2 Foundations of Fluid Mechanics: Governing Equations

In this chapter, we review the governing equations of fluid mechanics that describe flow fields in mathematical terms. Modern computational aerodynamic methods are based on the particular governing equations that they solve. Since computational aerodynamics is now a necessity, not a luxury, for many aspects of configuration aerodynamics, it is crucially important for aerodynamicists to have a good understanding and appreciation of the underlying assumptions and approximations behind an equation before using its associated computational aerodynamic method. We will see that developments in computational methods have resulted in a slightly different approach to fundamental conservation statements compared with presentations before the digital computing age. This chapter also defines the nomenclature and terminology used in current aerodynamics practice. If you are fully conversant with the derivation and characteristics of the governing equations of fluid mechanics, you might consider skipping the remainder of this chapter and going straight to Chapter 3

The presentation of material in this chapter presumes that the reader has previously had a course in fluid mechanics or aerodynamics. Many excellent discussions of the foundations of fluid mechanics for aerodynamics application are available in books by Karamcheti,[1] Bertin,[2] Anderson,[3] and Moran.[4] The best formal derivation of the equations was assembled by Grossman.[5] Indeed, an entire book has been written on the equations of fluid mechanics by Hoffman et al.[6]

2.1 Governing Equations of Fluid Mechanics

Fluid is assumed to be a continuum. For virtually all aerodynamics work, this is a valid assumption. One case where this may not be true is when fluid density is so low that the actual molecular motion must be analyzed, which is the purview of the field of rarefied gas dynamics. This may be important for vehicles in hypersonic flight. Aeroassisted orbital transfer vehicles (AOTV’s) are examples of the vehicles requiring noncontinuum flow field analysis.

The fluid is defined by an equation of state and by the thermodynamic and transport properties, namely, the ratio of specific heats, γ, viscosity, μ, and the coefficient of heat conduction, k. Governing equations and boundary conditions control the motion of the fluid. The governing equations are given by conservation laws listed in table 2-1.

Governing equations
Mass Continuity
Momentum Newton's Second Law, F = ma
Energy First Law of Thermodynamics

Table 2-1: Conservation laws for governing equations

Coordinate systems are also important in aerodynamics. The general equations of fluid motion are independent of the coordinate system. However, simplifying assumptions frequently introduce directional bias into approximate forms of the equations; they must be used with a specific coordinate system orientation relative to the flow field.

Traditionally, Cartesian coordinates were used to describe vehicle geometry. In this chapter, we will work entirely in the Cartesian coordinate system. It is frequently desirable to make calculations in non-Cartesian coordinate systems that are distorted to fit a particular shape. In general, these are non-orthogonal curvilinear coordinates. Even when using Cartesian coordinates, the x-, y-, and z-coordinates are oriented differently depending on whether the flow is two- or three-dimensional. Figure 2-1 shows the usual two-dimensional coordinate system.

For an airfoil using an x-y coordinate system centered at the leading edge, the x axis is aligned with the chordwise length of the airfoil, while the y axis is upwards normal to the chord axis. Flow approaching at a velocity of cap V sub infinity and an angle of attack alpha, can be broken into a horizontal portion of cap V sub infinity times cosine of alpha and a vertical portion portion of cap V sub infinity times sine of alpha.
Figure 2-1: Body-fixed Cartesian coordinate system for two-dimensional flow. From W. H. Mason. Adapted by S. Madden.

The standard coordinate system used in three dimensions is illustrated in figure 2-2. Note the different orientation of the y coordinate in figures 2-1 and 2-2. In three dimensions, x is chordwise, much like it is in 2D, but y is spanwise instead of being normal to the chord. The right-hand rule determines the direction of the z coordinate. Figure 2-2 also shows the components of the freestream velocity vector, V, in x, y, and z directions. The wing is flying at an angle of attack of α and a sideslip angle of β. The unit vectors in x, y, and z directions are denoted by i, j, and k, respectively.

Figure 2-2: Standard body-fixed Cartesian coordinate system for three-dimensional flows. From W. H. Mason. Adapted by S. Madden.

In Cartesian coordinates, the independent variables are x, y, z, and t. Here t denotes time. We want to know the velocities (u, v, w) and the fluid properties (p, ρ, T). (Note that u, v, and w are the components of the flow velocity in the x, y, and z directions, respectively.) These six unknowns require six equations which are shown in table 2-2.

Six equations
Continuity 1 equation
Momentum 3 equations
Energy 1 equation
Equation of state 1 equation

Table 2-2: Six equations of fluid mechanics

Assumptions frequently reduce the number of equations required; for example, incompressible, inviscid, and irrotational flow can be described by a single equation, as shown below in section 2.5. Prior to the 1980s, almost all aerodynamics work used a single partial differential equation, possibly coupled with another equation. An example of this approach is the calculation of potential flow for the inviscid portion of the flow field, which is used in combination with the boundary layer equations to compute the flow field where an estimate of the viscous effects is required.

2.2 Derivation of Governing Equations

Governing equations of fluid motion are mathematical models based on the conservation laws (for mass, momentum, and energy) and the fluid properties as listed in section 2.1. For most of the practical aerodynamic applications, the governing equations are numerically solved to determine the density, velocity, pressure, and temperature distributions. To develop the governing equations themselves, we can use two approaches, Lagrangian and Eulerian.

  1. Lagrangian: In this approach, we observe the trajectory of an individual fluid particle as it moves in time through the space surrounding a body. The space itself is defined by a coordinate system fixed to the body, commonly referred as a body-fixed coordinate system. Figures 2-1 and 2-2 show body-fixed coordinates systems in two and three dimensions, respectively. Note that the motion of every fluid particle is described in terms of a “fixed reference configuration” which could be (but isn’t necessarily) the position in space occupied by each fluid particle at an initial time, t = 0. The Lagrangian approach may be considered as the conventional application of Newton’s Second Law to each fluid particle. Even in steady flow, the forces encountered by the particle are a function of the time history of its motion.
  2. Eulerian: In contrast to the Lagrangian approach, the Eulerian approach considers the entire space around the body as a field, also called a flow field, and determines flow properties such as velocity and pressure at a given point in the field through which the fluid particles move. The space itself is defined by a body-fixed coordinate system. We essentially ignore the motion of individual fluid particles and instead consider the distribution of velocity and pressure throughout the space around a body. This approach imitates wind tunnels, in which fluid particles flow past a body and flow properties are measured at various points in the space surrounding the body.

It is worth noting that the Lagrangian and Eulerian approaches describe the same physical phenomena. Therefore, they are mathematically related. Karamcheti[7] provides a particularly good explanation of the underlying ideas in his Chapters 4 through 7.

The Eulerian approach is almost universally used to develop the governing equations of fluid motion. The use of this approach requires careful attention in the application of the conservation concepts and of Newton’s Second Law in particular. Computational aerodynamic methods have been developed to numerically solve the resulting equations. Newton’s Law governs the motion of every fluid particle. To apply this law in the Eulerian approach, we define a control volume that maintains a fixed location relative to the coordinate system but through which fluid particles traverse. The connection between the rate of change of the properties of a fluid particle (e.g., velocity, density, pressure) and the rate of change of fluid properties flowing through the control volume* requires special consideration. The substantial derivative, discussed in section 2.2.2, is employed to define the rate of change of the properties of the fluid particle as it moves through the flow field relative to the fixed coordinate system. An integral approach to the description of the change of properties of a fluid particle relative to the fixed coordinate system is available through the use of the Reynolds transport theorem, which is described in Owczarek[8] and section 1.2 of Grossman.[9]

The conservation equations of fluid motion can be expressed in either a differential or integral viewpoint. The differential form of the equations is found in most aerodynamics books. However, the integral form is preferred for numerically solving the equations since integrals are more accurately computed than derivatives. The integral form is also better suited for simulating discontinuities (shocks) in the flow field than the differential form, which assumes fluid properties to be continuous. We will use aspects of each approach in this book.

*The concept of a “control volume” arose as an engineering requirement for a means to formulate the physical description to allow calculations to be made. It differs from the viewpoint adopted by physicists. An explanation of the concept’s origins is contained in Walter G. Vincenti’s 1990 book What Engineers Know, and How They Know It: Analytical Studies from Aeronautical History, published by John Hopkins University Press. The relevant chapter is entitled “A Theoretical Tool for Design: Control Volume Analysis 1912–1953.”

2.2.1 Conservation of Mass: The Continuity Equation

In this section, we derive the continuity equation from a control volume viewpoint (in 2D), and then we look at the equivalent integral statement and the use of the Gauss divergence theorem to establish the connection. Other derivations are given by Moran (sections 2.2, 2.3, 2.4),[10] Anderson (Chapters 2 and 6),[11] and Bertin and Smith (Chapter 2).[12]

From a control volume viewpoint, the statement of conservation of mass is in words simply:

Net outflow of mass through the surface surrounding the volume = decrease of mass within the volume.

To translate this statement into a mathematical form, consider the control volume given in figure 2-3. Here, u is the velocity in the x-direction, v is the velocity in the y-direction, and ρ is the density. The following represents the net mass flow rate, or flux,* out of the volume, as illustrated in figure 2-3:

[Xout][Xin]+[Yout][Yin]=change of mass (decrease)=ρtΔXΔY(2-1)

For a control volume represented as an arbitrary area delta cap X by delta cap Y within the cap X cap Y plane, the total flow into the volume from the cap X and cap Y directions must equal the total flow out of the volume in the cap X and cap Y directions.
Figure 2-3: Control volume for conservation of mass.**

*A flux is a quantity that flows across the boundary of a defined surface. Typically we think of mass, momentum, and energy fluxes.

** Note that convention requires that control volumes be described using dashed lines to illustrate that the boundaries are fictitious and that fluid flows freely across them.

We use a Taylor series expansion of the mass fluxes into the volume around the origin of the volume. The flux per unit length through the surface is multiplied by the length of the surface.

[Xout]=[ρu+ρuxΔX2]ΔY[Xin]=[ρuρuxΔX2]ΔY[Yout]=[ρv+ρvyΔY2]ΔX[Yin]=[ρvρvyΔY2]ΔX(2-2)

Substituting these terms in equation (2-1), we arrive at equation (2-3) below.

[ρu+ρuxΔX2]ΔY[ρuρuxΔX2]ΔY+[ρv+ρvyΔY2]ΔX[ρvρvyΔY2]ΔX=ρtΔXΔY(2-3)

Summing up and canceling ∆X∆Y, we obtain

ρux+ρvy=ρt(2-4)

or, in three dimensions,

ρt+ρux+ρvy+ρwz=0.(2-5)

This is the differential form of the continuity equation. The more general vector form of the equation is

ρt+(ρV)=0(2-6)

where V = ui + vj + wk with i, j, and k denoting unit vectors in x-, y-, and z-coordinate directions, respectively.

Alternately, consider the arbitrary control volume shown in figure 2-4. The conservation of mass can then be written in an integral form quite simply. The surface integral of the flow out of the volume Ω with surface area S simply equals the change of mass in the volume as given in equation (2-7):

ρVndS=tρ(2-7)

An arbitrary volume is shown to be enclosed by a corresponding surface area. The velocity vector cap V is positive pointing outward from the volume, normal to the surface area.
Figure 2-4: Arbitrary fluid control volume. From W. H. Mason. Adapted by S. Madden.

This is true without making any assumption requiring continuous variables and differentiability. It holds for all flows—viscous or inviscid, compressible or incompressible. To relate this expression to the differential form, we make use of the Gauss divergence theorem, which assumes continuous partial derivatives. It is given by

AndS=AdΩ.(2-8)

The equivalent statement for a scalar is

ϕndS=gradϕdΩ.(2-9)

Using the divergence theorem, equation (2-8), the differential and integral forms can be shown to be the same. First, rewrite the surface integral in the conservation of mass, equation (2-7), as

ρVndS=(ρV)dΩ.(2-10)

Substituting it in equation (2-7), the continuity equation in integral form is written as equation (2-11).

(ρV)=tρ(2-11)

Since Ω refers to a fixed volume, we can move ∂/∂t inside the integral and rewrite equation (2-11) as

[(ρV)+ρt]=0.(2-12)

For this to be true in general, the integrand must be zero, which is just the differential form! Further discussion and other derivations are available in Moran (sections 2.2, 2.3, and 2.4),[13] Anderson (section 2.6),[14] and Bertin and Smith (Chapter 2).[15]

2.2.2 Conservation of Momentum and the Substantial Derivative

In this section, we derive the general equations for the conservation of momentum. This is a statement of Newton’s Second Law: The time rate of change of momentum of a body equals the net force exerted on it. For a fixed mass, this is the famous equation

F=ma=mDVDt.(2-13)

Notice a new term, D/Dt, called the substantial derivative, on the right-hand side of equation (2-13). It is the consequence of the need to apply Newton’s Law to a moving fluid element (the “body” in the Second Law statement given above) in our fixed coordinate system, which introduces some extra complications. We discuss the substantial derivative next.

2.2.2.1 Substantial Derivative

Let us look at what D/Dt means in a body-fixed coordinate system. Figure 2-5 shows a moving fluid particle at two instances of time.[16] In this figure, Q(r,t) represent any fluid property associated with the fluid particle at position r at time t; Q could be density or pressure or velocity. The change in the property Q between the position r at time t and r+∆s at t+∆t is

ΔQ=Q(r+Δs,t+Δt)Q(r,t).(2-14)

The space change ∆s is simply equal to Vt. Thus we can write

ΔQ=Q(r+VΔt,t+Δt)Q(r,t).(2-15)

Equation (2-15) is in a form that can be used to find the rate of change of Q:

DQDt=limΔt0ΔQΔt=limΔt0Q(r+VΔt,t+Δt)Q(r,t)Δt(2-16)

A fluid particle travels along a path. At a particular point, its location relative to a fixed observer is measured as r of t, and is observed to have a velocity cap V and poperty value of cap Q of r and t. After the particle has displaced by some distance along its path delta s, which is equal to cap V times delta t or delta r, its position is observed as r plus delta r at t plus delta t, and has a property value of cap Q of r plus delta r and t plus delta t.
Figure 2-5: Moving particle viewed from a fixed coordinate system. From W. H. Mason. Adapted by S. Madden.

Note that the rate of change is in two parts, one for a change in time and the other for a change in position. Thus we write the change of Q as a function of both time and space using the Taylor series expansion as

Q(r+VΔt,t+Δt)=Q(r,t)+Qt|r,tΔt++Qs|r,tVΔt+(2-17)

where the direction of s is understood from figure 2-5. Substituting into equation (2-16) and taking the limit, we obtain equation (2-18) below.

limΔt0ΔQΔt=Qt+QsV(2-18)

The noteworthy outcome of applying Newton’s Law for a moving particle in a stationary coordinate system is that the rate of change of Q at a point in space is the sum of two terms shown on the right-hand side of equation (2-18). The first term, local derivative, represents the temporal change or the instantaneous rate of change of Q at its location. The second term, convective derivative, represents the rate at which Q is convected to that location by the fluid motion. This term has the unknown velocity, V, multiplying a term containing the unknown Q. This is important as it introduces a fundamental nonlinearity into the system, as shown next.

We now put this result into a specific coordinate system:

Qs=eVQ(2-19)

where eV denotes the unit vector in the direction of V. Thus, V = VeV and

QsV=VQ.(2-20)

Thus, we use equations (2-18) and (2-20) to write the substantial derivative, equation (2-16), as

DDt=t+  (V)(2-21)

which can be applied to either a scalar as

DQDt=Qt+(V)Q(2-22)

or to a vector quantity as

DVDt=Vt+(V)V.(2-23)

In Cartesian coordinates, u, v, and w, are the components of V in the x, y, and z directions, respectively. The substantial derivative becomes equation (2-24).

DuDt=ut+uux+vuy+wuzDvDt=vt+uvx+vvy+wvzDwDt=wt+uwx+vwy+wwz(2-24)

To solve equations containing these nonlinear terms, we generally have to employ numerical methods. There are only a very few special cases where you can obtain analytic solutions to the nonlinear equations explicitly.

2.2.2.2 Forces

Next we need to find the net forces acting on the fluid element. The forces are:

  • Body forces
  • Pressure forces
  • Shear forces

Each of these forces applies to the control volume. Surface forces are shown in figure 2-6, with τ as a commonly used symbol for stresses. [Note that the orientation of axes in figure 2-6 is different from that in figure 2-3. However, both systems follow the right-hand rule. Therefore, the conclusions are equally valid in both systems.] In the figure, the first subscript for τ indicates the direction normal to the surface, and the second subscript defines the direction in which the force acts. Fluids of interest in aerodynamics are isotropic (i.e., properties are uniform in all directions). Therefore, the following expressions hold to satisfy equilibrium of moments about each axis:

τxy=τyxτxz=τzxτyz=τzy(2-25)

A control volume is represented as a cube, with an x-y-z coordinate frame centered at one of its bottom vertices. The stress on each surface is represented by tau, with subscripts corresponding to its face of application and positive direction. For example, normal stress on the x face, is represented as tau sub x x, while the shear stresses are represented as tau sub x y and tau sub x z, for positive shear on the x face in the y and z directions, respectively. These same conventions apply to the positive y and z faces as well.
Figure 2-6: Control volume showing the surface forces.

The connection between pressure and stress is defined more specifically when the properties of a fluid are prescribed. Figure 2-7 shows the details of the forces, with the surface forces expanded about the center of the control volume using a Taylor series and the body force per unit mass denoted by f acting at the center.

For a representative rectangle of length delta cap X and height delta cap Y, body forces f sub x and f sub y, are shown to act at the center of the element in the cap X and cap Y directions, respectively. Surface stresses on each face are represented using the same naming convention as the previous figure, plus their derivative with respect to x or y, times the distance from the midpoint to the face in question. For example, the shear stress on the rightmost face is represented as tau sub x y plus the partial derivative of tau sub x y with repsect to x times delta x over 2 and is positive up. The shear stress on the leftmost face is tau sub x y minus the partial derivative of tau sub x y with respect to x times delta x over 2, and is positive down. The same relationship holds on the top and bottom faces, with the shear on the top surface being positive to the right and the shear on the bottom surface being positive to the left. Normal stresses are always defined as positive out from the surface.
Figure 2-7: Details of forces acting on a two-dimensional control volume.

Considering the x-direction as an example and using the Taylor series expansion shown in figure 2-7, the net forces are found in a manner exactly analogous to the approach used in the derivation of the continuity equation. Thus, the net force in the x-direction is found to be

ρΔxΔyfx+x(τxx)ΔxΔy+y(τyx)ΔyΔx.(2-26)

Now we combine the forces, including the z-direction terms, and use them to substitute for the force term F in the original statement, F = ma, as seen in equation (2-13). Using the substantial derivative and the definition of the mass, m = ρ∆xyz, the x-momentum equation is equation (2-13) written as ma=F, the usual fluid mechanics convention; considering the x component, max = Fx,

ρΔxΔyΔzDuDt=ρΔxΔyΔzfx+x(τxx)ΔxΔyΔz+y(τyx)ΔyΔxΔz+z(τzx)ΔyΔxΔz.(2-27)

Dividing both sides by ∆xyz, we obtain the final set of three equations by appending the y- and z-momentum equations that can be easily derived by applying the approach used for equation (2-27):

ρDuDt=ρfx+τxxx+τyxy+τzxzρDvDt=ρfy+τxyx+τyyy+τzyzρDwDt=ρfz+τxzx+τyzy+τzzz(2-28)

These are general conservation of momentum relations, valid for anything!

To make equation (2-28) more specific for fluid flow problems, we need to relate the stresses to the motion of the fluid. For gases and water, stress is a linear function of the rate of strain. Such a fluid is called a Newtonian fluid, and equation (2-29) shows the expression for stress as

τ=μuy(2-29)

where μ is the coefficient of viscosity. In our work, we consider μ to be a function of temperature only. Note that in air, the viscosity coefficient increases with increasing temperature, and in water, the viscosity coefficient decreases with temperature increases.

To complete the specification of the relationship between stress and rate of strain, we need to define precisely the relation between the stresses and the motion of the fluid. This can become complicated. In general, the fluid description requires two coefficients of viscosity. The coefficient of viscosity arising from the shear stress is well defined. The second coefficient of viscosity is not. This coefficient depends on the normal stress and is only important in computing the detailed structure of shock waves. Various assumptions relating the coefficients of viscosity are made. The set of assumptions that leads to the equations known as the Navier–Stokes equations are:

  • The stress-rate-of-strain relations must be independent of coordinate system.
  • When the fluid is at rest and the velocity gradients are zero (the strain rates are zero), the stress reduces to the hydrostatic pressure.
  • Stoke’s hypothesis is used to eliminate the issue of mean pressure versus thermodynamic pressure. This is the assumption between viscosity coefficients.

Details of the theory associated with these requirements can be found in Schlichting[17] and Grossman.[18] Using the set of assumptions listed above leads to the following relations:

τxx=p23μV+2μuxτyy=p23μV+2μvyτzz=p23μV+2μwz(2-30)

and

τxy=τyx=μ(uy+vx)τxz=τzx=μ(uz+wx)τyz=τzy=μ(vz+wy)(2-31)

If we combine equations (2-28), (2-30), and (2-31) and we neglect the body force term (which is very small compared to the other terms since the air is so light), we get the standard set of equations for aerodynamics:

ρDuDt=px+x(2μux23μV)+y[μ(uy+vx)]+z[μ(wx+uz)]ρDvDt=py+x[μ(uy+vx)]+y(2μvy23μV)+z[μ(wy+vz)]ρDwDt=pz+x[μ(wx+uz)]+y[μ(vz+wy)]+z(2μwz23μV)(2-32)

These are the classic Navier–Stokes equations written in the standard aerodynamics form. Note that the equations are (i) non-linear (remember that superposition of solutions is not allowed—D/Dt!); (ii) second order; (iii) highly coupled, and (iv) long! As written above, it’s easy to identify F = ma, written in the fluid mechanics form ma = F.

When the viscous terms are small and thus ignored, the flow is termed inviscid. The resulting equations are known as the Euler equations.

There are also alternate integral formulations of the equations. Consider the momentum flux through an arbitrary control volume in a manner similar to the integral statement of the continuity equation pictured in figure 2-4 and given in equation (2-7). Here, the rate of momentum change is proportional to the force. The integral statement is

ρV(Vn)dS+tρV=F=Fvolume+Fsurface ,(2-33)

and this statement can also be converted to the differential form using the Gauss divergence theorem. Note that we use the partial derivative notation ∂/∂t to denote the change in the fixed “porous” control volume with fluid moving across the boundaries. The derivation of the Navier–Stokes equations is for general unsteady fluid motion. Because of limitations in our computational capability (for some time to come), these equations are directly applicable to solve for laminar flows. When the flow is turbulent, the usual approach is to Reynolds-average the equations, with the result that additional Reynolds stresses appear in the equations. Clearly, the addition of new unknowns requires additional equations. This problem is treated through turbulence modeling and is discussed, for example, in Tannehill, et al.[19]

2.2.3 The Energy Equation

The equation for the conservation of energy is required to complete the system of equations. This is a statement of the First Law of Thermodynamics: The sum of the work and heat added to a system will equal the increase of energy. Following the derivation given by White:[20]

dEtchange of total energyof the system=δQchange of heat added+δWchange of work doneon the system(2-34)

For our control volume in a fixed coordinate system, the rate of change is

DEtDt=Q˙+W˙(2-35)

where

Et=ρ(e+12V2gr)(2-36)

and e is the internal energy per unit mass. The last term is the potential energy (i.e., the body force). In aerodynamics, this term is neglected. Et can also be written in terms of specific energy as

Et=ρe0(2-37)

where

e0=e+12V2.(2-38)

To obtain the energy equation, we need to write the right-hand side (RHS) of equation (2-35) in terms of flow properties. Consider first the heat added to the system.* The heat flow into the control volume is found in the identical manner to the mass flow. Using figure 2-8 for reference, we obtain the expression for the net heat flow.

*We neglect heat addition due to radiation. See Grossman[21] for the extension to include this contribution.
For a control volume represented as an arbitrary area delta cap X by delta cap Y within the cap X cap Y plane, the heat flux into into the volume q in must equal the heat flux out of the volume q out, with all flux being shown in the cap X direction.
Figure 2-8: The x-component of heat flux into and out of the control volume. From W. H. Mason. Adapted by S. Madden.

The heat fluxes are:

qxin=(qxqxΔx2)Δyqxout=(qx+qxΔx2)Δy(2-39)

and the net heat flow into the control volume in the x-direction is qxin - qxout, or

qxΔxΔy.

Using the same analysis in the y- and z-directions, we obtain the net heat flux into the control volume (realizing that the ∆xyz terms will cancel):

Q˙=(qxx+qyy+qzz)=q(2-40)

Now relate the heat flow to the temperature field. Fourier’s law provides this connection:

q=kT(2-41)

where k is the coefficient of thermal conductivity. Combining equation (2-41) with equation (2-40), we get the heat conduction in terms of the temperature gradient in the flow field as

Q˙=q=+(kT).(2-42)

Next we find the work done on the system. Using the definition of work = force × distance, the rate of work is

W˙=force×velocity.(2-43)

Using the control volume again, we find the work, which is equal to the velocity times the stress. The work associated with the x-face of the control volume (for two-dimensional flow) is

wx=uτxx+vτxy.(2-44)

The complete description of the work on the control volume is shown in figure 2-9.

The same figure is shown as in Figure 2.7, however now the stresses are now multiplied by the velocity component in the corresponding direction, with u for the velocity in the cap X direction and v for the velocity in the cap Y direction. For example, tau sub x x is multiplied with u, while tau sub x y is multiplied with v, due to it acting in the cap Y direction.
Figure 2-9: Work done on a control volume.

Using the x-component of net work as an example again, the work done on the system is wxin or wxout, or

(wxwxxΔx2)Δy(wx+wxxΔx2)Δy=wxxΔxΔy.(2-45)

Including the other two directions, namely y and z, and dropping the ∆xyz terms, which cancel out, we get

W˙=divw=x(uτxx+vτxy)+y(uτyx+vτyy).*(2-46)

*Here we are using White’s notation. Realize there is a difference between W and w.

Substituting equations (2-37) and (2-38) into (2-35) for Et, equation (2-42) for the heat, and equation (2-46) for the work, we obtain

Dρ(e+12V2)Dt=(kT)divw.(2-47)

Many, many equivalent forms of the energy equation are found in the literature. Often the equation is thought of as an equation for the temperature. We now describe how to obtain one specific form. Substituting equation (2-46) into (2-47) and using the expressions for the τ’s in terms of μ and the velocity gradients in equations (2-29) and (2-30), we obtain the following lengthy expression (see Bertin and Smith,[22] pp. 40–42). After making use of the momentum and continuity equations to simplify and finally introducing the definition of enthalpy, h = e + p/ρ, we obtain a frequently written form of the classical energy equation given as:

ρDhDtDpDt=(kT)heat conduction+Φviscous dissipation(always positive)(2-48)

where

Φ=μ{2[(ux)2+(vy)2+(wz)2]+(vx+uy)2+(wy+vz)2+(uz+wx)223(ux+vy+wz)2}.(2-49)

The energy equation can be written in numerous forms, and many different but entirely equivalent forms are available. In particular, the energy equation is frequently written in terms of the total enthalpy, H, to good advantage in inviscid and boundary layer flows. A good discussion of the energy equation is also given by White.[23]

There is also an integral form of this equation:

ρ(e+V2/2)(Vn)dS+tρ(e+V2/2)dΩ=Q˙+W˙(2-50)

Here again note that we use the partial derivative notation ∂/∂t to denote the change in the fixed “porous” control volume with fluid moving across the boundaries.

2.3 Boundary Conditions

If all flow fields are governed by the same equations, what makes flow fields different? Boundary conditions are the means through which the solution of the governing equations produce different results for different shapes. For aerodynamic solutions, the specification of the arbitrarily shaped configuration geometry and of the boundary conditions constitutes the major part of any effort.

2.3.1 Boundary Conditions on the Surface

The boundary condition on the surface of the configuration is the most straightforward and most obvious physically. However, the statement of the boundary conditions is tightly connected to the flow field model in use and the type of surface (e.g., solid or porous).

For an inviscid steady flow over a solid surface, the statement of the boundary condition is

VRn=0.(2-51)

In this equation, VR is the relative velocity defined as the difference between fluid (or freestream) velocity V and the surface velocity VS, and n is the unit vector normal to the surface. Therefore, this boundary condition simply stipulates that the component of the relative velocity normal to the surface must be zero and is known as the no-normal-flow or nonpenetration condition. In other words, the flow must be parallel to the surface at every point on the surface. Equation (2-51) may be written as

(VVS)n=0.(2-52)

If the surface is fixed, VS = 0, and equation (2-52) becomes

Vn=0.(2-53)

For a viscous flow over a solid surface, the statement becomes even simpler: V = 0, known as the no-slip condition. If the surface is porous and there is mass flow, the values of the surface velocity must be specified as part of the problem definition. Numerical solutions of the Euler and Navier–Stokes solutions require that other boundary conditions be specified. In particular, conditions on pressure and temperature are required.

Let us next review how to compute the unit normal vector, n. Recall that to obtain the unit normal, the body is defined (in 2D) in the form F(x,y) = 0, which is the traditional analytic geometry nomenclature.

In the usual two-dimensional notation, the body shape is given by y = f(x), which is written as

F(x,y)=0=yf(x)(2-54)

and the unit normal is

n=F|F|.(2-55)

2.3.2 Boundary Conditions Away From the Surface

Conditions also must be specified away from the body. For most of the external flows, the most commonly used condition is that at large distances (approaching infinity) from the body, the flow field must approach the freestream conditions. In numerical computations, the question of the farfield boundary condition can become troublesome. How far away is infinity? Exactly how should you specify the farfield boundary condition numerically? How to best handle these issues is the basis for many papers in the literature, such as Thomas and Salas,[24] Verhoff,[25] and the survey by Colonius.[26]

Another important use of boundary conditions arises as a means of modeling physics that would be neglected otherwise. When an approximate flow field model is used, the boundary conditions frequently provide a means of including key elements of the physics in the problem without having to include the physics explicitly. The most famous example of this is the Kutta condition, wherein the viscous effects at the trailing edge can be accounted for in an inviscid calculation without treating the trailing-edge problem explicitly. Karamcheti[27] discusses boundary conditions in more detail.

2.4 Standard Forms and Terminology of Governing Equations

To understand the literature in computational aerodynamics, several other aspects of the terminology must be discussed. This section provides several of these considerations.

2.4.1 Nondimensionalization

The governing equations should be nondimensionalized. Considering fluid mechanics theory, nondimensionalization reveals important similarity parameters. In practice, many different nondimensionalizations are used, and for a particular computer program, care must be taken to understand exactly what nondimensionalization is used.

Sometimes the dimensional quantities are defined by *’s or ~’s. In other schemes, the nondimensionalized variables are designated by the special symbols. In the example given here, the nondimensionalized values are denoted by an asterisk (*). In this system, once the quantities are defined, the *’s are dropped and the nondimensionalization is understood.

Many different values can be used for nondimensionalization. We give an example here using the freestream velocity (V), flow properties (ρ, T, etc.), and a reference length, L, as follows:

x=xLy=yLz=zLt=tVLu=uVv=vVw=wVp=pρV2T=TTρ=ρρμ=μμeo=eoU2(2-56)

Each code will have a set of reference nondimensionalizations similar to these. A specific example is given in section 2.4.3. Frequently, the speed of sound is used as the reference velocity. Making sure that you understand the nondimensionalization used in a particular program is an important part of using computational aerodynamics programs to solve aerodynamic problems.

2.4.2 Use of Divergence Form of Governing Equations

The classical forms of the governing equations (shown in the preceding sections) that are normally given in textbooks are not used for computations. Instead, the divergence, or conservation, form* is preferred.

*Be careful to clearly distinguish between conservation equations and conservation forms, as the terminology can be confusing. The continuity, momentum, and energy equations are all conservation equations. “Conservation form” refers to the formulation where the variables are inside the derivatives. That’s why I prefer the use of “divergence form” to describe this mathematical arrangement. Conservation form is the more widely used terminology. They are both the same.

This form is found to be required for reliable numerical calculation. If discontinuities in the flow field exist, this form must be used to account for discontinuities correctly. It is a way to improve the capability of the differential form of the governing equations. For example, across a shock wave, the density and velocity both jump in value. However, the product of these quantities, the mass flow, is a constant. Thus we can easily see why it is better numerically to work with the product rather than the individual variables. In this section, we show how the divergence forms are obtained from the standard classical form. We use the 2D steady x-momentum equation as the example:

ρuux+ρvuy=px(2-57)

This equation is written using the following identities:

ρuux=ρuux+uρux(2-58)

or

ρuux=(ρu2)xuρux(2-59)

Similarly the second term on the left-hand side of equation (2-57) may be written as

ρvuy=ρvuy+uρvy(2-60)

or

ρvuy=ρvuyuρvy.(2-61)

Substituting (2-59) and (2-61) into (2-57), we get

ρu2xuρux+ρvuyuρvy+px=0(2-62)

which can be written as

ρu2x+ρvuyu(ρux+ρvx=0from continuity)+px=0.(2-63)

Finally, the x-momentum equation written in divergence form for 2D steady flow is given in equation (2-64).

(ρu2+p)x+(ρvu)y=0(2-64)

The equations must be written in divergence form to be valid when shock waves are present.

2.4.3 Standard Form of the Equations

Even after writing the governing equations in divergence form, the equations that you see in the literature won’t look like the ones we’ve been writing down. A standard form is used in the literature for numerical solutions of the Navier–Stokes equations. In this section, we provide one representative set used in the NASA Langley codes CFL3D and CFL3DE.[28] Professors Walters and Grossman (of Virginia Tech) and their students have made contributions to these codes. The Navier–Stokes equations (and the other equations required in the system) are written in vector divergence form as follows:

Qt+(FFv)x+(GGv)y+(HHv)z=0(2-65)

where the conserved variables are

Q={ρρuρvρwEt}={densityx- momentumy- momentumz- momentumtotal energy per unit volume}(2-66)

There are two sets of flux vectors in equation (2-65), inviscid and viscous. The inviscid flux vectors are F, G, and H in x-, y-, and z-directions, respectively, and the viscous flux vectors are Fv, Gv, and Hv in x-, y-, and z-directions, respectively.

The flux vectors in the x-direction are described in (2-67) below.

F=[ρuρu2+pρuvρuw(Et+p)u]Fv=[0τxxτxyτxzuτxx+vτxy+wτxzq˙x](2-67)

 

Similar expressions can be written down for the y- and z-direction fluxes, with the y-direction given as

G=[ρvρvuρv2+pρvw(Et+p)v]Gv=[0τyxτyyτyzuτyx+vτyy+wτyzq˙y](2-68)

and with the z-direction given as

H=[ρwρwuρwvρw2+p(Et+p)w]Hv=[0τzxτzyτzzuτzx+vτzy+wτzzq˙z].(2-69)

The equation of state (perfect gas) is written in this formulation as

p=(γ1)[Etρ(u2+v2+w2)/2].(2-70)

To complete the flow equations, we need to define (i) nondimensional variables using the freestream values of the flow properties like density, pressure, temperature, speed of sound, etc., and (ii) the shear stress and heat transfer nomenclature. In the following equations, the tilde (~) superscript denotes a dimensional quantity and the infinity (∞) subscript denotes evaluation at freestream conditions.

Equations (2-71) and (2-72) below show how nondimensional shear stress and heat transfer terms are written in indicial (or index*) notation.

*Index notation is a shorthand notation. xi denotes x, y, z for i = 1, 2, 3.

τxixj=MReL[μ(uixj+ujxi)+λukxkδij](2-71)

and

q˙xi=[MμReLPr(γ1)](a2)xi=[MμReLPr(γ1)]Txi(2-72)

The nondimensional molecular viscosity is found using Sutherland’s law:

μ=μ~/μ~=(T~T~)3/2[T~+c~T~+c~]=(T)3/2[(1+c~/T~)(T+c~/T~)](2-73)

where Sutherland’s constant (defined by the symbol c with a tilde (~) superscript) has a value of 198.6°R = 110.4°K.

Below are the definitions of the other quantities.

Reynolds number:

ReL=ρ~q~L~/μ~

Mach number:

M=q~/a~

Prandtl number:

Pr=μ~c~p/k~

Stoke’s hypothesis for bulk viscosity is used, meaning

λ+2μ/3=0

and the freestream velocity magnitude is

q~=[u~2+v~2+w~2]1/2.

The nondimensional velocity components are given by

u=u~/a~u=Mcosαcosβv=v~/a~v=Msinβw=w~/a~w=Msinαcosβ(2-74)

and the thermodynamic variables are given by

ρ=ρ~/ρ~,ρ=1p=p~/ρ~a~2,p=1/γT=T~/T~=γp/ρ=a2T=1(2-75)

Et=E~t/ρ~a~2Et=1/[γ(γ1)]+M2/2.(2-76)

This completes the nomenclature for one typical example of the application of the Navier–Stokes equations in an actual computer code, CFL3D. Note that these equations are for a Cartesian coordinate system. The general non-orthogonal curvilinear coordinate generalization is considerably more complicated.

2.5 The Gas Dynamics Equation and the Full-Potential Equation

For inviscid flow problems (and even some viscous flows), it is useful to combine the equations in a special form known as the gas dynamics equation. In particular, the gas dynamics form of the equation is used to obtain the complete or “full” nonlinear potential flow equation in section 2.5.3. Many valuable results can be obtained in computational aerodynamics using the potential flow approximation. When compressibility effects are important, a special form of the governing equation can be obtained based on the gas dynamics equation, which we derive here. The gas dynamics equation is valid for any flow assumed to be inviscid. The starting point for the derivation is the Euler equations, the continuity equation, and the equation of state.

2.5.1 The Gas Dynamics Equation

We demonstrate the derivation using two-dimensional steady flow. This is not required but is used for simplicity. Furthermore, the index notation xi is used where the index i = 1, 2, 3, denote x-, y-, z-axes, respectively. To start, we make use of a thermodynamic definition to rewrite the pressure term in the momentum equation as equation (2-77).

pxi=pρ)sρxi(2-77)

Using the definition of the speed of sound assuming isentropic or constant entropy flow,

a2=pρ)s(2-78)

allowing ∂p/∂xi to be written as

pxi=a2ρxi.(2-79)

We next write the x-momentum equation multiplied by u- and y-momentum equation multiplied by v:

u2ux+uvuy=uρpx=ua2ρρxvuvx+v2vy=vρpy=va2ρρy(2-80)

We use the continuity equation by expanding it from

ρux+ρvy=0(2-81)

to

uρx+ρux+vρy+ρvy=0(2-82)

or

uρx+vρy=ρuxρvy.(2-83)

We now add the modified x- and y-momentum equations, equation (2-80), which gives us equation (2-84) below.

u2ux+uvuy+vuvx+v2vy=ua2ρρxva2ρρy=a2ρ(uρx+vρy)(2-84)

We substitute the rewritten continuity equation, equation (2-83), into equation (2-84), resulting in

u2ux+uvuy+vuvx+v2vy=a2ρ(ρuxρvy)=a2ux+a2vy.(2-85)

Finally, we rearrange the terms in equation (2-85) to obtain the following gas dynamic equation in two dimensions:

(u2a2)ux+uv(uy+vx)+(v2a2)vy=0(2-86)

Extension to three dimensions is straightforward, creating the corresponding gas dynamic equation:

(u2a2)ux+(w2a2)wz+(v2a2)vy+uv(uy+vx)+vw(vz+wy)+wu(wx+uz)=0(2-87)

2.5.2 Derivation of the Classical Gas Dynamics-Related Energy Equation

The special form of the energy equation that is used to close the system (in two dimensions or 2D) is given below.

a2=a02(γ12)(u2+v2)(2-88)

We next show exactly how this relation is obtained. Let us start with the energy equation for inviscid, adiabatic flow expressed in the form of

DHDt=0(2-89)

where H is the total enthalpy, defined (in 2D) by

H=h+12(u2+v2).(2-90)

Equation (2-89) yields H = constant. Thus, we have a purely algebraic statement of the energy equation instead of a partial differential equation. This is an important reduction in complexity.

For a thermally and calorically perfect gas, h = cpT and cp = constant. Substituting for the enthalpy, we get equation (2-91).

cpT0=cpT+12(u2+v2)(2-91)

Recalling that a2= γRT and R = cp- cv, with γ = cp/cv, we write

a2=cpcv(cpcv)T=(cpcvcv)cpT(2-92)

or

cpT=(cvcpcv)a2=(1γ1)a2.(2-93)

Using equation (2-93), we can rewrite the total energy equation (H = constant), equation (2-91), as

a02γ1=a2γ1+12(u2+v2)(2-94)

or

a02=a2+(γ12)(u2+v2).(2-95)

The two-dimensional form shown in equation (2-88) is readily obtained by solving equation (2-95) for a. Extension to three dimensions is straightforward, and the equation in 3D is

a2=a02(γ12)(u2+v2+w2).(2-96)

2.5.3 Full Potential Equation

The gas dynamics equation is converted to the classical nonlinear potential equation when we make the irrotational flow assumption. The potential flow assumption requires that the flow be irrotational. This is valid for inviscid flow when the onset flow is uniform and there are no shock waves. However, we often continue to assume that the flow can be represented approximately by a scalar potential Φ when the Mach number normal to any shock wave is close to one (for example, Mn < 1.25). Recall that the irrotational flow assumption is stated mathematically as curl V= 0. When this is true, V can be defined as the gradient of a scalar potential, V = ∇Φ. Using the common subscript notation to represent partial derivatives, the velocity components are u = Φx ,v = Φy, and w = Φz. Using the gas dynamics equation, equation (2-87), the nonlinear or “full-potential” equation is written as

(Φx2a2)Φxx+(Φy2a2)Φyy+(Φz2a2)Φzz+2ΦxΦyΦxy+2ΦyΦzΦyz+2ΦzΦxΦzx=0.(2-97)

This is the classic form of the equation. This single nonlinear partial differential equation has been extensively used to obtain physical insights into a wide variety of flows. Note that, as written above, it is not in divergence (or conservation) form.

2.5.4 Equivalent Divergence Form and Energy Equation

The equivalent equation written in conservation form makes use of the continuity equation. This is the form that is used in most computational fluid dynamics codes. Equation (2-98) shows how it is written in two dimensions.

x(ρΦx)+y(ρΦy)=0(2-98)

The relation between ρ and the potential is given by

ρ=[1(γ1γ+1)(Φx2+Φy2)]1γ1(2-99)

which is a statement of the energy equation (see section 2.5.5). Note that the full-potential equation is still nonlinear when the density varies, and ρ must be considered a dependent variable.

2.5.5 Derivation of Another Form of the Related Energy Equation

It is informative to demonstrate the derivation of the energy equation, equation (2-99), in section 2.5.4. To get this standard form, understand the specific nondimensionalization employed with this form:

ρ=ρ~ρ0,Φx=u~a,Φy=v~a,(2-100)

where a* denotes the sonic value. Start with the previous energy equation and work with dimensional variables for the moment:

a2=a02(γ12)(u2+v2)(2-101)

or

a2a02=1(γ12)(u2+v2a02).(2-102)

Now, let us get a relation for ao in terms of the eventual nondimensionalizing velocity a*.

When the velocity is equal to the speed of sound, we can write

a02=a2+(γ12)(u2+v2)=a2.(2-103)

Since a = a* when the velocity is equal to the speed of sound, we obtain either

a02=a2+(γ12)a2=(1+γ12)a2(2-104)

or

a02=(γ+12)a2.(2-105)

Using a2 = γRT, the left-hand side of equation (2-102) becomes

(aa0)2=TT0.(2-106)

In addition, replacing ao2 with a*2 in the denominator of the last term on the right-hand side of equation (2-102), we can rewrite the energy equation, equation (2-102), as

TT0=1γ12u2+v2γ+12a2(2-107)

or

TT0=1(γ1γ+1)[(ua)2+(va)2].(2-108)

Recall that entropy, s, is constant for isentropic flows (a consistent assumption if the use of Φ is valid):

s=const(2-109)

and

pργ=const=p0ρ0γ(2-110)

Now, we introduce (~) to denote dimensional quantities and convert to the desired nondimensional form:

(p~p0)=(ρ~ρ0)γ=(T~T0)γγ1(2-111)

or

T~T0=(ρ~ρ0)γ1(2-112)

Using equation (2-112) we write the energy equation, equation (2-108), as

(ρ~ρ0)γ1=1(γ1γ+1)[(u~a)2+(v~a)2].(2-113)

Using the nondimensionalizing definition given in section 2.4.3, we finally obtain equation (2-114) below.

ρ=[1(γ1γ+1)(Φx2+Φy2)]1γ1(2-114)

This is an energy equation in ρ to use with the divergence form of the full-potential equation. It is also an example of how to get an energy equation in a typical nondimensional form used in the literature.

2.6 Special Cases

In this section, we present a number of special, simplified forms of the equations described above. These simplified equations are entirely adequate for many of the problems of computational aerodynamics, and until recently they were used nearly exclusively. The ability to obtain simpler relations that provide explicit physical insight into the flow field process has played an important role in the development of aerodynamic concepts. One key idea is the notion of small disturbance equations. The assumption is that the flow field is only slightly disturbed by the body. We expect this assumption to be valid for inviscid flows over streamlined shapes. These ideas are expressed mathematically by small perturbation or asymptotic expansion methods and are elegantly described in the book by Van Dyke.[29] Figure 2-10 summarizes the theoretical path required to obtain these equations.

2.6.1 Small Disturbance Form of the Energy Equation

The expansion of the simple algebraic statement of the energy equation provides an example of a small disturbance analysis. In this case, the square of the speed of sound (or equivalently the temperature) is linearly related to the velocity field. Start with the energy equation:

a2=a02(γ12)(u2+v2)(2-115)

and

a02=const=a2+(γ12)(u2+v2)=a2+γ12U2(2-116)

Assuming the freestream velocity, U, is aligned with the x-direction and letting the velocity components be u = U + u’ , v = v’ (where u’ and v’ are disturbance velocities in x- and y-directions, respectively), we can write equation (2-116) as 

a2=a2+γ12U2(γ12)[U2+2Uu+u2+v2].(2-117)

Combining terms, we obtain equation (2-118).

a2=a2(γ12)[2Uu+u2+v2](2-118)

At this point, the relation is still exact, but now it is written in a form that can be easily simplified. The basic idea is to take advantage of the small perturbation assumption:

u<U,v<U(2-119)

and thus,

uU<1(uU)20.(2-120)

Equation (2-120) is applicable to v’ as well. The implications of the small disturbance assumption for equation (2-118) are

a2=a2(γ12)[2Uu+u2+v2neglect as smallhenceforth].(2-121)

This is a linear relation between the disturbance velocity and the speed of sound. It is a heuristic example of the procedures used in a more formal approach known as perturbation theory.

2.6.2 Small Disturbance Expansion of the Full Potential Equation

We now use an approach similar to that in section 2.6.1 to show how to obtain a small disturbance version of the full-potential equation. Again consider the situation where we assume that the disturbance to the freestream is small. Now we examine the full-potential equation. First, we rewrite the full-potential equation, equation (2-97), in 2D for simplicity as

(Φx2a2)Φxx+2ΦxΦyΦxy+(Φy2a2)Φyy=0.(2-122)

Now write the velocity as a difference from the freestream velocity. Introduce a disturbance potential, ϕ, defined by

Φ=Ux+ϕ(x,y)Φx=u=U+ϕxΦy=v=ϕy(2-123)

where we have introduced a directional bias. The x-direction is the direction of the freestream velocity. We next assume that ϕx and ϕy are small compared to U. Using the idea of a small disturbance to the freestream, simplified (and even linear) forms of a small disturbance potential equation and an energy equation can be derived.

As an example of the expansion process, consider the first term in equation (2-122). Use the definition of the disturbance potential and the simplified energy equation as shown in equation (2-124) below.

(Φx2a2)(U+ϕx)2{a2(γ12)[2Uu]}U2+2Uϕx+ϕx2a2+γ122Uu=ϕx(2-124)

Regroup and drop the square of the disturbance velocity as small:

(Φx2a2)U2a2+2Uϕx+(γ1)UϕxU2a2+[2+(γ1)γ+1]UϕxU2a2+(γ+1)Uϕx(2-125)

Dividing by a2,

(Φx2a2a2a2)U2a21+(γ+1)UaϕxaM21+(γ+1)MUaUUϕxaϕxU(M21)+(γ+1)M2(ϕxU)(2-126)

Rewrite the potential equation, equation (2-122), by first dividing by a2 and then replacing the coefficient of the first term using equation (2-126):

(Φx2a2a2a2)[(M21)+(γ+1)M2(ϕxU)]Φxx+2ΦxaΦyaΦxy+(Φy2a2a2a2)Φyy=0(2-127)

Now, by definition,

Φxx=ϕxx,Φyy=ϕyy,Φxy=ϕxy(2-128)

while

Φxa=M(1+ϕxU),Φya=MϕyU.(2-129)

Using the same approach demonstrated above, we can write

(Φy2a2a2a2)1+(γ1)M2(ϕyU).(2-130)

 

Putting these relations all into the potential equation, we obtain

[M21+(γ+1)M2ϕxU]ϕxx+2M2(1+ϕxU)ϕyUϕxy+[1+(γ1)M2ϕyU]ϕyy=0(2-131)

where the ϕx2, ϕy2 terms are neglected in the coefficients. This equation is still nonlinear but is in a form ready for further simplifications described below.

2.6.3 Transonic Small Disturbance Equation

Transonic flows contain regions with both subsonic and supersonic flows. Any equation describing this flow must simulate the correct physics in the two different flow regimes. As we show below, this makes the problem difficult to solve numerically. Indeed, the numerical solution of transonic flows was one of the primary thrusts of research in CFD over the decades of the ’70s and ’80s. A small disturbance equation can be derived that captures the essential nonlinearity of transonic flow, which is the rapid streamwise variation of flow disturbances in the x-direction, including normal shock waves. Therefore, in transonic flows, we assume

x>y.(2-132)

The transonic small disturbance equation retains the key term in the convective derivative, u(∂u/∂x), which allows the shock to occur in the solution. Retaining this key nonlinear term, the small disturbance equation given above becomes

[(1M2)(γ+1)M2ϕxU]ϕxx+ϕyy=0.(2-133)

Using the definition of the potential from equation (2-123), we can identify the nonlinear term, u(∂u/∂x), which appears as the product of the second term in the bracket, u = ϕx , and the ϕxx term, which is ∂u/∂x.

This is one version of the transonic small disturbance equation. It is still nonlinear and can change mathematical type (to be discussed in section 2.8). This means that the sign of the coefficient of ϕxx can change in the flow field, depending on the value of the nonlinear term. It is valid for transonic flow, and as written, it is not in a divergence form. Transonic flows occur for Mach numbers from 0.6 to 1.2, depending on the degree of flow disturbance. They also occur under other circumstances. At high-lift conditions, the flow around the leading edge may become locally supersonic at freestream Mach numbers as low as 0.20 or 0.25. Transonic flow occurs on rotor blades and propellers. At hypersonic speeds, the flow between the bow shock and the body will frequently be locally subsonic. These are also transonic flows. The transonic small disturbance equation can be numerically solved on your personal computer.

2.6.4 Prandtl–Glauert Equation

When the flow field is entirely subsonic or supersonic, all terms involving products of small quantities can be neglected in the small disturbance equation. When this is done, we obtain the Prandtl–Glauert equation:

(1M2)ϕxx+ϕyy=0(2-134)

This is a linear equation valid for small disturbance flows that are either entirely supersonic or subsonic. For subsonic flows, this equation can be transformed to Laplace’s equation, while at supersonic speeds, this equation takes the form of a wave equation. The difference is important, as described below in the section on the mathematical type of partial differential equations (PDEs). This equation requires that the onset flow be in the x-direction, an example of the importance that coordinate systems assume when simplifying assumptions are made. Thus, use of simplifying assumptions introduced a directional bias into the resulting approximate equation.

The extension to three dimensions is shown in equation (2-135).

(1M2)ϕxx+ϕyy+ϕzz=0(2-135)

2.6.5 Incompressible, Irrotational Flow: Laplace’s Equation

Assuming that the flow is incompressible, ρ is a constant and can be removed from the modified continuity equation, equation (2-98), given above. Alternately, divide the full-potential equation by the speed of sound, a2, and take the limit as a goes to infinity. Either way, the following equation is obtained:

Φxx+Φyy=0(2-136)

This is Laplace’s equation. Frequently people call this equation the potential equation. For that reason, the complete potential equation, equation (2-97), is known as the full-potential equation. Do not confuse the true potential flow equation with Laplace’s equation, which requires the assumption of incompressible flow. When the flow is incompressible, this equation is exact when using the inviscid irrotational flow model and does not require the assumption of small disturbances.

2.6.6 The Boundary Layer Equations

The last special case retains a viscous term, while assuming that the pressure is a known function and independent of the y-coordinate value. These are Prandtl’s boundary layer equations that describe the flow immediately adjacent to the body surface. In a 2D, steady flow context, the boundary layer equations are detailed below.

ρux+ρvy=0(2-137)

ρuux+ρvuy=px+y(μuy)(2-138)

0=py(2-139)

The related energy equation must also be included if compressibility effects are important.

All the equations presented in this section provide physical models of classes of flows that, under the right circumstances, are completely adequate to obtain an accurate representation of the flow. Many, many other approximate flow models have been proposed. Those presented in this section represent by far the majority of methods currently used. Numerous versions of the Navier–Stokes equations (taken here to include the time-averaged Reynolds equations) have also been used. These equations are discussed as appropriate in subsequent chapters. Figure 2-10 summarizes the connection between the mathematical models of various types of flow fields.

All flowfield models begin with general governing equations including: Navier-Stokes equations, Newtonian fluid equations, compressibility, viscosity, unsteady flow equations, and heat-conducting equations. Two branches exist for further analysis. The branch on the left assumes inviscid flow, leading to Euler's Equations. Additional assumptions can then be made, including: dropping body force terms, usage of the divergence form, and eventually Irrotational flow where velocity cap V is equal to the gradient of the flow potential cap Phi. From there, one can use the gas dynamics equations in either the Full Potential Equations form or a reduced form. If the flow is assumed to be incompressible, you get Laplace's Equations, including integral equation representation. If small disturbances approximation is used, you instead get P G and T S D E Equations with sub, super, and transition included. Returning to the Navier Stokes Equations, if turbulence is instead included via Reynolds averaging and other turbulence modeling, you instead get the Reynolds Equations, sometimes referred to as Navier Stokes or N S. Restricting the viscous effects to gradients normal to the body's directional bias results in the Thin Layer N S equations. Introducing Prandtl Boundary Layer assumptions of constant pressure across a layer and only including the leading viscous terms results in the boundary layer equations.
Figure 2-10: Connection between various approximations to the Navier–Stokes equations. From W. H. Mason. Adapted by P. Raj.

2.7 Examples of Zones of Application

The appropriate version of the governing equation depends on the type of flow field being investigated. For high Reynolds number attached flow, the pressure can be obtained very accurately without considering viscosity. Recall that the use of a Kutta condition provides a simple way of enforcing key physics associated with viscosity by specifying this feature as a boundary condition on an otherwise inviscid solution. If the onset flow is uniform and any shocks are weak (characterized by Mach number normal to the shock, Mn, to be < 1.25 or 1.3), then the potential flow approximation is valid. If a slight flow separation exists, a special approach using the boundary layer equations can be used interactively with the inviscid solution to obtain a solution. As speed increases, shocks begin to get strong and are curved. Under these circumstances, the solution of the complete Euler equations is required.

When significant separation occurs or when you cannot figure out the preferred direction to apply a boundary layer approach, the Navier–Stokes equations are used. Note that many different “levels” of the N–S equations are in use.

To avoid having many different codes, some people would like to have just one code that does everything. While this may be a worthy goal, most applications are more effective using a variety of methods. A step in the right direction is the use of a system that employs a common geometry and grid processing system and a common output/graphics systems.

2.8 Mathematical Classification of Partial Differential Equations (PDEs)

A key property of any system of PDEs is the “type” of the equations. In mathematics, an equation type has a very precise meaning. Essentially, the type of the equation determines the domain on which boundary or initial conditions must be specified. The mathematical theory has been developed over a number of years for PDEs and is given in books on PDEs. Two examples include Sneddon[30] (pp. 105–109) and Chester[31] (Chapter 6). Discussions from the computational fluid dynamics viewpoint are available in Tannehill, Anderson, and Pletcher,[32] (Chapter 2), Fletcher[33] (Chapter 2), and Hoffman[34] (Chapter 1).

To successfully obtain the numerical solution of a PDE, you must satisfy the “spirit” of the theory for the type of a PDE. Usually the theory has been developed for model problems, frequently linear. For PDEs describing physical systems, the type will be related to the following categorization:

  1. Equilibrium problems. Examples include steady-state temperature distributions and steady incompressible flow. These are similar to boundary value problems for ordinary differential equations (ODEs).
  2. Marching or propagation problems. These are transient or transient-like problems. Examples include transient heat conduction and steady supersonic flow. These are similar to initial value problems for ODEs.

The three types of PDEs are elliptic, parabolic, and hyperbolic. A linear equation will be of one type. The nonlinear equations of fluid flow can change type locally depending on the local values of the variables. This “mixed-type” feature has had a profound influence on the development of methods for computational aerodynamics. A mismatch between the type of the PDE and the prescribed boundary conditions dooms any attempt at numerical solution.

The standard mathematical illustration of PDE type uses a second-order PDE:

Aϕxx+Bϕxy+Cϕyy+Dϕx+Eϕy+Fϕ+G=0(2-140)

where A, B, C, D, E, F, and G can be constants or functions of x, y, and ϕ. Depending on the values of A, B, and C, the PDE will be of different type. The specific type of the PDE depends on the characteristics of the PDE. One of the important properties of characteristics is that the second derivative of the dependent variables are allowed, although there can be no discontinuity of the first derivative. The slopes of the characteristics can be found from A, B, and C. From mathematical theory, the characteristics are found depending on the sign of determinant as shown in table 2-3.

Sign of determinant Characteristics Type
(B2 - 4AC) > 0 real hyperbolic
(B2 - 4AC) = 0 real, equal parabolic
(B2 - 4AC) < 0 imaginary elliptic

Table 2-3: Sign of the determinant classifies the type of governing PDE

2.8.1 Hyperbolic

The basic property is a limited domain of dependence. Initial data are required on a curve or a plane, which does not coincide with a characteristic curve. Figure 2-11 illustrates this requirement.

For a hyperbolic system, the initial data plane forms a wider wedge ahead of the characteristics, which form a narrower wedge inside of the inidial data plane. The both intersect at the vertex of the two wedges.
Figure 2-11: Connection between characteristics and initial condition data planes. From W. H. Mason. Adapted by S. Madden.

Classical linearized supersonic aerodynamic theory is an example of a hyperbolic system.

2.8.2 Parabolic

This is associated with a diffusion process. Data must be specified at an initial plane, marching forward in a time or time-like direction. There is no limited region of influence equivalent to the hyperbolic case. Data are required on the entire time-like surface. Figure 2-12 illustrates the requirement.

For a parabolic equation, the initial data set is a vertical line from which time t advances normal to it.
Figure 2-12: Initial data plane for parabolic equation. From W. H. Mason. Adapted by S. Madden.

In aerodynamics, boundary layers have a parabolic type.

2.8.3 Elliptic

These are equilibrium problems. They require boundary conditions everywhere, as shown in figure 2-13. Incompressible potential flow is an example of a governing equation of elliptic type. The region of influence and the zone of dependence are the same.

The boundary layer conditions apply to the outer surface of an elliptical object contained within a flow field, whose boundary conditions are required to be completely around the area in question and an infinite distance away.
Figure 2-13: Boundary conditions required for elliptic PDEs. From W. H. Mason. Adapted by S. Madden.

Consider the following examples. For the Prandtl–Glauert equation,

(1M2)ϕxx+ϕyy=0(2-141)

and

M<1ellipticM>1hyperbolic.(2-142)

For the transonic small disturbance equation,

(1M2)ϕxx+ϕyy=0.(2-143)

This is an equation of mixed type. It is required to treat the physics of transonic flows.

Type plays a key role in computational approaches. The type can be used to advantage. In the case of the Euler equations, the steady state Euler equations are hard to solve. It is standard procedure to consider the unsteady case, which is hyperbolic, and to obtain the steady state solution by marching in time until the solution does not change in time.

Alternate approaches are available for systems of first-order PDEs. Classification is sometimes difficult to determine. The type of an equation is determined with respect to a particular variable. The type of equations with respect to time may be completely different than their type with respect to space. The type of the equation often helps to define the appropriate solution coordinate system. The different types of the equations given above are responsible for the distinct numerical approaches that are adopted to solve different problems.

2.8.4 Elaboration on Characteristics

This section provides additional details that offer some insight into why the determinant of the coefficients of the second derivative terms define the type of the equation.

Consider equation (2-144) below.

Aϕxx+Bϕxy+Cϕyy+Dϕx+Eϕy+Fϕ+G=0(2-144)

  • Assume ϕ is a solution describing a curve in space.
  • These curves “patch” various solutions, known as characteristic curves.
  • Discontinuity of the second derivative of the dependent variable is allowed but no discontinuity of the first derivative.

The differentials of ϕx and ϕy that represent changes from x, y to x + dx, y + dy along characteristics are

dϕx=ϕxxdx+ϕxydy=ϕxxdx+ϕxydy(2-145)

and

dϕy=ϕyxdx+ϕyydy=ϕyxdx+ϕyydy.(2-146)

Express equation (2-144) as

Aϕxx+Bϕxy+Cϕyy=H(2-147)

with

H=(Dϕx+Eϕy+Fϕ+G).(2-148)

Assume equation (2-147) is linear. Solve it together with equations (2-145) and (2-146) for second derivatives of ϕ:

Aϕxx+Bϕxy+Cϕyy=Hdxϕxx+dyϕxy=dϕxdxϕxy+dyϕyy=dϕy(2-149)

or

[ABCdxdy00dxdy][ϕxxϕxyϕyy]=[Hdϕxdϕy](2-150)

and solve for ϕxx, ϕxy, ϕyy. Since second derivatives can be discontinuous on the characteristics, the derivatives are indeterminate and the coefficient matrix would be singular:

[ABCdxdy00dxdy]=0(2-151)

This expands into

A(dy)2Bdxdy+C(dx)2=0,(2-152)

and the slopes of the characteristics curves are found by dividing by (dx)2:

A(dydx)2B(dydx)+C=0.(2-153)

Solve for dy/dx.

dydx|α,β=B±B24AC2A(2-154)

Hence the requirement on (B2 - 4AC) shown in table 2-3 and discussed above to define the type of the PDE as related to the characteristics of the equation. See the references cited above for more details.

2.9 Requirements for a Complete Problem Formulation

When formulating a mathematical representation of a fluid flow problem, you have to carefully consider both the flow field model equations and the boundary conditions. An evaluation of the mathematical type of the PDEs that are being solved plays a key role in this. Boundary conditions must be properly specified. Either over- or under-specifying boundary conditions will doom your calculation before you start. A proper formulation requires:

  • Governing equations
  • Boundary conditions
  • Coordinate system specification

This is all necessary before even computing the first number! If this is done, then the mathematical problem being solved is considered to be well posed.

Chapter 2 Exercises

2.1    Convert the unsteady 3D Euler equations from classical nonconservative form to divergence form.

2.2    Equation (2-70) is an unusual form of the equation of state. It is from presentation slides defining the equations used in CFL3D.

Turn in your derivation of this equation. Is there a typo?

2.3    Show how equation (2-76) can be obtained.

2.4    Why is equation (2-97) not in divergence form?

2.5    Show that point source and point vortex singularities are solutions of Laplace’s equation in two dimensions.

Recall that a point source can be expressed as

ϕ(x,y)=q4πln(x2+y2)

and a point vortex as

ϕ(x,y)=Γ2πtan1(yx).

2.6    Consider the point source of problem 2.5.

What is the behavior of the velocity as the distance from the source becomes large?

What is the potential function for a point source?

How does it behave as the distance from the source becomes large?

Comment from the standpoint of having to satisfy the “infinity” boundary condition in a program for a potential flow solution.

2.7    Find the classification type of the following equations:

Laplace equation: Uxx + Uyy = 0

Heat equation : Uy = σ Uxx,       σ real

Wave equation:  Uxx = c2Uyy,      c real

Figure References

Figure 2-1: W. H. Mason. Adapted by S. Madden. CC BY-NC-SA 4.0

Figure 2-2: W. H. Mason. Adapted by S. Madden. CC BY-NC-SA 4.0

Figure 2-4: W. H. Mason. Adapted by S. Madden. CC BY-NC-SA 4.0

Figure 2-5: W. H. Mason. Adapted by S. Madden. CC BY-NC-SA 4.0

Figure 2-8: W. H. Mason. Adapted by S. Madden. CC BY-NC-SA 4.0

Figure 2-10: W. H. Mason. Adapted by P. Raj. CC BY-NC-SA 4.0

Figure 2-11: W. H. Mason. Adapted by S. Madden. CC BY-NC-SA 4.0

Figure 2-12: W. H. Mason. Adapted by S. Madden. CC BY-NC-SA 4.0

Figure 2-13: W. H. Mason. Adapted by S. Madden. CC BY-NC-SA 4.0


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