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Introductory lecture notes on Partial Differential Equations - c Anthony Peirce. Not to be copied, used, or revised without explicit written permission from the copyright owner. 1 Lecture 27: Wedges with cut-outs, Dirichlet and Neumann problems on Circular domains (Compiled 3 March 2014) In this lecture we continue with the solution of Laplace’s equation on circular domains. In particular, a wedge-shaped domain with a circular cut-out, i.e., a pizza slice with a bite taken out of it, as well as the Dirichlet and Neumann problems on the interior of a circle. This leads to the well known Poisson Integral Formula and an interesting application known as Electrical Impedance Tomography (EIT). Key Concepts: Laplace’s equation; Circular domains; Pizza Slice-shaped regions; Dirichlet and Neumann Boundary Conditions, Poisson Integral Formula; Applications to EIT. Reference Section: Boyce and Di Prima Section 10.8 27 Wedges with cut-outs, circles, holes, and annuli 27.1 Wedges with cut-outs Example 27.1 A circular wedge with a cut-out: Figure 1. Mixed boundary conditions on a wedge shaped domain with a cut-out (27.2) u rr + 1 r u r + 1 r 2 u θθ =0 (27.1) u θ (r, 0) = 0 u θ (r, α)=0 u(b, θ)=0 u(a, θ)= f (θ) (27.2) Let u(r, θ)= R(r)Θ(θ). r 2 (R 00 + 1 r R) R(r) = - Θ 00 (θ) Θ(θ) = λ 2 r 2 R 00 + rR 0 - λ 2 R =0 Θ 00 + λ 2 Θ=0 (27.3)

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  • Introductory lecture notes on Partial Differential Equations - c Anthony Peirce.Not to be copied, used, or revised without explicit written permission from the copyright owner.

    1

    Lecture 27: Wedges with cut-outs, Dirichlet and Neumannproblems on Circular domains

    (Compiled 3 March 2014)

    In this lecture we continue with the solution of Laplaces equation on circular domains. In particular, a wedge-shaped

    domain with a circular cut-out, i.e., a pizza slice with a bite taken out of it, as well as the Dirichlet and Neumann problems

    on the interior of a circle. This leads to the well known Poisson Integral Formula and an interesting application known

    as Electrical Impedance Tomography (EIT).

    Key Concepts: Laplaces equation; Circular domains; Pizza Slice-shaped regions; Dirichlet and Neumann BoundaryConditions, Poisson Integral Formula; Applications to EIT.

    Reference Section: Boyce and Di Prima Section 10.8

    27 Wedges with cut-outs, circles, holes, and annuli

    27.1 Wedges with cut-outs

    Example 27.1 A circular wedge with a cut-out:

    Figure 1. Mixed boundary conditions on a wedge shaped domain with a cut-out (27.2)

    urr +1rur +

    1r2u = 0 (27.1)

    u(r, 0) = 0 u(r, ) = 0u(b, ) = 0 u(a, ) = f()

    (27.2)

    Let u(r, ) = R(r)().

    r2(R + 1rR)R(r)

    = ()()

    = 2 {

    r2R + rR 2R = 0 + 2 = 0

    (27.3)

  • 2 equation + 2 = 0(0) = 0 = ()

    } = A cos +B sin(0) = B = 0 B or = 0, (27.4)

    = A sin +B cos() = A sin = 0, = npi n = 0, 1, . . .

    (27.5)

    R equation n = 0: (rR0) = 0 rR0 = B0 R0 = A0 +B0 ln r. Note

    u0(b, ) = R0(b)0() = 0 R0(b) = A0 +B0 ln b = 0, A0 = B0 ln b. (27.6)

    Therefore R0 = B0 ln(r/b). Choose B0 = 1.

    n 1: r2Rn + rRn 2Rn = 0 R(r) = Anrn +Bnrn

    Rn(b) = Anbn +Bnbn = 0 Bn = Anb2n (27.7)Rn(r) = An[rn b2nrn ] Choose An = 1. (27.8)

    un(r, ) =[r(

    npi ) b2(npi )r(npi )

    ]cos(npi

    )(27.9)

    u0(r, ) = ln(rb

    ) 1 (27.10)

    Therefore

    u(r, ) = c0 ln(rb

    )+

    n=1

    cn

    [r(

    npi ) b( 2npi )r(npi )

    ]cos(npi

    )(27.11)

    u(a, ) = f() = 2

    (c0 ln

    (ab

    ))2

    +n=1

    cn

    [a(

    npi ) b( 2npi )r(npi )

    ]cos(npi

    )(27.12)

    =a02+

    n=1

    an cos(npi

    ). (27.13)

    Therefore

    2c0 ln(a/b) =2

    0

    f() d. (27.14)

    cn =2

    [a(

    npi ) b( 2npi )anpi

    ] 0

    f() cos(npi

    )d (27.15)

    c0 =1

    ln(a/b)

    0

    f() d. (27.16)

    Observations: In the special case f() = 1, c0 =1

    log(a/b), and cn = 0 n 1. By Fourier basis function orthogonality

    0

    1 cos(npi

    )d = 0 so that the solution reduces to:

    u(r, ) =log(r/b)log(a/b)

    (27.17)

    which is purely radial i.e. has no dependence.

  • Laplaces Equation 3

    27.2 Problems with a complete circle as the boundary

    Example 27.2 Dirichlet problem in the interior of a circle

    Figure 2. Dirichlet boundary condition prescribed on the on boundary of a circle (??)

    urr +1rur +

    1r2u = 0 0 < r < a, 0 < < 2pi. (27.18)

    BC: u(a, ) = f() u(r, )

  • 4Now since u(r, )
  • Laplaces Equation 5

    u(r, ) =12pi

    (a2 r2)pi

    pi

    f()a2 2ar cos( ) + r2 d (27.37)

    Domain exterior to a circle:

    For problem exterior to a circle we require that u(r, )

  • 6Special Case - Electrical Impedance Tomography (EIT)

    Assume that f() = I0( pi

    2

    ) I0

    ( +

    pi

    2

    ).

    (a) Level sets of potential field (27.61) (b) BVP for U1 field and voltage mea-surements U1 with = const. Actualvoltage V1 with a feature (red)

    (c) Field U0 used in the sensitivity Thm

    Figure 4. Sensitivity Thm: V1 U1 ' 1I

    U1 U0dv & backprojection rule: ' (V1U1)U1

    f() = I0(( +

    pi

    2

    )) I0

    (( pi

    2

    ))(27.44)

    = I0( +

    pi

    2

    ) I0

    ( pi

    2

    )= f() (27.45)

    Thus f is odd a0 = an = 0.

    nan1bn =2pi

    pi0

    I0( pi

    2

    )sin(n) d (27.46)

    bn =2I0

    pinan1sin(npi2

    )(27.47)

    u(r, ) =2aI0pi

    n=1

    sin(n)n

    sin(npi2

    )( ra

    )n(27.48)

    For enrichment = 2aI0pi

    n=1

    ( ra

    )n 12

    [cosn

    ( pi2

    )n

    cosn( + pi2

    )n

    ](27.49)

    =aI0pi

    n=1

    ( ra

    )n [cosn ( pi2 )n

    cosn( + pi2

    )n

    ](27.50)

    =aI0piRe

    [ n=1

    zn1n

    n=1

    zn2n

    ]z1 =

    (ra

    )ei(

    pi2 )

    z2 =(ra

    )ei(+

    pi2 )

    . (27.51)

    Now for |z| < 1:1

    1 z = 1 + z + z2 + =

    k=0

    zk

    ln(1 z) = z + z2

    2+ =

    n=1

    zn

    n

    . (27.52)

  • Laplaces Equation 7

    Therefore

    u(r, ) = aI0piRe[ln(1 z11 z2

    )]. (27.53)

    Now if (1 z) = Aei then

    Re[ln(1 z)] = Re [ln (Aei)] = Re[lnA+ i] = lnA. (27.54)

    Therefore

    u(r, ) = aI02pi

    ln1 z11 z2

    2. (27.55)Now

    z1 =( ra

    )ei(

    pi2 ) = ei1 (27.56)

    1 z12 = (1 z1)(1 z1) =(1 ei1)(1 ei1) (27.57)

    = 1 (ei1 + ei1)+ 2 (27.58)= 1 2 cos1 + 2. (27.59)

    Similarly z2 =( ra

    )ei(+

    pi2 ) = ei2 and |1 z2|2 = 1 2 cos2 + 2. Therefore

    u(r, ) =aI02pi

    ln

    [1 2( ra ) cos( + pi2 ) + ( ra )21 2( ra ) cos( pi2 ) + ( ra )2

    ](27.60)

    u(r, ) =aI02pi

    ln[a2 + 2ar sin + r2

    a2 2ar sin + r2]

    (27.61)

    Electrical Impedance Tomography - from the US Patent

    (a) Level sets of potential field used inthe US Patent

    (b) Medical imaging device (c) Actual image obtained from EIT

    Figure 5. Figures taken from a US Patent for a medical imaging device based in EIT and the level sets of the solutiongiven in (27.61)

  • Mar 3rd 2012 | from the print edition

    Technology Quarterly: Q1 2012In this Technology QuarterlyWhat happened to the flying car?Weve got it coveredReviving autopsyAn open-source robo-surgeonPumping ionsPivoting pixelsNo more whirly-splatStarting from scratchMeaningful gesturesThis is not a video gameUnblinking eyes in the skyComputing with soupPacking some powerCan the scientists keep up?Counting every momentTaking the long viewReprintsMonitor

    Weve got it coveredMaterials: Smart paint promises to make it easier toidentify and repair cracks or corrosion in bridges and otherinfrastructure

    IT WOULD be much easier to locate and repair damage to bridges, windturbines and other dumb objects if those objects could tell you whatthe problem was. Researchers at the University of Strathclyde, inBritain, led by Mohamed Saafi, are therefore trying to give them avoice, by devising a new sort of smart paint.

    It is composed of what sounds like a bizarre mixture: fly-ash, a fine-grained waste product from coal-fired power stations; carbonnanotubes, cylindrical molecules made of elemental carbon; and twobinding agents, sodium silicate and sodium hydroxide. The result is a

    3/10/2012 Monitor: Weve got it covered | The Ec

    economist.com/node/21548497/print 1/2

  • Copyright The Economist Newspaper Limited 2012. All rights reserved. Legal disclaimer

    Accessibility Privacy policy Terms of use Help

    from the print edition | Technology Quarterly

    material similar to cement, which makes a suitably tough paint. When itdries, the fly-ash acts as a coating, able to withstand the elements inexposed places. The carbon nanotubes are there to conduct electricity.

    The smart bit is that the tubes conductivity is affected by cracks in, orcorrosion of, the painted surface. When put under stress, for example,the nanotubes bend and become less conductive. If inundated bychloride ions, as a result of corrosion by salt water, their conductivityincreases. This makes it possible to monitor damage.

    The voltage running through any part of the painted area can bemeasured remotely, with an array of electrodes distributed across itssurface, and data for the entire structure dispatched, via a centraltransmitter, to a computer. Using a medical-imaging technique calledelectrical-impedance tomography, Dr Safi and his colleague DavidMcGahon are devising software that can draw a conductivity map of anentire painted structure.

    Nanotechnology has been used in paints before. Sometimes the goal isto bind the paint tightly to the material it has been applied to.Sometimes it is to channel water molecules efficiently, thus keeping asurface clean. Some paints incorporate tiny silver particles, whichcapture atmospheric pollutants. But Dr Saafis smart paint is new inseveral ways.

    It is cheap, so it is possible to imagine whole structures being built outof it, instead of cement. It is also versatile, theoretically able to detecta broad range of stresses and pollutants. If it performs well, there arecurrently 3,500 wind turbinesand countingin Britain alone thatcould do with a lick of it.

    3/10/2012 Monitor: Weve got it covered | The Ec

    economist.com/node/21548497/print 2/2

    M257_316_2012_Lecture_27.pdfEIT_ The EconomistMonitor_ Weve got it covered _ The Economist.pdf