SlideShare a Scribd company logo
2007 ACES Conference


 Combined Loss Mechanism and Stability
Model for the Partial Element Equivalent
                              Circuit Technique
                                   Giulio Antonini
         UAq EMC Laboratory, Department of Electrical Engineering
                         University of L’Aquila, AQ 67040, ITALY
                                    Albert Ruehli
                           IBM T. J. Watson Research Center
                           Yorktown Heights, NY 10598, USA


Verona, March 22, 2007                                             Slide 1 of 33
Outline

  q PEEC modeling of skin-effect
        • volume filament approach
        • 1D macro-basis functions
        • higher order basis functions

  q Diffusion equation

  q Broadband combined loss and stability models

  q PEEC equivalent circuit

  q Numerical results

  q Conclusions and future work


Verona, March 22, 2007                             Slide 2 of 33
Frequency dependent phenomena modeling

   • Frequency dependent phenomena (skin-effect, dielectric losses)
        – easier to be modeled in the frequency domain.
   • Stability and passivity issues:
        – easier to be handled at a macromodel level.
   • Macromodels can be generated from either time-domain or
     frequency domain solvers.
   • Fast techniques (FMM, MLFMM, QR) are well established for
     frequency domain solvers.
   • A viable solution is: use frequency domain analysis to generate
     samples to be used for macromodeling (Adaptive Frequency
     Sampling can be useful).

Verona, March 22, 2007                                       Slide 3 of 33
Advanced frequency domain PEEC solver




                                                                                   Broadband
                                                                                   macromodel
                                                       PEEC frequency
                                                        domain solver
          Frequency dependent phenomena
               (skin-effect, dispersive
                and lossy dielectrics)




                                  Fitting techniques             Acceleration techniques
                                      powered by                  FMM, MLFMM, QR
                                   AFS algorithm




Verona, March 22, 2007                                                                          Slide 4 of 33
Overview of skin effect modelling
Key parameters
                          2
   • skin-depth δ =      µσω

   • layer thickness t

   • if t   δ the field diffusion can be neglected and the layer can be
     approximated as a PEC surface
   • if t   δ the tangential electric field is virtually constant through the
     layer: the sheet can be modeled by a surface resistance 1/σt;
   • if t ∼ δ the spatial resolution inside the conductor has to be very fine,
          =
     much shorter than the skin depth ⇒ memory and time consuming

Target
   • a symmetric, two-way macromodel which is valid for arbitrary t/δ
     ratios
Verona, March 22, 2007                                               Slide 5 of 33
PEEC modeling of skin-effect
Skin-effect modelling

   • Volume filament approach: large number of unknowns
   • Non-uniform discretization helps in reducing the number of unknowns




   • Macro-basis functions represent another possibility


Verona, March 22, 2007                                          Slide 6 of 33
PEEC modeling of skin-effect
                                    z                 I1


                                                                   d
                                                      I            d    y
                                                          2
                               I1



                   x
                               I2
                                    W




                                    J (r, s)
                           i
                         E (r, s) =          + sA(r, s) +     φ(r, s)
                                       σ

                V1 (s) = Z11 I1 + Z12 I2 + Lp11 sI1 +              Lp1j sIj
                                                               j

                V2 (s) = Z21 I1 + Z22 I2 + Lp22 sI2 +              Lp2j sIj
                                                               j


Verona, March 22, 2007                                                        Slide 7 of 33
PEEC modeling of skin-effect
                                                         
                             V1           Z11 Z12        I1
                                 =                       
                             V2           Z21 Z22        I2
The 2D and 3D cases are a combination of the 1D case.
                                                              l
                   z

                         y
                 x
                                                Iy                w

                              Ix



Hypothesis: transverse electric field distribution


Verona, March 22, 2007                                                Slide 8 of 33
PEEC modeling of skin-effect
            Ex (z) = Ae−γz + Beγz              Jx (z) = σ Ae−γz + Beγz
Since we associate a current with each cell, we can relate the current I1
to the the electric field as
                                       d                     d
                          I1
                                           e−γz dz + B           eγz dz
                             =A
                         σW        0                     0

                                   0                         0
                          I2
                                           e−γz dz + B           eγz dz
                             =A
                         σW       −d                     −d
After integration
                         I1 γ
                              = −A(e−γd − 1) + B(eγd − 1)
                         σW
                         I2 γ
                              = A(eγd − 1) − B(e−γd − 1)
                         σW

Verona, March 22, 2007                                                    Slide 9 of 33
PEEC modeling of skin-effect

     Jx (s, z) = σEx (s, z) = σ Ae−γz + Beγz
                  γ             1
                                             eγz − e−γz+γd I1
               =
                 W (e−2γd − e−γd + eγd − 1)
                          e−γz − e−γd+γz I2
                     +
                     = f1 (s, z)I1 + f2 (s, z)I2

For a conductor translated along the z axis the two basis functions de-
scribing current density profile in the same direction are:
                     γ            1
                                                eγ(z−zmax2 ) − e−γ(z−zmin2 )
f1 (s, z) =
                     W (e−2γd − e−γd + eγd − 1)
                     γ            1
                                                e−γ(z−zmin1 ) − eγ(z−zmax1 )
f2 (s, z) =
                     W (e−2γd − e−γd + eγd − 1)


Verona, March 22, 2007                                               Slide 10 of 33
PEEC modeling of skin-effect
The voltage across the top cell is given by integrating the electric field as
                                        L
                         V1 (s) =           Ex (s, d)dx = LEx (d)
                                    0

which results in
                                    eγd − e−2γd      e−γd − 1
                          γL
                 V1 (s) =                       I1 +          I2
                          σW            den            den

where den = e−2γd − e−γd + eγd − 1.
Finally, the impedances are identified as:

                                             eγd − e−2γd
                                   γL
               Z11 (s) = Z22 (s) =
                                   σW (e−2γd − e−γd − 1 + eγd )
                                              e−γd − 1
                                   γL
               Z12 (s) = Z21 (s) =
                                   σW (e−2γd − e−γd − 1 + eγd )

Verona, March 22, 2007                                              Slide 11 of 33
Asymptotic behavior



Limit as γ → 0
                                                     3L
                         lim Z11 (s) = lim Z22 (s) =
                                                     2 σW d
                         γ→0           γ→0
                                                       1L
                         lim Z12 (s) = lim Z21 (s) = −
                                                       2 σW d
                         γ→0           γ→0

At DC currents are equal, I1 = I2 = I:
                                                            L
                         RDC = lim [Z11 (s) + Z12 (s)] =
                                                           σW d
                                γ→0




Verona, March 22, 2007                                            Slide 12 of 33
Asymptotic behavior


Limit as γ → ∞

                         lim Z12 (s) =   lim Z21 (s) = 0
                         γ→∞             γ→∞

⇒ currents I1 and I2 are decoupled.
                                                      γL
                lim Z11 (s) = lim Z22 (s) = lim
                                                γ→∞ σW
               γ→∞                γ→∞
                                                         √
                                          √
Considering that for good conductors γ = jωµσ = (1 + j) πf µσ =
(1 + j) /δ, the standard surface impedance is obtained.




Verona, March 22, 2007                                     Slide 13 of 33
Thin and thick objects
                         Thin object               Thick object




         1-d macro PEEC model

         2-d macro PEEC model

          Standard PEEC model



   • Middle region: standard PEEC model adopting brick basis function
   • side regions: 1D macro PEEC model adopting 1D macro-basis func-
     tions
   • corner regions: 2D macro PEEC model adopting 2D macro-basis
     functions

Verona, March 22, 2007                                            Slide 14 of 33
Macro-basis functions


The basis functions can be used as testing functions within a Galerkin’s
procedure.
Let F (r, s) represent a generic vector term in the electric field integral
equation:
                           J (r, s)
                  i
                E (r, s) =          + sA(r, s) + φ(r, s)
                              σ
The inner product to test this equation is defined as:

                                                   f ∗ (s, z) · F (r, s)dr j
                     F (r, s), f i (s, z) =          i
                                              Vj

where Vj is the j − th elementary volume.




Verona, March 22, 2007                                                         Slide 15 of 33
Macro-basis functions




                                     J (r) =           f j (s, r)Ij
                                                   j


                         1
                                         f ∗ (s, r) · f j (s, r) dr i dr j
           Rij     =                       i
                         σ    Vj    Vi

                                                                    e−jk0 |r−r |
                          µ
                                          f ∗ (s, r)
           Lij     =                                   · f j (s, r)              dr i dr j
                                            i
                         4π                                          |r − r |
                               Vj    Vi




Verona, March 22, 2007                                                                   Slide 16 of 33
Diffusion equations

Inside a good conductor (e.g. σ    ωε) the displacement current can be
neglected and the fields can be described in terms of diffusion equations.
                         ∂Hy (z, s)
                                      = −σEx (z, s)
                           ∂z
                         ∂Ex (z, s)
                                      = −sµHy (z, s)
                           ∂z

                                         sµ
                              Zc (s) =
                                         σ
                                       √
                               γ (s) =  sµσ

The diffusion of magnetic and electric fields in the conductor can be
interpreted as diffusion of voltage and current in a LG transmission line.


Verona, March 22, 2007                                          Slide 17 of 33
Diffusion equations


Two-way macromodel
                                        
   E           Z (s) Z12 (s)          H
  x,1  =  11                      y,1 
   Ex,2        Z21 (s) Z22 (s)        Hy,2
                                                              
                sµ(s)
                       coth γ (s) t − sµ(s) csch γ (s) t    H
                                                           y,1 
              γ(s)                    γ(s)
          =
               − sµ(s) csch γ (s) t sµ(s) coth γ (s) t      Hy,2
                  γ(s)                γ(s)

where Ex,1 , Ex,2 are proportional to V1 , V2 and Hy,1 , Hy,2 are proportional
to the currents on side 1 and 2.




Verona, March 22, 2007                                               Slide 18 of 33
Stability

If the diffusion of magnetic and electric fields in the conductor are inter-
preted as diffusion of voltage and current in a LCG, (R = 0) transmission
line, poles can be analytically computed, by using a modal expansion, as:

                                                                nπ 2
                                                        2
                             1     G           1    G            t
                  pn,12   =−              ±                 −
                             2     C           4    C           LC

   • all the poles have a negative real part ⇒ stability is ensured
   • for large G (good conductors)

                                        ∼ 0, pn,2 ∼ − G , ∀n
                                 pn,1   =         =
                                                      C
       ⇒ the poles are multiple (numerically)



Verona, March 22, 2007                                                 Slide 19 of 33
Broadband stable PEEC models for skin-effect
               and magnetic-electric field couplings

Frequency dependent partial inductances ⇒ damping in the partial
elements (Kochetov, Wollenberg, 2005)
Distributed approach-suitable for time domain implementation

                                               e−s|r m −r n |/c0
                              µ
               Lp,mn (s) =                                       dvm dvn
                           4πam an               |r m − r n |
                                     vm   vn

                                     nL                  c
                                                        Np
                                      p
                                                                         Resc ∗
                                          Resr                 Resc
ZL,mn (s) = sLp,mn (s) = dL +                 k                    k         k
                                                    +                 +
                          mn
                                                                        s − pc ∗
                                         s − pr               s − pc
                                               k                    k         k
                                     k=1                k=1
   • Stability can be enforced during the fitting.
   • Passivity is enforced as a-posteriori step.
   • A large number of lumped elements is needed to synthesize
     ZL,mn (s).

Verona, March 22, 2007                                                     Slide 20 of 33
Broadband stable PEEC models for skin-effect
               and magnetic-electric field couplings
                              ZI          Z        V          Lp
                              12 2            11       L        11
                         I1

                     +                                                     +
                 V1                                                            V
                                                                                   2
                   −                                                       −

                                                                                  
                                          np R11                         R12
                                                                     p
                                  d11 +                    d12 +
                                          k=1 s−pk                   k=1 s−pk
                Z(s) =                                                            
                                          np R21                         R22
                                                                     p
                                  d21 +                    d22 +
                                          k=1 s−pk                   k=1 s−pk

Adaptive Frequency Sampling (AFS) can be useful to generate broadband
macromodels keeping the order np and the number of samples as low as
possible.

Verona, March 22, 2007                                                                 Slide 21 of 33
Global approach-frequency domain
                         implementation+fitting



   • the macromodel allows to reduce the number of unknowns
   • the macromodel is incorporated into a frequency domain solver
   • acceleration techniques are used to speed-up the solution at each
     frequency
   • frequency samples are used to generate a macromodel of the
     overall system via fitting techniques




Verona, March 22, 2007                                        Slide 22 of 33
Single conductor modeling with symmetrical boundary conditions



                         t                       L


                                W



   • length L = 1 mm
   • width W = 150 µm
   • thickness t = 2d = 30 µm
   • electrical conductivity σ = 5.8 · 107 S/m

Frequency range 0-50 GHz
Symmetrical boundary conditions ⇒ currents I1 = I2 = I = 1 mA.
Surface model: sµ/σL/W .

Verona, March 22, 2007                                     Slide 23 of 33
Single conductor modeling with symmetrical boundary conditions

      V (s) = Z11 (s) I1 (s) + Z12 (s) I2 (s) = [Z11 (s) + Z12 (s)] I (s)

                                                                  ˜
               Zse (s) = Z11 (s) + Z12 (s)                        Zse (s) = RDC + Zs (s)

                          −1
                         10
                                    Z
                                     s
                                    RDC
                                    Z
                                     11




                          −2
                         10




                          −3
                         10    −3          −2                      −1       0
                              10          10                      10       10
                                                Frequency [GHz]




  Comparison of impedance Zs (s), the DC resistance RDC and Z11 (s)

Verona, March 22, 2007                                                                     Slide 24 of 33
Single conductor modeling with symmetrical boundary conditions
Surface model Zs (s) =                    sµ/σL/W : well established skin-effect
                                                                          ˜
               Zse (s) = Z11 (s) + Z12 (s)                                Zse (s) = RDC + Zs (s)

                          1
                         10
                                                                                          Z +Z
                                                                                           11   12
                                                                                          Zs+RDC



                          0
                         10




                          −1
                         10




                          −2
                         10




                          −3
                         10    −5    −4      −3    −2          −1           0    1    2               3
                              10    10      10    10         10            10   10   10              10
                                                        Frequency [GHz]




Comparison of the exact impedance Zse (s) = Z11 (s) + Z12 (s) with the
                                ˜
              approximated one Zse (s) = RDC + Zs (s)
Verona, March 22, 2007                                                                                    Slide 25 of 33
Single conductor modeling with symmetrical boundary conditions
Transfer impedance Z12 = Z21 , f = 0 − 50 GHz

                          0
                         10




                          −5
                         10




                          −10
                         10




                          −15
                         10




                          −20
                         10




                          −25
                         10     −5    −4    −3     −2         −1    0    1    2
                              10     10    10    10          10    10   10   10
                                                 Frequency [GHz]




With the increasing of the frequency the coupling between the two half-
cells rapidly decreases.

Verona, March 22, 2007                                                            Slide 26 of 33
Single conductor modeling with symmetrical boundary conditions


                                                                                      I1=I2=1 mA




                                                            6
                                                         x 10

                                                  2.5


                                                    2


                                                  1.5




                                      J [A/m2]
                                            x
                                                    1


                                                  0.5


                                                    0
                                                    2

                                                                                                                                        1.5
                                                                1
                                                                                                                             1
                                                                                                                       0.5
                                                                      0
                                                    −4
                                                                                                                  0
                                                 x 10
                                                                                                          −0.5                      −5
                                                                            −1                                                   x 10
                                                                                                     −1
                                                                                              −1.5
                                                                                 −2   −2
                                                                    x [m]
                                                                                                          z [m]




  Left: electric field profile as a function of z coordinate and frequency;
         right: current density distribution over the cross section.



Verona, March 22, 2007                                                                                                Slide 27 of 33
Single conductor modeling with symmetrical boundary conditions


                                Frequency dependent basis functions
               10                                                                  10
            x 10                                                                x 10
      3.5                                                                 3.5



       3                                                                   3



      2.5                                                                 2.5



       2                                                                   2



      1.5                                                                 1.5



       1                                                                   1



      0.5                                                                 0.5



       0                                                                   0
       −2           −1.5   −1   −0.5           0   0.5   1          1.5    −2           −1.5   −1   −0.5           0   0.5   1          1.5
                                       z [m]                                                               z [m]
                                                                −5                                                                  −5
                                                             x 10                                                                x 10




                                                             f = 30 GHz



Verona, March 22, 2007                                                                                                       Slide 28 of 33
Single conductor modeling with symmetrical boundary conditions



                         Frequency dependent basis functions




Verona, March 22, 2007                                         Slide 29 of 33
Resistance and internal inductance

                          −1
                         10

                                    Rs
                                    RDC
                                    Rhf




                          −2
                         10




                          −3
                         10    −3          −2                 −1    0
                              10          10                 10    10
                                                Frequency [GHz]




Rs = Re(Z11 + Z12 )



Verona, March 22, 2007                                                  Slide 30 of 33
Resistance and internal inductance

                          −8
                         10
                                                                    L
                                                                     i
                                                                    Li,hf
                          −9
                         10



                          −10
                         10



                          −11
                         10



                          −12
                         10



                          −13
                         10     −6    −4     −2            0    2            4
                              10     10    10             10   10           10
                                             Frequency [GHz]




Li = Im(Z11 + Z12 )/jω



Verona, March 22, 2007                                                           Slide 31 of 33
Comparisons of per unit length resistance and internal inductance



                         t                         L


                                  W



f = 100 MHz

                 W ×t        Ri [Ω/m] (MoM)    Ri [Ω/m] (Macro)
        1.4 mil × 15 mil         4.8480                4.8504
                 W ×t        ωLi [Ω/m] (MoM)   ωLi [Ω/m] (Macro)
         1.4 mil × 15 mil        4.0287                4.0232

Reference: G. Antonini, A. Orlandi, C. R. Paul, Internal Impedance of
Conductors of Rectangular Cross Section, IEEE Tran. on Microwave and
Techniques, vol. 47, n. 7, July 1999.
Verona, March 22, 2007                                          Slide 32 of 33
Conclusions and future works

   • Macro-model for conductor modeling in the PEEC frame-
     work
        – New macro-basis functions have been computed;
        – a two-way symmetric macro-model has been developed
       The proposed method:
   • can be easily combined with frequency-dependent models of par-
     tial elements (partial inductances and coefficients of potential);
   • allows a reduction of the number of unknowns;
   • models the two-way coupling (broadband modeling);
   • can be used in a framework different from PEEC (TLs, power-
     bus structures).

Verona, March 22, 2007                                       Slide 33 of 33

More Related Content

Viewers also liked

Dgsid formation-dg-server-integrateurs-developpeurs-administrateurs
Dgsid formation-dg-server-integrateurs-developpeurs-administrateursDgsid formation-dg-server-integrateurs-developpeurs-administrateurs
Dgsid formation-dg-server-integrateurs-developpeurs-administrateursCERTyou Formation
 
La unidad
La unidadLa unidad
La unidad
Alex Palma
 
Herramientas web 2.0
Herramientas web 2.0Herramientas web 2.0
Herramientas web 2.0
adriancitoarturo
 
Onda verde
Onda verdeOnda verde
Onda verde
creacionesdanae
 
Presentación1
Presentación1Presentación1
Presentación1
Karem Ballesteros
 
Presentación INTERION
Presentación INTERIONPresentación INTERION
Presentación INTERION
gatoeyra
 
Act19 ghss
Act19 ghssAct19 ghss
Act19 ghss
GeoSanchezs
 
Colegio de bachilleres del estado de tlaxcala
Colegio de bachilleres del estado de tlaxcalaColegio de bachilleres del estado de tlaxcala
Colegio de bachilleres del estado de tlaxcala
MARIOBROS245
 
Residencial Giverny Freguesia Jacarepaguá
Residencial Giverny Freguesia JacarepaguáResidencial Giverny Freguesia Jacarepaguá
Residencial Giverny Freguesia Jacarepaguá
imoveisnorj
 
The perfect support ticket
The perfect support ticketThe perfect support ticket
The perfect support ticket
Fastly
 
Balance of payments,prashant jain
Balance of payments,prashant jainBalance of payments,prashant jain
Balance of payments,prashant jain
prashant jain
 
Maja Rosiak, Xylem
Maja Rosiak, XylemMaja Rosiak, Xylem
Cuaresma (b) dom 2 pagola
Cuaresma (b) dom 2  pagolaCuaresma (b) dom 2  pagola
Cuaresma (b) dom 2 pagola
Jesús Muñoz
 
Podrías vivir sin celular
Podrías vivir sin celularPodrías vivir sin celular
Podrías vivir sin celular
Jeniffer Ynfante
 
Plan lector
Plan lectorPlan lector
Plan lector
apl1980
 

Viewers also liked (15)

Dgsid formation-dg-server-integrateurs-developpeurs-administrateurs
Dgsid formation-dg-server-integrateurs-developpeurs-administrateursDgsid formation-dg-server-integrateurs-developpeurs-administrateurs
Dgsid formation-dg-server-integrateurs-developpeurs-administrateurs
 
La unidad
La unidadLa unidad
La unidad
 
Herramientas web 2.0
Herramientas web 2.0Herramientas web 2.0
Herramientas web 2.0
 
Onda verde
Onda verdeOnda verde
Onda verde
 
Presentación1
Presentación1Presentación1
Presentación1
 
Presentación INTERION
Presentación INTERIONPresentación INTERION
Presentación INTERION
 
Act19 ghss
Act19 ghssAct19 ghss
Act19 ghss
 
Colegio de bachilleres del estado de tlaxcala
Colegio de bachilleres del estado de tlaxcalaColegio de bachilleres del estado de tlaxcala
Colegio de bachilleres del estado de tlaxcala
 
Residencial Giverny Freguesia Jacarepaguá
Residencial Giverny Freguesia JacarepaguáResidencial Giverny Freguesia Jacarepaguá
Residencial Giverny Freguesia Jacarepaguá
 
The perfect support ticket
The perfect support ticketThe perfect support ticket
The perfect support ticket
 
Balance of payments,prashant jain
Balance of payments,prashant jainBalance of payments,prashant jain
Balance of payments,prashant jain
 
Maja Rosiak, Xylem
Maja Rosiak, XylemMaja Rosiak, Xylem
Maja Rosiak, Xylem
 
Cuaresma (b) dom 2 pagola
Cuaresma (b) dom 2  pagolaCuaresma (b) dom 2  pagola
Cuaresma (b) dom 2 pagola
 
Podrías vivir sin celular
Podrías vivir sin celularPodrías vivir sin celular
Podrías vivir sin celular
 
Plan lector
Plan lectorPlan lector
Plan lector
 

Similar to Aces Verona 07 Foils

On the Ellipsoidal Core for Cooperative Games under Ellipsoidal Uncertainty
On the Ellipsoidal Core for Cooperative Games under Ellipsoidal UncertaintyOn the Ellipsoidal Core for Cooperative Games under Ellipsoidal Uncertainty
On the Ellipsoidal Core for Cooperative Games under Ellipsoidal Uncertainty
SSA KPI
 
Iceaa07 Foils
Iceaa07 FoilsIceaa07 Foils
Iceaa07 Foils
Antonini
 
Munich07 Foils
Munich07 FoilsMunich07 Foils
Munich07 Foils
Antonini
 
Introduction to Common Spatial Pattern Filters for EEG Motor Imagery Classifi...
Introduction to Common Spatial Pattern Filters for EEG Motor Imagery Classifi...Introduction to Common Spatial Pattern Filters for EEG Motor Imagery Classifi...
Introduction to Common Spatial Pattern Filters for EEG Motor Imagery Classifi...
Tatsuya Yokota
 
3D cell lineage reconstruction of early embryogenesis in plant
3D cell lineage reconstruction of early embryogenesis in plant3D cell lineage reconstruction of early embryogenesis in plant
3D cell lineage reconstruction of early embryogenesis in plant
VSG - Visualization Sciences Group
 
Prediction of Financial Processes
Prediction of Financial ProcessesPrediction of Financial Processes
Prediction of Financial Processes
SSA KPI
 
Regression Theory
Regression TheoryRegression Theory
Regression Theory
SSA KPI
 
Nanotechnology
NanotechnologyNanotechnology
Nanotechnology
Isaaq Mohammed
 
Further Advanced Methods from Mathematical Optimization
Further Advanced Methods from Mathematical OptimizationFurther Advanced Methods from Mathematical Optimization
Further Advanced Methods from Mathematical Optimization
SSA KPI
 
Meteocast: a real time nowcasting system
Meteocast: a real time nowcasting systemMeteocast: a real time nowcasting system
Meteocast: a real time nowcasting system
Alessandro Staniscia
 
Presentation
PresentationPresentation
Presentation
guest635cb8
 
Calculation of grounding resistance and earth
Calculation of grounding resistance and earthCalculation of grounding resistance and earth
Calculation of grounding resistance and earth
iaemedu
 
Calculation of grounding resistance and earth
Calculation of grounding resistance and earthCalculation of grounding resistance and earth
Calculation of grounding resistance and earth
iaemedu
 
Multivariate Analysis of Cauchy’s Inequality
Multivariate Analysis of Cauchy’s InequalityMultivariate Analysis of Cauchy’s Inequality
Multivariate Analysis of Cauchy’s Inequality
IRJET Journal
 
Dr. Amir Nejat
Dr. Amir NejatDr. Amir Nejat
Dr. Amir Nejat
knowdiff
 
2.[9 17]comparative analysis between dct & dwt techniques of image compression
2.[9 17]comparative analysis between dct & dwt techniques of image compression2.[9 17]comparative analysis between dct & dwt techniques of image compression
2.[9 17]comparative analysis between dct & dwt techniques of image compression
Alexander Decker
 
2.[9 17]comparative analysis between dct & dwt techniques of image compression
2.[9 17]comparative analysis between dct & dwt techniques of image compression2.[9 17]comparative analysis between dct & dwt techniques of image compression
2.[9 17]comparative analysis between dct & dwt techniques of image compression
Alexander Decker
 
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
JaresJournal
 
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
JaresJournal
 
Extended Analysis of Cauchy’s Inequality
Extended Analysis of Cauchy’s InequalityExtended Analysis of Cauchy’s Inequality
Extended Analysis of Cauchy’s Inequality
IRJET Journal
 

Similar to Aces Verona 07 Foils (20)

On the Ellipsoidal Core for Cooperative Games under Ellipsoidal Uncertainty
On the Ellipsoidal Core for Cooperative Games under Ellipsoidal UncertaintyOn the Ellipsoidal Core for Cooperative Games under Ellipsoidal Uncertainty
On the Ellipsoidal Core for Cooperative Games under Ellipsoidal Uncertainty
 
Iceaa07 Foils
Iceaa07 FoilsIceaa07 Foils
Iceaa07 Foils
 
Munich07 Foils
Munich07 FoilsMunich07 Foils
Munich07 Foils
 
Introduction to Common Spatial Pattern Filters for EEG Motor Imagery Classifi...
Introduction to Common Spatial Pattern Filters for EEG Motor Imagery Classifi...Introduction to Common Spatial Pattern Filters for EEG Motor Imagery Classifi...
Introduction to Common Spatial Pattern Filters for EEG Motor Imagery Classifi...
 
3D cell lineage reconstruction of early embryogenesis in plant
3D cell lineage reconstruction of early embryogenesis in plant3D cell lineage reconstruction of early embryogenesis in plant
3D cell lineage reconstruction of early embryogenesis in plant
 
Prediction of Financial Processes
Prediction of Financial ProcessesPrediction of Financial Processes
Prediction of Financial Processes
 
Regression Theory
Regression TheoryRegression Theory
Regression Theory
 
Nanotechnology
NanotechnologyNanotechnology
Nanotechnology
 
Further Advanced Methods from Mathematical Optimization
Further Advanced Methods from Mathematical OptimizationFurther Advanced Methods from Mathematical Optimization
Further Advanced Methods from Mathematical Optimization
 
Meteocast: a real time nowcasting system
Meteocast: a real time nowcasting systemMeteocast: a real time nowcasting system
Meteocast: a real time nowcasting system
 
Presentation
PresentationPresentation
Presentation
 
Calculation of grounding resistance and earth
Calculation of grounding resistance and earthCalculation of grounding resistance and earth
Calculation of grounding resistance and earth
 
Calculation of grounding resistance and earth
Calculation of grounding resistance and earthCalculation of grounding resistance and earth
Calculation of grounding resistance and earth
 
Multivariate Analysis of Cauchy’s Inequality
Multivariate Analysis of Cauchy’s InequalityMultivariate Analysis of Cauchy’s Inequality
Multivariate Analysis of Cauchy’s Inequality
 
Dr. Amir Nejat
Dr. Amir NejatDr. Amir Nejat
Dr. Amir Nejat
 
2.[9 17]comparative analysis between dct & dwt techniques of image compression
2.[9 17]comparative analysis between dct & dwt techniques of image compression2.[9 17]comparative analysis between dct & dwt techniques of image compression
2.[9 17]comparative analysis between dct & dwt techniques of image compression
 
2.[9 17]comparative analysis between dct & dwt techniques of image compression
2.[9 17]comparative analysis between dct & dwt techniques of image compression2.[9 17]comparative analysis between dct & dwt techniques of image compression
2.[9 17]comparative analysis between dct & dwt techniques of image compression
 
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
 
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
ON OPTIMIZATION OF MANUFACTURING OF ELEMENTS OF AN BINARY-ROM CIRCUIT TO INCR...
 
Extended Analysis of Cauchy’s Inequality
Extended Analysis of Cauchy’s InequalityExtended Analysis of Cauchy’s Inequality
Extended Analysis of Cauchy’s Inequality
 

Recently uploaded

Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
shyamraj55
 
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
DianaGray10
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
Zilliz
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Matthew Sinclair
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
Tatiana Kojar
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Tosin Akinosho
 
Mariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceXMariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceX
Mariano Tinti
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
panagenda
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Tomaz Bratanic
 
June Patch Tuesday
June Patch TuesdayJune Patch Tuesday
June Patch Tuesday
Ivanti
 
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation TechniquesWeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
Postman
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
Octavian Nadolu
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
Wouter Lemaire
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
Hiroshi SHIBATA
 
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Malak Abu Hammad
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
panagenda
 
Recommendation System using RAG Architecture
Recommendation System using RAG ArchitectureRecommendation System using RAG Architecture
Recommendation System using RAG Architecture
fredae14
 
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Brandon Minnick, MBA
 

Recently uploaded (20)

Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
 
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
 
Mariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceXMariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceX
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
 
June Patch Tuesday
June Patch TuesdayJune Patch Tuesday
June Patch Tuesday
 
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation TechniquesWeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
 
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
 
Recommendation System using RAG Architecture
Recommendation System using RAG ArchitectureRecommendation System using RAG Architecture
Recommendation System using RAG Architecture
 
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
 

Aces Verona 07 Foils

  • 1. 2007 ACES Conference Combined Loss Mechanism and Stability Model for the Partial Element Equivalent Circuit Technique Giulio Antonini UAq EMC Laboratory, Department of Electrical Engineering University of L’Aquila, AQ 67040, ITALY Albert Ruehli IBM T. J. Watson Research Center Yorktown Heights, NY 10598, USA Verona, March 22, 2007 Slide 1 of 33
  • 2. Outline q PEEC modeling of skin-effect • volume filament approach • 1D macro-basis functions • higher order basis functions q Diffusion equation q Broadband combined loss and stability models q PEEC equivalent circuit q Numerical results q Conclusions and future work Verona, March 22, 2007 Slide 2 of 33
  • 3. Frequency dependent phenomena modeling • Frequency dependent phenomena (skin-effect, dielectric losses) – easier to be modeled in the frequency domain. • Stability and passivity issues: – easier to be handled at a macromodel level. • Macromodels can be generated from either time-domain or frequency domain solvers. • Fast techniques (FMM, MLFMM, QR) are well established for frequency domain solvers. • A viable solution is: use frequency domain analysis to generate samples to be used for macromodeling (Adaptive Frequency Sampling can be useful). Verona, March 22, 2007 Slide 3 of 33
  • 4. Advanced frequency domain PEEC solver Broadband macromodel PEEC frequency domain solver Frequency dependent phenomena (skin-effect, dispersive and lossy dielectrics) Fitting techniques Acceleration techniques powered by FMM, MLFMM, QR AFS algorithm Verona, March 22, 2007 Slide 4 of 33
  • 5. Overview of skin effect modelling Key parameters 2 • skin-depth δ = µσω • layer thickness t • if t δ the field diffusion can be neglected and the layer can be approximated as a PEC surface • if t δ the tangential electric field is virtually constant through the layer: the sheet can be modeled by a surface resistance 1/σt; • if t ∼ δ the spatial resolution inside the conductor has to be very fine, = much shorter than the skin depth ⇒ memory and time consuming Target • a symmetric, two-way macromodel which is valid for arbitrary t/δ ratios Verona, March 22, 2007 Slide 5 of 33
  • 6. PEEC modeling of skin-effect Skin-effect modelling • Volume filament approach: large number of unknowns • Non-uniform discretization helps in reducing the number of unknowns • Macro-basis functions represent another possibility Verona, March 22, 2007 Slide 6 of 33
  • 7. PEEC modeling of skin-effect z I1 d I d y 2 I1 x I2 W J (r, s) i E (r, s) = + sA(r, s) + φ(r, s) σ V1 (s) = Z11 I1 + Z12 I2 + Lp11 sI1 + Lp1j sIj j V2 (s) = Z21 I1 + Z22 I2 + Lp22 sI2 + Lp2j sIj j Verona, March 22, 2007 Slide 7 of 33
  • 8. PEEC modeling of skin-effect      V1 Z11 Z12 I1  =   V2 Z21 Z22 I2 The 2D and 3D cases are a combination of the 1D case. l z y x Iy w Ix Hypothesis: transverse electric field distribution Verona, March 22, 2007 Slide 8 of 33
  • 9. PEEC modeling of skin-effect Ex (z) = Ae−γz + Beγz Jx (z) = σ Ae−γz + Beγz Since we associate a current with each cell, we can relate the current I1 to the the electric field as d d I1 e−γz dz + B eγz dz =A σW 0 0 0 0 I2 e−γz dz + B eγz dz =A σW −d −d After integration I1 γ = −A(e−γd − 1) + B(eγd − 1) σW I2 γ = A(eγd − 1) − B(e−γd − 1) σW Verona, March 22, 2007 Slide 9 of 33
  • 10. PEEC modeling of skin-effect Jx (s, z) = σEx (s, z) = σ Ae−γz + Beγz γ 1 eγz − e−γz+γd I1 = W (e−2γd − e−γd + eγd − 1) e−γz − e−γd+γz I2 + = f1 (s, z)I1 + f2 (s, z)I2 For a conductor translated along the z axis the two basis functions de- scribing current density profile in the same direction are: γ 1 eγ(z−zmax2 ) − e−γ(z−zmin2 ) f1 (s, z) = W (e−2γd − e−γd + eγd − 1) γ 1 e−γ(z−zmin1 ) − eγ(z−zmax1 ) f2 (s, z) = W (e−2γd − e−γd + eγd − 1) Verona, March 22, 2007 Slide 10 of 33
  • 11. PEEC modeling of skin-effect The voltage across the top cell is given by integrating the electric field as L V1 (s) = Ex (s, d)dx = LEx (d) 0 which results in eγd − e−2γd e−γd − 1 γL V1 (s) = I1 + I2 σW den den where den = e−2γd − e−γd + eγd − 1. Finally, the impedances are identified as: eγd − e−2γd γL Z11 (s) = Z22 (s) = σW (e−2γd − e−γd − 1 + eγd ) e−γd − 1 γL Z12 (s) = Z21 (s) = σW (e−2γd − e−γd − 1 + eγd ) Verona, March 22, 2007 Slide 11 of 33
  • 12. Asymptotic behavior Limit as γ → 0 3L lim Z11 (s) = lim Z22 (s) = 2 σW d γ→0 γ→0 1L lim Z12 (s) = lim Z21 (s) = − 2 σW d γ→0 γ→0 At DC currents are equal, I1 = I2 = I: L RDC = lim [Z11 (s) + Z12 (s)] = σW d γ→0 Verona, March 22, 2007 Slide 12 of 33
  • 13. Asymptotic behavior Limit as γ → ∞ lim Z12 (s) = lim Z21 (s) = 0 γ→∞ γ→∞ ⇒ currents I1 and I2 are decoupled. γL lim Z11 (s) = lim Z22 (s) = lim γ→∞ σW γ→∞ γ→∞ √ √ Considering that for good conductors γ = jωµσ = (1 + j) πf µσ = (1 + j) /δ, the standard surface impedance is obtained. Verona, March 22, 2007 Slide 13 of 33
  • 14. Thin and thick objects Thin object Thick object 1-d macro PEEC model 2-d macro PEEC model Standard PEEC model • Middle region: standard PEEC model adopting brick basis function • side regions: 1D macro PEEC model adopting 1D macro-basis func- tions • corner regions: 2D macro PEEC model adopting 2D macro-basis functions Verona, March 22, 2007 Slide 14 of 33
  • 15. Macro-basis functions The basis functions can be used as testing functions within a Galerkin’s procedure. Let F (r, s) represent a generic vector term in the electric field integral equation: J (r, s) i E (r, s) = + sA(r, s) + φ(r, s) σ The inner product to test this equation is defined as: f ∗ (s, z) · F (r, s)dr j F (r, s), f i (s, z) = i Vj where Vj is the j − th elementary volume. Verona, March 22, 2007 Slide 15 of 33
  • 16. Macro-basis functions J (r) = f j (s, r)Ij j 1 f ∗ (s, r) · f j (s, r) dr i dr j Rij = i σ Vj Vi e−jk0 |r−r | µ f ∗ (s, r) Lij = · f j (s, r) dr i dr j i 4π |r − r | Vj Vi Verona, March 22, 2007 Slide 16 of 33
  • 17. Diffusion equations Inside a good conductor (e.g. σ ωε) the displacement current can be neglected and the fields can be described in terms of diffusion equations. ∂Hy (z, s) = −σEx (z, s) ∂z ∂Ex (z, s) = −sµHy (z, s) ∂z sµ Zc (s) = σ √ γ (s) = sµσ The diffusion of magnetic and electric fields in the conductor can be interpreted as diffusion of voltage and current in a LG transmission line. Verona, March 22, 2007 Slide 17 of 33
  • 18. Diffusion equations Two-way macromodel      E Z (s) Z12 (s) H  x,1  =  11   y,1  Ex,2 Z21 (s) Z22 (s) Hy,2    sµ(s) coth γ (s) t − sµ(s) csch γ (s) t H   y,1   γ(s) γ(s) = − sµ(s) csch γ (s) t sµ(s) coth γ (s) t Hy,2 γ(s) γ(s) where Ex,1 , Ex,2 are proportional to V1 , V2 and Hy,1 , Hy,2 are proportional to the currents on side 1 and 2. Verona, March 22, 2007 Slide 18 of 33
  • 19. Stability If the diffusion of magnetic and electric fields in the conductor are inter- preted as diffusion of voltage and current in a LCG, (R = 0) transmission line, poles can be analytically computed, by using a modal expansion, as: nπ 2 2 1 G 1 G t pn,12 =− ± − 2 C 4 C LC • all the poles have a negative real part ⇒ stability is ensured • for large G (good conductors) ∼ 0, pn,2 ∼ − G , ∀n pn,1 = = C ⇒ the poles are multiple (numerically) Verona, March 22, 2007 Slide 19 of 33
  • 20. Broadband stable PEEC models for skin-effect and magnetic-electric field couplings Frequency dependent partial inductances ⇒ damping in the partial elements (Kochetov, Wollenberg, 2005) Distributed approach-suitable for time domain implementation e−s|r m −r n |/c0 µ Lp,mn (s) = dvm dvn 4πam an |r m − r n | vm vn nL c Np p Resc ∗ Resr Resc ZL,mn (s) = sLp,mn (s) = dL + k k k + + mn s − pc ∗ s − pr s − pc k k k k=1 k=1 • Stability can be enforced during the fitting. • Passivity is enforced as a-posteriori step. • A large number of lumped elements is needed to synthesize ZL,mn (s). Verona, March 22, 2007 Slide 20 of 33
  • 21. Broadband stable PEEC models for skin-effect and magnetic-electric field couplings ZI Z V Lp 12 2 11 L 11 I1 + + V1 V 2 − −   np R11 R12 p d11 + d12 + k=1 s−pk k=1 s−pk Z(s) =   np R21 R22 p d21 + d22 + k=1 s−pk k=1 s−pk Adaptive Frequency Sampling (AFS) can be useful to generate broadband macromodels keeping the order np and the number of samples as low as possible. Verona, March 22, 2007 Slide 21 of 33
  • 22. Global approach-frequency domain implementation+fitting • the macromodel allows to reduce the number of unknowns • the macromodel is incorporated into a frequency domain solver • acceleration techniques are used to speed-up the solution at each frequency • frequency samples are used to generate a macromodel of the overall system via fitting techniques Verona, March 22, 2007 Slide 22 of 33
  • 23. Single conductor modeling with symmetrical boundary conditions t L W • length L = 1 mm • width W = 150 µm • thickness t = 2d = 30 µm • electrical conductivity σ = 5.8 · 107 S/m Frequency range 0-50 GHz Symmetrical boundary conditions ⇒ currents I1 = I2 = I = 1 mA. Surface model: sµ/σL/W . Verona, March 22, 2007 Slide 23 of 33
  • 24. Single conductor modeling with symmetrical boundary conditions V (s) = Z11 (s) I1 (s) + Z12 (s) I2 (s) = [Z11 (s) + Z12 (s)] I (s) ˜ Zse (s) = Z11 (s) + Z12 (s) Zse (s) = RDC + Zs (s) −1 10 Z s RDC Z 11 −2 10 −3 10 −3 −2 −1 0 10 10 10 10 Frequency [GHz] Comparison of impedance Zs (s), the DC resistance RDC and Z11 (s) Verona, March 22, 2007 Slide 24 of 33
  • 25. Single conductor modeling with symmetrical boundary conditions Surface model Zs (s) = sµ/σL/W : well established skin-effect ˜ Zse (s) = Z11 (s) + Z12 (s) Zse (s) = RDC + Zs (s) 1 10 Z +Z 11 12 Zs+RDC 0 10 −1 10 −2 10 −3 10 −5 −4 −3 −2 −1 0 1 2 3 10 10 10 10 10 10 10 10 10 Frequency [GHz] Comparison of the exact impedance Zse (s) = Z11 (s) + Z12 (s) with the ˜ approximated one Zse (s) = RDC + Zs (s) Verona, March 22, 2007 Slide 25 of 33
  • 26. Single conductor modeling with symmetrical boundary conditions Transfer impedance Z12 = Z21 , f = 0 − 50 GHz 0 10 −5 10 −10 10 −15 10 −20 10 −25 10 −5 −4 −3 −2 −1 0 1 2 10 10 10 10 10 10 10 10 Frequency [GHz] With the increasing of the frequency the coupling between the two half- cells rapidly decreases. Verona, March 22, 2007 Slide 26 of 33
  • 27. Single conductor modeling with symmetrical boundary conditions I1=I2=1 mA 6 x 10 2.5 2 1.5 J [A/m2] x 1 0.5 0 2 1.5 1 1 0.5 0 −4 0 x 10 −0.5 −5 −1 x 10 −1 −1.5 −2 −2 x [m] z [m] Left: electric field profile as a function of z coordinate and frequency; right: current density distribution over the cross section. Verona, March 22, 2007 Slide 27 of 33
  • 28. Single conductor modeling with symmetrical boundary conditions Frequency dependent basis functions 10 10 x 10 x 10 3.5 3.5 3 3 2.5 2.5 2 2 1.5 1.5 1 1 0.5 0.5 0 0 −2 −1.5 −1 −0.5 0 0.5 1 1.5 −2 −1.5 −1 −0.5 0 0.5 1 1.5 z [m] z [m] −5 −5 x 10 x 10 f = 30 GHz Verona, March 22, 2007 Slide 28 of 33
  • 29. Single conductor modeling with symmetrical boundary conditions Frequency dependent basis functions Verona, March 22, 2007 Slide 29 of 33
  • 30. Resistance and internal inductance −1 10 Rs RDC Rhf −2 10 −3 10 −3 −2 −1 0 10 10 10 10 Frequency [GHz] Rs = Re(Z11 + Z12 ) Verona, March 22, 2007 Slide 30 of 33
  • 31. Resistance and internal inductance −8 10 L i Li,hf −9 10 −10 10 −11 10 −12 10 −13 10 −6 −4 −2 0 2 4 10 10 10 10 10 10 Frequency [GHz] Li = Im(Z11 + Z12 )/jω Verona, March 22, 2007 Slide 31 of 33
  • 32. Comparisons of per unit length resistance and internal inductance t L W f = 100 MHz W ×t Ri [Ω/m] (MoM) Ri [Ω/m] (Macro) 1.4 mil × 15 mil 4.8480 4.8504 W ×t ωLi [Ω/m] (MoM) ωLi [Ω/m] (Macro) 1.4 mil × 15 mil 4.0287 4.0232 Reference: G. Antonini, A. Orlandi, C. R. Paul, Internal Impedance of Conductors of Rectangular Cross Section, IEEE Tran. on Microwave and Techniques, vol. 47, n. 7, July 1999. Verona, March 22, 2007 Slide 32 of 33
  • 33. Conclusions and future works • Macro-model for conductor modeling in the PEEC frame- work – New macro-basis functions have been computed; – a two-way symmetric macro-model has been developed The proposed method: • can be easily combined with frequency-dependent models of par- tial elements (partial inductances and coefficients of potential); • allows a reduction of the number of unknowns; • models the two-way coupling (broadband modeling); • can be used in a framework different from PEEC (TLs, power- bus structures). Verona, March 22, 2007 Slide 33 of 33