Topology Optimization of a Piezoelectric Loudspeaker Coupled with the Acoustic Domain
Transcript of Topology Optimization of a Piezoelectric Loudspeaker Coupled with the Acoustic Domain
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Topology Optimization of a PiezoelectricLoudspeaker Coupled with the Acoustic Domain
F. Wein, M. Kaltenbacher, F. Schury, E. Bansch, G. Leugering
WCSMO-803. June 2009
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Motivation
Overview
• Ersatz material/ “SIMP” optimization
• Piezoelectric-mechanical laminate coupled with acoustics
• Piezoelectric layer is design domain
Topics
• Acoustic optimization vs. structural approximation
• Self-penalized piezoelectric optimization without . . .• penalization (e.g. RAMP)• volume constraint• regularization (filtering)
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Piezoelectric-Mechanical Laminate
Bending due to inverse piezoelectric effect
Piezoelectric layer: PZT-5A, 5 cm×5 cm, 50 µm thick, ideal electrodes
Mechanicial layer: Aluminum, 5 cm×5 cm, 100 µm thick, no glue layer
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Coupling to Acoustic Domain
• Discretization of Ωair via cair = 343 m/s = λacf
• Dimension of Ωair determined by acoustic far field
• Fine discretization of Ωpiezo and Ωplate
• Non-matching grids Ωplate → Ωair-fine and Ωair-fine → Ωair-coarse
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Coupled Piezoelectric-Mechanical-Acoustic PDEs
PDEs: ρmu− BT(
[cE ]Bu + [e]T∇φ)
= 0 in Ωpiezo
BT(
[e]Bu− [εS ]∇φ)
= 0 in Ωpiezo
ρmu− BT [c]Bu = 0 in Ωplate
1
c2ψ −∆ψ = 0 in Ωair
1
c2ψ −A2 ψ = 0 in ΩPML
Interface conditions: n · u = −∂ψ∂n
on Γiface × (0,T )
σn = −n ρf ψ on Γiface × (0,T )
Full 3D FEM formulation (quadratic / linear with softening)
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Solid Isotropic Material with Penalization
• Sample reference: Kogl, Silva; 2005
• Design vector ρ (pseudo density)
• ρ = (ρ1 . . . ρne )T is piecewise constant within elements
• ρe ∈ [ρmin : 1] from void (ρmin) to full (1) material
• Replace piezoelectric material constants:
[cEe ] = ρe [cE ], ρm
e = ρeρm, [ee ] = ρe [e], [εS
e ] = ρe [εS ]
• Intermediate values are non-physical!• Small ρ → low stiffness• Large ρ → high piezoelectric coupling
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Linear Systems
• Piezoelectric-mechanical-acoustic couplingSψ ψ Cψ um 0 0
CTψ um
Sumum Sumup(ρ) 0
0 ST
umup(ρ) Supup(ρ) Kupφ(ρ)
0 0 KT
upφ(ρ) −Kφφ(ρ)
ψ(ρ)um(ρ)up(ρ)φ(ρ)
=
000qφ
• Piezoelectric-mechanical laminate Sumum Sumup (ρ) 0
STumup
(ρ) Supup (ρ) Kupφ(ρ)
0 KTupφ(ρ) −Kφφ(ρ)
um(ρ)
up(ρ)φ(ρ)
=
00qφ
• Harmonic excitation: S(ω) = K + jω(αKK + αMM)− ω2M
• Short form: S u = f
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Sound Power
• What one wants to optimize
Pac =1
2
∫Γopt
Rep v∗n dΓ
Sound power Pac, pressure p, normal particle velocity vn
• Acoustic impedance Z
Z (x) =p(x)
vn(x)
• Z can bee assumed to be constant on Γopt
• For plane waves• In the acoustic far field (some wavelengths)
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Optimizing for the Sound Power
Use∫
ΓoptRep v∗
n dΓ with Z = p/vn and u = (ψ um up φ)T
Optimization framework
• J = uTL u∗ with L selecting from u ≈ Sigmund, Jensen; 2003
∂J
∂ρe= 2 ReλT ∂S
∂ρeu where λ solves ST λ = −Lu∗
Acoustic optimization assume Z constant on Γopt
• Jac = ω2ψTLψ∗ with vn = p/Z and p = ρf ψ
• ≈ Duhring, Jensen, Sigmund; 2008
Structural optimization assume Z constant on Γiface
• Jst = ω2umTLu∗m with p = vn Z and v = u
• ≈ Du, Olhoff; 2007 (approximation is discussed!)
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Eigenfrequency Analysis
We want resonating structures, so consider eigenmodes
(a) 1. mode (b) 2./3. m (c) 4. mode (d) 5. mode
(e) 6. mode (f) 7./8. m (g) 9./10. m (h) 11. mode
• Only (a) and (e) can be excited electrically• Acoustic short circuits for all patterns but (a) and (e)
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Structural Optimization
• Objective function Jst = ω2umTLu∗m
• Several hundred mono-frequent optimizations
10-1100101102103104105
0 500 1000 1500 2000Obj
ectiv
e F
unct
ion
(m2 /s
2 )
Target Frequency (Hz)
Jst (max Jst)Jst (max Jac)
Jst (Sweep full plate)
• Robust shifting/ creation of resonances
• KKT-condition often not reached
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Validate Acoustic Approximation
• Validate Jac = ω2ψTLψ∗ against∫
ΓoptRep v∗
n dΓ
• Use one mesh (23 cm height)
10-1100101102103104105106107
0 500 1000 1500 200010-810-710-610-510-410-310-210-1100
Obj
ectiv
e F
unct
ion
(Pa2 )
Aco
ustic
Pow
er (
W)
Target Frequency (Hz)
Jac (Sweep full plate)Pac (Sweep full plate)
• Good approximation above 1000 Hz (0.64 wave length)
• Two antiresonances (acoustic short circuits)
• Approximation detects only one antiresonance!
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Acoustic Optimization
• Objective function Jac = ω2ψTLψ∗
10-1100101102103104105106107
0 500 1000 1500 200010-710-610-510-410-310-210-1100
Obj
ectiv
e F
unct
ion
(Pa2 )
Aco
ustic
Pow
er (
W)
Target Frequency (Hz)
Jac (max Jac)Pac (max Jst)
Jac (Sweep full plate)
• Jac avoids acoustic short circuits
• Structural approximation unfeasible (above first mode)
• Note Jac approximation unfeasible below 1000 Hz
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Grayness and Volumes
• Remember No penalization, no volume constraint
• Normalized grayness: g(ρ) = 4∫
Ω(1− ρ) ρ dx ,
0
0.05
0.1
0.15
0.2
0.25
0.3
0 500 1000 1500 2000
Grayness over Target Frequenzy (Hz)
g(Jst)g(Jac)
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 500 1000 1500 2000
Volume over Target Frequenzy (Hz)
Vol(Jst)Vol(Jac)
• Good avoidance of grayness
• Optimal volumes 25% . . . 100%
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Selected Results
(a) 565Hz (b) 575 Hz (c) 875 Hz (d) 975 Hz
(e) 985 Hz (f) 1405Hz (g) 1585 Hz (h) 2160 Hz
Legend: black = full material; white = void material
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Experimental Prototype (200 µm Piezoceramic)
(a) Original (b) Sputter (c) Lasing
(d) Temper (e) Polarize (f) Prototype
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
Conclusions and Future Work
Conclusions
• Structural approximation does not handle acoustic shortcircuits
• Piezoelectric-mechanical laminate allows optimization . . .• without penalization and regularization• without constraints (especially volume)
Future Work
• Use Taylor-Hood elements to compute p and v simultanuously
• Find suitable structural approximation
• Create more resonance patterns
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization
Motivation Model SIMP Objective Functions Numeriacal Results Conclusions
The End
Thank you for listening and for questions!
Fabian Wein Acoustic Piezoelectric Loudspeaker Optimization