High order transmission conditions for conductive thin sheets Asymptotic Expansions versus Thin Sheet Bases

Μέγεθος: px
Εμφάνιση ξεκινά από τη σελίδα:

Download "High order transmission conditions for conductive thin sheets Asymptotic Expansions versus Thin Sheet Bases"

Transcript

1 High order transmission conditions for conductive thin sheets Asymptotic Expansions versus Thin Sheet Bases Kersten Schmidt, Sébastien Tordeux 2 Project POEMS, INRIA Paris-Rocquencourt, 2 Toulouse Mathematics Institute Workshop Asymptotic methods, mechanics and other applications, ENS Cachan Bretagne, September st 29

2 Outline Introduction Applications The meshing problem Model problem Geometry for the transmission problem and different frameworks Thin sheet basis First order impedance boundary condition Bound of modelling error by best approximation error Derivation of basis to any order Numerical results Asymptotic Expansions Derivation of the iterative models Existence, uniqueness, regularity and convergence Decoupling and models only exterior field Numerical experiments with high-order FEM Collectively computed model of order Collectively computed models of higher orders Comparison of thin sheet basis and asymptotic expansions Conclusion K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 2/ 43

3 Introduction Applications Transformator inside a conducting casing. Protection of integrated circuits. Cable with a foil shield. Thin conducting sheets for electromagnetic shielding, for mechanical stability, as casing for liquids and gases, with little material wastage. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

4 Introduction The meshing problem Difficult to create by most mesh generators. High number of triangles. Even more triangles for resolving the sheet. Triangle mesh inside the sheet. Conforming triangle mesh resolving the sheet. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 4/ 43

5 Introduction The meshing problem Difficult to create by most mesh generators. High number of triangles. Even more triangles for resolving the sheet. Triangle mesh inside the sheet. Conforming triangle mesh resolving the sheet. Quadrilateral cells with large aspect ratio. Thin sheet basis functions inside the sheet (and no lateral refinement). Conforming quadrilateral mesh resolving a thin sheet. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 4/ 43

6 Introduction The meshing problem Difficult to create by most mesh generators. High number of triangles. Even more triangles for resolving the sheet. Triangle mesh inside the sheet. Conforming triangle mesh resolving the sheet. Quadrilateral cells with large aspect ratio. Thin sheet basis functions inside the sheet (and no lateral refinement). Replace the thin sheet by an interface. Replace its behaviour by transmission conditions resulting from asymptotic expansions. Conforming quadrilateral mesh resolving a thin sheet. Conforming triangle mesh resolving an interface. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 4/ 43

7 Introduction The Model Time-harmonic Eddy-current model for low frequency applications Two important effects curle = iωµh, curlh = σe + j Shielding effect in conductors induced currents diminish electromagnetic fields (behind the conductors) Skin effect major current flow in a boundary layer (skins of the conductor) Without conducting sheet. With conducting sheet. Field generated by an alternating current inside a cylindrical conductor. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 5/ 43

8 Introduction Model Time-harmonic Eddy-current model for low frequency applications Two important effects curle = iωµh, curlh = σe + j Shielding effect in conductors induced currents diminish electromagnetic fields (behind the conductors) Skin effect major current flow in a boundary layer (skins of the conductor) δ q δ = 2 δ d δ d δ d µσω Skin depth in solid body. Skin effect in thin conducting sheets. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 6/ 43

9 Introduction Model Time-harmonic Eddy-current model for low frequency applications Two important effects curle = iωµh, curlh = σe + j Shielding effect in conductors induced currents diminish electromagnetic fields (behind the conductors) Skin effect major current flow in a boundary layer (skins of the conductor) Time-harmonic Eddy-current model in 2D (TM mode) e(x) + iωµ σe(x) = iωµ j (x) Consider the Model problem in 2D including these effects u + cu = f, with conductivity c(x) vanishing outside the thin conductive sheet. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 7/ 43

10 Introduction Geometry for the transmission problem Geometry Ω ε int... thin conducting sheet of thickness ε Ω ε ext... non-conducting domain ε t Ω = Ω ε int Ωε ext Ω ε int n Ω ε ext s Γ m... midline of Ω ε int smooth mapping b Γ R Γ m Ω Ω local orthogonal coordinate system in Ω ε int local coordinates (t, s) b Γ [ ε 2, ε 2 ] n... left unit normal vector Goal : Description of thin conducting sheets of higher order. Two strategies A. Approximation of the solution inside the sheet by an optimal basis. B. Asymptotic analysis of the solution inside and outside the sheet. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 8/ 43

11 Introduction Geometry for the transmission problem and different frameworks Ω ε int n Ω ε ext ε s t Geometry Ω ε int... thin conducting sheet of thickness ε Ω ε ext... non-conducting domain Ω = Ω ε int Ωε ext Γ m... midline of Ω ε int smooth mapping b Γ R Γ m Ω Ω local orthogonal coordinate system in Ω ε int local coordinates (t, s) b Γ [ ε 2, ε 2 ] n... left unit normal vector Frameworks with ε varying conductivity u ε + c(ε) u ε == f c(ε) = c... compare sheets of constant material c(ε) = c ε... compare sheets of constant shielding Modelling error in ε related to a particular framework K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 8/ 43

12 Outline Introduction Applications The meshing problem Model problem Geometry for the transmission problem and different frameworks Thin sheet basis First order impedance boundary condition Bound of modelling error by best approximation error Derivation of basis to any order Numerical results Asymptotic Expansions Derivation of the iterative models Existence, uniqueness, regularity and convergence Decoupling and models only exterior field Numerical experiments with high-order FEM Collectively computed model of order Collectively computed models of higher orders Comparison of thin sheet basis and asymptotic expansions Conclusion K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 9/ 43

13 Thin sheet basis First order impedance boundary condition.8 First order impedance boundary conditions (e. g. Igarashi et. al., 998) use fundamental solutions of the ODE in thickness direction after neglecting longitudinal variations and the curvature. u ε int + cuε int = 2 s u ε int + cuε int e± cs ε 2 φ ε int, φ ε int, ε s 2 ε t Ω ε int Ω ε ext s n Ω Ω K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. / 43

14 Thin sheet basis First order impedance boundary condition.8 First order impedance boundary conditions (e. g. Igarashi et. al., 998) use fundamental solutions of the ODE in thickness direction after neglecting longitudinal variations and the curvature. u ε int + cuε int = 2 s u ε int + cuε int e± cs ε 2 φ ε int, φ ε int, ε s 2 Dirichlet-to-Neumann map is derived on Γ ε nuint ε (t, + ε 2 ) «u ε nuint ε (t, ε 2 ) int (t, + ε 2 ) «uint ε (t, ε 2 ) Ω ε int n Ω ε ext ε s t Ω Ω K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. / 43

15 Thin sheet basis First order impedance boundary condition.8 First order impedance boundary conditions (e. g. Igarashi et. al., 998) use fundamental solutions of the ODE in thickness direction after neglecting longitudinal variations and the curvature. u ε int + cuε int = 2 s u ε int + cuε int e± cs ε 2 φ ε int, φ ε int, ε s 2 Dirichlet-to-Neumann map is derived on Γ ε nuint ε (t, + ε 2 ) «u ε nuint ε (t, ε 2 ) int (t, + ε 2 ) «uint ε (t, ε 2 ) Ω ε int n Ω ε ext ε s t and used for transmission conditions on the mid-line Γ m nuext ε ««(t, +) u ε nuext ε (t, ) ext (t, +) uext ε (t, ) Ω Ω Condition at Γ ε used at Γ m Modelling error of O(ε) independent of any improvement in the interior Γ m n Ω ext Ω Ω K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. / 43

16 Thin sheet basis Extension to higher orders Approximation of higher order without reduction to an interface Ansatz for the solution inside the sheet N uint ε (t, s) uε int,n (t, s) = X φ ε int,i (s, t)uε int,i (t). i= Ω ε int n Ω ε ext ε s t with N 2 linear independent basis functions φ ε int,i spanning V ε N, and uε int,i H ( b Γ). Ω Ω Estimate of the overall modelling error only that in the sheet WN nu ε := : u ext H (Ω ε ext ),u int VN ε H ( b o Γ), u ext = u int H (Γ ε ) H (Ω) H (Ω)-ellipticity estimate by best-approximation by Cea s Lemma u ε u ε N H (Ω) C inf u N W ε N u ε u N H (Ω) K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. / 43

17 Thin sheet basis Extension to higher orders Approximation of higher order without reduction to an interface Ansatz for the solution inside the sheet N uint ε (t, s) uε int,n (t, s) = X φ ε int,i (s, t)uε int,i (t). i= Ω ε int n Ω ε ext ε s t with N 2 linear independent basis functions φ ε int,i spanning V ε N, and uε int,i H ( b Γ). Ω Ω Estimate of the overall modelling error only that in the sheet fw N nu ε := : u ext H (Ω ε ext ),u int VN ε H ( b o Γ), u ext = u int = u ε H (Γ ε ) WN ε H (Ω)-ellipticity estimate by best-approximation by Cea s Lemma u ε u ε N H (Ω) C inf u N W ε N = C inf u N f W ε N u ε u N H (Ω) C u ε u N H (Ω ε ext ) {z } inf u N f W ε N u ε u N H (Ω) +C inf u ε u N H u N W f N ε (Ω ε int ) K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. / 43

18 Thin sheet basis Extension to higher orders Approximation of higher order without reduction to an interface Ansatz for the solution inside the sheet N uint ε (t, s) uε int,n (t, s) = X φ ε int,i (s, t)uε int,i (t). i= Ω ε int n Ω ε ext ε s t with N 2 linear independent basis functions φ ε int,i spanning V ε N, and uε int,i H ( b Γ). Ω Ω Estimate of the overall modelling error only that in the sheet fw N nu ε := : u ext H (Ω ε ext ),u int VN ε H ( b o Γ), u ext = u int = u ε H (Γ ε ) WN ε H (Ω)-ellipticity estimate by best-approximation by Cea s Lemma u ε u ε N H (Ω) C inf u N W ε N = C inf u N f W ε N u ε u N H (Ω) C u ε u N H (Ω ε ext ) {z } inf u N f W ε N u ε u N H (Ω) +C inf u ε u N H u N W f N ε (Ω ε int ) C u ε w ε N H (Ω ε int ) for some candidate function w ε N K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. / 43

19 Thin sheet basis Extension to higher orders for the circular sheet Dirichlet boundary value problem in Ω ε int u ε int + c(ε) uε int = in Ωε int. Circular sheet + c(ε) = ( 2 s κ +sκ s + c(ε)) (+sκ) 2 2 t Corresponding bilinear form (v H (Ωε int )) a int (u, v) := ( su su + c(ε)uv) ( + sκ) + tu tv ds dt Ω ε + sκ int Error of candidate function in H (Ω ε int )-seminorm u ε wn ε 2 H (Ω ε int ) a int(u ε wn ε,uε wn ε ) = a int(wn ε,uε wn ε ) min K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 2/ 43

20 Thin sheet basis Extension to higher orders for the circular sheet Error of candidate function in H (Ω ε int )-seminorm u ε wn ε 2 H (Ω ε int ) a int(u ε wn ε,uε wn ε ) = a int(wn ε,uε wn ε ) min Bilinear form (u H 2 (Ω ε int ), v H (Ωε int )) a int (u, v) := Ω ε int ( + sκ)( s 2 κ s + c(ε)) + sκ {z } scales with ε uv + sκ 2 t uv ds dt Candidate function for N = 2 satisfying boundary data with φ ε int, (± ε 2 ) =, φε int, (± ε 2 ) = ± 2 a int (w ε 2, v) = Ω ε int w2 ε (s, t) = φε int, (s){uε }(t) + φ ε int, (s) [uε ](t). {z } for illustration (+sκ){u ε }(t)( s 2 κ +sκ s + c(ε))φε int, (s) 2 t {uε }(t) +sκ φε int, (s)v ds dt {z } Choose basis functions φ ε int,, φε int, in the kernel of ( 2 s κ +sκ + c(ε)) K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

21 Thin sheet basis Extension to higher orders for the circular sheet Error of candidate function in H (Ω ε int )-seminorm u ε wn ε 2 H (Ω ε int ) a int(u ε wn ε,uε wn ε ) = a int(wn ε,uε wn ε ) min Bilinear form (u H 2 (Ω ε int ), v H (Ωε int )) a int (u, v) := ( + sκ)( Ω ε s 2 κ s + c(ε)) uv + sκ + sκ 2 t uv ds dt int {z } scales with ε Candidate function for N = 4 satisfying boundary data with φ ε int,2 (± ε 2 ) = φε int,3 (± ε 2 ) = w ε 4 (s, t) = wε 2 (s, t) + φε int,2 (s)uε int,2 (t). a int (w4 ε,v) = 2 t {uε }(t) Ω ε +sκ φε int, (s)v + (+sκ)uε int,2 (t)( 2 s κ +sκ s + c(ε))φε int,2 (s)v ds dt int + 2 t uε int,2 (t) +sκ φε int,2(s) v ds dt Ω ε int Choose basis functions φ ε int,2, φε int,3 such that ( 2 s κ +sκ + c(ε))φε int,2 (s) = ε2 φ ε int, (s) K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

22 Thin sheet basis Extension to higher orders for the circular sheet Error of candidate function in H (Ω ε int )-seminorm u ε wn ε 2 H (Ω ε int ) a int(u ε wn ε,uε wn ε ) = a int(wn ε,uε wn ε ) min Bilinear form (u H 2 (Ω ε int ), v H (Ωε int )) a int (u, v) := ( + sκ)( Ω ε s 2 κ s + c(ε)) + sκ int {z } scales with ε uv + sκ 2 t uv ds dt Choose basis functions ( 2 s κ + sκ + c(ε))φε int, (s) = ( 2 s κ + sκ + c(ε))φε int,2 (s) = ε2 φ ε int, (s) Candidate function for N = 2, N = 4 satisfying boundary data w ε 2 (s, t) = {uε }(t)φ ε int, (s) it remains a int (w ε 2, v) = wε 4 (s,t) = wε 2 (s, t) ε2 2 t {uε }(t) (+sκ) 2 φε int,2 (s) Ω ε int a int (w ε 4, v) = ε2 2 t {uε }(t) +sκ φε int, (s)v ds dt Ω ε int t 4{uε }(t) (+sκ) 3 φε int,2 (s)v ds dt K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

23 Thin sheet basis Extension to higher orders for the circular sheet Error of candidate function in H (Ω ε int )-seminorm u ε wn ε 2 H (Ω ε int ) a int(u ε wn ε,uε wn ε ) = a int(wn ε,uε wn ε ) min Bilinear form (u H 2 (Ω ε int ), v H (Ωε int )) a int (u, v) := ( + sκ)( Ω ε s 2 κ s + c(ε)) uv + sκ + sκ 2 t uv ds dt int {z } scales with ε Choose basis functions ( s 2 κ + sκ + c(ε))φε int,j (s) = j =, ( s 2 κ + sκ + c(ε))φε int,j (s) = ε2 φ ε int,j 2 (s), j = 2,..., N Candidate function satisfying boundary data it remains N 2 wn ε (s, t) = X a int (w ε N, v) = εn 2 Ω ε int i= ε 2i ( t) 2i (+sκ) 2i {u ε }(t)φ ε int,2i (s) + [uε ](t)φ ε int,2i+ (s) ( t 2) N 2 (+sκ) N+ {u ε }(t)φ ε int,n 2 (s) + [uε ](t)φ ε int,n (s) v ds dt K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

24 Thin sheet basis Extension to higher orders for the circular sheet Error of candidate function in H (Ω ε int )-seminorm u ε wn ε 2 H (Ω ε int ) a int(u ε wn ε,uε wn ε ) = a int(wn ε,uε wn ε ) min Bilinear form (u H 2 (Ω ε int ), v H (Ωε int )) a int (u, v) := ( + sκ)( Ω ε s 2 κ s + c(ε)) uv + sκ + sκ 2 t uv ds dt int {z } scales with ε Choose basis functions ( s 2 κ + sκ + c(ε))φε int,j (s) = j =, ( s 2 κ + sκ + c(ε))φε int,j (s) = ε2 φ ε int,j 2 (s), j = 2,..., N it remains a int (w ε N,v) = εn 2 = ε N Ω ε int ( t 2) N 2 (+sκ) N+ {u ε }(t)φ ε int,n 2 (s) + [uε ](t)φ ε int,n (s) v ds dt (+sκ) N+ ( 2 s κ +sκ s + c(ε)) ( 2 t ) N 2 {u ε }(t)φ ε int,n (s) +... {z } rn ε (s, t)(+sκ) Ω ε int Scaling of φ ε int,j (s) with O( ε) in the L 2 ([ ε 2, ε ])-norm and Cauchy-Schwarz 2 K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

25 Thin sheet basis Extension to higher orders for the circular sheet Error of candidate function in H (Ω ε int )-seminorm u ε w ε N 2 H (Ω ε int ) a int(u ε w ε N,uε w ε N ) = a int(w ε N, uε w ε N ) O(ε2N ) Bilinear form (u H 2 (Ω ε int ), v H (Ωε int )) a int (u, v) := ( + sκ)( Ω ε s 2 κ s + c(ε)) uv + sκ + sκ 2 t uv ds dt int {z } scales with ε Choose basis functions ( s 2 κ + sκ + c(ε))φε int,j (s) = j =, ( s 2 κ + sκ + c(ε))φε int,j (s) = ε2 φ ε int,j 2 (s), j = 2,..., N it remains a int (w ε N,v) = εn 2 = ε N Ω ε int ( t 2) N 2 (+sκ) N+ {u ε }(t)φ ε int,n 2 (s) + [uε ](t)φ ε int,n (s) v ds dt (+sκ) N+ ( 2 s κ +sκ s + c(ε)) ( 2 t ) N 2 {u ε }(t)φ ε int,n (s) +... {z } rn ε (s, t)(+sκ) Ω ε int Scaling of φ ε int,j (s) with O( ε) in the L 2 ([ ε 2, ε ])-norm and Cauchy-Schwarz 2 K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

26 Thin sheet basis Extension to higher orders for the circular sheet Theorem (The modelling error of a candidate function) Let N be an even integer. There exists a function wn ε W f int,n ε such that w ε N uε int H (Ω ε int ) C Nε N /2, w ε N uε int L 2 (Ω ε int ) C Nε N+/2, with a constant C N independent of ε and the choice of c(ε). This result transfers to the overall modelling error due to Cea s lemma. u ε u ε N H (Ω) C inf u N f W ε N u ε u N H (Ω) = C inf u N f W ε int,n Corollary (The modelling error for the circular sheet) Let N be an even integer, κ (t) = and un ε W N ε the solution of un ε v dx + un ε v + c(ε)uε N v dx = Ω ε ext Ω ε int Then, there exists a constant C N independent of ε such that u ε u ε N H (Ω) C Nε N 2. u ε u N H (Ω ε int ). Ω ε ext fv dx, K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 4/ 43

27 Thin sheet basis Extension to higher orders curved sheet Circular sheet + c(ε) = ( s 2 κ s + c(ε)) + sκ {z } scales with ε Choose basis functions φ ε 2j, φε 2j+ in the kernel of ( 2 s p p Basis I c(ε) +sκ p(s), K κ c(ε) +sκ κ +sκ t +sκ t κ +sκ s + c(ε))j+, j N p(s) instable for small curvatures K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 5/ 43

28 Thin sheet basis Extension to higher orders curved sheet Circular sheet + c(ε) = ( s 2 κ s + c(ε)) + sκ {z } scales with ε Choose basis functions φ ε 2j, φε 2j+ in the kernel of ( 2 s p p Basis I c(ε) +sκ p(s), K κ c(ε) +sκ κ + c(ε) = s 2 κ «2 + sκ s + c(ε) + κ +sκ {z } scales with ε Choose basis functions φ ε 2j, φε 2j+ in the kernel of 2 s +sκ t +sκ t κ +sκ s + c(ε))j+, j N p(s) instable for small curvatures Basis e± c(ε) s +sκ p(s) stable for small curvatures 2 +sκ t +sκ t κ +sκ «κ(t) 2 j+ +sκ(t) s + c(ε) + κ +sκ φ ε int,.5.5 φ ε int,2.5 φ ε int,4 κ = +8 κ = 8 φ ε int, ε ε 2 s 2 φ ε int, ε ε 2 s 2 φ ε int, ε ε 2 s 2 K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 5/ 43

29 Thin sheet basis Numerical results for a circular sheet ε 2.5 φ = /R ΓD,2 4 Ω ε ext Ω ε ext Ω ε int 6 ΓD, φ = r = R R R + Semianalytical study with f =, g = sin(πt) on Γ D, Γ D,2, otherwise g = Error in H -seminorm inside the sheet ε N = N = 2 N = 3 N = 4 N = (a) Constant conductivity c =. κ = N = N = 2 N = 3 N = N = N = 2 N = 3 N = (b) Conductivity c(ε) = ε. κ = 2. ε ε (c) Conductivity c(ε) = ε 2. κ = 2. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 6/ 43

30 Thin sheet basis Numerical results for a circular sheet ε φ = /R ΓD,2 5 Ω ε ext Ω ε ext Ω ε int ΓD, φ = r = R R R + Semianalytical study with f =, g = sin(πt) on Γ D, Γ D,2, otherwise g = Error in H -seminorm outside the sheet. 5 N = N = 2 N = 3 N = 4 N = 5 N = (a) Constant conductivity c =. κ = 2. ε N = N = 2 N = 3 N = 4 N = 5 N = N = N = 2 N = 3 N = ε (b) Conductivity c(ε) = ε. κ = 2. (c) Conductivity c(ε) = ε 2. κ = 2. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 7/ 43 ε

31 Thin sheet basis Numerical results for a straight sheet Dependance of the number of basis functions in comparison with polynomial basis c = 4 c = 4 c = 4 c = 4 5 c = 4 5 ε = (a) Error in the H -norm inside the sheet. N c = 4 c = 4 c = 4 c = 4 5 c = (b) Error in the H -norm outside the sheet. N K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 8/ 43

32 Outline Introduction Applications The meshing problem Model problem Geometry for the transmission problem and different frameworks Thin sheet basis First order impedance boundary condition Bound of modelling error by best approximation error Derivation of basis to any order Numerical results Asymptotic Expansions Derivation of the iterative models Existence, uniqueness, regularity and convergence Decoupling and models only exterior field Numerical experiments with high-order FEM Collectively computed model of order Collectively computed models of higher orders Comparison of thin sheet basis and asymptotic expansions Conclusion K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 9/ 43

33 Asymptotic Expansions Choice of the asymptotics α = ε R 2R asymptotically no shielding for ε α =.5 ε = 2 ε = 3 ε = 4 ε Families of problems with c(ε) = c ε α Choose α = (borderline case) asymptotically constant shielding for ε α = 2 asymptotically impermeable sheet for ε.5 ε = 2 ε = 3 ε = 4 ε K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 2/ 43

34 Asymptotic Expansions Expansion of u ε t b Γ Ω ε int Ω ε ext ε s t Γ m Ω ext bω n n Ω Ω Ω Ω 2 2 S Stretched variable in Ω ε int S = ε s normalised domain b Ω := b Γ [ 2, 2 ]. Notation v(x) = v(t,s) = V(t, S) for a function v in Ω ε int. (t, S) b Ω. Expansion of uext ε (x) and Uε int (t, S) : We seek the exact solution with the form u ε ext(x) = X i= ε i u i ext(x) + o (ε ) ε, U ε int (t, S) = X where the terms uext i (x) and Ui int (t, S) do not depend on ε. i= ε i U i int (t, S) + o (ε ) ε K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 2/ 43

35 Asymptotic Expansions Taylor expansion of u i (t, ±ε/2) t b Γ Ω ε int Ω ε ext ε s t Γ m Ω ext bω n n Ω Ω Ω Ω 2 2 S Dirichlet transmission condition for expansion coefficient = uext ε (t, ± ε 2 ) Uε int (t, ± 2 ) = X ix ε j `± 2 j! j s ui j ext (t, ±) Ui int (t, ± 2 ) A + o (ε ). i= j= ε Neumann transmission condition = ε su ε ext (t, ± ε 2 ) SU ε int (t, ± 2 ) = X Xi ε i i= j= j `± 2 j! j+ s «u i j ext (t, ±) S Uint i (t, ± 2 ) + o (ε ). ε K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 22/ 43

36 Asymptotic Expansions Expansion of Laplace operator = 2 s + κ(t) + sκ(t) s + + sκ(t) t = ε 2 2 S + ε κ(t) + εsκ(t) S + + εsκ(t) t Laplacian () can be expanded in powers of ε = ε 2 where for l, L there are defined ba l (t) := ( κ(t))l 2 (l ) + sκ(t) t «, in Ω ε int + εsκ(t) t «. in b Ω ()! L S 2 + X ε l A l + ε L R L ε, for all L, (2) l= 2 t + l 2 2 A l (t, S) := b A l (t)sl 2 + b A l (t)sl S, κ «(t) κ(t) t, A b l (t) := ( κ(t)) l, K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 23/ 43

37 Asymptotic Expansions Hierarchical coupled problem 8 >< >: Hierarchical definition of external and internal expansion functions. c 2 2 u i ext = f δi in Ω ext, u i ext = gδi ix 2 S Ui int (t, S) = cui int (t, S) l= ix U i int (t, ± 2 ) ui ext (t, ± ) = U i int (t, S) ds k(t) hu i int ix 2 l= Jumps and mean values l= S U i int (t, ± 2 ) = ix 2 l= i h i (t) su i ext (t) = on Ω, A l U i l int (t, S) in b Ω. ± «l 2 l! l s ui l ext (t, ± ) on Γ m, ± «l 2 (l )! l s ui l ext (t, ± ) «l/2 «A l+ U i l int (t, S) ds + 4 l! [ l+ s u i l ext ]l (t) on Γ m on Γ m (3) [V](t) := V(t, /2) V(t, /2), {V }(t) := 2 (V(t, /2) + V(t, /2)), [v](t) := v(t, + ) v(t, ), {v}(t) := `v(t, + ) + v(t, ). 2 j [v] n [v](t) n even (t) := {v}(t) n odd. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 24/ 43

38 Asymptotic Expansions Existence, Uniqueness and Regularity Existence, Uniqueness and Regularity of the hierarchical problem Theorem The sequences (uext i ) and (Ui int ) exist and are uniquely defined. Ui int are polynomials in S of degree 2i with monomial coefficients Uint,j i, j =,..., 2i. For any k N and i N there exists a constant C i,k < + such that u i ext (x) H k ( e Ω ext ) C i,k, U i int,j (t) H k+/2 (Γ m ) C i,k, given that Γ m is C. Convergence of the modelling error Lemma The remainder r ε,n+ (x) := uext/int ε (x) uε,n (x) satisfies ext/int r ε,n+ H (Ω ε ext ) + ε r ε,n+ H (Ω ε int ) C Nε N+. Are the expansion functions u i ext and so uε,n ext computable? K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 25/ 43

39 Asymptotic Expansions Uncoupled problems for the first three exterior expansion functions Solving the equation for U e int i (t, s) and {Ui int }(t) interface conditions yields. Problem in Ω ext for ui ext (x) 8 u ext (x) = f in Ω ext Γ m n Ω ext Ω Ω Order Order 8 >< >: >< >: uext (x) = g i (t) = h u ext h nuext i (t) c uext (t, ) = u ext (x) = uext (x) = h uext i (t) =, on Ω on Γ m on Γm in Ω ext on Ω on Γ m h nu i ext (t) c u ext (t) = c2 6 u ext (t, ) on Γm 8 u 2 ext (x) = in Ω ext Order 2 >< >: uext 2 (x) = h u 2 i ext (t) = c 24 κ(t)u ext (t, ) c 2 n 24 κ(t) nu ext 7 + c 24 c2! 2 t uext (t, ) 2 h nu 2 i ext (t) c nu 2 o ext (t) = c2 6 u ext (t) + c on Ω n nu o ext (t) on Γ m, o (t) on Γm K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 26/ 43

40 Asymptotic Expansions Numerical Results computations for an ellipsoidal sheet with Concepts C++ class library Concepts Started by Christian Lage during his Ph.D. studies (995). Used and improved by Frauenfelder, Matache, Schmidlin, Schmidt, Kauf and severals students. Concept Oriented Design using mathematical principles []. Currently two parts: hp-fem (nodal and edge elements), BEM (wavelet and multipole methods). most of it is released under GPL, Features used and/or implemented in this project quadrilateral elements with high-order tensor product basis functions, elements on edges with high-order basis functions, bilinear and linear forms on these respective elements, exact mapping of curved boundaries, various functions of finite element solutions (trace, jump, extension, gradient,...). [] Ph. Frauenfelder and Ch. Lage, Concepts An Object Oriented Software Package for Partial Differential Equations, Math. Model. Numer. Anal. 36 (5), pp (22). K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 27/ 43

41 Asymptotic Expansions Numerical Results computations for an ellipsoidal sheet with Concepts Ω ε int Γ m Meshes M ε resolving the thin sheets of thickness ε for the reference solutions u ε (x). Limit mesh M for the computation of the asymptotic expansion functions u i ext (x). Following computation of the polynomials Uint i (t, S), representation of u ε,n (x) = P N i= εi u i (x) on meshes M ε to calculate the modelling error in dependence of ε. K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 28/ 43

42 Asymptotic Expansions Numerical Results computations for an ellipsoidal sheet with Concepts uε uext -2-2 y y - - x x 2 c = 2 2 (c) ε = /8 2 (d) Order y y - - x x (e) Order K. Schmidt, S. Tordeux 2 uext -. - uext -2 ENS Cachan Bretagne, September st 29 2 (f) Order 2 p. 29/ 43

43 Asymptotic Expansions Numerical Results computations for an ellipsoidal sheet with Concepts 2 Order Order Order 2 3 u ε u ε,i H (Ω ε ext ) H -seminorm in the exterior sub-domain Ω ε ext. ε K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

44 Asymptotic Expansions Numerical Results computations for an ellipsoidal sheet with Concepts Order Order Order u ε u ε,i H (Ω ε int ) H -seminorm in the sheet Ω ε int. ε K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

45 Asymptotic Expansions Collectively computed model of order Transmission condition of order N = 8 >< h >: nũ ε, ext Stability for Ic > and Rc ũ ε, ext (x) = f in Ω ext h i, ũ ε, ext (t) = on Γ m, i(t) c + c 6 ε ũ ε, ext (t, ) = on Γm, ũ ε, ext (x) = g ũ ε, H (Ω ext ) C f L 2 (Ω ext ). on Ωext. Modelling error ũ ε, u ε H (Ω ε ext ) C ε2 2 4 L2-norm H-seminorm 2 L 2 -norm H -seminorm error error ε (a) Errors in the exterior sub-domain Ω ε ext (b) Errors in the sheet Ω ε int. ε K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 3/ 43

46 Asymptotic Expansions Collectively computed models of higher orders Rewrite the systems in general form u i ext (x) = f δi, in Ω ext, h i u i ext (t) = h i n o nu i ext (t) c u i ext (t) = with the operators (up to order 3) ix l=2 ix l= u i ext (x) = gδi (γ l u j l ext )(t), on Γm, (ζ l u j l ext )(t), on Γm, on Ω (γ 2 u)(t) := c `κ(t){u}(t) + 2{ nu}(t), (γ 3 u)(t) := c2 `κ(t){u}(t) + 2{ nu}(t), (ζ u)(t) := c2 6 {u}(t), (ζ 2 u)(t) := c 2 (ζ 3 u)(t) := c c2 7 κ2 (t) 2 t 7 2 c2 2 t «{u}(t) c2 24 κ(t){ nu}(t). «{u}(t) + c 24 κ(t){ nu}(t) K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 32/ 43

47 Asymptotic Expansions Collectively computed models for higher orders Transmission condition of order N > h with γ ε,n l nũ ε,n ext h i u i ext (t) γ ε,n {ũ ε,n ext n ũ ε,n ext i (t) (c + ζ ε,n ) ũ ε,n ext (x) = f, in Ω ext, }(t) γε,n { nũ ε,n ext }(t) =, on Γm, o (t) ζ ε,n { nũ ε,n ext }(t) =, on Γm, ũ ε,n ext (x) = g on Ω := P N j=2 εj γ j,l and ζ ε,n l := P N j= εj ζ j,l and the operators (up to order 3) γ ε,2 = ε 2 c κ(t), γε,3 = γ ε,2 + ε 3 c κ(t) γ ε,2 = ε 2 c ζ ε,2 = ε c2 6 + ε2 c 2 2, γε,3 = γ ε,2 + ε 3 c 2 2, «7 2 c2 2 t, ζ ε,3 = ζ ε,2 + ε 3 c 2 4 ζ ε,2 = ε 2 c κ(t), ζε,3 = ζ ε,2 ε 3 c κ(t) 7 4 c2 7 κ2 (t) 2 t Greens formula gives ũ ε,n Ω ext v dx + { nũ ε,n ext Γ m ext {z } [v] + [ nũ ε,n ext } ]{v} dt = λ Ω ext fv dx K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 33/ 43 «

48 Asymptotic Expansions Collectively computed models for higher orders Transmission condition of order N > h nũ ε,n ext Ω ext h i ũ ε,n ext (t) γ ε,n i (t) (c + ζ ε,n ) {ũ ε,n ext n ũ ε,n ext }(t) γε,n { nũ ε,n ũ ε,n ext (x) = f, in Ω ext, ext }(t) =, on Γm, o (t) ζ ε,n { nũ ε,n ext }(t) =, on Γm, ũ ε,n ext (x) = g on Ω Mixed variational formulation Seek (ũ ε,n ext, λ) HT, (Ω ext, g) L2 (Γ m ) such that for all (v, λ ) HT, (Ω ext, ) L2 (Γ m ) ũ ε,n ext v dx + (c + ζ ε,n Γ m ){ũ ε,n ext }{v} + λ[v]dt = fv dx Γ m ([ũ ε,n ext Stability for N = 2, 3, Ic > and Rc ](t) γε,n {ũ ε,n ext }(t))λ γ ε,n λλ dt =. Ω ext ũ ε,n H (Ω ext ) + ε λ L 2 (Γ m ) + ε [ũ ε,n ] L 2 (Γ m ) C f L 2 (Ω ext ). Modelling error ũ ε,n u ε H (Ω ε ext ) C εn+ K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 34/ 43

49 Comparison of thin sheet basis and asymptotic expansions Thin sheet basis Order Mesh Usability Any for circular sheets. Sheet has to be resolved. Simple definition of basis to any order. Condition Local. Computation In one step. Convergence For ε and for N. DOF Additional variable for each function. Discretisation H -continuous elements. Ω ε int K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 35/ 43

50 Comparison of thin sheet basis and asymptotic expansions Thin sheet basis Asymptotic expansions Order Any for circular sheets. Any proven order for C -sheets. Mesh Sheet has to be resolved. Only interface. Usability Simple definition of basis to any order. Practically limited order, more and more terms (derived up to order 4). Condition Local. Local. Computation In one step. Iteratively or in one step. Convergence For ε and for N. For ε. DOF Additional variable for each function. No additional variable. Discretisation H -continuous elements. High order tangential continuity on Γ m needed with increasing order. Ω ε int Γ m K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 35/ 43

51 Conclusions Introduction Applications like casings or shielding layer. Difficult to create meshes for thin sheets and expensive to use. Model problem considering shielding and skin effects. Thin sheet basis First order impedance boundary conditions based on fundamental solutions of an ODE in thickness direction Resolving the sheet for higher order approximations. Derivation of the basis for circular sheet in kernel of 2 s j. κ +sκ s + c(ε) Proof of convergence: Best-approximation, candidate function, cancelling of low order terms. Validation by semi-analytical studies. Convergence for ε and N Asymptotic Expansions Expansion for c(ε) = c ε (asymptotically constant shielding). Derived (coupled) model by asymptotic expansions of arbitrary order. Showed existence, uniqueness, regularity and consistency. Models only for exterior field for order, and 2. Validation by numerical results with high-order FEM (Concepts). Collectively computed model of order N =. Same formulation. Collectively computed models of order N >. Mixed formulation. Showed existence, uniqueness and convergence up to order 3. Comparison K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 36/ 43

52 Asymptotic Expansions Collectively computed models for higher orders Problem with this structure u(x) = f, in Ω ext, [u] (t) + ε 2 c { nu}(t) =, on Γ m, [ nu] (t) c {u}(t) =, on Γ m, u = and the associated variational formulation u v dx + c {u}{v} + λ[v]dt = Ω ext Γ m [u]λ + ε 2 c λλ dt =. Γ m on Ω Ω ext fv dx Ellipticity?? Testing with v = u and λ = λ and substracting second from first eq. u 2 dx + c ` {u} 2 ε 2 λ 2 dt Γ m Ω ext K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 37/ 43

53 Asymptotic Expansions Collectively computed models for higher orders Lemma (Stability) Let N = 2, 3, Ic > and Rc. It holds ũ ε,n H (Ω ext ) + ε λ L 2 (Γ m ) + ε [ũ ε,n ] L 2 (Γ m ) C f L 2 (Ω ext ). Proof. u v dx + c {u}{v} + λ[v] + [u]λ + ε 2 c λλ dt = fv dx. Ω ext Γ m Ω ext. Testing with v = u and λ such that ε 2 c λ = [u]. u 2 dx + c {u} 2 ε 2 c λ 2 dt = Γ m Ω ext and taking imaginary part Ic {u} Γ 2 + ε 2 λ 2 dt = I m Ω ext Ω ext f u dx f u dx, and we have {u} L 2 (Γ m ) C f L 2 (Ω ext ), [u] L 2 (Γ m ) Cε f L 2 (Ω ext ). K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 38/ 43

54 Asymptotic Expansions Collectively computed models for higher orders Lemma (Stability) Let N = 2, 3, Ic > and Rc. It holds ũ ε,n H (Ω ext ) + ε λ L 2 (Γ m ) + ε [ũ ε,n ] L 2 (Γ m ) C f L 2 (Ω ext ). Proof. u v dx + c {u}{v} + λ[v] + [u]λ + ε 2 c λλ dt = fv dx. Ω ext Γ m Ω ext. We have {u} L 2 (Γ m ) C f L 2 (Ω ext ), [u] L 2 (Γ m ) Cε f L 2 (Ω ext ). 2. Testing with v = and λ such that ε 2 c λ = [u] λ[u]dt Γ m c ε 2 [u] 2 L 2 (Γ m ) C f 2 L 2 (Ω ). ext 3. Testing with v = u and λ =, multiplying with ( + i) and taking real part γ u 2 H (Ω ext ) u 2 dx + R (( + i)c ) {u} 2 Ω ext Γ m «= R `( + i) f u dx λ[u]dt C f 2 Γ m L 2 (Ω ). ext Ω ext K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 39/ 43

55 Asymptotic Expansions Collectively computed models for higher orders Lemma (Stability) Let N = 2, 3, Ic > and Rc. It holds ũ ε,n H (Ω ext ) + ε λ L 2 (Γ m ) + ε [ũ ε,n ] L 2 (Γ m ) C f L 2 (Ω ext ). Proof. u v dx + c {u}{v} + λ[v] + [u]λ + ε 2 c λλ dt = fv dx. Ω ext Γ m Ω ext. We have {u} L 2 (Γ m ) C f L 2 (Ω ext ), [u] L 2 (Γ m ) Cε f L 2 (Ω ext ). 2. We have RΓ m λ[u]dt C f 2 L 2 (Ω ext ). 3. We have u H (Ω ext ) C f L 2 (Ω ext ). 4. Testing with v = and λ such that ε 2 c λ = λ λ 2 dt ε 2 λ[u] dt Cε 2 f 2 Γ m c Γ m L 2 (Ω ). ext K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 4/ 43

56 Asymptotic Expansions Collectively computed models for higher orders System for order N = 2, 3 and general right hand sides. h nũ ε,n ext h i ũ ε,n ext (t) γ ε,n i (t) (c + ζ ε,n ) {ũ ε,n ext n ũ ε,n ext }(t) γε,n { nũ ε,n ũ ε,n ext (x) = f, in Ω ext, ext }(t) = g(t), on Γm, o (t) ζ ε,n { nũ ε,n ext }(t) = g2(t), on Γm, ũ ε,n ext (x) = on Ω Lemma (Stability) Let N = 2, 3, Ic > and Rc. It holds ũ ε,n H (Ω ext ) + ε λ L 2 (Γ m ) C f L 2 (Ω ext ) + ε 2 g L 2 (Γ m ) + g 2 H /2 (Γ m ). Error r ε,n+ ext = ũ ε,n ext uε,n ext solves system of the same structure with f =, g = O(ε N+ ) and g 2 = O(ε N+ ). Attention: Error only O(ε N )?? K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 4/ 43

57 Asymptotic Expansions Collectively computed models for higher orders System for order N = 2, 3 and general right hand sides. h nũ ε,n ext h i ũ ε,n ext (t) γ ε,n i (t) (c + ζ ε,n ) {ũ ε,n ext n ũ ε,n ext Lemma (Stability) Let N = 2, 3, Ic > and Rc. It holds }(t) γε,n { nũ ε,n ũ ε,n ext (x) = f, in Ω ext, ext }(t) = g(t), on Γm, o (t) ζ ε,n { nũ ε,n ext }(t) = g2(t), on Γm, ũ ε,n ext (x) = on Ω ũ ε,n H (Ω ext ) + ε λ L 2 (Γ m ) C f L 2 (Ω ext ) + ε 2 g L 2 (Γ m ) + g 2 H /2 (Γ m ). However, we can find functions v N,j ext solving similar system than un ext and r ε,n+,k ext = ũ ε,n ext uε,n ext P N+k j=n+ εj v {z} N,j solves system of the above structure with O() f =, g = O(ε N++k ), g 2 = O(ε N++k ). Result: r ε,n+,k ext is O(ε N+k ) and so with k = 2 ũ ε,n ext uε,n ext H (Ω ext ) rε,n+,2 ext Cε N+ H (Ω ext ) + εn+ v N,N+ ext H (Ω ext ) + εn+2 v N,N+2 ext H (Ω ext ) K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 42/ 43

58 Asymptotic Expansions Asymptotic expansion N uext ε (x) uε,n ext (x) := X ε i uext i (x), i= N uε int (t, s) uε,n int (t, s) := X ε i Uint i (t, s ε ) i= Hierarchical partly uncoupled problem Existence, Uniqueness and Regularity for any order Convergence of asymptotic expansion u ε u ε,n ext H (Ω ε ext ) + ε u ε u ε,n ext H (Ω ε int ) C Nε N+ Hierarchical uncoupled problem for u i ext derived up to order 4, numerical experiments up to order 2 Collective computation for ũ ε,n ext uε,n ext system for order like for uext i, well-posed, regularity, convergence mixed variational system for order higher than well-posedness and convergence for Ic > for order 2 and 3 K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 43/ 43

59 Thin sheet basis Extension to higher orders Dirichlet-to-Neumann-map of high-order, Extension of the outer solution up to the mid-line Power loss Jump in normal derivative L 2 -norm ε 2 R 2R relative error Consider resolved sheets for methods of higher order thickness ε K. Schmidt, S. Tordeux ENS Cachan Bretagne, September st 29 p. 44/ 43

Partial Differential Equations in Biology The boundary element method. March 26, 2013

Partial Differential Equations in Biology The boundary element method. March 26, 2013 The boundary element method March 26, 203 Introduction and notation The problem: u = f in D R d u = ϕ in Γ D u n = g on Γ N, where D = Γ D Γ N, Γ D Γ N = (possibly, Γ D = [Neumann problem] or Γ N = [Dirichlet

Διαβάστε περισσότερα

On optimal FEM and impedance conditions for thin electromagnetic shielding sheets

On optimal FEM and impedance conditions for thin electromagnetic shielding sheets On optimal FEM and impedance conditions for thin electromagnetic shielding sheets Kersten Schmidt Research Center Matheon, Berlin, Germany, Institut für Mathematik, Technische Universität Berlin, Germany

Διαβάστε περισσότερα

EE512: Error Control Coding

EE512: Error Control Coding EE512: Error Control Coding Solution for Assignment on Finite Fields February 16, 2007 1. (a) Addition and Multiplication tables for GF (5) and GF (7) are shown in Tables 1 and 2. + 0 1 2 3 4 0 0 1 2 3

Διαβάστε περισσότερα

Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3

Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3 Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3 1 State vector space and the dual space Space of wavefunctions The space of wavefunctions is the set of all

Διαβάστε περισσότερα

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

Chapter 6: Systems of Linear Differential. be continuous functions on the interval Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations

Διαβάστε περισσότερα

Example Sheet 3 Solutions

Example Sheet 3 Solutions Example Sheet 3 Solutions. i Regular Sturm-Liouville. ii Singular Sturm-Liouville mixed boundary conditions. iii Not Sturm-Liouville ODE is not in Sturm-Liouville form. iv Regular Sturm-Liouville note

Διαβάστε περισσότερα

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

Chapter 6: Systems of Linear Differential. be continuous functions on the interval Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations

Διαβάστε περισσότερα

Uniform Convergence of Fourier Series Michael Taylor

Uniform Convergence of Fourier Series Michael Taylor Uniform Convergence of Fourier Series Michael Taylor Given f L 1 T 1 ), we consider the partial sums of the Fourier series of f: N 1) S N fθ) = ˆfk)e ikθ. k= N A calculation gives the Dirichlet formula

Διαβάστε περισσότερα

Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics

Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics Fourier Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Introduction Not all functions can be represented by Taylor series. f (k) (c) A Taylor series f (x) = (x c)

Διαβάστε περισσότερα

Appendix to On the stability of a compressible axisymmetric rotating flow in a pipe. By Z. Rusak & J. H. Lee

Appendix to On the stability of a compressible axisymmetric rotating flow in a pipe. By Z. Rusak & J. H. Lee Appendi to On the stability of a compressible aisymmetric rotating flow in a pipe By Z. Rusak & J. H. Lee Journal of Fluid Mechanics, vol. 5 4, pp. 5 4 This material has not been copy-edited or typeset

Διαβάστε περισσότερα

Econ 2110: Fall 2008 Suggested Solutions to Problem Set 8 questions or comments to Dan Fetter 1

Econ 2110: Fall 2008 Suggested Solutions to Problem Set 8  questions or comments to Dan Fetter 1 Eon : Fall 8 Suggested Solutions to Problem Set 8 Email questions or omments to Dan Fetter Problem. Let X be a salar with density f(x, θ) (θx + θ) [ x ] with θ. (a) Find the most powerful level α test

Διαβάστε περισσότερα

2 Composition. Invertible Mappings

2 Composition. Invertible Mappings Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Composition. Invertible Mappings In this section we discuss two procedures for creating new mappings from old ones, namely,

Διαβάστε περισσότερα

Homework 8 Model Solution Section

Homework 8 Model Solution Section MATH 004 Homework Solution Homework 8 Model Solution Section 14.5 14.6. 14.5. Use the Chain Rule to find dz where z cosx + 4y), x 5t 4, y 1 t. dz dx + dy y sinx + 4y)0t + 4) sinx + 4y) 1t ) 0t + 4t ) sinx

Διαβάστε περισσότερα

Statistical Inference I Locally most powerful tests

Statistical Inference I Locally most powerful tests Statistical Inference I Locally most powerful tests Shirsendu Mukherjee Department of Statistics, Asutosh College, Kolkata, India. shirsendu st@yahoo.co.in So far we have treated the testing of one-sided

Διαβάστε περισσότερα

C.S. 430 Assignment 6, Sample Solutions

C.S. 430 Assignment 6, Sample Solutions C.S. 430 Assignment 6, Sample Solutions Paul Liu November 15, 2007 Note that these are sample solutions only; in many cases there were many acceptable answers. 1 Reynolds Problem 10.1 1.1 Normal-order

Διαβάστε περισσότερα

derivation of the Laplacian from rectangular to spherical coordinates

derivation of the Laplacian from rectangular to spherical coordinates derivation of the Laplacian from rectangular to spherical coordinates swapnizzle 03-03- :5:43 We begin by recognizing the familiar conversion from rectangular to spherical coordinates (note that φ is used

Διαβάστε περισσότερα

Reminders: linear functions

Reminders: linear functions Reminders: linear functions Let U and V be vector spaces over the same field F. Definition A function f : U V is linear if for every u 1, u 2 U, f (u 1 + u 2 ) = f (u 1 ) + f (u 2 ), and for every u U

Διαβάστε περισσότερα

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit Ting Zhang Stanford May 11, 2001 Stanford, 5/11/2001 1 Outline Ordinal Classification Ordinal Addition Ordinal Multiplication Ordinal

Διαβάστε περισσότερα

Second Order Partial Differential Equations

Second Order Partial Differential Equations Chapter 7 Second Order Partial Differential Equations 7.1 Introduction A second order linear PDE in two independent variables (x, y Ω can be written as A(x, y u x + B(x, y u xy + C(x, y u u u + D(x, y

Διαβάστε περισσότερα

SCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions

SCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions SCHOOL OF MATHEMATICAL SCIENCES GLMA Linear Mathematics 00- Examination Solutions. (a) i. ( + 5i)( i) = (6 + 5) + (5 )i = + i. Real part is, imaginary part is. (b) ii. + 5i i ( + 5i)( + i) = ( i)( + i)

Διαβάστε περισσότερα

Arithmetical applications of lagrangian interpolation. Tanguy Rivoal. Institut Fourier CNRS and Université de Grenoble 1

Arithmetical applications of lagrangian interpolation. Tanguy Rivoal. Institut Fourier CNRS and Université de Grenoble 1 Arithmetical applications of lagrangian interpolation Tanguy Rivoal Institut Fourier CNRS and Université de Grenoble Conference Diophantine and Analytic Problems in Number Theory, The 00th anniversary

Διαβάστε περισσότερα

Finite Field Problems: Solutions

Finite Field Problems: Solutions Finite Field Problems: Solutions 1. Let f = x 2 +1 Z 11 [x] and let F = Z 11 [x]/(f), a field. Let Solution: F =11 2 = 121, so F = 121 1 = 120. The possible orders are the divisors of 120. Solution: The

Διαβάστε περισσότερα

Other Test Constructions: Likelihood Ratio & Bayes Tests

Other Test Constructions: Likelihood Ratio & Bayes Tests Other Test Constructions: Likelihood Ratio & Bayes Tests Side-Note: So far we have seen a few approaches for creating tests such as Neyman-Pearson Lemma ( most powerful tests of H 0 : θ = θ 0 vs H 1 :

Διαβάστε περισσότερα

Homework 3 Solutions

Homework 3 Solutions Homework 3 Solutions Igor Yanovsky (Math 151A TA) Problem 1: Compute the absolute error and relative error in approximations of p by p. (Use calculator!) a) p π, p 22/7; b) p π, p 3.141. Solution: For

Διαβάστε περισσότερα

Inverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- -----------------

Inverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- ----------------- Inverse trigonometric functions & General Solution of Trigonometric Equations. 1. Sin ( ) = a) b) c) d) Ans b. Solution : Method 1. Ans a: 17 > 1 a) is rejected. w.k.t Sin ( sin ) = d is rejected. If sin

Διαβάστε περισσότερα

Appendix A. Curvilinear coordinates. A.1 Lamé coefficients. Consider set of equations. ξ i = ξ i (x 1,x 2,x 3 ), i = 1,2,3

Appendix A. Curvilinear coordinates. A.1 Lamé coefficients. Consider set of equations. ξ i = ξ i (x 1,x 2,x 3 ), i = 1,2,3 Appendix A Curvilinear coordinates A. Lamé coefficients Consider set of equations ξ i = ξ i x,x 2,x 3, i =,2,3 where ξ,ξ 2,ξ 3 independent, single-valued and continuous x,x 2,x 3 : coordinates of point

Διαβάστε περισσότερα

Congruence Classes of Invertible Matrices of Order 3 over F 2

Congruence Classes of Invertible Matrices of Order 3 over F 2 International Journal of Algebra, Vol. 8, 24, no. 5, 239-246 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/.2988/ija.24.422 Congruence Classes of Invertible Matrices of Order 3 over F 2 Ligong An and

Διαβάστε περισσότερα

6.3 Forecasting ARMA processes

6.3 Forecasting ARMA processes 122 CHAPTER 6. ARMA MODELS 6.3 Forecasting ARMA processes The purpose of forecasting is to predict future values of a TS based on the data collected to the present. In this section we will discuss a linear

Διαβάστε περισσότερα

Numerical Analysis FMN011

Numerical Analysis FMN011 Numerical Analysis FMN011 Carmen Arévalo Lund University carmen@maths.lth.se Lecture 12 Periodic data A function g has period P if g(x + P ) = g(x) Model: Trigonometric polynomial of order M T M (x) =

Διαβάστε περισσότερα

Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in

Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in : tail in X, head in A nowhere-zero Γ-flow is a Γ-circulation such that

Διαβάστε περισσότερα

CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS

CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS CHAPTER 5 SOLVING EQUATIONS BY ITERATIVE METHODS EXERCISE 104 Page 8 1. Find the positive root of the equation x + 3x 5 = 0, correct to 3 significant figures, using the method of bisection. Let f(x) =

Διαβάστε περισσότερα

ST5224: Advanced Statistical Theory II

ST5224: Advanced Statistical Theory II ST5224: Advanced Statistical Theory II 2014/2015: Semester II Tutorial 7 1. Let X be a sample from a population P and consider testing hypotheses H 0 : P = P 0 versus H 1 : P = P 1, where P j is a known

Διαβάστε περισσότερα

Approximation of distance between locations on earth given by latitude and longitude

Approximation of distance between locations on earth given by latitude and longitude Approximation of distance between locations on earth given by latitude and longitude Jan Behrens 2012-12-31 In this paper we shall provide a method to approximate distances between two points on earth

Διαβάστε περισσότερα

D Alembert s Solution to the Wave Equation

D Alembert s Solution to the Wave Equation D Alembert s Solution to the Wave Equation MATH 467 Partial Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Objectives In this lesson we will learn: a change of variable technique

Διαβάστε περισσότερα

Section 8.3 Trigonometric Equations

Section 8.3 Trigonometric Equations 99 Section 8. Trigonometric Equations Objective 1: Solve Equations Involving One Trigonometric Function. In this section and the next, we will exple how to solving equations involving trigonometric functions.

Διαβάστε περισσότερα

The Pohozaev identity for the fractional Laplacian

The Pohozaev identity for the fractional Laplacian The Pohozaev identity for the fractional Laplacian Xavier Ros-Oton Departament Matemàtica Aplicada I, Universitat Politècnica de Catalunya (joint work with Joaquim Serra) Xavier Ros-Oton (UPC) The Pohozaev

Διαβάστε περισσότερα

Every set of first-order formulas is equivalent to an independent set

Every set of first-order formulas is equivalent to an independent set Every set of first-order formulas is equivalent to an independent set May 6, 2008 Abstract A set of first-order formulas, whatever the cardinality of the set of symbols, is equivalent to an independent

Διαβάστε περισσότερα

Second Order RLC Filters

Second Order RLC Filters ECEN 60 Circuits/Electronics Spring 007-0-07 P. Mathys Second Order RLC Filters RLC Lowpass Filter A passive RLC lowpass filter (LPF) circuit is shown in the following schematic. R L C v O (t) Using phasor

Διαβάστε περισσότερα

Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ.

Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ. Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο The time integral of a force is referred to as impulse, is determined by and is obtained from: Newton s 2 nd Law of motion states that the action

Διαβάστε περισσότερα

4.6 Autoregressive Moving Average Model ARMA(1,1)

4.6 Autoregressive Moving Average Model ARMA(1,1) 84 CHAPTER 4. STATIONARY TS MODELS 4.6 Autoregressive Moving Average Model ARMA(,) This section is an introduction to a wide class of models ARMA(p,q) which we will consider in more detail later in this

Διαβάστε περισσότερα

Srednicki Chapter 55

Srednicki Chapter 55 Srednicki Chapter 55 QFT Problems & Solutions A. George August 3, 03 Srednicki 55.. Use equations 55.3-55.0 and A i, A j ] = Π i, Π j ] = 0 (at equal times) to verify equations 55.-55.3. This is our third

Διαβάστε περισσότερα

CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS

CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS EXERCISE 01 Page 545 1. Use matrices to solve: 3x + 4y x + 5y + 7 3x + 4y x + 5y 7 Hence, 3 4 x 0 5 y 7 The inverse of 3 4 5 is: 1 5 4 1 5 4 15 8 3

Διαβάστε περισσότερα

Graded Refractive-Index

Graded Refractive-Index Graded Refractive-Index Common Devices Methodologies for Graded Refractive Index Methodologies: Ray Optics WKB Multilayer Modelling Solution requires: some knowledge of index profile n 2 x Ray Optics for

Διαβάστε περισσότερα

CRASH COURSE IN PRECALCULUS

CRASH COURSE IN PRECALCULUS CRASH COURSE IN PRECALCULUS Shiah-Sen Wang The graphs are prepared by Chien-Lun Lai Based on : Precalculus: Mathematics for Calculus by J. Stuwart, L. Redin & S. Watson, 6th edition, 01, Brooks/Cole Chapter

Διαβάστε περισσότερα

Exercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1.

Exercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1. Exercises 0 More exercises are available in Elementary Differential Equations. If you have a problem to solve any of them, feel free to come to office hour. Problem Find a fundamental matrix of the given

Διαβάστε περισσότερα

Lecture 34 Bootstrap confidence intervals

Lecture 34 Bootstrap confidence intervals Lecture 34 Bootstrap confidence intervals Confidence Intervals θ: an unknown parameter of interest We want to find limits θ and θ such that Gt = P nˆθ θ t If G 1 1 α is known, then P θ θ = P θ θ = 1 α

Διαβάστε περισσότερα

Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013

Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013 Notes on Average Scattering imes and Hall Factors Jesse Maassen and Mar Lundstrom Purdue University November 5, 13 I. Introduction 1 II. Solution of the BE 1 III. Exercises: Woring out average scattering

Διαβάστε περισσότερα

Finite difference method for 2-D heat equation

Finite difference method for 2-D heat equation Finite difference method for 2-D heat equation Praveen. C praveen@math.tifrbng.res.in Tata Institute of Fundamental Research Center for Applicable Mathematics Bangalore 560065 http://math.tifrbng.res.in/~praveen

Διαβάστε περισσότερα

ES440/ES911: CFD. Chapter 5. Solution of Linear Equation Systems

ES440/ES911: CFD. Chapter 5. Solution of Linear Equation Systems ES440/ES911: CFD Chapter 5. Solution of Linear Equation Systems Dr Yongmann M. Chung http://www.eng.warwick.ac.uk/staff/ymc/es440.html Y.M.Chung@warwick.ac.uk School of Engineering & Centre for Scientific

Διαβάστε περισσότερα

Matrices and Determinants

Matrices and Determinants Matrices and Determinants SUBJECTIVE PROBLEMS: Q 1. For what value of k do the following system of equations possess a non-trivial (i.e., not all zero) solution over the set of rationals Q? x + ky + 3z

Διαβάστε περισσότερα

b. Use the parametrization from (a) to compute the area of S a as S a ds. Be sure to substitute for ds!

b. Use the parametrization from (a) to compute the area of S a as S a ds. Be sure to substitute for ds! MTH U341 urface Integrals, tokes theorem, the divergence theorem To be turned in Wed., Dec. 1. 1. Let be the sphere of radius a, x 2 + y 2 + z 2 a 2. a. Use spherical coordinates (with ρ a) to parametrize.

Διαβάστε περισσότερα

Wavelet based matrix compression for boundary integral equations on complex geometries

Wavelet based matrix compression for boundary integral equations on complex geometries 1 Wavelet based matrix compression for boundary integral equations on complex geometries Ulf Kähler Chemnitz University of Technology Workshop on Fast Boundary Element Methods in Industrial Applications

Διαβάστε περισσότερα

Local Approximation with Kernels

Local Approximation with Kernels Local Approximation with Kernels Thomas Hangelbroek University of Hawaii at Manoa 5th International Conference Approximation Theory, 26 work supported by: NSF DMS-43726 A cubic spline example Consider

Διαβάστε περισσότερα

Exercise 1.1. Verify that if we apply GS to the coordinate basis Gauss form ds 2 = E(u, v)du 2 + 2F (u, v)dudv + G(u, v)dv 2

Exercise 1.1. Verify that if we apply GS to the coordinate basis Gauss form ds 2 = E(u, v)du 2 + 2F (u, v)dudv + G(u, v)dv 2 Math 209 Riemannian Geometry Jeongmin Shon Problem. Let M 2 R 3 be embedded surface. Then the induced metric on M 2 is obtained by taking the standard inner product on R 3 and restricting it to the tangent

Διαβάστε περισσότερα

The Simply Typed Lambda Calculus

The Simply Typed Lambda Calculus Type Inference Instead of writing type annotations, can we use an algorithm to infer what the type annotations should be? That depends on the type system. For simple type systems the answer is yes, and

Διαβάστε περισσότερα

Phys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required)

Phys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required) Phys460.nb 81 ψ n (t) is still the (same) eigenstate of H But for tdependent H. The answer is NO. 5.5.5. Solution for the tdependent Schrodinger s equation If we assume that at time t 0, the electron starts

Διαβάστε περισσότερα

3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β

3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β 3.4 SUM AND DIFFERENCE FORMULAS Page Theorem cos(αβ cos α cos β -sin α cos(α-β cos α cos β sin α NOTE: cos(αβ cos α cos β cos(α-β cos α -cos β Proof of cos(α-β cos α cos β sin α Let s use a unit circle

Διαβάστε περισσότερα

Fractional Colorings and Zykov Products of graphs

Fractional Colorings and Zykov Products of graphs Fractional Colorings and Zykov Products of graphs Who? Nichole Schimanski When? July 27, 2011 Graphs A graph, G, consists of a vertex set, V (G), and an edge set, E(G). V (G) is any finite set E(G) is

Διαβάστε περισσότερα

On the Galois Group of Linear Difference-Differential Equations

On the Galois Group of Linear Difference-Differential Equations On the Galois Group of Linear Difference-Differential Equations Ruyong Feng KLMM, Chinese Academy of Sciences, China Ruyong Feng (KLMM, CAS) Galois Group 1 / 19 Contents 1 Basic Notations and Concepts

Διαβάστε περισσότερα

Institut de Recherche MAthématique de Rennes

Institut de Recherche MAthématique de Rennes Oberwolfach meeting on Computational Electromagnetism Feb 22 - Feb 28 Singularities of electromagnetic fields in the Maxwell and eddy current formulations Martin COSTABEL, Monique DAUGE, Serge NICAISE

Διαβάστε περισσότερα

Higher Derivative Gravity Theories

Higher Derivative Gravity Theories Higher Derivative Gravity Theories Black Holes in AdS space-times James Mashiyane Supervisor: Prof Kevin Goldstein University of the Witwatersrand Second Mandelstam, 20 January 2018 James Mashiyane WITS)

Διαβάστε περισσότερα

Dr. D. Dinev, Department of Structural Mechanics, UACEG

Dr. D. Dinev, Department of Structural Mechanics, UACEG Lecture 4 Material behavior: Constitutive equations Field of the game Print version Lecture on Theory of lasticity and Plasticity of Dr. D. Dinev, Department of Structural Mechanics, UACG 4.1 Contents

Διαβάστε περισσότερα

Parametrized Surfaces

Parametrized Surfaces Parametrized Surfaces Recall from our unit on vector-valued functions at the beginning of the semester that an R 3 -valued function c(t) in one parameter is a mapping of the form c : I R 3 where I is some

Διαβάστε περισσότερα

ECE Spring Prof. David R. Jackson ECE Dept. Notes 2

ECE Spring Prof. David R. Jackson ECE Dept. Notes 2 ECE 634 Spring 6 Prof. David R. Jackson ECE Dept. Notes Fields in a Source-Free Region Example: Radiation from an aperture y PEC E t x Aperture Assume the following choice of vector potentials: A F = =

Διαβάστε περισσότερα

New bounds for spherical two-distance sets and equiangular lines

New bounds for spherical two-distance sets and equiangular lines New bounds for spherical two-distance sets and equiangular lines Michigan State University Oct 8-31, 016 Anhui University Definition If X = {x 1, x,, x N } S n 1 (unit sphere in R n ) and x i, x j = a

Διαβάστε περισσότερα

Discretization of Generalized Convection-Diffusion

Discretization of Generalized Convection-Diffusion Discretization of Generalized Convection-Diffusion H. Heumann R. Hiptmair Seminar für Angewandte Mathematik ETH Zürich Colloque Numérique Suisse / Schweizer Numerik Kolloquium 8 Generalized Convection-Diffusion

Διαβάστε περισσότερα

5. Choice under Uncertainty

5. Choice under Uncertainty 5. Choice under Uncertainty Daisuke Oyama Microeconomics I May 23, 2018 Formulations von Neumann-Morgenstern (1944/1947) X: Set of prizes Π: Set of probability distributions on X : Preference relation

Διαβάστε περισσότερα

Lecture 26: Circular domains

Lecture 26: Circular domains Introductory lecture notes on Partial Differential Equations - c Anthony Peirce. Not to be copied, used, or revised without eplicit written permission from the copyright owner. 1 Lecture 6: Circular domains

Διαβάστε περισσότερα

Areas and Lengths in Polar Coordinates

Areas and Lengths in Polar Coordinates Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the

Διαβάστε περισσότερα

Nonlinear Fourier transform for the conductivity equation. Visibility and Invisibility in Impedance Tomography

Nonlinear Fourier transform for the conductivity equation. Visibility and Invisibility in Impedance Tomography Nonlinear Fourier transform for the conductivity equation Visibility and Invisibility in Impedance Tomography Kari Astala University of Helsinki CoE in Analysis and Dynamics Research What is the non linear

Διαβάστε περισσότερα

DiracDelta. Notations. Primary definition. Specific values. General characteristics. Traditional name. Traditional notation

DiracDelta. Notations. Primary definition. Specific values. General characteristics. Traditional name. Traditional notation DiracDelta Notations Traditional name Dirac delta function Traditional notation x Mathematica StandardForm notation DiracDeltax Primary definition 4.03.02.000.0 x Π lim ε ; x ε0 x 2 2 ε Specific values

Διαβάστε περισσότερα

Pg The perimeter is P = 3x The area of a triangle is. where b is the base, h is the height. In our case b = x, then the area is

Pg The perimeter is P = 3x The area of a triangle is. where b is the base, h is the height. In our case b = x, then the area is Pg. 9. The perimeter is P = The area of a triangle is A = bh where b is the base, h is the height 0 h= btan 60 = b = b In our case b =, then the area is A = = 0. By Pythagorean theorem a + a = d a a =

Διαβάστε περισσότερα

Math 446 Homework 3 Solutions. (1). (i): Reverse triangle inequality for metrics: Let (X, d) be a metric space and let x, y, z X.

Math 446 Homework 3 Solutions. (1). (i): Reverse triangle inequality for metrics: Let (X, d) be a metric space and let x, y, z X. Math 446 Homework 3 Solutions. (1). (i): Reverse triangle inequalit for metrics: Let (X, d) be a metric space and let x,, z X. Prove that d(x, z) d(, z) d(x, ). (ii): Reverse triangle inequalit for norms:

Διαβάστε περισσότερα

Tridiagonal matrices. Gérard MEURANT. October, 2008

Tridiagonal matrices. Gérard MEURANT. October, 2008 Tridiagonal matrices Gérard MEURANT October, 2008 1 Similarity 2 Cholesy factorizations 3 Eigenvalues 4 Inverse Similarity Let α 1 ω 1 β 1 α 2 ω 2 T =......... β 2 α 1 ω 1 β 1 α and β i ω i, i = 1,...,

Διαβάστε περισσότερα

Math221: HW# 1 solutions

Math221: HW# 1 solutions Math: HW# solutions Andy Royston October, 5 7.5.7, 3 rd Ed. We have a n = b n = a = fxdx = xdx =, x cos nxdx = x sin nx n sin nxdx n = cos nx n = n n, x sin nxdx = x cos nx n + cos nxdx n cos n = + sin

Διαβάστε περισσότερα

forms This gives Remark 1. How to remember the above formulas: Substituting these into the equation we obtain with

forms This gives Remark 1. How to remember the above formulas: Substituting these into the equation we obtain with Week 03: C lassification of S econd- Order L inear Equations In last week s lectures we have illustrated how to obtain the general solutions of first order PDEs using the method of characteristics. We

Διαβάστε περισσότερα

6.1. Dirac Equation. Hamiltonian. Dirac Eq.

6.1. Dirac Equation. Hamiltonian. Dirac Eq. 6.1. Dirac Equation Ref: M.Kaku, Quantum Field Theory, Oxford Univ Press (1993) η μν = η μν = diag(1, -1, -1, -1) p 0 = p 0 p = p i = -p i p μ p μ = p 0 p 0 + p i p i = E c 2 - p 2 = (m c) 2 H = c p 2

Διαβάστε περισσότερα

k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R +

k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R + Chapter 3. Fuzzy Arithmetic 3- Fuzzy arithmetic: ~Addition(+) and subtraction (-): Let A = [a and B = [b, b in R If x [a and y [b, b than x+y [a +b +b Symbolically,we write A(+)B = [a (+)[b, b = [a +b

Διαβάστε περισσότερα

ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ

ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ ΕΛΕΝΑ ΦΛΟΚΑ Επίκουρος Καθηγήτρια Τµήµα Φυσικής, Τοµέας Φυσικής Περιβάλλοντος- Μετεωρολογίας ΓΕΝΙΚΟΙ ΟΡΙΣΜΟΙ Πληθυσµός Σύνολο ατόµων ή αντικειµένων στα οποία αναφέρονται

Διαβάστε περισσότερα

Section 7.6 Double and Half Angle Formulas

Section 7.6 Double and Half Angle Formulas 09 Section 7. Double and Half Angle Fmulas To derive the double-angles fmulas, we will use the sum of two angles fmulas that we developed in the last section. We will let α θ and β θ: cos(θ) cos(θ + θ)

Διαβάστε περισσότερα

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM Solutions to Question 1 a) The cumulative distribution function of T conditional on N n is Pr (T t N n) Pr (max (X 1,..., X N ) t N n) Pr (max

Διαβάστε περισσότερα

w o = R 1 p. (1) R = p =. = 1

w o = R 1 p. (1) R = p =. = 1 Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών ΗΥ-570: Στατιστική Επεξεργασία Σήµατος 205 ιδάσκων : Α. Μουχτάρης Τριτη Σειρά Ασκήσεων Λύσεις Ασκηση 3. 5.2 (a) From the Wiener-Hopf equation we have:

Διαβάστε περισσότερα

Concrete Mathematics Exercises from 30 September 2016

Concrete Mathematics Exercises from 30 September 2016 Concrete Mathematics Exercises from 30 September 2016 Silvio Capobianco Exercise 1.7 Let H(n) = J(n + 1) J(n). Equation (1.8) tells us that H(2n) = 2, and H(2n+1) = J(2n+2) J(2n+1) = (2J(n+1) 1) (2J(n)+1)

Διαβάστε περισσότερα

ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2

ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2 ΤΜΗΜΑ ΗΛΕΚΤΡΟΛΟΓΩΝ ΜΗΧΑΝΙΚΩΝ ΚΑΙ ΜΗΧΑΝΙΚΩΝ ΥΠΟΛΟΓΙΣΤΩΝ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΥΠΡΟΥ ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος 2007-08 -- Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2 Ημερομηνία Παραδόσεως: Παρασκευή

Διαβάστε περισσότερα

Problem Set 9 Solutions. θ + 1. θ 2 + cotθ ( ) sinθ e iφ is an eigenfunction of the ˆ L 2 operator. / θ 2. φ 2. sin 2 θ φ 2. ( ) = e iφ. = e iφ cosθ.

Problem Set 9 Solutions. θ + 1. θ 2 + cotθ ( ) sinθ e iφ is an eigenfunction of the ˆ L 2 operator. / θ 2. φ 2. sin 2 θ φ 2. ( ) = e iφ. = e iφ cosθ. Chemistry 362 Dr Jean M Standard Problem Set 9 Solutions The ˆ L 2 operator is defined as Verify that the angular wavefunction Y θ,φ) Also verify that the eigenvalue is given by 2! 2 & L ˆ 2! 2 2 θ 2 +

Διαβάστε περισσότερα

Solutions to Exercise Sheet 5

Solutions to Exercise Sheet 5 Solutions to Eercise Sheet 5 jacques@ucsd.edu. Let X and Y be random variables with joint pdf f(, y) = 3y( + y) where and y. Determine each of the following probabilities. Solutions. a. P (X ). b. P (X

Διαβάστε περισσότερα

Practice Exam 2. Conceptual Questions. 1. State a Basic identity and then verify it. (a) Identity: Solution: One identity is csc(θ) = 1

Practice Exam 2. Conceptual Questions. 1. State a Basic identity and then verify it. (a) Identity: Solution: One identity is csc(θ) = 1 Conceptual Questions. State a Basic identity and then verify it. a) Identity: Solution: One identity is cscθ) = sinθ) Practice Exam b) Verification: Solution: Given the point of intersection x, y) of the

Διαβάστε περισσότερα

Areas and Lengths in Polar Coordinates

Areas and Lengths in Polar Coordinates Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the

Διαβάστε περισσότερα

2. Let H 1 and H 2 be Hilbert spaces and let T : H 1 H 2 be a bounded linear operator. Prove that [T (H 1 )] = N (T ). (6p)

2. Let H 1 and H 2 be Hilbert spaces and let T : H 1 H 2 be a bounded linear operator. Prove that [T (H 1 )] = N (T ). (6p) Uppsala Universitet Matematiska Institutionen Andreas Strömbergsson Prov i matematik Funktionalanalys Kurs: F3B, F4Sy, NVP 2005-03-08 Skrivtid: 9 14 Tillåtna hjälpmedel: Manuella skrivdon, Kreyszigs bok

Διαβάστε περισσότερα

ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007

ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007 Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Αν κάπου κάνετε κάποιες υποθέσεις να αναφερθούν στη σχετική ερώτηση. Όλα τα αρχεία που αναφέρονται στα προβλήματα βρίσκονται στον ίδιο φάκελο με το εκτελέσιμο

Διαβάστε περισσότερα

Lecture 21: Properties and robustness of LSE

Lecture 21: Properties and robustness of LSE Lecture 21: Properties and robustness of LSE BLUE: Robustness of LSE against normality We now study properties of l τ β and σ 2 under assumption A2, i.e., without the normality assumption on ε. From Theorem

Διαβάστε περισσότερα

Matrices and vectors. Matrix and vector. a 11 a 12 a 1n a 21 a 22 a 2n A = b 1 b 2. b m. R m n, b = = ( a ij. a m1 a m2 a mn. def

Matrices and vectors. Matrix and vector. a 11 a 12 a 1n a 21 a 22 a 2n A = b 1 b 2. b m. R m n, b = = ( a ij. a m1 a m2 a mn. def Matrices and vectors Matrix and vector a 11 a 12 a 1n a 21 a 22 a 2n A = a m1 a m2 a mn def = ( a ij ) R m n, b = b 1 b 2 b m Rm Matrix and vectors in linear equations: example E 1 : x 1 + x 2 + 3x 4 =

Διαβάστε περισσότερα

ANSWERSHEET (TOPIC = DIFFERENTIAL CALCULUS) COLLECTION #2. h 0 h h 0 h h 0 ( ) g k = g 0 + g 1 + g g 2009 =?

ANSWERSHEET (TOPIC = DIFFERENTIAL CALCULUS) COLLECTION #2. h 0 h h 0 h h 0 ( ) g k = g 0 + g 1 + g g 2009 =? Teko Classes IITJEE/AIEEE Maths by SUHAAG SIR, Bhopal, Ph (0755) 3 00 000 www.tekoclasses.com ANSWERSHEET (TOPIC DIFFERENTIAL CALCULUS) COLLECTION # Question Type A.Single Correct Type Q. (A) Sol least

Διαβάστε περισσότερα

Coefficient Inequalities for a New Subclass of K-uniformly Convex Functions

Coefficient Inequalities for a New Subclass of K-uniformly Convex Functions International Journal of Computational Science and Mathematics. ISSN 0974-89 Volume, Number (00), pp. 67--75 International Research Publication House http://www.irphouse.com Coefficient Inequalities for

Διαβάστε περισσότερα

Forced Pendulum Numerical approach

Forced Pendulum Numerical approach Numerical approach UiO April 8, 2014 Physical problem and equation We have a pendulum of length l, with mass m. The pendulum is subject to gravitation as well as both a forcing and linear resistance force.

Διαβάστε περισσότερα

Aquinas College. Edexcel Mathematical formulae and statistics tables DO NOT WRITE ON THIS BOOKLET

Aquinas College. Edexcel Mathematical formulae and statistics tables DO NOT WRITE ON THIS BOOKLET Aquinas College Edexcel Mathematical formulae and statistics tables DO NOT WRITE ON THIS BOOKLET Pearson Edexcel Level 3 Advanced Subsidiary and Advanced GCE in Mathematics and Further Mathematics Mathematical

Διαβάστε περισσότερα

Differential equations

Differential equations Differential equations Differential equations: An equation inoling one dependent ariable and its deriaties w. r. t one or more independent ariables is called a differential equation. Order of differential

Διαβάστε περισσότερα

PARTIAL NOTES for 6.1 Trigonometric Identities

PARTIAL NOTES for 6.1 Trigonometric Identities PARTIAL NOTES for 6.1 Trigonometric Identities tanθ = sinθ cosθ cotθ = cosθ sinθ BASIC IDENTITIES cscθ = 1 sinθ secθ = 1 cosθ cotθ = 1 tanθ PYTHAGOREAN IDENTITIES sin θ + cos θ =1 tan θ +1= sec θ 1 + cot

Διαβάστε περισσότερα

ΠΤΥΧΙΑΚΗ ΕΡΓΑΣΙΑ "ΠΟΛΥΚΡΙΤΗΡΙΑ ΣΥΣΤΗΜΑΤΑ ΛΗΨΗΣ ΑΠΟΦΑΣΕΩΝ. Η ΠΕΡΙΠΤΩΣΗ ΤΗΣ ΕΠΙΛΟΓΗΣ ΑΣΦΑΛΙΣΤΗΡΙΟΥ ΣΥΜΒΟΛΑΙΟΥ ΥΓΕΙΑΣ "

ΠΤΥΧΙΑΚΗ ΕΡΓΑΣΙΑ ΠΟΛΥΚΡΙΤΗΡΙΑ ΣΥΣΤΗΜΑΤΑ ΛΗΨΗΣ ΑΠΟΦΑΣΕΩΝ. Η ΠΕΡΙΠΤΩΣΗ ΤΗΣ ΕΠΙΛΟΓΗΣ ΑΣΦΑΛΙΣΤΗΡΙΟΥ ΣΥΜΒΟΛΑΙΟΥ ΥΓΕΙΑΣ ΤΕΧΝΟΛΟΓΙΚΟ ΕΚΠΑΙΔΕΥΤΙΚΟ ΙΔΡΥΜΑ ΚΑΛΑΜΑΤΑΣ ΣΧΟΛΗ ΔΙΟΙΚΗΣΗΣ ΟΙΚΟΝΟΜΙΑΣ ΤΜΗΜΑ ΜΟΝΑΔΩΝ ΥΓΕΙΑΣ ΚΑΙ ΠΡΟΝΟΙΑΣ ΠΤΥΧΙΑΚΗ ΕΡΓΑΣΙΑ "ΠΟΛΥΚΡΙΤΗΡΙΑ ΣΥΣΤΗΜΑΤΑ ΛΗΨΗΣ ΑΠΟΦΑΣΕΩΝ. Η ΠΕΡΙΠΤΩΣΗ ΤΗΣ ΕΠΙΛΟΓΗΣ ΑΣΦΑΛΙΣΤΗΡΙΟΥ ΣΥΜΒΟΛΑΙΟΥ

Διαβάστε περισσότερα

Partial Trace and Partial Transpose

Partial Trace and Partial Transpose Partial Trace and Partial Transpose by José Luis Gómez-Muñoz http://homepage.cem.itesm.mx/lgomez/quantum/ jose.luis.gomez@itesm.mx This document is based on suggestions by Anirban Das Introduction This

Διαβάστε περισσότερα