Boundary Element Domain Decomposition Methods Challenges and Applications
|
|
- Emil York
- 8 years ago
- Views:
Transcription
1 Boundary Element Doman Decomposton Methods Challenges and Applcatons Olaf Stenbach Insttut für Numersche Mathematk Technsche Unverstät Graz SFB 404 Mehrfeldprobleme n der Kontnuumsmechank, Stuttgart n collaboraton wth U. Langer, G. Of, W. L. Wendland, W. Zulehner 1 / 23
2 Couplng of Fnte and Boundary Element Methods [Bettess, Kelly, Zenkewcz 77, 79; Brezz, Johnson, Nedelec 78; Brezz, Johnson 79; Johnson, Nedelec 80;...] 2 / 23
3 Couplng of Fnte and Boundary Element Methods [Bettess, Kelly, Zenkewcz 77, 79; Brezz, Johnson, Nedelec 78; Brezz, Johnson 79; Johnson, Nedelec 80;...] Symmetrc Couplng of Fnte and Boundary Element Methods [Costabel 87; Langer 94;...] 2 / 23
4 Couplng of Fnte and Boundary Element Methods [Bettess, Kelly, Zenkewcz 77, 79; Brezz, Johnson, Nedelec 78; Brezz, Johnson 79; Johnson, Nedelec 80;...] Symmetrc Couplng of Fnte and Boundary Element Methods [Costabel 87; Langer 94;...] Symmetrc Boundary Element Doman Decomposton Methods [Hsao, Wendland 90; Carstensen, Kuhn, Langer 98; OS 96;...] 2 / 23
5 Couplng of Fnte and Boundary Element Methods [Bettess, Kelly, Zenkewcz 77, 79; Brezz, Johnson, Nedelec 78; Brezz, Johnson 79; Johnson, Nedelec 80;...] Symmetrc Couplng of Fnte and Boundary Element Methods [Costabel 87; Langer 94;...] Symmetrc Boundary Element Doman Decomposton Methods [Hsao, Wendland 90; Carstensen, Kuhn, Langer 98; OS 96;...] Steklov Poncaré Operator Doman Decomposton Methods [Agoshkov, Lebedev 85; Hsao, Wendland 92; Hsao, Schnack, Wendland 99, 00; OS 03;...] 2 / 23
6 Couplng of Fnte and Boundary Element Methods [Bettess, Kelly, Zenkewcz 77, 79; Brezz, Johnson, Nedelec 78; Brezz, Johnson 79; Johnson, Nedelec 80;...] Symmetrc Couplng of Fnte and Boundary Element Methods [Costabel 87; Langer 94;...] Symmetrc Boundary Element Doman Decomposton Methods [Hsao, Wendland 90; Carstensen, Kuhn, Langer 98; OS 96;...] Steklov Poncaré Operator Doman Decomposton Methods [Agoshkov, Lebedev 85; Hsao, Wendland 92; Hsao, Schnack, Wendland 99, 00; OS 03;...] Hybrd Doman Decomposton Methods (Mortar, Three Feld, FETI) [Agouzal, Thomas 85; Bernard, Maday, Patera 85; Wohlmuth 01; Brezz, Marn 04; Farhat, Roux 91; Klawonn, Wdlund 01; Tosell, Wdlund 05;...] 2 / 23
7 Couplng of Fnte and Boundary Element Methods [Bettess, Kelly, Zenkewcz 77, 79; Brezz, Johnson, Nedelec 78; Brezz, Johnson 79; Johnson, Nedelec 80;...] Symmetrc Couplng of Fnte and Boundary Element Methods [Costabel 87; Langer 94;...] Symmetrc Boundary Element Doman Decomposton Methods [Hsao, Wendland 90; Carstensen, Kuhn, Langer 98; OS 96;...] Steklov Poncaré Operator Doman Decomposton Methods [Agoshkov, Lebedev 85; Hsao, Wendland 92; Hsao, Schnack, Wendland 99, 00; OS 03;...] Hybrd Doman Decomposton Methods (Mortar, Three Feld, FETI) [Agouzal, Thomas 85; Bernard, Maday, Patera 85; Wohlmuth 01; Brezz, Marn 04; Farhat, Roux 91; Klawonn, Wdlund 01; Tosell, Wdlund 05;...] Sparse Boundary Element Tearng and Interconnectng Methods [Langer, OS 03; Langer, Of, OS, Zulehner 05; Of 05] 2 / 23
8 Model Problem dv[α(x) u(x)] = f (x) for x Ω, u(x) = g(x) for x Γ = Ω Nonoverlappng Doman Decomposton Ω = p Ω, Ω Ω j = for j, Γ = Ω =1 3 / 23
9 Model Problem dv[α(x) u(x)] = f (x) for x Ω, u(x) = g(x) for x Γ = Ω Nonoverlappng Doman Decomposton Ω = p Ω, Ω Ω j = for j, Γ = Ω =1 Local Boundary Value Problems α u (x) = f (x) for x Ω, u (x) = g(x) for x Γ Γ Transmsson Boundary Condtons u (x) = u j (x), α n u (x) + α j n j u j (x) = 0 for x Γ j = Γ Γ j 3 / 23
10 Local Drchlet Boundary Value Problem α u (x) = f (x) for x Ω, u (x) = g (x) for x Γ = Ω 4 / 23
11 Local Drchlet Boundary Value Problem α u (x) = f (x) for x Ω, u (x) = g (x) for x Γ = Ω Representaton Formula for x Ω u (x) = U (x,y)t (y)ds y g (y) U (x,y)ds y + 1 n y α Γ Γ Ω U (x,y)f (y)dy Fundamental Soluton U (x,y) = 1 1 4π x y, t (y) = u (y), y Γ n y 4 / 23
12 Local Drchlet Boundary Value Problem α u (x) = f (x) for x Ω, u (x) = g (x) for x Γ = Ω Representaton Formula for x Ω u (x) = U (x,y)t (y)ds y g (y) U (x,y)ds y + 1 n y α Γ Γ Ω U (x,y)f (y)dy Fundamental Soluton U (x,y) = 1 1 4π x y, t (y) = u (y), y Γ n y Boundary Integral Equaton for x Γ 1 t (y) 4π x y ds y = 1 2 g (x)+ 1 1 g (y) 4π n (y) x y ds y 1 1 α 4π Γ Γ Ω f (y) x y dy 4 / 23
13 Boundary Integral Equaton for x Γ (V t )(x) = 1 2 g (x) + (K g )(x) 1 α (N 0, f )(x) 5 / 23
14 Boundary Integral Equaton for x Γ (V t )(x) = 1 2 g (x) + (K g )(x) 1 α (N 0, f )(x) Sngle Layer Potental V : H 1/2 (Γ ) H 1/2 (Γ ), V w,w Γ c V 1 w 2 H 1/2 (Γ ), n = 2 : damω < 1 5 / 23
15 Boundary Integral Equaton for x Γ (V t )(x) = 1 2 g (x) + (K g )(x) 1 α (N 0, f )(x) Sngle Layer Potental V : H 1/2 (Γ ) H 1/2 (Γ ), V w,w Γ c V 1 w 2 H 1/2 (Γ ), n = 2 : damω < 1 Drchlet to Neumann Map t = V 1 ( 1 2 I + K )g 1 V 1 N 0, f α 5 / 23
16 Boundary Integral Equaton for x Γ (V t )(x) = 1 2 g (x) + (K g )(x) 1 α (N 0, f )(x) Sngle Layer Potental V : H 1/2 (Γ ) H 1/2 (Γ ), V w,w Γ c V 1 w 2 H 1/2 (Γ ), n = 2 : damω < 1 Drchlet to Neumann Map t = V 1 Steklov Poncaré Operator ( 1 2 I + K )g 1 V 1 N 0, f α S = V 1 ( 1 2 I + K ) 5 / 23
17 Representaton Formula for x Ω u (x) = U (x,y)t (y)ds y g (y) U (x,y)ds y + 1 n y α Γ Γ Ω U (x,y)f (y)dy 6 / 23
18 Representaton Formula for x Ω u (x) = U (x,y)t (y)ds y g (y) U (x,y)ds y + 1 n y α Γ Γ Ω U (x,y)f (y)dy Computaton of the Normal Dervatve t (x) = 1 2 t (x) + U (x,y)t (y)ds y n x n x Γ Γ + 1 U (x,y)f (y)dy α n x Ω g (y) U (x,y)ds y n y 6 / 23
19 Representaton Formula for x Ω u (x) = U (x,y)t (y)ds y g (y) U (x,y)ds y + 1 n y α Γ Γ Ω U (x,y)f (y)dy Computaton of the Normal Dervatve t (x) = 1 2 t (x) + U (x,y)t (y)ds y n x n x Γ Γ + 1 U (x,y)f (y)dy α n x Ω g (y) U (x,y)ds y n y Hypersngular Boundary Integral Equaton for x Γ t (x) = 1 2 t (x) + (K t )(x) + (D g )(x) + 1 α (N 1, f )(x) 6 / 23
20 Drchlet to Neumann Map t = D g + ( 1 2 I + K )t + 1 α N 1, f 7 / 23
21 Drchlet to Neumann Map t = D g + ( 1 2 I + K )t + 1 α N 1, f = D g + ( 1 2 I + K )[V 1 ( 1 2 I + K )g 1 V 1 N 0, f ] + 1 N 1, f α α 7 / 23
22 Drchlet to Neumann Map t = D g + ( 1 2 I + K )t + 1 α N 1, f = D g + ( 1 2 I + K )[V 1 ( 1 2 I + K )g 1 V 1 N 0, f ] + 1 N 1, f α α = S g 1 α N f Steklov Poncaré Operator S = V 1 ( 1 2 I + K ) = D + ( 1 2 I + K )V 1 ( 1 2 I + K ) =... 7 / 23
23 Drchlet to Neumann Map t = D g + ( 1 2 I + K )t + 1 α N 1, f = D g + ( 1 2 I + K )[V 1 ( 1 2 I + K )g 1 V 1 N 0, f ] + 1 N 1, f α α = S g 1 α N f Steklov Poncaré Operator S = V 1 ( 1 2 I + K ) = D + ( 1 2 I + K )V 1 ( 1 2 I + K ) =... Mappng Propertes of S : H 1/2 (Γ ) H 1/2 (Γ ) Defnton of S va Doman Varatonal Formulaton (FEM) 7 / 23
24 Boundary Integral Equatons (Calderon Projector) for f = 0 ( ) ( 1 u 2 = I K ) ( ) V u 1 t D 2 I + K t 8 / 23
25 Boundary Integral Equatons (Calderon Projector) for f = 0 ( ) ( 1 u 2 = I K ) ( ) V u 1 t D 2 I + K t Corollary [Plemelj 1911] K V = V K, V D = 1 4 I K2 8 / 23
26 Boundary Integral Equatons (Calderon Projector) for f = 0 ( ) ( 1 u 2 = I K ) ( ) V u 1 t D 2 I + K t Corollary [Plemelj 1911] K V = V K, V D = 1 4 I K2 Theorem [OS, Wendland 2001] ( 1 2 I + K )v V 1 c K (Γ ) v V 1 for all v H 1/2 (Γ ) wth c K (Γ ) = cv 1 cd 1 < 1 shape senstve 8 / 23
27 Theorem S v V c K (Γ ) v V 1 for all v H 1/2 (Γ ) 9 / 23
28 Theorem S v V c K (Γ ) v V 1 for all v H 1/2 (Γ ) S v,v Γ [1 c K (Γ )] v 2 V 1 for all v H 1/2 (Γ ),v 1 9 / 23
29 Theorem S v V c K (Γ ) v V 1 for all v H 1/2 (Γ ) Defne S v,v Γ [1 c K (Γ )] v 2 V 1 for all v H 1/2 (Γ ),v 1 S u,v Γ = S u,v Γ + β u,w eq, Γ v,w eq, Γ, V w eq, = 1 9 / 23
30 Theorem S v V c K (Γ ) v V 1 for all v H 1/2 (Γ ) Defne S v,v Γ [1 c K (Γ )] v 2 V 1 for all v H 1/2 (Γ ),v 1 S u,v Γ = S u,v Γ + β u,w eq, Γ v,w eq, Γ, V w eq, = 1 Theorem wth c e S 1 1 S V v,v Γ S v,v Γ c e 2 1 V v,v Γ c e S 1 = mn{1 c K(Γ ),β 1,w eq, Γ }, c e S 2 = max{c K(Γ ),β 1,w eq, Γ } 9 / 23
31 Theorem S v V c K (Γ ) v V 1 for all v H 1/2 (Γ ) Defne S v,v Γ [1 c K (Γ )] v 2 V 1 for all v H 1/2 (Γ ),v 1 S u,v Γ = S u,v Γ + β u,w eq, Γ v,w eq, Γ, V w eq, = 1 Theorem wth c e S 1 1 S V v,v Γ S v,v Γ c e 2 1 V v,v Γ c e S 1 = mn{1 c K(Γ ),β 1,w eq, Γ }, c e S 2 = max{c K(Γ ),β 1,w eq, Γ } Optmal Scalng 1 β = 2 1,w eq, Γ 9 / 23
32 Drchlet to Neumann Map (Partal Dfferental Equaton) α t (x) = α (S u )(x) (N f )(x) for x Γ Drchlet Boundary Condton u (x) = g(x) for x Γ Γ Transmsson Condtons u (x) = u j (x), α t (x) + α j t j (x) = 0 for x Γ j 10 / 23
33 Drchlet to Neumann Map (Partal Dfferental Equaton) α t (x) = α (S u )(x) (N f )(x) for x Γ Drchlet Boundary Condton u (x) = g(x) for x Γ Γ Transmsson Condtons u (x) = u j (x), α t (x) + α j t j (x) = 0 for x Γ j Drchlet Doman Decomposton Approach Fnd u H 1/2 (Γ S ) such that u(x) = g(x) for x Γ and α (S u Γ )(x) + α j (S j u Γj )(x) = (N f )(x) + (N j f j )(x) for x Γ j 10 / 23
34 Varatonal Problem Fnd u H 1/2 (Γ S ) such that u(x) = g(x) for x Γ and p α =1 Γ (S u Γ )(x)v Γ (x)ds x = p =1 Γ (N f )(x)v Γ (x)ds x for all v H 1/2 (Γ S ), v(x) = 0 for x Γ 11 / 23
35 Varatonal Problem Fnd u H 1/2 (Γ S ) such that u(x) = g(x) for x Γ and p α =1 Γ (S u Γ )(x)v Γ (x)ds x = p =1 Γ (N f )(x)v Γ (x)ds x for all v H 1/2 (Γ S ), v(x) = 0 for x Γ Galerkn Varatonal Problem Fnd u 0,h S 1 h (Γ S) H 1/2 0 (Γ S ) such that p α =1 Γ (S u 0,h Γ )(x)v h Γ (x)ds x = p =1 Γ [(N f )(x) α (S u g )(x)]v Γ (x)ds x for all v h S 1 h (Γ S), where u g s some bounded extenson of g. 11 / 23
36 Lnear System p α A S,h A u = =1 p A f, =1 S,h [l,k] = S ϕ k,ϕ l Γ 12 / 23
37 Lnear System p p α A S,h A u = A f, =1 =1 Non Symmetrc BEM Approxmaton S,h [l,k] = S ϕ k,ϕ l Γ S u = V 1 ( 1 2 I + K )u = w : V w,τ Γ = ( 1 2 I + K )u,τ Γ 12 / 23
38 Lnear System p p α A S,h A u = A f, =1 =1 Non Symmetrc BEM Approxmaton S,h [l,k] = S ϕ k,ϕ l Γ S u = V 1 ( 1 2 I + K )u = w : V w,τ Γ = ( 1 2 I + K )u,τ Γ Galerkn Approxmaton w,h S 0 h(γ ) : V w,h,τ,h Γ = ( 1 2 I + K )u,τ,h Γ 12 / 23
39 Lnear System p p α A S,h A u = A f, =1 =1 Non Symmetrc BEM Approxmaton S,h [l,k] = S ϕ k,ϕ l Γ S u = V 1 ( 1 2 I + K )u = w : V w,τ Γ = ( 1 2 I + K )u,τ Γ Galerkn Approxmaton Approxmaton w,h S 0 h(γ ) : V w,h,τ,h Γ = ( 1 2 I + K )u,τ,h Γ Ŝ u = w,h, Ŝ,h = M,hV 1,h (1 2 M,h + K,h ) 12 / 23
40 Lnear System p p α A S,h A u = A f, =1 =1 Non Symmetrc BEM Approxmaton S,h [l,k] = S ϕ k,ϕ l Γ S u = V 1 ( 1 2 I + K )u = w : V w,τ Γ = ( 1 2 I + K )u,τ Γ Galerkn Approxmaton Approxmaton w,h S 0 h(γ ) : V w,h,τ,h Γ = ( 1 2 I + K )u,τ,h Γ Stablty Condton Ŝ u = w,h, Ŝ,h = M,hV 1,h (1 2 M,h + K,h ) c S v,h H 1/2 (Γ ) v,h,τ,h Γ sup 0 τ,h Sh 0(Γ ) τ,h H 1/2 (Γ ) for all v,h S 1 h(γ ) 12 / 23
41 Symmetrc BEM Approxmaton where S u = D u + ( 1 2 I + K )V 1 ( 1 2 I + K )u = D u + ( 1 2 I + K )w V w,τ Γ = ( 1 2 I + K )u,τ Γ 13 / 23
42 Symmetrc BEM Approxmaton where S u = D u + ( 1 2 I + K )V 1 ( 1 2 I + K )u = D u + ( 1 2 I + K )w Galerkn Approxmaton V w,τ Γ = ( 1 2 I + K )u,τ Γ Approxmaton w,h S 0 h(γ ) : V w,h,τ,h Γ = ( 1 2 I + K )u,τ,h Γ Ŝ = D u + ( 1 2 I + K )w,h, Ŝ,h = D,h + ( 1 2 M,h + K,h)V 1,h (1 2 M,h + K,h ) 13 / 23
43 Symmetrc BEM Approxmaton where S u = D u + ( 1 2 I + K )V 1 ( 1 2 I + K )u = D u + ( 1 2 I + K )w Galerkn Approxmaton V w,τ Γ = ( 1 2 I + K )u,τ Γ Approxmaton w,h S 0 h(γ ) : V w,h,τ,h Γ = ( 1 2 I + K )u,τ,h Γ Ŝ = D u + ( 1 2 I + K )w,h, Ŝ,h = D,h + ( 1 2 M,h + K,h)V 1,h (1 2 M,h + K,h ) Stablty Ŝv,v Γ D v,v Γ c D 1 v 2 H 1/2 (Γ ) 13 / 23
44 Symmetrc BEM Approxmaton where S u = D u + ( 1 2 I + K )V 1 ( 1 2 I + K )u = D u + ( 1 2 I + K )w Galerkn Approxmaton V w,τ Γ = ( 1 2 I + K )u,τ Γ Approxmaton w,h S 0 h(γ ) : V w,h,τ,h Γ = ( 1 2 I + K )u,τ,h Γ Ŝ = D u + ( 1 2 I + K )w,h, Ŝ,h = D,h + ( 1 2 M,h + K,h)V 1,h (1 2 M,h + K,h ) Stablty Ŝv,v Γ D v,v Γ c D 1 v 2 H 1/2 (Γ ) FEM Approxmaton Ŝ,h = K C C K C I K 1 I I K C I 13 / 23
45 Tearng and Interconnectng Ω 1 Ω 2 Ω 3 Ω 4 14 / 23
46 Tearng and Interconnectng Ω 1 Ω 2 Ω 3 Ω 4 14 / 23
47 Tearng and Interconnectng Ω 1 Ω 2 Ω 3 Ω 4 All Floatng BETI [Of 05] Total FETI [Dostal et. al. 05] 14 / 23
48 Lnear System α 1 Ŝ 1,h B α p Ŝ p,h Bp B 1... B p u 1. u p λ = f 1. f p g 15 / 23
49 Lnear System α 1 Ŝ 1,h B α p Ŝ p,h Bp B 1... B p u 1. u p λ = f 1. f p g Local System α Ŝ,h u = f + B λ, S,h 1 = 0 15 / 23
50 Lnear System α 1 Ŝ 1,h B α p Ŝ p,h Bp B 1... B p u 1. u p λ = f 1. f p g Local System α Ŝ,h u = f + B λ, S,h 1 = 0 Solvablty Condton (f + B λ,1) = 0 15 / 23
51 Lnear System α 1 Ŝ 1,h B α p Ŝ p,h Bp B 1... B p u 1. u p λ = f 1. f p g Local System α Ŝ,h u = f + B λ, S,h 1 = 0 Solvablty Condton (f + B λ,1) = 0 Extended Lnear System α S,h u = α [Ŝ,h + β a a ]u = f + B λ, a,k = ϕ k,w eq, Γ 15 / 23
52 Lnear System α 1 Ŝ 1,h B α p Ŝ p,h Bp B 1... B p u 1. u p λ = f 1. f p g Local System α Ŝ,h u = f + B λ, S,h 1 = 0 Solvablty Condton (f + B λ,1) = 0 Extended Lnear System α S,h u = α [Ŝ,h + β a a ]u = f + B λ, a,k = ϕ k,w eq, Γ Soluton u = 1 α S 1,h [f + B λ] + γ 1, (f + B λ,1) = 0 15 / 23
53 Dual Problem p =1 1 α B S 1 B λ + p γ B 1 = =1 p =1 1 α B S 1,h f, (f + B λ,1) = 0 16 / 23
54 Dual Problem p =1 1 α B S 1 B λ + p γ B 1 = =1 p =1 1 α B S 1,h f, (f + B λ,1) = 0 Fλ + Gγ = d, G λ = e 16 / 23
55 Dual Problem p =1 1 α B S 1 B λ + p γ B 1 = =1 p =1 1 α B S 1,h f, (f + B λ,1) = 0 Fλ + Gγ = d, G λ = e Projecton P = I G(G G) 1 G, P Gγ = 0 16 / 23
56 Dual Problem p =1 1 α B S 1 B λ + p γ B 1 = =1 p =1 1 α B S 1,h f, (f + B λ,1) = 0 Fλ + Gγ = d, G λ = e Projecton Lnear System P = I G(G G) 1 G, P Gγ = 0 P Fλ = P d 16 / 23
57 Dual Problem p =1 1 α B S 1 B λ + p γ B 1 = =1 p =1 1 α B S 1,h f, (f + B λ,1) = 0 Projecton Lnear System Precondtoner Fλ + Gγ = d, G λ = e P = I G(G G) 1 G, P Gγ = 0 P Fλ = P d p 1 1 C F F = B S α =1 B 16 / 23
58 Dual Problem p =1 1 α B S 1 B λ + p γ B 1 = =1 p =1 1 α B S 1,h f, (f + B λ,1) = 0 Projecton Lnear System Precondtoner Fλ + Gγ = d, G λ = e P = I G(G G) 1 G, P Gγ = 0 C F F = P Fλ = P d p 1 1 B S α =1 Scaled Hypersngular BETI Precondtoner [Langer, OS 03] C 1 F = (BC 1 α B ) 1 BC 1 α D h C 1 α B (BC 1 α B ) 1 B 16 / 23
59 Coupled Lnear System α 1 V 1,h α 1 K1,h α p V p,h α p Kp,h α 1 K 1,h α 1 D1,h B α p K p,h α p Dp,h B p B 1... B p t 1... t p u 1... u p λ = f 0,1.. f 0,p f 1,1... f 1,p g 17 / 23
60 Coupled Lnear System α 1 V 1,h α 1 K1,h α p V p,h α p Kp,h α 1 K 1,h α 1 D1,h B α p K p,h α p Dp,h B p B 1... B p t 1... t p u 1... u p λ = f 0,1.. f 0,p f 1,1... f 1,p g Twofold Saddle Pont Problem Transformaton nto postve defnte symmetrc system [Bramble, Pascak 88; Zulehner 02; Langer, Of, OS, Zulehner 05] Scalng of Precondtoners s needed! 17 / 23
61 Precondtoner for Dscrete Steklov Poncaré Operator: C S S,h Sngle Layer Potental [OS, Wendland 95, 98] C 1 S = M 1 V,h,h M 1,h Geometrc/Algebrac Multgrd for dscrete Hypersngular Integral Operator D,h S,h 18 / 23
62 Precondtoner for Dscrete Steklov Poncaré Operator: C S S,h Sngle Layer Potental [OS, Wendland 95, 98] C 1 S = M 1 V,h,h M 1,h Geometrc/Algebrac Multgrd for dscrete Hypersngular Integral Operator D,h S,h Precondtoner for Dscrete Sngle Layer Potental Geometrc Multgrd/Multlevel [Maschak, Stephan, Tran,...] Artfcal Multlevel Precondtonng [OS 03] Algebrac Multgrd for Sparse BEM [Langer, Pusch 05; Of 05] 18 / 23
63 Galerkn Dscretsaton of Boundary Integral Operators non local kernels dense stffness matrces sngular fundamental soluton sngular surface ntegrals ntegraton by parts weakly sngular surface ntegrals only 19 / 23
64 Galerkn Dscretsaton of Boundary Integral Operators non local kernels dense stffness matrces sngular fundamental soluton sngular surface ntegrals ntegraton by parts weakly sngular surface ntegrals only Fast Boundary Element Methods Fast Multpole Algorthm [Greengard, Rokhln 87;...] Panel Clusterng [Hackbusch, Nowak 89;...] Adaptve Cross Approxmaton [Bebendorf, Rjasanow 03;...] Herarchcal Matrces [Hackbusch 99;...] Wavelets [Dahmen, Prößdorf, Schneder 93;...] 19 / 23
65 Galerkn Dscretsaton of Boundary Integral Operators non local kernels dense stffness matrces sngular fundamental soluton sngular surface ntegrals ntegraton by parts weakly sngular surface ntegrals only Fast Boundary Element Methods Fast Multpole Algorthm [Greengard, Rokhln 87;...] Panel Clusterng [Hackbusch, Nowak 89;...] Adaptve Cross Approxmaton [Bebendorf, Rjasanow 03;...] Herarchcal Matrces [Hackbusch 99;...] Wavelets [Dahmen, Prößdorf, Schneder 93;...] Complexty O(N log q N ) (Fast Multpole: q = 2) 19 / 23
66 Theorem Requrement: algebrac multgrd precondtoner for V,h s optmal. Solvng by Bramble Pascak transformaton and conjugate gradent method: Twofold saddle pont problem of the standard BETI method: number of teratons O((1 + log(h/h)) 2 ) O((H/h) 2 (1 + log(h/h)) 4 ) arthmetcal operatons 20 / 23
67 Theorem Requrement: algebrac multgrd precondtoner for V,h s optmal. Solvng by Bramble Pascak transformaton and conjugate gradent method: Twofold saddle pont problem of the standard BETI method: number of teratons O((1 + log(h/h)) 2 ) O((H/h) 2 (1 + log(h/h)) 4 ) arthmetcal operatons Twofold saddle pont problem of the all floatng BETI method: number of teratons O(1 + log(h/h)) O((H/h) 2 (1 + log(h/h)) 3 ) arthmetcal operatons 20 / 23
68 Theorem Requrement: algebrac multgrd precondtoner for V,h s optmal. Solvng by Bramble Pascak transformaton and conjugate gradent method: Twofold saddle pont problem of the standard BETI method: number of teratons O((1 + log(h/h)) 2 ) O((H/h) 2 (1 + log(h/h)) 4 ) arthmetcal operatons Twofold saddle pont problem of the all floatng BETI method: number of teratons O(1 + log(h/h)) O((H/h) 2 (1 + log(h/h)) 3 ) arthmetcal operatons The use of fast boundary element methods does not perturb the convergence rates of the approxmaton. 20 / 23
69 Example: Lnear elastcty (steel and concrete) 18 subdomans BETI all floatng L t 2 It. t 2 It ( 21( 10)) 39 22( 17( 10)) ( 33( 14)) ( 27( 14)) ( 44( 14)) ( 33( 14)) ( 51( 14)) ( 36( 14)) ( 54( 14)) ( 38( 15)) 21 / 23
70 Example: Lnear elastcty (steel and concrete) 18 subdomans BETI all floatng L t 2 It. t 2 It ( 21( 10)) 39 22( 17( 10)) ( 33( 14)) ( 27( 14)) ( 44( 14)) ( 33( 14)) ( 51( 14)) ( 36( 14)) ( 54( 14)) ( 38( 15)) Drchlet DD BETI all floatng L N t 2 It. t 2 It. t 2 It ( 10) ( 14) ( 14) ( 14) ( 14) ( 16) / 23
71 [Courtesy to Z. Andjelc, H. Andrä, J. Breuer, G. Of, S. Rjasanow] 22 / 23
72 References 1. O. Stenbach: Stablty Estmates for Hybrd Coupled Doman Decomposton Methods. Sprnger Lecture Notes n Mathematcs, vol. 1809, U. Langer, O. Stenbach: Boundary element tearng and nterconnectng methods. Computng 71 (2003) S. Rjasanow, O. Stenbach: The Fast Soluton of Boundary Integral Equatons. Mathematcal and Analytcal Technques wth Applcatons to Engneerng, Sprnger, New York, 2006, n press. 4. G. Of, O. Stenbach, W. L. Wendland: Boundary Element Tearng and Interconnectng Doman Decomposton Methods. In: Multfeld Problems n Flud and Sold Mechancs (R. Helmg, A. Melke, B. I. Wohlmuth eds.). Lecture Notes n Appled and Computatonal Mechancs, vol. 28, pp , 2006, n press. 5. U. Langer, G. Of, O. Stenbach, W. Zulehner: Inexact data sparse boundary element tearng and nterconnectng methods. Berchte aus dem Insttut für Mathematk D, Bercht 2005/4, TU Graz, / 23
Loop Parallelization
- - Loop Parallelzaton C-52 Complaton steps: nested loops operatng on arrays, sequentell executon of teraton space DECLARE B[..,..+] FOR I :=.. FOR J :=.. I B[I,J] := B[I-,J]+B[I-,J-] ED FOR ED FOR analyze
More informationNatural hp-bem for the electric field integral equation with singular solutions
Natural hp-bem for the electrc feld ntegral equaton wth sngular solutons Alexe Bespalov Norbert Heuer Abstract We apply the hp-verson of the boundary element method (BEM) for the numercal soluton of the
More information8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by
6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng
More informationPoint cloud to point cloud rigid transformations. Minimizing Rigid Registration Errors
Pont cloud to pont cloud rgd transformatons Russell Taylor 600.445 1 600.445 Fall 000-014 Copyrght R. H. Taylor Mnmzng Rgd Regstraton Errors Typcally, gven a set of ponts {a } n one coordnate system and
More informationSupport Vector Machines
Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.
More informationA hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
More informationFinite difference method
grd ponts x = mesh sze = X NÜÆ Fnte dfference method Prncple: dervatves n the partal dfferental eqaton are approxmated by lnear combnatons of fncton vales at the grd ponts 1D: Ω = (0, X), (x ), = 0,1,...,
More informationOn the Solution of Indefinite Systems Arising in Nonlinear Optimization
On the Soluton of Indefnte Systems Arsng n Nonlnear Optmzaton Slva Bonettn, Valera Ruggero and Federca Tnt Dpartmento d Matematca, Unverstà d Ferrara Abstract We consder the applcaton of the precondtoned
More informationNMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING. Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582
NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582 7. Root Dynamcs 7.2 Intro to Root Dynamcs We now look at the forces requred to cause moton of the root.e. dynamcs!!
More informationDie Multipol Randelementmethode in industriellen Anwendungen
Fast Boundary Element Methods in Industrial Applications Söllerhaus, 15. 18. Oktober 2003 Die Multipol Randelementmethode in industriellen Anwendungen G. Of, O. Steinbach, W. L. Wendland Institut für Angewandte
More informationImperial College London
F. Fang 1, C.C. Pan 1, I.M. Navon 2, M.D. Pggott 1, G.J. Gorman 1, P.A. Allson 1 and A.J.H. Goddard 1 1 Appled Modellng and Computaton Group Department of Earth Scence and Engneerng Imperal College London,
More informationComputers and Mathematics with Applications. POD reduced-order unstructured mesh modeling applied to 2D and 3D fluid flow
Computers and Mathematcs wth Applcatons 65 (2013) 362 379 Contents lsts avalable at ScVerse ScenceDrect Computers and Mathematcs wth Applcatons journal homepage: www.elsever.com/locate/camwa POD reduced-order
More informationA frequency decomposition time domain model of broadband frequency-dependent absorption: Model II
A frequenc decomposton tme doman model of broadband frequenc-dependent absorpton: Model II W. Chen Smula Research Laborator, P. O. Box. 134, 135 Lsaker, Norwa (1 Aprl ) (Proect collaborators: A. Bounam,
More informationApplication of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance
Applcaton of Quas Monte Carlo methods and Global Senstvty Analyss n fnance Serge Kucherenko, Nlay Shah Imperal College London, UK skucherenko@mperalacuk Daro Czraky Barclays Captal DaroCzraky@barclayscaptalcom
More informationESTIMATION OF RELAXATION AND THERMALIZATION TIMES IN MICROSCALE HEAT TRANSFER MODEL
JOURNAL OF THEORETICAL AND APPLIED MECHANICS 51, 4, pp. 837-845, Warsaw 2013 ESTIMATION OF RELAXATION AND THERMALIZATION TIMES IN MICROSCALE HEAT TRANSFER MODEL Bohdan Mochnack Częstochowa Unversty of
More informationIntroduction to Differential Algebraic Equations
Dr. Abebe Geletu Ilmenau Unversty of Technology Department of Smulaton and Optmal Processes (SOP) Wnter Semester 2011/12 4.1 Defnton and Propertes of DAEs A system of equatons that s of the form F (t,
More informationRing structure of splines on triangulations
www.oeaw.ac.at Rng structure of splnes on trangulatons N. Vllamzar RICAM-Report 2014-48 www.rcam.oeaw.ac.at RING STRUCTURE OF SPLINES ON TRIANGULATIONS NELLY VILLAMIZAR Introducton For a trangulated regon
More informationv a 1 b 1 i, a 2 b 2 i,..., a n b n i.
SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 455 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces we have studed thus far n the text are real vector spaces snce the scalars are
More informationComputational Fluid Dynamics II
Computatonal Flud Dynamcs II Eercse 2 1. Gven s the PDE: u tt a 2 ou Formulate the CFL-condton for two possble eplct schemes. 2. The Euler equatons for 1-dmensonal, unsteady flows s dscretsed n the followng
More informationIn the rth step, the computaton of the Householder matrx H r requres only the n ; r last elements of the rth column of A T r;1a r;1 snce we donothave
An accurate bdagonal reducton for the computaton of sngular values Ru M. S. Ralha Abstract We present a new bdagonalzaton technque whch s compettve wth the standard bdagonalzaton method and analyse the
More informationA high-order compact method for nonlinear Black-Scholes option pricing equations of American Options
Bergsche Unverstät Wuppertal Fachberech Mathematk und Naturwssenschaften Lehrstuhl für Angewandte Mathematk und Numersche Mathematk Lehrstuhl für Optmerung und Approxmaton Preprnt BUW-AMNA-OPAP 10/13 II
More informationSolving Factored MDPs with Continuous and Discrete Variables
Solvng Factored MPs wth Contnuous and screte Varables Carlos Guestrn Berkeley Research Center Intel Corporaton Mlos Hauskrecht epartment of Computer Scence Unversty of Pttsburgh Branslav Kveton Intellgent
More informationAutomated information technology for ionosphere monitoring of low-orbit navigation satellite signals
Automated nformaton technology for onosphere montorng of low-orbt navgaton satellte sgnals Alexander Romanov, Sergey Trusov and Alexey Romanov Federal State Untary Enterprse Russan Insttute of Space Devce
More informationProduction. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem.
Producer Theory Producton ASSUMPTION 2.1 Propertes of the Producton Set The producton set Y satsfes the followng propertes 1. Y s non-empty If Y s empty, we have nothng to talk about 2. Y s closed A set
More informationLECTURES on COMPUTATIONAL NUMERICAL ANALYSIS of PARTIAL DIFFERENTIAL EQUATIONS
LECTURES on COMPUTATIONAL NUMERICAL ANALYSIS of PARTIAL DIFFERENTIAL EQUATIONS J. M. McDonough Departments of Mechancal Engneerng and Mathematcs Unversty of Kentucky c 1985, 00, 008 Contents 1 Introducton
More informationLiptracking and MPEG4 Animation with Feedback Control
Lptrackng and MPEG4 Anmaton wth Feedback Control Brce Beaumesnl, Franck Luthon, Marc Chaumont To cte ths verson: Brce Beaumesnl, Franck Luthon, Marc Chaumont. Lptrackng and MPEG4 Anmaton wth Feedback Control.
More informationConsider a 1-D stationary state diffusion-type equation, which we will call the generalized diffusion equation from now on:
Chapter 1 Boundary value problems Numercal lnear algebra technques can be used for many physcal problems. In ths chapter we wll gve some examples of how these technques can be used to solve certan boundary
More informationSUMMARY. Topology optimization, buckling, eigenvalue, derivative, structural optimization 1. INTRODUCTION
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Int. J. Numer. Meth. Engng 0000; 00:1 20 Publshed onlne n Wley InterScence (www.nterscence.wley.com). A fast method for solvng bnary programmng
More informationWhat is Candidate Sampling
What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble
More informationNumerical Methods 數 值 方 法 概 說. Daniel Lee. Nov. 1, 2006
Numercal Methods 數 值 方 法 概 說 Danel Lee Nov. 1, 2006 Outlnes Lnear system : drect, teratve Nonlnear system : Newton-lke Interpolatons : polys, splnes, trg polys Approxmatons (I) : orthogonal polys Approxmatons
More informationStability, observer design and control of networks using Lyapunov methods
Stablty, observer desgn and control of networks usng Lyapunov methods von Lars Naujok Dssertaton zur Erlangung des Grades enes Doktors der Naturwssenschaften - Dr. rer. nat. - Vorgelegt m Fachberech 3
More informationA fast method for binary programming using first-order derivatives, with application to topology optimization with buckling constraints
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Int. J. Numer. Meth. Engng (2012) Publshed onlne n Wley Onlne Lbrary (wleyonlnelbrary.com)..4367 A fast method for bnary programmng usng frst-order
More informationQuantization Effects in Digital Filters
Quantzaton Effects n Dgtal Flters Dstrbuton of Truncaton Errors In two's complement representaton an exact number would have nfntely many bts (n general). When we lmt the number of bts to some fnte value
More informationPower-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts
Power-of-wo Polces for Sngle- Warehouse Mult-Retaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)
More informationDamage detection in composite laminates using coin-tap method
Damage detecton n composte lamnates usng con-tap method S.J. Km Korea Aerospace Research Insttute, 45 Eoeun-Dong, Youseong-Gu, 35-333 Daejeon, Republc of Korea yaeln@kar.re.kr 45 The con-tap test has the
More informationCompiling for Parallelism & Locality. Dependence Testing in General. Algorithms for Solving the Dependence Problem. Dependence Testing
Complng for Parallelsm & Localty Dependence Testng n General Assgnments Deadlne for proect 4 extended to Dec 1 Last tme Data dependences and loops Today Fnsh data dependence analyss for loops General code
More informationMooring Pattern Optimization using Genetic Algorithms
6th World Congresses of Structural and Multdscplnary Optmzaton Ro de Janero, 30 May - 03 June 005, Brazl Moorng Pattern Optmzaton usng Genetc Algorthms Alonso J. Juvnao Carbono, Ivan F. M. Menezes Luz
More informationThe difference between voltage and potential difference
Slavko Vjevć 1, Tonć Modrć 1 and Dno Lovrć 1 1 Unversty of Splt, Faclty of electrcal engneerng, mechancal engneerng and naval archtectre Splt, Croata The dfference between voltage and potental dfference
More informationThe descriptive complexity of the family of Banach spaces with the π-property
Arab. J. Math. (2015) 4:35 39 DOI 10.1007/s40065-014-0116-3 Araban Journal of Mathematcs Ghadeer Ghawadrah The descrptve complexty of the famly of Banach spaces wth the π-property Receved: 25 March 2014
More informationTechnische Universität Graz
Technische Universität Graz Boundary element methods for Dirichlet boundary control problems Günther Of, Thanh Phan Xuan, Olaf Steinbach Berichte aus dem Institut für Numerische Mathematik Bericht 2010/1
More informationA Prefix Code Matching Parallel Load-Balancing Method for Solution-Adaptive Unstructured Finite Element Graphs on Distributed Memory Multicomputers
Ž. The Journal of Supercomputng, 15, 25 49 2000 2000 Kluwer Academc Publshers. Manufactured n The Netherlands. A Prefx Code Matchng Parallel Load-Balancng Method for Soluton-Adaptve Unstructured Fnte Element
More informationPRACA DOKTORSKA AKADEMIA GÓRNICZO-HUTNICZA KATEDRA INFORMATYKI MARCIN SIENIEK STRATEGIE ADAPTACYJNE DLA PROBLEMÓW WIELOSKALOWYCH
AKADEMIA GÓRNICZO-HUTNICZA IM. STANISŁAWA STASZICA W KRAKOWIE Wydzał Informatyk Elektronk Telekomunkac KATEDRA INFORMATYKI PRACA DOKTORSKA MARCIN SIENIEK STRATEGIE ADAPTACYJNE DLA PROBLEMÓW WIELOSKALOWYCH
More informationInstitute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic
Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange
More informationAnalysis of Lattice Boltzmann Boundary Conditions
Analyss of Lattce Boltzmann Boundary Condtons Dssertaton zur Erlangung des akademschen Grades des Doktors der Naturwssenschaften (Dr. rer. nat.) an der Unverstät Konstanz Mathematsch-Naturwssenschaftlche
More informationOn fourth order simultaneously zero-finding method for multiple roots of complex polynomial equations 1
General Mathematcs Vol. 6, No. 3 (2008), 9 3 On fourth order smultaneously zero-fndng method for multple roots of complex polynomal euatons Nazr Ahmad Mr and Khald Ayub Abstract In ths paper, we present
More informationO(n) mass matrix inversion for serial manipulators and polypeptide chains using Lie derivatives Kiju Lee, Yunfeng Wang and Gregory S.
Robotca 7) volume 5, pp 739 75 7 Cambrdge Unversty Press do:7/s6357477385 Prnted n the Unted Kngdom On) mass matrx nverson for seral manpulators and polypeptde chans usng Le dervatves Ku Lee, Yunfeng Wang
More informationAn Integrated Semantically Correct 2.5D Object Oriented TIN. Andreas Koch
An Integrated Semantcally Correct 2.5D Object Orented TIN Andreas Koch Unverstät Hannover Insttut für Photogrammetre und GeoInformaton Contents Introducton Integraton of a DTM and 2D GIS data Semantcs
More informationModern Problem Solving Techniques in Engineering with POLYMATH, Excel and MATLAB. Introduction
Modern Problem Solvng Tehnques n Engneerng wth POLYMATH, Exel and MATLAB. Introduton Engneers are fundamentally problem solvers, seekng to aheve some objetve or desgn among tehnal, soal eonom, regulatory
More informationOptimal Scheduling in the Hybrid-Cloud
Optmal Schedulng n the Hybrd-Cloud Mark Shfrn Faculty of Electrcal Engneerng Technon, Israel Emal: shfrn@tx.technon.ac.l Ram Atar Faculty of Electrcal Engneerng Technon, Israel Emal: atar@ee.technon.ac.l
More informationAdaptive Fractal Image Coding in the Frequency Domain
PROCEEDINGS OF INTERNATIONAL WORKSHOP ON IMAGE PROCESSING: THEORY, METHODOLOGY, SYSTEMS AND APPLICATIONS 2-22 JUNE,1994 BUDAPEST,HUNGARY Adaptve Fractal Image Codng n the Frequency Doman K AI UWE BARTHEL
More informationDescriptive Models. Cluster Analysis. Example. General Applications of Clustering. Examples of Clustering Applications
CMSC828G Prncples of Data Mnng Lecture #9 Today s Readng: HMS, chapter 9 Today s Lecture: Descrptve Modelng Clusterng Algorthms Descrptve Models model presents the man features of the data, a global summary
More informationLecture 2: Single Layer Perceptrons Kevin Swingler
Lecture 2: Sngle Layer Perceptrons Kevn Sngler kms@cs.str.ac.uk Recap: McCulloch-Ptts Neuron Ths vastly smplfed model of real neurons s also knon as a Threshold Logc Unt: W 2 A Y 3 n W n. A set of synapses
More informationHowHow to Find the Best Online Stock Broker
A GENERAL APPROACH FOR SECURITY MONITORING AND PREVENTIVE CONTROL OF NETWORKS WITH LARGE WIND POWER PRODUCTION Helena Vasconcelos INESC Porto hvasconcelos@nescportopt J N Fdalgo INESC Porto and FEUP jfdalgo@nescportopt
More informationBERNSTEIN POLYNOMIALS
On-Lne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful
More informationA Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression
Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy S-curve Regresson Cheng-Wu Chen, Morrs H. L. Wang and Tng-Ya Hseh Department of Cvl Engneerng, Natonal Central Unversty,
More information"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *
Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
More informationImmersed interface methods for moving interface problems
Numercal Algorthms 14 (1997) 69 93 69 Immersed nterface methods for movng nterface problems Zhln L Department of Mathematcs, Unversty of Calforna at Los Angeles, Los Angeles, CA 90095, USA E-mal: zhln@math.ucla.edu
More informationbenefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).
REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or
More informationFace Verification Problem. Face Recognition Problem. Application: Access Control. Biometric Authentication. Face Verification (1:1 matching)
Face Recognton Problem Face Verfcaton Problem Face Verfcaton (1:1 matchng) Querymage face query Face Recognton (1:N matchng) database Applcaton: Access Control www.vsage.com www.vsoncs.com Bometrc Authentcaton
More information+ + + - - This circuit than can be reduced to a planar circuit
MeshCurrent Method The meshcurrent s analog of the nodeoltage method. We sole for a new set of arables, mesh currents, that automatcally satsfy KCLs. As such, meshcurrent method reduces crcut soluton to
More informationLuby s Alg. for Maximal Independent Sets using Pairwise Independence
Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent
More informationMultiplication Algorithms for Radix-2 RN-Codings and Two s Complement Numbers
Multplcaton Algorthms for Radx- RN-Codngs and Two s Complement Numbers Jean-Luc Beuchat Projet Arénare, LIP, ENS Lyon 46, Allée d Itale F 69364 Lyon Cedex 07 jean-luc.beuchat@ens-lyon.fr Jean-Mchel Muller
More informationExtending Probabilistic Dynamic Epistemic Logic
Extendng Probablstc Dynamc Epstemc Logc Joshua Sack May 29, 2008 Probablty Space Defnton A probablty space s a tuple (S, A, µ), where 1 S s a set called the sample space. 2 A P(S) s a σ-algebra: a set
More informationwhere the coordinates are related to those in the old frame as follows.
Chapter 2 - Cartesan Vectors and Tensors: Ther Algebra Defnton of a vector Examples of vectors Scalar multplcaton Addton of vectors coplanar vectors Unt vectors A bass of non-coplanar vectors Scalar product
More informationLecture 2 Sequence Alignment. Burr Settles IBS Summer Research Program 2008 bsettles@cs.wisc.edu www.cs.wisc.edu/~bsettles/ibs08/
Lecture 2 Sequence lgnment Burr Settles IBS Summer Research Program 2008 bsettles@cs.wsc.edu www.cs.wsc.edu/~bsettles/bs08/ Sequence lgnment: Task Defnton gven: a par of sequences DN or proten) a method
More informationHow To Assemble The Tangent Spaces Of A Manfold Nto A Coherent Whole
CHAPTER 7 VECTOR BUNDLES We next begn addressng the queston: how do we assemble the tangent spaces at varous ponts of a manfold nto a coherent whole? In order to gude the decson, consder the case of U
More informationMeasurement and Simulation of Vector Hysteresis Characteristics
Measurement and Smulaton of Vector Hsteress Characterstcs Mklós Kuczmann Laborator of Electromagnetc Felds Department of Telecommuncaton Széchen István Unverst Gır, Hungar Mklós Kuczmann, Ph.D. Széchen
More informationCOMPRESSED NETWORK MONITORING. Mark Coates, Yvan Pointurier and Michael Rabbat
COMPRESSED NETWORK MONITORING Mark Coates, Yvan Ponturer and Mchael Rabbat Department of Electrcal and Computer Engneerng McGll Unversty 348 Unversty Street, Montreal, Quebec H3A 2A7, Canada ABSTRACT Ths
More informationluis m. rocha school of informatics and computing indiana university, bloomington, usa and instituto gulbenkian de ciência oeiras, portugal
sem-metrc topology and collectve computaton Informatcs n complex networks lus m. rocha school of nformatcs and computng ndana unversty, bloomngton, usa and nsttuto gulbenkan de cênca oeras, portugal complex
More informationHow To Calculate The Accountng Perod Of Nequalty
Inequalty and The Accountng Perod Quentn Wodon and Shlomo Ytzha World Ban and Hebrew Unversty September Abstract Income nequalty typcally declnes wth the length of tme taen nto account for measurement.
More informationLaddered Multilevel DC/AC Inverters used in Solar Panel Energy Systems
Proceedngs of the nd Internatonal Conference on Computer Scence and Electroncs Engneerng (ICCSEE 03) Laddered Multlevel DC/AC Inverters used n Solar Panel Energy Systems Fang Ln Luo, Senor Member IEEE
More informationPOLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with and
POLYSA: A Polynomal Algorthm for Non-bnary Constrant Satsfacton Problems wth and Mguel A. Saldo, Federco Barber Dpto. Sstemas Informátcos y Computacón Unversdad Poltécnca de Valenca, Camno de Vera s/n
More informationGRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM
GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM BARRIOT Jean-Perre, SARRAILH Mchel BGI/CNES 18.av.E.Beln 31401 TOULOUSE Cedex 4 (France) Emal: jean-perre.barrot@cnes.fr 1/Introducton The
More informationMean Value Coordinates for Closed Triangular Meshes
Mean Value Coordnates for Closed Trangular Meshes Tao Ju, Scott Schaefer, Joe Warren Rce Unversty (a) (b) (c) (d) Fgure : Orgnal horse model wth enclosng trangle control mesh shown n black (a). Several
More informationREGULAR MULTILINEAR OPERATORS ON C(K) SPACES
REGULAR MULTILINEAR OPERATORS ON C(K) SPACES FERNANDO BOMBAL AND IGNACIO VILLANUEVA Abstract. The purpose of ths paper s to characterze the class of regular contnuous multlnear operators on a product of
More informationLecture 5,6 Linear Methods for Classification. Summary
Lecture 5,6 Lnear Methods for Classfcaton Rce ELEC 697 Farnaz Koushanfar Fall 2006 Summary Bayes Classfers Lnear Classfers Lnear regresson of an ndcator matrx Lnear dscrmnant analyss (LDA) Logstc regresson
More informationCredit Limit Optimization (CLO) for Credit Cards
Credt Lmt Optmzaton (CLO) for Credt Cards Vay S. Desa CSCC IX, Ednburgh September 8, 2005 Copyrght 2003, SAS Insttute Inc. All rghts reserved. SAS Propretary Agenda Background Tradtonal approaches to credt
More informationPERRON FROBENIUS THEOREM
PERRON FROBENIUS THEOREM R. CLARK ROBINSON Defnton. A n n matrx M wth real entres m, s called a stochastc matrx provded () all the entres m satsfy 0 m, () each of the columns sum to one, m = for all, ()
More informationSngle Snk Buy at Bulk Problem and the Access Network
A Constant Factor Approxmaton for the Sngle Snk Edge Installaton Problem Sudpto Guha Adam Meyerson Kamesh Munagala Abstract We present the frst constant approxmaton to the sngle snk buy-at-bulk network
More informationThe Noether Theorems: from Noether to Ševera
14th Internatonal Summer School n Global Analyss and Mathematcal Physcs Satellte Meetng of the XVI Internatonal Congress on Mathematcal Physcs *** Lectures of Yvette Kosmann-Schwarzbach Centre de Mathématques
More informationarxiv:1311.2444v1 [cs.dc] 11 Nov 2013
FLEXIBLE PARALLEL ALGORITHMS FOR BIG DATA OPTIMIZATION Francsco Facchne 1, Smone Sagratella 1, Gesualdo Scutar 2 1 Dpt. of Computer, Control, and Management Eng., Unversty of Rome La Sapenza", Roma, Italy.
More informationOn-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features
On-Lne Fault Detecton n Wnd Turbne Transmsson System usng Adaptve Flter and Robust Statstcal Features Ruoyu L Remote Dagnostcs Center SKF USA Inc. 3443 N. Sam Houston Pkwy., Houston TX 77086 Emal: ruoyu.l@skf.com
More informationWhen Network Effect Meets Congestion Effect: Leveraging Social Services for Wireless Services
When Network Effect Meets Congeston Effect: Leveragng Socal Servces for Wreless Servces aowen Gong School of Electrcal, Computer and Energy Engeerng Arzona State Unversty Tempe, AZ 8587, USA xgong9@asuedu
More informationOn the Interaction between Load Balancing and Speed Scaling
On the Interacton between Load Balancng and Speed Scalng Ljun Chen and Na L Abstract Speed scalng has been wdely adopted n computer and communcaton systems, n partcular, to reduce energy consumpton. An
More informationLearning from Multiple Outlooks
Learnng from Multple Outlooks Maayan Harel Department of Electrcal Engneerng, Technon, Hafa, Israel She Mannor Department of Electrcal Engneerng, Technon, Hafa, Israel maayanga@tx.technon.ac.l she@ee.technon.ac.l
More informationAlternate Approximation of Concave Cost Functions for
Alternate Approxmaton of Concave Cost Functons for Process Desgn and Supply Chan Optmzaton Problems Dego C. Cafaro * and Ignaco E. Grossmann INTEC (UNL CONICET), Güemes 3450, 3000 Santa Fe, ARGENTINA Department
More informationRecurrence. 1 Definitions and main statements
Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.
More informationHeuristic Static Load-Balancing Algorithm Applied to CESM
Heurstc Statc Load-Balancng Algorthm Appled to CESM 1 Yur Alexeev, 1 Sher Mckelson, 1 Sven Leyffer, 1 Robert Jacob, 2 Anthony Crag 1 Argonne Natonal Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439,
More informationRealistic Image Synthesis
Realstc Image Synthess - Combned Samplng and Path Tracng - Phlpp Slusallek Karol Myszkowsk Vncent Pegoraro Overvew: Today Combned Samplng (Multple Importance Samplng) Renderng and Measurng Equaton Random
More informationResearch on Engineering Software Data Formats Conversion Network
2606 JOURNAL OF SOFTWARE, VOL. 7, NO. 11, NOVEMBER 2012 Research on Engneerng Software Data Formats Converson Network Wenbn Zhao School of Instrument Scence and Engneerng, Southeast Unversty, Nanng, Jangsu,
More informationVision Mouse. Saurabh Sarkar a* University of Cincinnati, Cincinnati, USA ABSTRACT 1. INTRODUCTION
Vson Mouse Saurabh Sarkar a* a Unversty of Cncnnat, Cncnnat, USA ABSTRACT The report dscusses a vson based approach towards trackng of eyes and fngers. The report descrbes the process of locatng the possble
More informationImplementation of Deutsch's Algorithm Using Mathcad
Implementaton of Deutsch's Algorthm Usng Mathcad Frank Roux The followng s a Mathcad mplementaton of Davd Deutsch's quantum computer prototype as presented on pages - n "Machnes, Logc and Quantum Physcs"
More informationAn alternate point-wise scheme for Electric Field Integral Equations
An alternate pont-wse scheme for Electrc Feld Integral Equatons Gabrele Rosat, Juan R. Mosg Laboratory of Electromagnetcs and Acoustcs (LEMA) Ecole Polytechnque Fédérale de Lausanne (EPFL), CH-05 Lausanne,
More informationHYBRID ANALYSIS METHOD FOR RELIABILITY-BASED DESIGN OPTIMIZATION
Proceedngs of DETC 01 ASME 2001 Desgn Engneerng Techncal Conferences and Computers and Informaton n Engneerng Conference Pttsburgh, Pennsylvana, September 9-12, 2001 DETC2001/DAC-21044 HYBRID ANALYSIS
More informationThe issue of June, 1925 of Industrial and Engineering Chemistry published a famous paper entitled
Revsta Cêncas & Tecnologa Reflectons on the use of the Mccabe and Thele method GOMES, João Fernando Perera Chemcal Engneerng Department, IST - Insttuto Superor Técnco, Torre Sul, Av. Rovsco Pas, 1, 1049-001
More informationActive Compensation of Transducer Nonlinearities
Actve Compensaton of Transducer Nonlneartes Wolfgang Klppel Klppel GmbH, Dresden, 01277, Germany, www.klppel.de ABSTRACT Nonlneartes nherent n electromechancal and electroacoustcal transducers produce
More informationPeriod and Deadline Selection for Schedulability in Real-Time Systems
Perod and Deadlne Selecton for Schedulablty n Real-Tme Systems Thdapat Chantem, Xaofeng Wang, M.D. Lemmon, and X. Sharon Hu Department of Computer Scence and Engneerng, Department of Electrcal Engneerng
More informationOut-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering
Out-of-Sample Extensons for LLE, Isomap, MDS, Egenmaps, and Spectral Clusterng Yoshua Bengo, Jean-Franços Paement, Pascal Vncent Olver Delalleau, Ncolas Le Roux and Mare Oumet Département d Informatque
More informationA Penalty Method for American Options with Jump Diffusion Processes
A Penalty Method for Amercan Optons wth Jump Dffuson Processes Y. d Hallun, P.A. Forsyth, and G. Labahn March 9, 23 Abstract The far prce for an Amercan opton where the underlyng asset follows a jump dffuson
More informationAn Overview of Computational Fluid Dynamics
An Overvew of Computatonal Flud Dynamcs Joel Ducoste Assocate Professor Department of Cvl, Constructon, and Envronmental Engneerng MBR Tranng Semnar Ghent Unversty July 15 17, 2008 Outlne CFD? What s that?
More information