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Multi-Point Constraints

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Page 1: Multi-Point Constraintsmashayekhi.iut.ac.ir/sites/mashayekhi.iut.ac.ir/files/files_course/... · Multi-Point Constraints- Lagrange Multiplier Method ... Five bar truss with inclined

Multi-Point Constraints

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Multi-Point Constraints

Single point constraint examples

Multi-Point constraint examples

linear, homogeneous

linear, non-homogeneous

linear, homogeneous

linear, non-homogeneous

nonlinear, homogeneous

Multi-Point Constraints

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Modelling of joints

turbine blade

turbine disc nodes at

interface

(a) (b)

Perfect connection ensured here

Multi-Point Constraints (Example)

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u

v

u

v

1

Mismatch between DOFs of

beams and 2D solid – beam is

free to rotate (rotation not

transmitted to 2D solid)

1

Perfect connection by

artificially extending

beam into 2D solid

(Additional mass)

Modelling of joints

Multi-Point Constraints (Example)

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Using MPC equations

d1

d2

d3

d4 d6

d5

d7

2a disc model

blade model

d5

ad7

d2 d6

d1

1 5d d

2 6 7d d ad

3 5d d

4 6 7d d ad

Modelling of joints

Multi-Point Constraints (Example)

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Rigid

body

Node on neutral-

surface of the plate

Node of the beam element

Neutral surface

of the plate

Multi-Point Constraints (Example)

Creation of MPC equations for offsets

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Creation of MPC equations for offsets

d6 = d1 + d5 or d1 + d5 - d6 = 0

d7 = d2 - d4 or d2 - d4 - d7 = 0

d8 = d3 or d3 - d8 = 0

d9 = d5 or d5 - d9 = 0

Multi-Point Constraints (Example)

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Mesh for plate

Mesh for Solid

Similar for plate connected to 3D solid

Modelling of joints

Multi-Point Constraints (Example)

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u

v

900

Axis of symmetry

n

Axis of symmetry x

y

1

2

3

1

2

3

dn = 0

ui cos + vi sin=0

or ui+vi tan =0

for i=1, 2, 3

Modelling of symmetric boundary conditions

Multi-Point Constraints (Example)

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d1

Quad Linear

d2

d4

d5

d3 d6

0

-1

1

1

2

3

dx = 0.5(1-) d1 + 0.5(1+) d3

dy = 0.5(1-) d4 + 0.5(1+) d6

Substitute value of at node 2

0.5 d1 - d2 + 0.5 d3 =0

0.5 d4 - d5 + 0.5 d6 =0

Use lower order shape function to interpolate

Enforcement of mesh compatibility

Multi-Point Constraints (Example)

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d1

Quad Quad

d2 d6

d8

d5 d10

0

-1

1

d3

d4

d7

d9

-0.5

0.5

Use shape function of longer element to interpolate

dx = -0.5 (1-) d1 + (1+)(1-) d3 + 0.5 (1+) d5

Substituting the values of for the two additional nodes

d2 = 0.251.5 d1 + 1.50.5 d3 - 0.250.5 d5

d4 = -0.250.5 d1 + 0.51.5 d3 + 0.251.5 d5

Enforcement of mesh compatibility

Multi-Point Constraints (Example)

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d1

Quad Quad

d2 d6

d8

d5 d10

0

-1

1

d3

d4

d7

d9

-0.5

0.5

In x direction,

0.375 d1 - d2 + 0.75 d3 - 0.125 d5 = 0

-0.125 d1 + 0.75 d3 - d4 + 0.375 d5 = 0

In y direction,

0.375 d6- d7+0.75 d8- 0.125 d10 = 0

-0.125 d6+0.75 d8 - d9 + 0.375 d10 = 0

Enforcement of mesh compatibility

Multi-Point Constraints (Example)

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l1

l3

l2

q2 q1

d1 d2 d3 d4

Rigid slab

d1 = q1

d2 = q1+q2 l1

d3=q1+q2 l2

d4=q1+q2 l3

(l2 /l1-1) d1 - ( l2 /l1) d2 + d3 = 0

(l3 /l1-1) d1 - ( l3 /l1) d2 + d4 = 0

Eliminate q1 and q2

(DOF in x direction not considered)

Modelling of constraints by rigid body attachment

Multi-Point Constraints (Example)

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Sources of Multi-Point Constraints

Skew displacement BCs

Coupling nonmatched FEM meshes

Global-local and multiscale analysis

Incompressibility

Multi-Point Constraints

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MPC Application Methods

Master-Slave Elimination

Penalty Function Augmentation

Lagrange Multiplier Adjunction

Multi-Point Constraints

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Example 1D Structure to Illustrate MPCs

Multi-Point constraint:

Linear homogeneous MPC

Multi-Point Constraints

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Example 1D Structure to Illustrate MPCs

Multi-Point Constraints

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Master Slave Method for Example Structure

Recall:

Taking u as master:

Multi-Point Constraints- Master Slave Method

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Forming the Modified Stiffness Equations

Unconstrained master

stiffness equations:

Master-slave transformation:

Congruential transformation:

Modified stiffness equations:

Multi-Point Constraints- Master Slave Method

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Modified Stiffness Equations for Example Structure

u2 as master and u6 as slave DOF.

Multi-Point Constraints- Master Slave Method

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Modified Stiffness Equations for Example Structure

u6 as master and u2 as slave DOF.

Although they are algebraically equivalent, the latter would be

processed faster if a skyline solver is used for the modified equations.

Multi-Point Constraints- Master Slave Method

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Multiple MPCs

Suppose

take 3, 4 and 6 as slaves:

and put in matrix form:

Multi-Point Constraints- Master Slave Method

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Nonhomogeneous MPCs

In matrix form

Multi-Point Constraints- Master Slave Method

ˆ u Tu g

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Nonhomogeneous MPCs

modified system:

in which:

For the example structure

Multi-Point Constraints- Master Slave Method

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The General Case of MPCs

For implementation in general-purpose programs the master-slave method

can be described as follows. The degrees of freedoms in u are classified

into three types: independent or uncommitted, masters and slaves.

The MPCs may be written in matrix form as

Inserting into the partitioned stiffness matrix and symmetrizing

Multi-Point Constraints- Master Slave Method

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ADVANTAGES

exact if precautions taken

easy to understand

retains positive definiteness

important applications to model reduction

DISADVANTAGES

requires user decisions

messy implementation for general MPCs

sensitive to constraint dependence

restricted to linear constraints

Assessment of Master-Slave Method

Multi-Point Constraints- Master Slave Method

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Penalty Function Method, Physical Interpretation

Recall the example structure

under the homogeneous MPC

u2 = u6

Multi-Point Constraints- Penalty Function Method

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Penalty Function Method, Physical Interpretation

"penalty element" of axial rigidity w

Multi-Point Constraints- Penalty Function Method

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Penalty Function Method, Physical Interpretation

Upon merging the penalty element the modified stiffness equations are

This modified system is submitted to the equation solver.

Note that u retains the same arrangement of DOFs.

Multi-Point Constraints- Penalty Function Method

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Penalty Function Method - General MPCs

Premultiply both sides by

Scale by w and merge:

Multi-Point Constraints- Penalty Function Method

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Theory of Penalty Function Method - General MPCs

t CU Q (Constrain equations)

T T T1 1

2 2 U KU U F t t pΠ

=[1 2 ... m] is a diagonal matrix of ‘penalty numbers’

[ ]T T K C C U F C Q

stationary condition of the modified functional requires the derivatives of p

with respect to the Ui to vanish

Penalty matrix

Multi-Point Constraints- Penalty Function Method

p T TΠ

0d

KU F C CU + C Q 0

U

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Theory of Penalty Function Method - General MPCs

[Zienkiewicz et al., 2000] :

= constant (1/h)p+1

characteristic

size of element

p is the order of

element used

4 61.0 10 max (diagonal elements in the

stiffness matrix)

5 81.0 10

or

Young’s modulus

Multi-Point Constraints- Penalty Function Method

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ADVANTAGES

general application (inc' nonlinear MPCs)

easy to implement using FE library and standard assembler

no change in vector of unknowns

retains positive definiteness

insensitive to constraint dependence

DISADVANTAGES

selection of weight left to user

accuracy limited by ill-conditioning

the constraint equations can only be satisfied approximately.

Assessment of Penalty Function Method

Multi-Point Constraints- Penalty Function Method

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Lagrange Multiplier Method, Physical Interpretation

Multi-Point Constraints- Lagrange Multiplier Method

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Lagrange Multiplier Method

Because λ is unknown, it is passed to the LHS

and appended to the node-displacement vector:

This is now a system of 7 equations and 8 unknowns.

Needs an extra equation: the MPC.

Multi-Point Constraints- Lagrange Multiplier Method

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Lagrange Multiplier Method

Append MPC as additional equation:

This is the multiplier-augmented system. The new coefficient matrix

is called the bordered stiffness.

Multi-Point Constraints- Lagrange Multiplier Method

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IMPLEMENTATION OF MPC EQUATIONS

KU F

CU -Q 0 (Matrix form of MPC equations)

(Global system equation)

Constant matrices

Multi-Point Constraints- Lagrange Multiplier Method

Optimization problem for solution of nodal degrees of freedom:

Find U to

Minimize:

Subject to:

p

T T1

2 U KU U F

CU -Q 0

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Lagrange multiplier method

1 2 m

T

{ } 0T CU Q

{ }T T T1L

2 U KU U F CU Q

(Lagrange multipliers)

Multiplied to MPC equations

Added to functional

T

U FK C

λ QC 0

The stationary condition requires the derivatives of L with respect to the Ui and i to

vanish.

Matrix equation

is solved

Multi-Point Constraints- Lagrange Multiplier Method

Find U and to

Minimize:

TL0

d

L0

d

KU F C 0U

CU Q 0

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Lagrange Multiplier Method - Multiple MPCs

Three MPCs:

Recipe step #1:

append the

3 constraints

Recipe step #2:

append multipliers,

symmetrize

and fill

Multi-Point Constraints- Lagrange Multiplier Method

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E = 70 Gpa, A = 10-3 m2, P = 20 kN.

Multi-Point Constraints- Lagrange Multiplier Method

Example: Five bar truss with inclined support

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Multi-Point Constraints- Lagrange Multiplier Method

Example: Five bar truss with inclined support

(1) k

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Multi-Point Constraints- Lagrange Multiplier Method

Example: Five bar truss with inclined support

(2) k

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Multi-Point Constraints- Lagrange Multiplier Method

Example: Five bar truss with inclined support

(3) k

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Multi-Point Constraints- Lagrange Multiplier Method

Example: Five bar truss with inclined support

(4) k

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Multi-Point Constraints- Lagrange Multiplier Method

Example: Five bar truss with inclined support

(4) k

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Multi-Point Constraints- Lagrange Multiplier Method

Example: Five bar truss with inclined support

(5) k

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Multi-Point Constraints- Lagrange Multiplier Method

Example: Five bar truss with inclined support

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Multi-Point Constraints- Lagrange Multiplier Method

After adjusting for essential boundary conditions

Multipoint constraint due to inclined support at node 1:

The augmented global equations with the Lagrange multiplier are as follows.

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Multi-Point Constraints- Lagrange Multiplier Method

Solving the final system of global equations we get

Global to local transformation matrix

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Multi-Point Constraints- Lagrange Multiplier Method

Element nodal displacements in global coordinates

Element nodal displacements

in local coordinates lu

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ADVANTAGES

General application

Constraint equations are satisfied exactly

DISADVANTAGES

Difficult implementation

Total number of unknowns is increased

Expanded stiffness matrix is non-positive definite due to the

presence of zero diagonal terms

Efficiency of solving the system equations is lower

sensitive to constraint dependence

Assessment of Lagrange Multiplier Method

Multi-Point Constraints- Lagrange Multiplier Method

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MPC Application Methods: Assessment Summary

Multi-Point Constraints- Lagrange Multiplier Method

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References

1- Finite Element Method: A Practical Course by: S. S. Quek, G.R. Liu,

2003.

2- Introduction to Finite Element Methods, by: Carlos Felippa, University

of Colorado at Boulder .

http://www.colorado.edu/engineering/cas/courses.d/IFEM.d/