32 (1   

j

)(1 

j

2  9  2  10) for corner nodes

j

 1, 2, 3, 4

N j

 9 32 (1   

j

)(1   2 for side nodes

j

 

j

)  7, 8, 11, 12 where 

j N j

 9 32 (1   

j

)(1   2 )(1  9  

j

) for side nodes

j

 5, 6, 9, 10 where 

j

  1 and    1 3 and 

j j

  1 3   1 (twelve node cubic element)

ELEMENT WITH CURVED EDGES

3 3 5 5 6 6 2 2 4 4 1 1 4 1 8 7 5 3 2 6 8 1 4 7 3 6 5 2

COMMENTS (GAUSS INTEGRATION)

 When the Gauss integration scheme is used, one has to decide how many Gauss points should be used.

 Theoretically, for a one-dimensional integral, using

m

points can give the exact solution for the integral of a polynomial integrand of up to an order of (2

m

 1).

 As a general rule of thumb, more points should be used for higher order of elements.

COMMENTS (GAUSS INTEGRATION)

 Using smaller number of Gauss points tends to counteract the

over-stiff behaviour

associated with the displacement based method.

 Displacement in an element is assumed using shape functions. This implies that the deformation of the element is somehow prescribed in a fashion of the shape function.

This prescription gives a constraint to the element. The so constrained element behaves stiffer than it should be. It is often observed that higher order elements are usually softer than lower order ones. This is because using higher order elements gives less constraint to the elements.

COMMENTS (GAUSS INTEGRATION)

 Two gauss points for linear elements, and two or three points for quadratic elements in each direction should be sufficient for many cases.  Most of the explicit FEM codes based on explicit formulation tend to use one-point integration to achieve the best performance in saving CPU time.

CASE STUDY

 Side drive micro-motor

10N/m

CASE STUDY

10N/m 10N/m Elastic Properties of Polysilicon Young’s Modulus, E Poisson’s ratio,  Density,  169GPa 0.262

2300kgm -3

CASE STUDY

Analysis no. 1: Von Mises stress distribution using 24 bilinear quadrilateral elements (41 nodes)

CASE STUDY

Analysis no. 2: Von Mises stress distribution using 96 bilinear quadrilateral elements (129 nodes)

CASE STUDY

Analysis no. 3: Von Mises stress distribution using 144 bilinear quadrilateral elements (185 nodes)

CASE STUDY

Analysis no. 4: Von Mises stress distribution using 24 eight-nodal, quadratic elements (105 nodes)

CASE STUDY

Analysis no. 5: Von Mises stress distribution using 192 three-nodal, triangular elements (129 nodes)

Analysis no.

1 2 3 4 5

CASE STUDY

Number / type of elements Total number of nodes in model Maximum Von Mises Stress (GPa) 24 bilinear, quadrilateral 41 0.0139

96 bilinear, quadrilateral 129 0.0180

144 bilinear, quadrilateral 24 quadratic, quadrilateral 192 linear, triangular 185 105 129 0.0197

0.0191

0.0167