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  • 8/13/2019 Week 09 - NS Eqs

    1/19

    11/10/2

    Computational Fluid Dynamics

    Constitutive Relationship for Viscous Fluids

    For Newtonian fluids, such as water, theconstitutive relationship between the stress

    tensor and the strain-rate tensor is simple:

    Where is a constant called the coefficient of

    viscosity.

    This constitutive relationship preserves the

    defining property of a fluid; that is, that any

    small shear stress will produce strain.

    10-Nov-13

    38

    ijij 2

    Computational Fluid Dynamics

    Stress Tensor for Viscous Fluids

    Now the stress tensor in terms of strains, and

    then in terms of the velocity gradients is:

    10-Nov

    -13

    39

    z

    v

    y

    v

    z

    v

    x

    v

    z

    v

    y

    v

    z

    v

    y

    v

    x

    v

    y

    v

    x

    v

    z

    v

    x

    v

    y

    v

    x

    v

    zzyzx

    zyyyx

    zxyxx

    zzzyzx

    yzyyyx

    xzxyxx

    ij

    2

    1

    2

    1

    2

    1

    2

    1

    2

    1

    2

    1

    22

    z

    v

    y

    v

    z

    v

    x

    v

    z

    v

    y

    v

    z

    v

    y

    v

    x

    v

    y

    v

    x

    v

    z

    v

    x

    v

    y

    v

    x

    v

    zzyzx

    zyyyx

    zxyxx

    2

    2

    2

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    Computational Fluid Dynamics

    Newtons 2ndlaw for Viscous Fluids

    We can now substitute this expression for thestress tensor, into the expression for Newtons

    2ndLaw (the viscous forces term):

    10-Nov-13

    40

    z

    v

    y

    v

    z

    v

    x

    v

    z

    v

    y

    v

    z

    v

    y

    v

    x

    v

    y

    v

    x

    v

    z

    v

    x

    v

    y

    v

    x

    v

    Pkg

    PkgDt

    vD

    zzyzx

    zyyyx

    zxyxx

    ij

    2

    2

    2

    Computational Fluid Dynamics

    Newtons 2ndlaw for Viscous Fluids

    By carrying out the divergence operator on the

    stress tensor we get:

    10-Nov

    -13

    41

    z

    v

    y

    v

    z

    v

    x

    v

    z

    v

    y

    v

    z

    v

    y

    v

    x

    v

    y

    v

    x

    v

    z

    v

    x

    v

    y

    v

    x

    v

    zzyzx

    zyyyx

    zxyxx

    2

    2

    2

    z

    v

    zy

    v

    z

    v

    yx

    v

    z

    v

    x

    y

    v

    z

    v

    zy

    v

    yx

    v

    y

    v

    x

    x

    v

    z

    v

    zx

    v

    y

    v

    yx

    v

    x

    zzyzx

    zyyyx

    zxyxx

    2

    2

    2

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    Computational Fluid Dynamics

    Newtons 2ndLaw for Viscous Fluids

    This can be expanded to produce secondderivatives and cross-derivatives:

    10-Nov-13

    42

    zyv

    zxv

    yv

    xv

    zv

    zy

    v

    yx

    v

    z

    v

    x

    v

    y

    v

    zx

    v

    yx

    v

    z

    v

    y

    v

    x

    v

    yxzzz

    zxyyy

    zyxxx

    22

    2

    2

    2

    2

    2

    2

    22

    2

    2

    2

    2

    2

    2

    22

    2

    2

    2

    2

    2

    2

    2

    2

    2

    Computational Fluid Dynamics

    Newtons 2ndLaw for Viscous Fluids

    Finally, we separate the first term in each row

    and rearrange as follows:

    10-Nov

    -13

    43

    2

    222

    2

    2

    2

    2

    2

    2

    2

    2

    22

    2

    2

    2

    2

    2

    2

    22

    2

    2

    2

    2

    2

    2

    2

    2

    z

    v

    zy

    v

    zx

    v

    z

    v

    y

    v

    x

    v

    zyv

    yv

    yxv

    zv

    yv

    xv

    zx

    v

    yx

    v

    x

    v

    z

    v

    y

    v

    x

    v

    zyxzzz

    zyxyyy

    zyxxxx

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    Computational Fluid Dynamics

    Newtons 2ndLaw for Viscous Fluids

    The last three terms in each row can now beexpressed as the partial derivative of a sum:

    The sum in brackets is the divergence of the velocity:

    It is zero for incompressible flow.

    10-Nov-13

    44

    z

    v

    y

    v

    x

    v

    zz

    v

    y

    v

    x

    v

    z

    v

    y

    v

    x

    v

    yz

    v

    y

    v

    x

    v

    z

    v

    y

    v

    x

    v

    xz

    v

    y

    v

    x

    v

    zyxzzz

    zyxyyy

    zyxxxx

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    z

    v

    y

    v

    x

    vv

    zyx

    Computational Fluid Dynamics

    Newtons 2ndLaw for Viscous Fluids

    Therefore the last three terms in each row drop

    out and we end up with the three components

    of the viscous force vector:

    10-Nov

    -13

    45

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    z

    v

    y

    v

    x

    v

    z

    v

    y

    v

    x

    v

    z

    v

    y

    v

    x

    v

    z

    v

    y

    v

    x

    v

    z

    v

    y

    v

    x

    v

    z

    v

    y

    v

    x

    v

    zzz

    yyy

    xxx

    zzz

    yyy

    xxx

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    Computational Fluid Dynamics

    Newtons 2ndLaw for Viscous Fluids

    For example, the viscous force per unit volumein thex-direction is:

    The term in the parentheses is often

    expressed via another vector operator called

    the Laplacian defined as:

    10-Nov-13

    46

    2

    2

    2

    2

    2

    2

    z

    v

    y

    v

    x

    v xxx

    2

    2

    2

    2

    2

    22

    z

    f

    y

    f

    x

    ff

    Computational Fluid Dynamics

    Newtons 2ndLaw for Viscous Fluids

    We now have the last piece to the Navier-Stokes

    equations.

    Substituting the expression for the divergence of the

    stress tensor we arrive at the final expression showing

    the balance of forces as per Newtons 2ndlaw:

    These three equations (one for each direction) are

    known as the Navier-Stokes equations.

    They apply to incompressible Newtonian fluids that

    follow the constitutive relationship:

    10-Nov

    -13

    47

    vPkgDt

    vD

    2

    ijij 2

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    Computational Fluid Dynamics

    Newtons 2ndLaw for Viscous Fluids

    Again, this equation is deceptively concise; itcan be written out as:

    10-Nov-13

    48

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    z

    v

    y

    v

    x

    v

    z

    Pkg

    z

    vv

    y

    vv

    x

    vv

    t

    v

    z

    v

    y

    v

    x

    v

    y

    P

    z

    vv

    y

    vv

    x

    vv

    t

    v

    z

    v

    y

    v

    x

    v

    x

    P

    z

    vv

    y

    vv

    x

    vv

    t

    v

    zzzz

    z

    z

    y

    z

    x

    z

    yyyy

    z

    y

    y

    y

    x

    y

    xxxx

    z

    x

    y

    x

    x

    x

    Computational Fluid Dynamics

    Example

    Couette Flow

    Set up the equations and boundary conditions

    to solve for the following problem at steady

    state and fully developed:

    10-Nov

    -13

    49

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    Computational Fluid Dynamics

    Solution

    Only 2D Steady Navier Stokes:

    First eliminate all the t and y components.

    10-Nov-13

    50

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    2

    z

    v

    y

    v

    x

    v

    z

    Pkg

    z

    vv

    y

    vv

    x

    vv

    t

    v

    z

    v

    y

    v

    x

    v

    y

    P

    z

    vv

    y

    vv

    x

    vv

    t

    v

    z

    v

    y

    v

    x

    v

    x

    P

    z

    vv

    y

    vv

    x

    vv

    t

    v

    zzzz

    z

    z

    y

    z

    x

    z

    yyyy

    z

    y

    y

    y

    x

    y

    xxxx

    z

    x

    y

    x

    x

    x

    Computational Fluid Dynamics

    Next eliminate all the Vz terms due to

    impermeability of walls.

    Fluid can not pass through walls so there is no

    flow in the z direction.

    10-Nov

    -13

    51

    2

    2

    2

    2

    2

    2

    2

    2

    z

    v

    x

    v

    z

    Pkg

    z

    vv

    x

    vv

    zv

    xv

    xP

    zvv

    xvv

    zzzz

    zx

    xxxz

    xx

  • 8/13/2019 Week 09 - NS Eqs

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    Computational Fluid Dynamics

    Solution

    If the flow is fully developed the velocity in theflow direction doesnt change.

    10-Nov-13

    52

    z

    Pkg

    z

    v

    x

    v

    x

    P

    x

    vv xxxx

    0

    2

    2

    2

    2

    z

    Pkg

    z

    v

    x

    P x

    2

    2

    Computational Fluid Dynamics

    Example

    The velocity profile for fully developed laminar

    flow between two parallel plates separated by

    distance 2b is given by

    umaxis at y = 0.

    Determine the shear force per unit volume on a

    fluid element in the x-direction. Find the maximum value of this quantity for this

    flow, when b =1 m, umax=2 m/s and =10-1N s/m2

    (SAE-10W).

    10-Nov

    -13

    54

    2

    2

    maxb

    y1uu

    umaxx

    y

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    Computational Fluid Dynamics

    Solution

    Given:1. Velocity Profile u(y)

    At y = 0, u = umax

    At y = b, u = 0

    Find:

    1. Shear Force,

    2. The maximum value of the result of the above.

    10-Nov-13

    55

    zy

    zxyx

    umax

    Computational Fluid Dynamics

    Solution

    Governing equation: Naviersequations x-

    component, with

    Shear force per unit volume along the x-

    direction is given by

    10-Nov

    -13

    56

    y

    u

    y

    u

    x

    vyx

    0z

    u

    x

    wzx

    0 00

    2

    2

    0y

    u

    zy

    u

    yzy

    zxyx

    2max

    2

    b

    yu

    y

    u

    2

    max

    2

    2 2

    b

    u

    y

    u

    constant22

    max

    b

    u

    zy

    zxyx

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    Computational Fluid Dynamics

    Solution

    Maximum value =

    N/m3

    This value is fixed everywhere in the channel.

    10-Nov-13

    57

    4.)1(

    )2()10(2 1

    Computational Fluid Dynamics

    CONSERVATION OF ENERGY

    10-Nov

    -13

    58

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    Computational Fluid Dynamics 59

    Conservation of energy

    First law of thermodynamics: rate of change of energy of a fluid particle is equal

    to the rate of heat addition plus the rate of workdone.

    Rate of increase of energy is DE/Dt.

    Energy, E = i + (u2+v2+w2)/2. Here, iis the internal (thermal energy).

    (u2+v2+w2)/2 is the kinetic energy.

    10-Nov-13

    Computational Fluid Dynamics 60

    Conservation of energy

    Potential energy (gravitation) is usually treatedseparately and included as a source term.

    We will derive the energy equation by settingthe total derivative equal to the change inenergy as a result of work done by viscousstresses and the net heat conduction.

    Next we will subtract the kinetic energyequation to arrive at a conservation equationfor the internal energy.

    10-Nov

    -13

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    Computational Fluid Dynamics

    Work done by surface stresses in x-direction:

    Conservation of energy10-Nov-13

    61

    x

    z

    y

    zyx

    x

    upup

    2

    1.

    zyx

    x

    upup

    2

    1.

    zyz

    z

    uu zxzx

    2

    1.

    yxz

    z

    uu zxzx

    2

    1.

    zxy

    y

    uu

    yx

    yx

    2

    1.

    zxy

    y

    uu

    yx

    yx

    2

    1.

    zyxx

    u

    u

    xx

    xx

    2

    1

    .

    zyx

    x

    uu xxxx

    2

    1.

    Computational Fluid Dynamics 62

    Conservation of energy

    The total rate of work done by surface stresses

    is calculated as follows:

    For work done by x-components of stresses add all

    terms in the previous slide.

    Do the same for the y- and z-components.

    Divide by xyzto get the work done per unitvolume by the surface stresses:

    z

    w

    y

    w

    x

    w

    z

    v

    y

    v

    x

    v

    z

    u

    y

    u

    x

    updiv

    zzyzxzzyyy

    xyzxyxxx

    )()()()()(

    )()()()()(

    u

    10-Nov

    -13

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    Computational Fluid Dynamics

    Energy flux due to heat conduction

    Conservation of energy10-Nov-13

    63

    x

    z

    y

    yxzz

    qq zz )

    2

    1.(

    yxzz

    qq zz )

    2

    1.(

    zyxx

    qq xx )

    2

    1.(

    zyxx

    qq xx )

    2

    1.(

    zxyy

    qq

    y

    y )2

    1.(

    zxyy

    qq

    y

    y )2

    1.(

    Computational Fluid Dynamics 64

    Conservation of energy Add all terms and divide by xyzgives the net rate of heat transfer to

    the fluid particle per unit volume:

    Fouriers law of heat conduction relates the heat flux to the localtemperature gradient:

    In vector form:

    Thus, energy flux due to conduction:

    This is the final form used in the energy equation.

    qdivz

    q

    y

    q

    x

    qzyx

    z

    Tkq

    y

    Tkq

    x

    Tkq zyx

    Tgradkq

    )( Tgradkdivdiv q

    10-Nov

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    Computational Fluid Dynamics 65

    Conservation of energy

    Setting the total derivative for the energy in a fluidparticle equal to the previously derived work andenergy flux terms, results in the following energyequation:

    Note that we also added a source term SEthat includessources (potential energy, sources due to heatproduction from chemical reactions, etc.).

    E

    zzyzxzzyyy

    xyzxyxxx

    STgradkdiv

    z

    u

    y

    w

    x

    w

    z

    v

    y

    v

    x

    v

    z

    u

    y

    u

    x

    updiv

    Dt

    DE

    )(

    )()()()()(

    )()()()()(

    u

    10-Nov-13

    Computational Fluid Dynamics 67

    Conservation of energy

    To derive a conservation equation for the kineticenergy of the fluid multiply the u-momentum equation by u,

    the v-momentum equation by v, and

    the w-momentum equation by w.

    Then add the results together to obtain thefollowing equation for the kinetic energy:

    Mzzyzxzzyyyxy

    zxyxxx

    zyxw

    zyxv

    zyxupgrad

    Dt

    wvuD

    Su

    u

    .

    .)]([ 222

    2

    1

    10-Nov

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    Computational Fluid Dynamics 68

    Conservation of energy

    Internal energy equation Subtract the kinetic energy equation from the energy

    equation.

    Define a new source term for the internal energy

    Si = SE - u.SM. This results in:

    i

    zzyzxzzyyy

    xyzxyxxx

    STgradkdiv

    zu

    yw

    xw

    zv

    yv

    x

    v

    z

    u

    y

    u

    x

    udivp

    Dt

    Di

    )(

    u

    10-Nov-13

    Computational Fluid Dynamics 69

    Conservation of energy

    Enthalpy equationAn often used alternative form of the energy equation

    is the total enthalpy equation. Specific enthalpy h = i + p/.

    Total enthalpy h0= h + (u2+v2+w2) = E + p/.

    0

    0

    ( )

    ( ) ( )

    ( ) ( )( ) ( )

    ( ) ( ) ( )( ) ( )

    yx xyxx zx

    yy zy yzxz zz

    h

    h

    div h div k grad T t

    u vu u

    x y z x

    v v ww u

    y z x y z

    S

    u

    10-Nov

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    Computational Fluid Dynamics 70

    Equations of state

    Fluid motion is described by five partial differential equations for mass,momentum, and energy.

    Amongst the unknowns are four thermodynamic variables: ,p, i, andT.

    We will assume thermodynamic equilibrium, i.e. that the time it takes

    for a fluid particle to adjust to new conditions is short relative to the

    timescale of the flow.

    We add two equations of state using the two state variables and T:p=p(,T) and i=i(,T).

    For a perfect gas, these become: p=RTand i=CvT.

    At low speeds (e.g. Ma < 0.3), the fluids can be consideredincompressible. There is no linkage between the energy equation, and

    the mass and momentum equation. We then only need to solve for

    energy if the problem involves heat transfer.

    10-Nov-13

    Computational Fluid Dynamics 71

    Viscous stresses

    A model for the viscous stresses ijis required.

    We will express the viscous stresses as functions of the

    local deformation rate (strain rate) tensor.

    There are two types of deformation:

    Linear deformation rates due to velocity gradients.

    Elongating stress components (stretching).

    Shearing stress components. Volumetric deformation rates due to expansion or compression.

    All gases and most fluids are isotropic: viscosity is a scalar.

    Some fluids have anisotropic viscous stress properties,

    such as certain polymers and dough. We will not discuss

    those here.

    10-Nov

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    Computational Fluid Dynamics 74

    Viscous dissipation

    Substituting the stresses in the internal energy equationand rearranging results as follows:

    Here Fis the viscous dissipation term. This term isalways positive and describes the conversion ofmechanical energy to heat.

    iSTgradkdivdivpidivt

    ienergyInternal F

    )()(

    )(: uu

    2

    22

    2222

    )(3

    2

    2

    udivy

    w

    z

    v

    x

    w

    z

    u

    x

    v

    y

    u

    z

    w

    y

    v

    x

    u

    F

    10-Nov-13

    Computational Fluid Dynamics

    SUMMARY

    10-Nov

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    75

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    Computational Fluid Dynamics 76

    Equations in conservation form

    0)(: u div

    tMass

    MxSugraddivx

    pudiv

    t

    umomentumx

    )()(

    )(:

    u

    MySvgraddivy

    pvdiv

    t

    vmomentumy

    )()(

    )(:

    u

    MzSwgraddivz

    pwdiv

    t

    wmomentumz

    )()(

    )(:

    u

    iSTgradkdivdivpidivtienergyInternal F

    )()()(: uu

    TCiandRTpgasperf ectforge

    TiiandTppstateofEquations

    v

    :..

    ),(),(:

    10-Nov-13

    Computational Fluid Dynamics 77

    The system of equations is now closed, with seven equations for seven

    variables: pressure, three velocity components, enthalpy, temperature, and

    density.

    There are significant commonalities between the various equations. Using a

    general variable , the conservative form of all fluid flow equations can usefully

    be written in the following form:

    Or, in words:

    General transport equations

    Sgraddivdivt

    u

    Rate of increase

    of of fluid

    elementNet rate of flow

    of out of

    fluid element

    (convection)

    Rate of increase

    of due to

    diffusion

    Rate of increase

    of due to

    sources=+ +

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    Computational Fluid Dynamics 78

    Integral form

    The key step of the finite volume method is to integrate the differential equationshown in the previous slide, and then to apply Gauss divergence theorem,which for a vector astates:

    This then leads to the following general conservation equation in integral form:

    This is the actual form of the conservation equations solved by finite volumebased CFD programs to calculate the flow pattern and associated scalar fields.

    ACV

    dAdVdiv ana

    dVSdAgraddAdVt CVAACV

    )()( nun

    Rate of

    increase

    of

    Net rate of

    decrease of due

    to convectionacross boundaries

    Net rate of

    increase of due

    to diffusionacross boundaries

    Net rate of

    creation

    of =+ +

    10-Nov-13