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1

XFEM as an Alternative for the Classicalh-refinement

bySafdar Abbas & Thomas-Peter Fries

USNCCMJuly 17, 2009

2

The XFEM as an Alternative for h-Adaptivity

• Enrichment functions for high gradient solutions.

• Optimal set of enrichment functions.

• Stationary high gradient developing over time.

• Moving high gradient (position known a priori).

• Moving high gradient (position not known).

• Moving high gradient in 2D (position known a priori)..

• Conclusions.

• Future outlook.

3

The XFEM as an Alternative for h-Adaptivity

• Enrichment functions for high gradient solutions.

• Optimal set of enrichment functions.

• Stationary high gradient developing over time.

• Moving high gradient (position known a priori).

• Moving high gradient (position not known).

• Moving high gradient in 2D (position known a priori)..

• Conclusions.

• Future outlook.

4

Enrichment Functions for High Gradient Solutions

• Motivation: Standard FEM (No Stabilization)

5

Enrichment Functions for High Gradient Solutions

• Motivation: Stabilized FEM (SUPG Stabilization)

6

Enrichment Functions for High Gradient Solutions

• XFEM approximation.

– Standard finite element approximation.

– Enrichment.

W

W

s

• Instead of stabilization and/or refinement we want to enrich the

approximation space.

7

Enrichment Functions for High Gradient Solutions

• Enrichment Functions

– Weak discontinuity Abs-Enrichment

– Strong discontinuity Sign/Heaviside Enrichment

8

Enrichment Functions for High Gradient Solutions

• Enrichment functions–Regularized sign function [Patzak and Jirasek, 2003] ( C4 continuous at ).

9

The XFEM as an Alternative for h-Adaptivity

• Enrichment functions for high gradient solutions.

• Optimal set of enrichment functions.

• Stationary high gradient developing over time.

• Moving high gradient (position known a priori).

• Moving high gradient (position not known).

• Moving high gradient in 2D (position known a priori)..

• Conclusions.

• Future outlook.

10

Optimal Set of Enrichment Functions

Can be integrated

Can be captured

by FEM

Interpolation Problem:Interpolated function fInterpolating functions Ψ = [ψ1, ψ2, ψ3]

Find ∫ ωuh = ∫ ωf, for ω ∈ Ψ, where uh = ∑ ψiui= ΨΤuminimize the error |f – uh|

11

Enrichment Functions for High Gradient Solutions

• An optimal set of 7 enrichment functions.

• Enrichment functions are relative to the element size.

12

Enrichment Functions for High Gradient Solutions

• An optimal set of 7 enrichment functions.

• Enrichment functions are relative to the element size.

13

The XFEM as an Alternative for h-Adaptivity

• Enrichment functions for high gradient solutions.

• Optimal set of enrichment functions.

• Stationary high gradient developing over time.

• Moving high gradient (position known a priori).

• Moving high gradient (position not known).

• Moving high gradient in 2D (position known a priori)..

• Conclusions.

• Future outlook.

14

Stationary High Gradient Developing Over Time

• First test case: In-stationary Burger’s Equation with stationary high gradientthat develops over time.

– Time-Stepping for the temporal discretization.

– Non-linear term is linearized using Newton-Raphson iterations.

– Diffusion coefficient is very small.

– No stabilization is used.

– Position of the highest gradient is known and stationary.

15

Stationary High Gradient Developing Over Time

XFEM Results

(No Stabilization)

16

Stationary High Gradient Developing Over Time

17

The XFEM as an Alternative for h-Adaptivity

• Enrichment functions for high gradient solutions.

• Optimal set of enrichment functions.

• Stationary high gradient developing over time.

• Moving high gradient (position known a priori).

• Moving high gradient (position not known).

• Moving high gradient in 2D (position known a priori)..

• Conclusions.

• Future outlook.

18

Moving High Gradient (position known a priori)

• Second test case: In-stationary linear advection equation with moving high

gradient specified as an initial condition.

– Time stepping is not fully appropriate.

– Equation is discretized using Space-Time discretization with

Discontinuous-Galerkin in time.

– No stabilization is used.

– Position of the highest gradient known a priori at each time.

19

Moving High Gradient (position known a priori)

XFEM Results

(No stabilization)

20

The XFEM as an Alternative for h-Adaptivity

• Enrichment functions for high gradient solutions.

• Optimal set of enrichment functions.

• Stationary high gradient developing over time.

• Moving high gradient (position known a priori).

• Moving high gradient (position not known).

• Moving high gradient in 2D (position known a priori)..

• Conclusions.

• Future outlook.

21

Moving High Gradient (position not known)

• Third test case: In-stationary Burger’s Equation with unknown position ofthe highest gradient.

– Level-set function is transported using transport equation for the level-set.

– Equation is discretized using Space-Time discretization withDiscontinuous-Galerkin in time.

– Non-linear term is linearized using Newton-Raphson iterations.– Diffusion coefficient is very small.– No stabilization is used.– Position of the highest gradient in each time step is found iteratively by

a strong coupling loop.

22

Moving High Gradient (position not known)

Strong Coupling

Solution ofBurger’s Equation

Solution ofTransportEquation

Solution ofBurger’s Equation

Solution ofTransportEquation

tn tn+1

23

Moving High Gradient (position not known)

XFEMResultsSpace-Timeview

24

Moving High Gradient (position not known)

FEMResults

25

Moving High Gradient (position not known)

XFEMResults

26

The XFEM as an Alternative for h-Adaptivity

• Enrichment functions for high gradient solutions.

• Optimal set of enrichment functions.

• Stationary high gradient developing over time.

• Moving high gradient (position known a priori).

• Moving high gradient (position not known).

• Moving high gradient in 2D (position known a priori).

• Conclusions.

• Future outlook.

27

Moving High Gradient in 2D (position known a priori).

• Fourth test case: A high gradient scalar function transported in a circular

velocity field.

28

Moving High Gradient in 2D (position known a priori).

2d Advectionequation

(No stabilization)

29

The XFEM as an Alternative for h-Adaptivity

• Enrichment functions for high gradient solutions.

• Optimal set of enrichment functions.

• Stationary high gradient developing over time.

• Moving high gradient (position known a priori).

• Moving high gradient (position not known).

• Moving high gradient in 2D (position known a priori)..

• Conclusions.

• Future outlook.

30

Conclusions

• A complete range of gradients is captured using an optimal set of high

gradient enrichment functions.

• No oscillations are observed near the high gradient.

• Solution quality is better than that achieved from stabilization without

refining the mesh.

31

The XFEM as an Alternative for h-Adaptivity

• Enrichment functions for high gradient solutions.

• Optimal set of enrichment functions

• Stationary high gradient developing over time.

• Moving high gradient (position known a priori).

• Moving high gradient (position not known).

• Moving high gradient in 2D (position known a priori)..

• Conclusions.

• Future outlook.

32

Future Outlook

• Using the optimal set of enrichment functions to simulate the cohesive

cracks in quasi-brittle materials.

33

Financial support from the DeutscheForschungsgemeinschaft (German ResearchAssociation) through grant GSC 111 is gratefullyacknowledged.

Acknowledgements

34

Thanks for your Attention

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