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  • 8/13/2019 Week 08 - Gov Eqs

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    2011 Sajid

    Chapter

    Dr Muhammad Sajid

    Assistant Professor

    NUST, SMME.

    Reference Text:Fundamental of

    Computational Fluid

    Dynamics, J. Anderson.

    Email: [email protected]

    Tel: 9085 6065

    Computational Fluid

    Dynamics

    4-Nov-130

    3 Governing Equations

    Review

    Conservation of mass

    Conservation of LinearMomentum

    Navier Stokes Equation

    Computational Fluid Dynamics

    Introduction

    CFD is fundamentally based on the governing

    equations of fluid dynamics.

    These equations represent mathematical

    statements of the laws of physicsregarding the

    conservation of mass, momentum and energy.

    The purpose of this chapter is to introduce thederivation and discussion of these equations.

    All of CFD is based on these equations; we must

    therefore begin our understanding at the most

    basic description of the fluid flow processes.

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    13

    1

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    Computational Fluid Dynamics

    Introduction

    After these equations are obtained, forms suited

    for use in formulating CFD solutions will be

    highlighted.

    At the end of this chapter, some of the mysteries

    surrounding CFD based predictions of fluid flow

    problems will be replaced with an understanding

    of the equations governing the fluid transport.

    4-Nov-13

    2

    Computational Fluid Dynamics 3

    Review of basic concepts

    Fluid properties:

    Physical laws are stated in terms of parameters like v, a etc.

    Let represent a fluid parameter/property and the amountof that parameter per unit mass, i.e. = m.

    is extensive property and is an intensive property.

    Fluid element is a volume stationary in space,

    Fluid particle is a volume of fluid moving with the flow. A fluid particle in motion experiences two rates of

    changes:

    Due to changes in the fluid as a function of time.

    Due to the fact that it moves to a different location in the fluidwith different conditions.

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    Computational Fluid Dynamics 4

    Review of basic concepts

    The sum of these two rates of changes for aproperty per unit mass (extensive) is called

    the totalor substantivederivative D/Dt:

    With dx/dt=u, dy/dt=v, dz/dt=w, this results in:

    dt

    dz

    zdt

    dy

    ydt

    dx

    xtDt

    D

    4-Nov-13

    .u

    tDt

    D

    w

    vu

    u zyx

    zw

    yv

    xu

    tDt

    D

    Computational Fluid Dynamics 5

    Review of basic concepts

    Fluid element and properties The behavior of the fluid is

    described in terms of macroscopicproperties: Velocity u.

    Pressure p.

    Density r.

    Temperature T. Energy E.

    dy

    dx

    dz(x,y,z)

    1 1

    2 2W E

    p pp p x p p x

    x xd d

    Properties at faces are expressed as first

    two terms of a Taylor series expansion,

    e.g. for p : and

    Properties are averages of a sufficiently largenumber of molecules.

    A fluid element can be thought of as the smallestvolume for which the continuum assumption isvalid.

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    Computational Fluid Dynamics

    Review of basic concepts

    Field representation The flow field of a fluid can be thought of as being

    comprised of a large number of finite sized fluid particleswhich have mass, momentum, internal energy, and otherproperties.

    The distribution of fluid parameters (r, v, P& a) overspace and time is called field representation.

    Velocity field Representation of fluid velocity as function of spatial

    coordinates and time, V = f(x,y,z,t).

    4-Nov-13

    6

    k),,,(j),,,(i),,,( tzyxwtzyxvtzyxuV

    222 wvuVV

    Computational Fluid Dynamics

    Review of basic concepts

    System:A fixed quantity of matter, and no mass is allowed to

    cross the system boundary.

    Control Volume:A space of interest where mass can cross the boundary,

    cv.

    Control Surface: The boundary of the control volume is called the controlsurface, cs.

    Reynolds transport theorem

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    13

    7

    dAnVVdtDt

    D

    cscv

    sys

    rr

    ()()()

    V

    tDt

    D

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    Computational Fluid Dynamics

    Review of basic concepts

    Lagrangian approach: Fluid particles are tagged/identified

    and their properties are determined

    as they move in space.

    Eulerian approach:

    Fluid properties are determined at

    fixed points in space as fluid flows

    by.

    Governing equations can bederived using each method and

    converted to the other form.

    4-Nov-13

    8

    Computational Fluid Dynamics 10

    The governing equations include the followingconservation laws of physics: Conservation of mass.

    Newtons second law: the change of momentumequals the sum of forces on a fluid particle.

    First law of thermodynamics (conservation of energy):

    rate of change of energy equals the sum of rate of heataddition to and work done on fluid particle.

    The fluid is treated as a continuum. For lengthscales of, say, 1m and larger, the molecularstructure and motions may be ignored.

    Governing equations4-Nov-

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    Computational Fluid Dynamics

    Conservation of mass

    Time rate of change of system mass = 0

    For a fixed and nondeforming control volume:

    t - dt, t (coincident), t + dt

    From Reynolds transport theorem, we have.

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    11

    0sysmDt

    D sys

    sys Vdm r

    dAnVVdt

    mDt

    D

    cscv

    sys

    rr

    dAnVVdtDt

    D

    cscv

    sys

    rr

    Computational Fluid Dynamics

    Conservation of mass & Continuity

    Or,

    The continuity equation is an expression for the

    conservation of mass in a control volume.

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    13

    12

    rfacecontrol su

    orughof mass th

    f flownet rate o

    lumecontrol vo

    side theof mass in

    of changetime rate

    systemcoincident

    s of theof the mas

    of changetime rate

    cv

    Vdt

    lumecontrol vo

    side theof mass in

    of changetime rate

    r

    cs

    dAnV

    rfacecontrol su

    roughof mass th

    f flownet rate o

    r

    0 dAnVVdt

    cscv

    rr

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    Computational Fluid Dynamics

    Conservation of mass

    Consider a differential fluid element.

    Let density and velocities components at the

    center of the element be , u, v and w.

    The volume integral can be expressed as.

    Next, we need to find the mass flow rate

    through the surfaces

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    13

    0

    dAnVVdtcscv

    rr

    zyxt

    Vdt

    cv

    dddr

    r

    Computational Fluid Dynamics

    Conservation of mass

    If ru is the horizontal mass flux at the center of

    the element than at the faces the mass flux in

    horizontal direction is.

    Net rate of mass flowing through the surfaces is.

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    13

    14

    zyx

    x

    uzy

    x

    x

    uuzy

    x

    x

    uu ddd

    rdd

    drrdd

    drr

    22

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    Computational Fluid Dynamics 15

    Conservation of mass

    The inflows (positive) and outflows (negative)in all directions are:

    x

    yz

    ( ) 1.2

    ww z x y

    z

    rr d d d

    ( ) 1

    .2

    vv y x z

    y

    rr d d d

    zyxx

    uu ddd

    rr

    2

    1.

    )(

    zxyy

    vv ddd

    rr

    2

    1.

    )(

    yxzz

    ww ddd

    rr

    2

    1.

    )(

    ( ) 1.2

    uu x y z

    x

    rr d d d

    4-Nov-13

    Computational Fluid Dynamics

    Conservation of mass

    Mass flow rate in the y and z directions is.

    Combining these equations we get.

    Thus,

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    13

    16

    zyx

    y

    vddd

    r

    directiony''inrateflowmassnet

    zyxz

    w

    y

    v

    x

    udAnV

    cs

    dddrrr

    r

    rateflowmassnet

    0

    zyx

    z

    w

    y

    v

    x

    uzyx

    tddd

    rrrddd

    r

    zyx

    y

    wddd

    r

    directionz''inrateflowmassnet

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    Computational Fluid Dynamics 17

    Continuity equation

    Summing all terms in the previous slide anddividing by the volume dxdydzresults in:

    In vector notation:

    For incompressible fluids r/ t=0, and the

    equation becomes: div u= 0. Alternative ways to write this:

    0)()()(

    zw

    yv

    xu

    trrrr

    0)(

    urr

    divt

    Change in densityNet flow of mass across boundaries

    Convective term

    0

    zw

    yv

    xu 0

    i

    i

    x

    u

    4-Nov-13

    Computational Fluid Dynamics

    CONSERVATION OF MOMENTUM

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    Computational Fluid Dynamics 22

    Momentum equation in three dimensions

    Newtons second law:the sum of forces equals the rate of change ofmomentum.

    Rate of increase of momentum along x, y, and zaxis's.

    Forces on fluid particles are: Surface forces such as pressure and viscous forces.

    Body forces, which act on a volume, such as gravity,centrifugal and electromagnetic forces.

    Dt

    Dw

    Dt

    Dv

    Dt

    Durrr

    4-Nov-13

    ()()()

    V

    tDt

    D

    Computational Fluid Dynamics

    Conservation of Momentum

    The surface forces are due to the stresses,

    exerted on the sides of the fluid element.

    Stresses are forces per area. = N/m2or Pa.

    4-Nov-

    13

    23

    Two types of stresses:

    normal stress (ij), often shown as

    (ij) and

    shear stress (ij).

    i refers to the axis normal to the surface,

    j represents the direction of the stress.

    Forces in direction of an axis are

    positive, else negative.

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    All surface forces acting in the x-direction on thefluid element are:

    Conservation of momentum4-Nov-13

    24

    x

    z

    y

    zyxx

    pp ddd )

    2

    1.(

    zyxx

    pp ddd )

    2

    1.(

    zyzz

    zxzx

    ddd

    )2

    1.(

    yxzz

    zxzx

    ddd

    )2

    1.(

    zxyy

    yx

    yx ddd

    )

    2

    1.(

    zxyy

    yx

    yx ddd

    )

    2

    1.(

    zyxx

    xxxx

    ddd

    )2

    1.(

    zyxx

    xxxx ddd

    )

    2

    1.(

    Computational Fluid Dynamics 25

    Conservation of Momentum

    Set the rate of change of x-momentum for a

    fluid particle Du/Dt equal to:

    the sum of the forces due to surface stresses

    shown in the previous slide, plus

    the body forces. These are usually lumped

    together into a source term SM:

    p is a compressive stress and xxis a tensile

    stress.

    Mxzxyxxx S

    zyx

    p

    Dt

    Du

    r

    )(

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    Computational Fluid Dynamics 26

    Conservation of Momentum

    Similarly for y- and z-momentum:

    Mxzxyxxx S

    zyx

    p

    Dt

    Du

    r

    )(

    My

    zyyyxyS

    zy

    p

    xDt

    Dv

    r

    )(

    Mzzzyzxz

    Sz

    p

    yxDt

    Dw

    )( r

    4-Nov-13

    Computational Fluid Dynamics

    Cauchys equation of motion

    It is an expression for the acceleration, the

    body forces, the pressure gradient forces, and

    the viscous forces coupled with Newtons 2nd

    Law:

    Note that this is an incredibly succinct

    equation, and is much more complicated than

    it at first appears.

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    27

    ij

    PkgDt

    vDrr

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    Computational Fluid Dynamics

    Cauchys equation of motion

    The full expanded version can be written foreach component,x, y, and zas:

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    28

    zyxzPkg

    zvv

    yvv

    xvv

    tv

    zyxy

    P

    z

    vv

    y

    vv

    x

    vv

    t

    v

    zyxx

    P

    z

    vv

    y

    vv

    x

    vv

    t

    v

    zyyyxyzz

    zy

    zx

    z

    zyyyxyy

    z

    y

    y

    y

    x

    y

    zxyxxxx

    z

    x

    y

    x

    x

    x

    rr

    r

    r

    Computational Fluid Dynamics

    Cauchys equation of motion

    Things to notice about these equations: only the zcomponent equation has a body force,

    because gravity only works in the zdirection;

    thex- and y-component equations are identical exceptfor subscripts;

    the equations cannot be solved in their present form

    because the stresses have not yet been recast interms of velocities.

    In order to solve this equation for a specificsubstance, like a fluid, we need to substituteexpressions involving velocity for the viscousstress gradients.

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    Computational Fluid Dynamics

    Constitutive Relationship for Viscous Fluids

    The mechanical behavior of every substance canbe described in terms of stress and strain, and the

    relationship between these variables is called a

    constitutive relationship.

    Generally, these must be determined through

    experiments and differ for every type of substance

    (i.e., rock, plastic, fluid, gas, etc.).

    Mathematically, the relationship is between the

    stress tensor and the strain tensor (for rigidsolids) or strain-rate tensor (for fluids).

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    Computational Fluid Dynamics

    Constitutive Relationship for Viscous Fluids

    Strain is a measure of distortion and the strain-rate tensor has nine components just like thestress tensor:

    The diagonal entries , , and representnormal strain rates (elongation, contraction) andthe off-diagonal strains represent shear strainsrates. Remember

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    31

    zzzyzx

    yzyyyx

    xzxyxx

    ij

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    Computational Fluid Dynamics

    Strain and strain rate

    The strain rates in the strain-rate tensor can be describedin terms of velocity gradients.

    Consider a small elongate element of fluid moving in the

    x-direction with a non-constant velocity.

    The element is stretching as it is moving, resulting in a

    normal strain-rate in thex-direction.

    The element has a length ofxand undergoes strain

    which stretches it tox+ xin the time t. xis the

    small elongation ofxand is always smaller thanx.

    The strain xxis:

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    32

    x

    xxx

    d

    d

    Computational Fluid Dynamics

    Strain and strain rate

    There are different ways to determine the

    relationship between strain rate and velocity gradients.

    First Method:

    The only way the box can deform (i.e., stretch; i.e.,

    strain) is if the right-hand side moves faster than the

    left-hand slide, which happens when > 0.

    The rateof strain will equal because this is the

    amount by which the right-hand side is moving faster

    than the left-hand side.

    So we can deduce the answer as: =

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    Strain and strain rate

    Second Method: Take the expression for strain = and

    divide by the time increment, t;

    The term in parentheses is the rate at which the

    increment xgrows with time or differential velocity,

    the difference in velocity between the left and right

    sides of the original box.

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    35

    x

    v

    x

    vx

    xt

    x

    xt

    xxxxxx

    11

    d

    d

    d

    d

    x

    vxv

    x

    vxvvv

    t

    x xL

    x

    LLR

    d

    d

    x

    xxx

    d

    d

    t

    x

    xtx

    x

    t

    xx

    d

    d

    d

    d

    d

    d 1

    Computational Fluid Dynamics

    Strain and strain rate

    Similar arguments show that the other diagonal

    elements in the strain-rate tensor, are:

    This is an example how just one of the 9

    components of the strain-rate tensor is related to

    the gradients of velocity in thex, y, and zdirections.

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    36

    z

    v

    y

    vz

    zz

    y

    yy

    ;

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    Computational Fluid Dynamics

    Strain and strain rate

    The full strain-rate tensor can be expressed in terms ofvelocity gradients as follows:

    This is a symmetric tensor across the diagonal elements. This strain-rate tensor is valid for all materials, including fluids.

    It expresses the strain rates as a function of the velocity

    gradients, and is constructed entirely from geometry.

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    37

    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