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Optimal internal stabilization of the linear system of elasticity

Abstract

We consider the nonlinear optimal design problem which consists in finding the best position and shape of the internal viscous damping set for the stabilization of the linear system of elasticity. Since non-existence of classical designs is usual in this context, a relaxation of the original problem is proposed. Then, the relaxed problem is solved numerically. Finally, a penalization technique to recover quasi-optimal classical designs from the relaxed ones and the over-damping phenomenon are analyzed in several numerical experiments.

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Optimal internal stabilization of the linear system of elasticity

Author: Münch, Arnaud; Pedregal Tercero, Pablo; Periago Esparza, Francisco
Year: 2007
Source: https://idus.us.es/bitstreams/f7366a3e-1c9f-4093-a671-e109c3a5b3a0/download
XX Cong eso de Ecuaciones Di e enciales y Aplicaciones
X Cong eso de Ma em´
a ica Aplicada
Se illa, 24-28 sep iemb e 2007
(pp. 1–8)
Op imal in e nal s abiliza ion o he linea sys em o
elas ici y
A. M¨
unch1, P. Ped egal2, F. Pe iago3
1Labo a oi e de Ma h´ema iques de Besan¸con, Uni e si ´e de F anche-Com ´e, UMR CNRS 6623, 16,
ou e de G ay 25030 Besan¸con, F ance. E-mail: [email p o ec ed].
2Dp o. de Ma em´a icas, ETSI Indus iales, Uni e sidad de Cas illa-La Mancha, 13071 Ciudad Real.
E-mail: [email p o ec ed].
3Dp o. de Ma em´a ica Aplicada y Es ad´ıs ica, ETSI Indus iales, Uni e sidad Poli ´ecnica de Ca agena,
30203 Ca agena. E-mail: [email p o ec ed].
Palab as cla e: Relaxa ion, s abiliza ion, sys em o elas ici y, nonlinea op imal design, g adien
descen me hod.
Resumen
We conside he nonlinea op imal design p oblem which consis s in inding he
bes posi ion and shape o he in e nal iscous damping se o he s abiliza ion o
he linea sys em o elas ici y. Since non-exis ence o classical designs is usual in his
con ex , a elaxa ion o he o iginal p oblem is p oposed. Then, he elaxed p oblem is
sol ed nume ically. Finally, a penaliza ion echnique o eco e quasi-op imal classical
designs om he elaxed ones and he o e -damping phenomenon a e analyzed in
se e al nume ical expe imen s.
1. P oblem o mula ion
Conside he ollowing nonlinea op imal design p oblem:
(P) ´ın
ω∈ΩL
J(Xω) = 1
2ZT
0ZΩ³¯¯u0¯¯
2+σ(u) : ε(u)´dxd (1)
whe e o a ixed 0 < L < 1,
ΩL={ω⊂Ω : |ω|=L|Ω|} ,
1
A. M¨unch, P. Ped egal, F. Pe iago
|ω|and |Ω|being he Lebesgue measu e o ωand Ω, espec i ely, and uis he solu ion o
he elas ici y sys em







u00 − ∇x·σ+a(x)Xω(x)u0= 0 in (0, T)×Ω,
u= 0 on (0, T)×Γ0,
σ·n= 0 on (0, T)×Γ1,
u(0,·) = u0,u0(0,·) = u1in Ω.
(2)
As usual,
ε=ε(u) = 1
2³∇xu+ (∇xu)T´(3)
is he linea ized s ain enso and
σ=σ(u) = (σij =aijklεkl) (4)
he s ess enso . The coe icien s aijkl ∈W1,∞(Ω), i, j, k, l = 1,· · · , N, a e such ha
aijkl =aklij =ajikl and aijklεijεkl ≥αεijεij in Ω (5)
o some ixed α > 0. Mo eo e , Xωis he cha ac e is ic unc ion o ω, ∇x·is he di e gence
ope a o conside ed wi h espec o he spa ial a iable x, n= (n1,· · · , nN) is he ou wa d
uni no mal ec o o Γ1,0< T ≤ ∞,and a=a(x)∈L∞(Ω) is a damping po en ial
sa is ying
a(x)≥a0>0 a. e. x∈ω.
As o he physical meaning o sys em (2), he dissipa i e e m a(x)Xω(x)u0is usually
e e ed in he li e a u e as a iscous damping because i is caused o he iscosi y o he
medium in which he ib a ions o he sys em ake place. F om an enginee ing iewpoin ,
his e m may also be seen as a eedback con ol mechanism which measu es he eloci y o
ib a ions, h ough use o senso s, and ac s on he sys em acco dingly o hese measu es
by means o ac ua o s. In his sense, Xωindica es he place and shape o senso s and
ac ua o s. I is hen na u al and e y impo an in p ac ise o analyze he ques ion o
de e mining he bes posi ion and shape o senso s and ac ua o s ha minimize he ene gy
o he sys em o e a ime in e al. This is ou p oblem (P).
2. Relaxa ion
As shown ecen ly by he au ho s o he case o he wa e equa ion [4, 5] (see also [2, 3]
o some ela ed wo ks), (P) is usually ill-posed in he sense ha he e is no minimize
in he class o cha ac e is ic unc ions. Then, a ull elaxa ion o he o iginal p oblem was
ca ied ou by using a sui able ep esen a ion o di e gence- ee ec o ields which enables
o ans o m he o iginal p oblem in o a non-con ex, ec o a ia ional one.
The aim o his wo k is o ex end he esul s in [4, 5] o he case o he sys em o linea
elas ici y. Howe e , ou app oach he e does no equi e he in oduc ion o auxilia y po en-
ials associa ed wi h di e gence- ee ec o ields. Ins ead o hose, we use di -cu l Young
measu es as gi en by [7]. This makes he ea men much mo e di ec and dimension-
independen . P ecisely, conside he elaxed p oblem
(RP) ´ın
s∈L∞(Ω) J(s) = ZT
0ZΩ³¯¯u0¯¯
2+σ(u) : ε(u)´dxd (6)
2
Op imal in e nal s abiliza ion o he elas ici y sys em
whe e usol es he new sys em







u00 − ∇x·σ+a(x)s(x)u0= 0 in (0, T)×Ω,
u= 0 on (0, T)×Γ0,
σ·n= 0 on (0, T)×Γ1,
u(0,·) = u0,u0(0,·) = u1in Ω,
(7)
and now he compe ing unc ions ssa is y he poin -wise and olume cons ain s
0≤s(x)≤1 and ZΩ
s(x)dx =L|Ω|.(8)
Ou main heo e ical esul ollows.
Theo em 1 Assume ha he ini ial da a o sys em (2) ha e he egula i y
(u0,u1)∈³¡H2(Ω)¢N∩V0´×V0.(9)
Then (RP)is a ull elaxa ion o (P)in he sense:
(i) The e a e op imal solu ions o (RP ).
(ii) The minimum o (RP )equals he in imum o (P).
(iii) Minimizing sequences o (P)a e eco e ed by i s -o de lamina es wi h any no mal
in space and independen o ime.
Fo a ull p oo o his esul we e e o [6]. Ne e heless, a ew commen s on i a e
now in o de . Fi s , he egula i y condi ion (9) on he ini ial da a is a su icien condi ion
in o de o a oid concen a ion o ene gy phenomena and he e o e his enables us o
use he Young measu e heo y o compu e he cos limi o a minimizing sequence o
p oblem (P). Second, we will show la e on ha o some alues o he damping po en ial
a he e is a nume ical e idence ha p oblem (P) is ill-posed. This jus i ies he elaxa ion
s a ed in poin s (i) and (ii) abo e. Finally, in wha conce ns poin (iii), i ells us how
he mic os uc u e o he op imal damping designs looks like. This in o ma ion is codi ied
by he op imal Young measu e associa ed wi h he elaxed p oblem (RP). In ac , om
his i can be p o ed ha i Xωjis a minimizing sequence o (P), hen he associa ed
displacemen s ujcon e ge o he op imal displacemen u o he elaxed p oblem (RP)
in a s ong sense.
3. Nume ical esolu ion o p oblems (P)and (RP )
3.1. Algo i hm o minimiza ion
We p opose a i s -o de g adien descen me hod o sol e (RP). P ecisely, we de ine
he descen di ec ion
s1(x) = −µa(x)ZT
0
u0( , x)·p( , x)d +γ¶,∀x∈Ω,(10)
3
A. M¨unch, P. Ped egal, F. Pe iago
whe e he mul iplie γis de e mined so ha o any unc ion η∈L∞(Ω,R+), wi h η6= 0,
and ||s+ηs1||L1(Ω) =L|Ω|we ha e Jγ(s+ηs1)≤Jγ(s) o
Jγ(s) = J(s) + γ||s||L1(Ω).(11)
This leads o ake
γ=(RΩs(x)dx −L|Ω|)−RΩη(x)a(x)RT
0u0( , x)·p( , x)d dx
RΩη(x)dx .(12)
As o p, his is he solu ion o he adjoin p oblem







p00 − ∇x·σ(p)−a(x)s(x)p0=u00 +∇x·σ(u),in (0, T)×Ω,
p= 0,on (0, T)×Γ0,
p·n= 0,on (0, T)×Γ1,
p(T, ·) = 0,p0(T, ·) = u0(T, ·) in Ω.
(13)
A las , he unc ion ηis chosen so ha s(x) + η(x)s1(x)∈[0,1], o all x∈Ω. A
simple and e icien choice consis s in aking η(x) = ²s(x)(1 −s(x)) o all x∈Ω wi h ²a
small eal posi i e.
Consequen ly, he descen algo i hm o sol e nume ically he elaxed p oblem (RP)
may be s uc u ed as ollows : le Ω ⊂RN, (u0,u1)∈((H2(Ω))N∩V0)×V0,L∈(0,1),
T > 0, and ² < 1, ²1<< 1 be gi en :
Ini ializa ion o he densi y unc ion s0∈L∞(Ω; ]0,1[);
Fo k≥0, i e a ion un il con e gence (i.e. |J(sk+1)−J(sk)| ≤ ²1|J(s0)|) as ollows :
•Compu a ion o he solu ion usko (7) and hen he solu ion psko (13), bo h
co esponding o s=sk.
•Compu a ion o he descen di ec ion sk
1de ined by (10) whe e he mul iplie
γkis de ined by (12).
•Upda e he densi y unc ion in Ω:
sk+1 =sk+²sk(1 −sk)sk
1(14)
wi h ε∈R+small enough in o de o ensu e he dec ease o he cos unc ion
and sk+1 ∈L∞(Ω,[0,1]).
3.2. Nume ical expe imen s
Nex , we p esen some nume ical simula ions o N= 2 and he uni squa e Ω = (0,1)2.
Fo simplici y, we conside he case Γ0=∂Ω and assume ha Ω is composed o an iso opic
homogeneous ma e ial o which
aijkl =λδijδkl +µ(δikδjl +δilδjk).
λ > 0 and µ > 0 a e he Lam´e coe icien s and δdesigna es he K onecke symbol. The
s ess enso becomes simply: σ(u) = λ (∇x·u)IN×N+ 2µε(u).
4
Op imal in e nal s abiliza ion o he elas ici y sys em
Sys ems (7) and (13) a e sol ed in space using a C0- ini e elemen me hod and he ime
disc e iza ion is pe o med in a s anda d way using cen e ed ini e di e ences o o de wo.
Wi hou loss o gene ali y, we conside a cons an damping unc ion a(x) = aXΩ(x) in Ω
since he dependence in xis con ained in he densi y s. We ea he simple condi ions :
u0= (sin(πx1) sin(πx2),sin(πx1) sin(πx2)),u1= (0,0).(15)
Resul s a e ob ained wi h h= 10−2,²1= 10−5,L= 10−1,T= 1, s0(x) = Lon Ω and
²= 10−2(see he algo i hm).
3.2.1. In luence o he damping cons an alue a
Nume ical simula ions exhibi a bi u ca ion phenomenon wi h espec o he alue o
he damping cons an a. When his alue is small enough, he op imal densi y is always a
cha ac e is ic unc ion which sugges s ha he o iginal p oblem (P) is well-posed. On he
o he hand, o ala ge enough i appea s ha he op imal densi y akes alues s ic ly in
(0,1). In his case, he ill-posedness is ela ed o he o e -damping phenomenon : when
m´ınωa(x)goes o in ini y, he damping e m a(x)Xωac s as penaliza ion e m and en o ces
he solu ion u o be cons an in ime in ω: a he limi , he e is no mo e dissipa ion in ω
(and so in Ω) and he ene gy is cons an (see also [1]). In o de o a oid his phenomenon
(which hus appea s i as(x) is oo la ge), he densi y smus ake (a leas locally) alues
lowe han 1 in o de o compensa e a. As a esul , (P) is no mo e well-posed. This jus i ies
he in oduc ion o he elaxed p oblem (RP ).
Fo (λ, µ) = (1/2,1), Figu e 1 depic s he iso- alues o he op imal densi y sop -
ob ained a he con e gence o he algo i hm - o se e al alues o a.
3.2.2. F om op imal elaxed designs o quasi-op imal classical designs
In he case whe e he op imal densi y sop is no in L∞((0, T)×Ω; {0,1}), one may
associa e o sop a cha ac e is ic unc ion spen ∈L∞((0, T )×Ω; {0,1}) whose cos J(spen)
is a bi a ily nea o J(sop ). Following [5], one may p oceed as ollows: we i s decompose
he domain (0,1)×(0,1) in o M×Ncells such ha Ω = ∪i=1,M [xi, xi+1]×∪j=1,N [yj, yj+1]
whe e {xi}(i=1,M+1) and {yj}(j=1,N+1) designa e wo uni o m subdi isions o he in e al
(0,1). Then, we associa e o each cell he mean alue mi,j ∈[0,1] de ined by
mi,j =1
(xi+1 −xi)(yj+1 −yj)Zxi+1
xiZyj+1
yj
sop (x, y)dx dy (16)
A las , we de ine he unc ion spen
M,N in L∞(Ω,{0,1}) by
spen
M,N (x, y) =
M
X
i=1
N
X
j=1
X[xi,(1−√mi,j )xi+√mi,j xi+1]×[yj,(1−√mi,j )yj+√mi,j yj+1](x, y).(17)
We easily check ha ||spen
M,N ||L1(Ω) =||sop ||L1(Ω), o all M, N > 0. Thus, he cha ac e is ic
unc ion spen
M,N akes ad an age o he in o ma ion codi ied in he densi y sop .
Le us illus a e his poin wi h he op imal densi y ob ained o (λ, µ) = (1/2,1)
and a= 50 (see Figu e 1 bo om igh ). The co esponding alue o he cos unc ion is
J(sop )≈2,0883. Table 1 collec s he alue o J(spen
M,N ) o se e al alues o M=Nand
sugges s he con e gence o J(spen
M,N ) owa d J(sop )≈2,0883 as Ninc eases.
5

A. M¨unch, P. Ped egal, F. Pe iago
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Figu a 1: T= 1, (λ, µ) = (1/2,1), a(x) = aXΩ(x) - Iso- alue o he op imal densi y sop
on Ω o a= 5 ( op le ), a= 10 ( op igh ), a= 25 (bo om le ) and a= 50 (bo om
igh ).
6
Op imal in e nal s abiliza ion o he elas ici y sys em
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E( )
N=1
N=2
N=5
N=16
Figu a 2: T= 1, (λ, µ) = (1/2,1), a(x) = 50XΩ(x) - Iso- alue o he penalized densi y o
N= 2, N= 5 and N= 16 - Bo om igh :E( ) s. associa ed o spen
N,N .
7
A. M¨unch, P. Ped egal, F. Pe iago
N1 2 3 4 5 6 7 16 N→ ∞
J(spen
N,N ) 3.824 3.261 2.446 2.238 2.161 2.137 2.109 2.096 2.0883
Tabla 1: (λ, µ) = (1/2,1), T= 1 - a= 50- Value o he cos unc ion o he penalized
cha ac e is ic densi y.
Ag adecimien os
The second au ho is suppo ed by p ojec s MTM2004-07114 om Minis e io de Edu-
caci´on y Ciencia (Spain), and PAI05-029 om JCCM (Cas illa-La Mancha). The hi d
au ho is suppo ed by p ojec s MTM2004-07114 om Minis e io de Educaci´on y Ciencia
(Spain) and 00675/PI/04 om Fundaci´on S´eneca (Gobie no Regional de Mu cia).
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