Generalized Eigenvalue Problem in FEM Modelling of the ...typically, we are not interested in all...

Generalized Eigenvalue Problem in FEMModelling of the Resonance Frequencies

Piezoelectric ResonatorsP. Ralek

Department of Modelling of Processes,

Faculty of Mechatronics and Interdisciplinary Engineering Studies,

Technical University in Liberec, Czech Republic

SNA Ostrava 2005

Generalized Eigenvalue Problem in FEM Modelling of the Resonance Frequencies Piezoelectric Resonators – p.1/16

Introduction

Motivation:

efficient numerical computing of resonance frequencies of piezoelectricresonators, which would be possible for large problems (complicated shapes)

why modelling? - analytical method have restricted area of their usage

Solving:* physical description of the piezoelectric material

* application of FEM

* large sparse linear algebraic system, which defines the generalized eigenvalueproblem

resonance frequencies are subsequently found by solving this algebraic problem

typically, we are not interested in all eigenvalues (resonance frequencies)⇒ for determining of several of them we consider iterative methods

Introduction

Motivation:efficient numerical computing of resonance frequencies of piezoelectricresonators, which would be possible for large problems (complicated shapes)

Introduction

Solving:

* physical description of the piezoelectric material

Introduction

Physical formulation

linear piezoelectric constitutive equations:

generalized Hook’s law

Tij = cijkl Skl − dkij Ek, i, j = 1, 2, 3, (1)

equation of the direct piezoelectric effect

Dk = dkij Sij + εkj Ej, k = 1, 2, 3. (2)

symmetric stress tensor T, symmetric strain tensor S,vector of intensity of electric field E, vector of electric displacement D

cijkl, dkij , εij ... material tensors (c is symmetric in all four indices and PD, d issymmetric in last two indices and ε is symmetric and PD)

linear piezoelectric constitutive equations:

generalized Hook’s law

Tij = cijkl Skl − dkij Ek, i, j = 1, 2, 3, (1)

equation of the direct piezoelectric effect

Dk = dkij Sij + εkj Ej, k = 1, 2, 3. (2)

symmetric stress tensor T, symmetric strain tensor S,vector of intensity of electric field E, vector of electric displacement D

cijkl, dkij , εij ... material tensors (c is symmetric in all four indices and PD, d issymmetric in last two indices and ε is symmetric and PD)

Sij =1

+∂uj

, Ek = −∂ϕ

, i, j, k = 1, 2, 3,

u = (u1, u2, u3)T is the displacement vector and ϕ is the electric potential

governing equation for piezoelectric continuum

%∂2ui

∂t2=

∂Tij

i = 1, 2, 3, x ∈ Ω, t ∈ (0, T), (3)

∇. D =∂Dj

= 0, (4)

with density %, volume of the resonator Ω and its boundary Γ.

Sij =1

+∂uj

, Ek = −∂ϕ

, i, j, k = 1, 2, 3,

u = (u1, u2, u3)T is the displacement vector and ϕ is the electric potential

governing equation for piezoelectric continuum

%∂2ui

∂t2=

∂Tij

i = 1, 2, 3, x ∈ Ω, t ∈ (0, T), (3)

∇. D =∂Dj

= 0, (4)

with density %, volume of the resonator Ω and its boundary Γ.

(1) + (2) + (3) + (4) ⇒

%∂2ui

∂t2=

+∂ul

i = 1, 2, 3, (5)

0 =∂

+∂uj

−εkj

initial conditions, Dirichlet boundary conditions and Neumann boundaryconditions are added:

ui(., 0) = ui, x ∈ Ω, ui = 0, x ∈ Γu, Tijnj = fi, x ∈ Γf , i = 1, 2, 3, (7)

ϕ(., 0) = ϕ, ϕ = ϕD, x ∈ Γϕ, Dknk = q, x ∈ Γq,

whereΓu ∪ Γf = Γ, Γu ∩ Γf = ∅, Γϕ ∪ Γq = Γ, Γϕ ∩ Γq = ∅.

(1) + (2) + (3) + (4) ⇒

%∂2ui

∂t2=

+∂ul

i = 1, 2, 3, (5)

0 =∂

+∂uj

−εkj

initial conditions, Dirichlet boundary conditions and Neumann boundaryconditions are added:

ui(., 0) = ui, x ∈ Ω, ui = 0, x ∈ Γu, Tijnj = fi, x ∈ Γf , i = 1, 2, 3, (7)

ϕ(., 0) = ϕ, ϕ = ϕD, x ∈ Γϕ, Dknk = q, x ∈ Γq,

whereΓu ∪ Γf = Γ, Γu ∩ Γf = ∅, Γϕ ∪ Γq = Γ, Γϕ ∩ Γq = ∅.

Right-hand side fi represents mechanical excitation by external mechanicalforces, q denotes electrical excitation by imposing surface charge (in the case offree oscillations, they are both zero

Equations (5)-(6) define the problem of harmonic oscillation of the piezoelectriccontinuum under given conditions (7)

We will discretize the problem using FEM:

* standard weak formulation, H0, using boundary conditions

* discretization using the linear Lagrange finite elements in 3D (with GMSH code)

* system of ODEs for unknown values of u, ϕ in nodes of discretization results(our c++ code)

Discretization of the problem, BC

MU + KU + PTΦ = F,

PU − EΦ = Q.

after introduction of Dirichlet boundary conditions, sub-matrices M, K and E aresymmetric and positive definite

Discretization of the problem, BC

MU + KU + PTΦ = F,

PU − EΦ = Q.

after introduction of Dirichlet boundary conditions, sub-matrices M, K and E aresymmetric and positive definite

Point of interest

resonance ⇐ frequency of excitation = eigenfrequency of the resonator

eigenfrequencies - free harmonic oscillation

K − ω2M PT

P −E

where ω is the frequency of oscillation

eigenfrequencies can be computed by solving the generalized eigenvalueproblem

AX = λBX (8)

P −E

, λ = ω2,

A being symmetric and B being symmetric and positive semi-definite matrix

Point of interest

K − ω2M PT

P −E

AX = λBX (8)

P −E

, λ = ω2,

Point of interest

K − ω2M PT

P −E

AX = λBX (8)

P −E

, λ = ω2,

Numerical solution

for solving the generalized eigenvalue problem (8), we use implicitly restartedArnoldi method implemented in Arpack library (Fortran code)

inner steps in the process use algorithm SYMMLQ for solving the symmetricnon-definite linear systems

partial eigenvalue problem with possibility of shift

the method solves the partial eigenvalue problem (computes severaleigenvalues with high precision)

deals with the sparseness of the matrices

static condensation, i.e. to transform the problem (8) to the positive definite eigenvalue problem

K?U = λMU, K

?= K− P

TE−1

this approach was used in [Maryska, Novak, Ra - ECMS 03]

it losts the sparseness of the matrices; generalized Schur decomposition

Numerical solution

K?U = λMU, K

?= K− P

TE−1

Numerical solution

K?U = λMU, K

?= K− P

TE−1

Numerical solution

K?U = λMU, K

?= K− P

TE−1

Numerical solution

K?U = λMU, K

?= K− P

TE−1

Numerical solution

K?U = λMU, K

?= K− P

TE−1

Numerical solution

K?U = λMU, K

?= K− P

TE−1

Numerical solution

what is the shift:

we can focust to wanted part of the spectra - time and memory saving, higherprecision

Numerical solution

what is the shift:

we can focust to wanted part of the spectra - time and memory saving, higherprecision

Oscillation of planparallel quartz resonator

shear vibration mode in x direction

rrmountingmounting

u=0u=0electrodes

three different samples

sample R (mm) r (mm) h (mm) res. freq.

1 7 3.5 0.333 5 MHz2 3.975 2.5 0.168 10 MHz3 3.475 1.5 0.0833 20 MHz

Oscillation of planparallel quartz resonator

shear vibration mode in x direction

rrmountingmounting

u=0u=0electrodes

three different samples

sample R (mm) r (mm) h (mm) res. freq.

1 7 3.5 0.333 5 MHz2 3.975 2.5 0.168 10 MHz3 3.475 1.5 0.0833 20 MHz

Results

comparison of measured and computed resonance frequencies:

sample measured res. frequency (kHz) computed res. frequency (kHz)

1 5000.200 50802 10000.125 101043 19990.700 20100

Convergence of computed resonance frequency

(sample 1)

50 100 150 200 250 300 350 400 450 500 550 600

number of elements

resonance frequency 5 Mhz

Results

comparison of measured and computed resonance frequencies:

sample measured res. frequency (kHz) computed res. frequency (kHz)

1 5000.200 50802 10000.125 101043 19990.700 20100

Convergence of computed resonance frequency

(sample 1)

50 100 150 200 250 300 350 400 450 500 550 600

number of elements

resonance frequency 5 Mhz

Results

rezidual in Arnoldi algorithm and # of inner iteration in SYMMLQ

30 110 142 165 184 357 427 588

N_iter_SYMMLQ

rezidual about 10−13 in worst case

Results

rezidual in Arnoldi algorithm and # of inner iteration in SYMMLQ

30 110 142 165 184 357 427 588

N_iter_SYMMLQ

rezidual about 10−13 in worst case

Postprocessing

visulization in GMSH

problems with recognition of vibrational modes - which are the right?

Postprocessing

Conclusion

numerical alhorithm using Krylov subspace method brings fast and efficient toolfor solving the GEP and the resonance frequencies

handling with the system matrices is more simple and it saves their sparsestructure

computing is much faster (depending on the problem and its discretization)

* about 100 times faster than methods working with dense matrices and solvingthe full eigenproblems - Lapack etc... (moreover, they are not usable for largerproblems)

* about 10 times faster than black boxes working with sparse matrices - Matlabetc...

What to focust on:

postprocessing

feedback with reality

physicians usually know, what should result and why; focust on practicalproblems

Conclusion

What to focust on:

postprocessing

Conclusion

What to focust on:

postprocessing

Conclusion

What to focust on:

postprocessing

Conclusion

What to focust on:

postprocessing

Conclusion

What to focust on:

postprocessing

Conclusion

What to focust on:

postprocessing

Conclusion

What to focust on:

postprocessing

Conclusion

What to focust on:

postprocessing

Generalized Eigenvalue Problem in FEM Modelling of the ...typically, we are not interested in all...

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