The discipline of Aircraft Flight Mechanics requires the formulation of relationships between aircraft forces, and aircraft motion. In order to define motion, it was necessary to define the different airspeeds in the preceding section.
Aircraft have six degrees of freedom - three translational (\(x, y, z\)), and three rotational (\(\phi, \theta, \psi\)), and in order to develop the expressions describing aircraft flight, nine coupled equations are required. This course will get to that point, and those equations will derived and utilised - but before that, some really handy relationships can be defined for flight constrained to a single direction.
The simplest flight regime is best to start with, which is steady, level (meaning no change in altitude) flight.
The definition of forces on the aircraft can change depending on the purpose - and it is only be convention that we define lift and drag in the directions we do.
The semantics notwithstanding, it is traditional to define four mutually-orthogonal forces - see Equilibrium Forces.
For this regime, it is further assumed that the aerodynamic incidence is small, and that the thrust offset is negligible. Therefore we assume that lift and weight are perpendicular to aircraft motion, and that thrust and drag are parallel to aircraft motion.
Vertical Forces¶
Looking at the vertical forces, \(\sum F_z =0\), therefore \(L=W\):
\[C_L = \frac{L}{\tfrac{1}{2}\rho V^2S}\]
\[ = \frac{W}{\tfrac{1}{2}\rho V^2S}\]
rearranging to find flight speed:
(5)¶\[V = \sqrt{\frac{\frac{W}{S}}{\tfrac{1}{2}\rho C_L}}\]
Equation (5) is the Aircraft Speed Equation for steady level flight, and some basic aerodynamic behaviour may be inferred from it:
Slower flight is possible by reducing wing loading - reducing aircraft mass, or increasing wing area. Or by increasing \(C_L\) - increasing \(\alpha\)
The minimum possible flight speed occurs at \(C_{L_{max}}\) - just before stall
Flight speed may be increased by reducing \(\rho\) - by flying at increased altitude
Stall speed¶
From (5), the stall speed may be determined if \(C_{L_{max}}\) is known.
Longitudinal Forces¶
Looking at the longitudinal forces, \(\sum F_x =0\), therefore \(T=D\):
\[\begin{split}\begin{aligned} C_D &= \frac{D}{\tfrac{1}{2}\rho V^2S}\nonumber\\ &= \frac{T}{\tfrac{1}{2}\rho V^2S}\nonumber\end{aligned}\end{split}\]
Drag estimation is complex, and can be performed via a variety of means from datasheets, CFD, wind tunnel testing or - more commonly - a combination of all. A good breakdown of drag sources is given by MacCormick[Mac95], and a reproduction of the breakdown given is found in the dropdown below - but this is far beyond the complexity required for Aircraft Performance.
Drag Breakdown (well beyond what we need, but included for reference)
The following is an extract from MacCormick[Mac95] [pp. 162-163]:
Induced Drag The drag that results from the generation of a trailing vortex system downstream of a lifting surface of finite aspect ratio.
Parasite Drag The total drag of an airplane minus the induced drag. Thus, it is the drag not directly associated with the production of lift. The parasite drag is composed of many drag components, the definitions of which follow.
Skin Friction Drag The drag on a body resulting from viscous shearing stresses over its wetted surface.
Form Drag (Sometimes Called Pressure Drag) The drag on a body resulting from the integrated effect of the static pressure acting normal to its surface resolved in the drag direction.
Interference Drag The increment in drag resulting from bringing two bodies in proximity to each other. For example, the total drag of a wing-fuselage combination will usually be greater than the sum of the wing drag and fuselage drag independent of each other.
Trim Drag The increment in drag resulting from the aerodynamic forces required to trim the airplane about its center of gravity. Usually this takes the form of added induced and form drag on the horizontal tail.
Profile Drag Usually taken to mean the total of the skin friction drag and form drag for a two-dimensional airfoil section.
Cooling Drag The drag resulting from the momentum lost by the air that passes through the power plant installation for purposes of cooling the engine, oil, and accessories.
Base Drag The specific contribution to the pressure drag attributed to the blunt after-end of a body.
Wave Drag Limited to supersonic flow, this drag is a pressure drag resulting from non-canceling static pressure components to either side of a shock wave acting on the surface of the body from which the wave is emanating.
In flight performance, we assume that the aircraft is operating in the region of linear aerodynamics, and utilise a drag model as given by Equation (6):
(6)¶\[\begin{split} \underbrace{C_D}_{\text{Total Drag}} = \underbrace{C_{D0}}_{\substack{\text{Zero incidence} \\ \text{drag}}} + \underbrace{K\cdot C_L^2}_{\substack{\text{Induced Drag +} \\ \text{$\alpha$-dependent form drag}}}\end{split}\]
where
\[ K=\frac{k}{\pi AR} = \frac{1}{\pi\,e_0\,AR}\]
The first term represents the drag that is independent of aerodynamic incidence, whilst the second term is proportional to \(C_L^2\), which represents the induced drag and the component of form drag that varies with incidence.
The parameter \(k\sim 1.1-1.4\) for most aircraft, and \(AR\) is the wing aspect ratio \(AR = \frac{b^2}{S}\). \(K\), \(C_{D0}\) usually assumed constant, but can depend on:
configuration changes (flap deployment)
Reynolds Number (speed and height)
Compressibility (shock waves)
Or sometimes can be presented as the Oswold efficiency factor, \(e_0\), which can be related to \(K\) through the aspect ratio.
Equation (6) assumes that the minimum drag occurs at zero lift. This is the case for a symmetric aerofoil, but not for a cambered one. Since most airfcraft have a cambered wing, Equation (6) should be modified to
\[C_D = C_{D, min} + K\left(C_L - C_{L0}\right)^2\]
The second equation is more realistic for real aircraft - but adds complexity to the algebra, and the difference between \(C_{D0}\) and \(C_{D,min}\) is very small even for wings of moderate camber[And99]. For simplicity, Equation (6) will be used in development of the Aircraft Performance Equations.
Equation (5) and Equation (6) underpin the basics of aircraft performance.
Drag Polar¶
The relationship between lift and drag is given through the aircraft drag polar - often plotted as \(C_L\) vs \(C_D\). Values for \(C_L\) and \(C_D\) are commonplace in the literature - a quick search yielded data for the Cessna 172S [Hab16].
You will see that the drag model works well for low values of lift - that is, in the linear aerodynamic region. The behaviour at the ‘bottom’ of the curve is sometimes called the ‘drag bucket’ - and I spent many years collecting these data in a wind tunnel.
The drag polar shows the aerodynamic efficiency of a given aircraft - that is, it represents the lift-to-drag ratio. You can find the best (highest) lift to drag ratio as the tangent of a line drawn from the origin to the curve.
It would be great to be able to find the best lift to drag ratio without having to draw the drag polar. If you looka the source code for the image below, then it’s obvious that I haven’t drawn the tangent to find the best lift to drag ratio - rather I have drawn the tangent after having found the best lift to drag ratio.
Expand the code to see the source data and coefficients used in the drag model.
# Aircraft Drag polarimport numpy as npimport matplotlib.pyplot as plt# Data for this graph has been taken from here: # https://www.researchgate.net/figure/Figure-A10-Drag-polar-for-the-Cessna-172S-This-plot-is-created-for-NACA-2412-airfoil_fig25_328578766# Discrete points:Cd = np.array([0.033099, 0.035185, 0.035214, 0.041961, 0.051143,\0.064192, 0.080106, 0.096683, 0.104613, 0.11364, 0.121425, 0.130259, 0.138232])Cl = np.array([0.1454, -0.09219, 0.38303, 0.6238, 0.86305, 1.09772,\1.31082, 1.45757, 1.51784, 1.55342, 1.58437, 1.60452, 1.58455])a = np.asarray([Cl, Cd])np.savetxt("CessnaDragPolar.csv", a.transpose(), delimiter=",", header="Cl, Cd")plt.plot(Cd, Cl, 'x', label='Data')# Put the drag model on topClvector = np.linspace(min(Cl) - .2, max(Cl) + .2, int(1e3))Cd0 = 0.033Cl0 = 0.14K = 0.035Cdvector = Cd0 + K*(Clvector - Cl0)**2plt.plot(Cdvector, Clvector, '-r', label="Drag Model")plt.legendplt.xlabel('$C_D$')plt.ylabel('$C_L$')plt.title('Drag Polar: Data vs. Drag Model');# Determine minimum dragClmind = np.sqrt(Cd0/K + Cl0**2)Cdmind = Cd0 + K*(Clmind - Cl0)**2# plot itplt.plot(Cdmind, Clmind, 'ob', label="$\\frac{L}{D}_{max}$")# show that this is the tangentplt.plot([0, Cdmind*2], [0, Clmind*2], '-b', label="Tangent")plt.gca().set_xlim(0, .14);plt.gca().set_ylim(-.5, 2);plt.gca().grid('on')plt.axhline(0, color='black');# Legendplt.legend();
Best lift to drag ratio¶
The highest lift to drag ratio gives the position of best aerodynamic efficiency, and sets the best glide ratio for an aircraft.
In the following, the values of \(C_L\) and \(C_D\) for optimum aerodynamic efficiency - but before diving into the mathematics, some consideration of their significance might be necessary for some readers.
Why do we want to know \(C_L\)?
In the aviation world, pilots tend to be excellent at intuiting flight physics - and being able to relate control movement to aircraft flight, without needed to understand the physics (often in spite of thinking they do).
By contrast, aerospace engineers tend to be be excellent and understanding the mathematics of flight physics - without any consideration of the physical significance of what they are actually deriving. By way of an example ask yourself - ‘what control would you change to effect an altitude change?’, and if your answer is simply ‘pull the stick/yoke back’, then this highlights a misunderstanding of the aircraft controls and physics. In reality, it would be a combination of throttle and stick, but fundamentally you need to gain potential energy which requires an increase in energy from somewhere, i.e., the engine.
Back to the problem at hand:
Consider what “to fly at a \(C_L=X\)” actually means - the pilot controls the pitch of the aircraft using fore-aft motion of the stick/yoke. A change in pitch changes the angle of attack of the aircraft, which changes the aircraft lift coefficient.
In reality, a pilot will not tend to consider the numerical value of \(\alpha\) they are flying at - and they are even less likely to know the \(C_L\) of the aircraft under a given flight regime.
For a given \(C_L\), the aircraft speed determines the dimensional value of lift being produced. If \(L=W\), this is steady level flight. If \(L>W\), the aircraft climbs, if \(L<W\), the aircraft descends.
Through a combination of throttle setting, and elevator deflection (stick fore/aft), steady flight can be achieved. Again - the pilot probably isn’t considering the \(C_L\) value, and won’t know whether they’re at the best lift to drag ratio or not.
So - there is a certain speed, in EAS, that will give the best lift to drag ratio. If the pilot is able to maintain this speed with no throttle adjustment, and finds that the aircraft is not climbing nor descending, then they are flying at the best lift to drag ratio - which will give the best endurance.
These speeds are usually listed in the aircraft (though in the light aircraft I’ve been in, they’re listed in IAS, and the following questions about EAS fell on deaf ears).
So we, as aerospace engineers, wish to know the lift coefficient for optimum aerodynamic efficiency - but it will be translated into a more pilot-friendly parameter, such as a post-it note on the airspeed indicator.
The best lift to drag ratio can be determined from Equation (6). Consider that the lift to drag ratio is equal in dimensional and coefficient form:
\[\frac{L}{D}=\frac{C_L}{C_D}\]
Into which Equation (6) may be inserted
\[\frac{L}{D}=\frac{C_L}{C_{D0} + K\cdot C_L^2}\]
The best lift to drag ratio can then be found from minimising \(\frac{D}{L}\), so differentiate by \(C_L\):
\[\left.\frac{D}{L}\right|_{min}=\left.\frac{C_{D0} + K\cdot C_L^2}{C_L}\right|_{min}\]
A bit of elementary calculus gives the minima of the right hand side as given by
\[C_{L, md}=\sqrt{\frac{C_{D0}}{K}}\]
What about a real aircraft?
Remember that Equation (6) as used above is only valid for an uncambered wing - the expression for \(C_{L, md}\) changes in that case. If you look at the source code for the drag polar, you can see what it changes to. Try to derive this yourself.
Thrust required¶
The drag equation can be multiplied by the numerator of the lift and drag coefficients, \(\frac{1}{2}\rho\,V^2S\), to yield dimensional drag - this can be considered as the thrust required in order to fly at a certain speed:
\[ C_D\cdot \frac{1}{2}\rho\,V^2S = C_{D0}\cdot\frac{1}{2}\rho\,V^2S + K\cdot C_L^2\cdot\frac{1}{2}\rho\,V^2S\]
In steady level flight, \(L=W\), so the lift coefficient can be expressed as
\[C_L = \frac{W}{\frac{1}{2}\rho\,V^2S}\]
and hence
\[D = C_{D0}\frac{1}{2}\rho\,V^2S + \frac{K\,W^2}{\frac{1}{2}\rho\,V^2S}\]
or
\[D = A\,V^2 + B\,V^{-2}\]
where \(A\) and \(B\) are functions of density (and therefore functions of altitude).
\(A=C_{D0}\frac{1}{2}\rho S\) represents the profile drag, which gets larger with forward speed squared
\(B=\frac{K\,W^2}{\frac{1}{2}\rho S}\) represents the induced drag, which gets smaller with forward speed squared
The above should make sense to you intuitively. Profile drag is largely viscous drag, which will get larger in proportion to the dynamic pressure. The induced drag is proportional to the bound vortex maintaining lift, which will be proportional to \(C_L\) which, for a steady flight, is inversely proportional to the dynamic pressure.
Minimum drag speed¶
From the drag equation in dimensional form, the minmum drag speed can be shown
\[D = A\,V^2 + B\,V^{-2}\]
\[\frac{\text{d} D}{\text{d} V} = 2\cdot A\,V - 2 B\,V^{-3}\]
\[\implies V_{md} = \left[\frac{B}{A}\right]^{\frac{1}{4}}\]
\[=\left[\frac{2\,W}{\rho\,S}\right]^{\frac{1}{2}}\left[\frac{K}{C_{D0}}\right]^{\frac{1}{4}}\]
Alternative method
It has already been shown that the lift at minimum drag is \(C_{L, md}=\sqrt{\frac{C_{D0}}{K}}\). Substitute this into the aircraft speed equation to show the same answer as above
For a set of parameters, the drag equation can be plotted from the aircraft stall speed. You can zoom in on the plot, or expand the source to see how the plot was made.
import plotly.io as pioimport plotly.express as pximport plotly.offline as pyimport plotly.graph_objects as gofrom ambiance import Atmosphereimport numpy as np# Define constantsCD0=0.016 # Zero incidence dragK=0.045 # Induced drag factorS=50 # Wing area, m^2W=160e3 # Aircarft weight, NewtonsClmax = 1.5alt=0; # Altitudemosphere = Atmosphere(alt*1000)rho = mosphere.density# Determine stall speedVstall = np.sqrt(W / (0.5 * rho * S * Clmax))# Determine A and BA = CD0 * 0.5 * rho * SB = K * W ** 2 / 0.5 / rho / S# Flight speed vectorVs = np.linspace(Vstall[0], 200, 1000)# Define dragsDind = B * Vs**-2Dprof = A * Vs**2D = Dind + Dprof# Get minimum dragVmd = (B/A)**.25md = A * Vmd**2 + B * Vmd**-2fig = go.Figure()fig.add_trace(go.Scatter(x=Vs, y=Dind, name="Induced Drag"))fig.add_trace(go.Scatter(x=Vs, y=Dprof, name="Profile Drag"))fig.add_trace(go.Scatter(x=Vs, y=D, name="Total Drag"))fig.add_trace(go.Scatter(x=Vmd, y=md, mode="markers+text", text="Minimum Drag", textposition="top center", name="Annotation"))fig.update_layout( title=f"Variation of Profile, Induced, and Total Drag - CD0 = {CD0}, K={K}, altitude={alt}km, S={S}m^2, W={W/1e3}", xaxis_title="TAS / (m/s)", yaxis_title="Drag / N", legend_title="Drag Breakdown",)for trace in fig['data']: if(trace['name'] == "Annotation"): trace['showlegend'] = Falsefig.update_xaxes(range=[0, 200])fig.update_yaxes(range=[0, 20e3])
Variation of drag with altitude¶
With the drag equation presented in dimensional form the effect of altitude on drag may be determined. Since \(A\) and \(B\) are directly and inversely proportional to density, it can be expected that they will be inversely, and directly proportional to altitude, respectively.
That is - for an increase in altitude, \(A\) (profile drag) will decrease whilst \(B\) (induced drag) will increase.
Think: does that make sense?
Whenever you derive a relationship between physical parameters, you should see if the answer is intuitively correct.
Profile drag is fundamentally a viscous effect, so it makes sense that for fewer air particles in a given volume, the profile drag would decrease.
Induced drag is proportional to the amount of circulation. For a reduction in density, a larger amount of circulation is required to effect the same dimensional value of lift. Hence, induced drag will increase.
It has been shown above that \(V_{md}\propto\frac{1}{\sqrt{\rho}}\) (see Minimum drag speed), so these cancel with the density terms in the \(A\) and \(B\) expressions - accordingly, the minimum drag remains constant with altitude whilst the minimum drag speed increases. See:
fig = go.Figure()fig.update_xaxes(range=[0, 300])fig.update_yaxes(range=[0, 20e3])for alt in [0, 5000, 15000]: mosphere = Atmosphere(alt) rho = mosphere.density # Determine stall speed Vstall = np.sqrt(W / (0.5 * rho * S * Clmax)) # Determine A and B A = CD0 * 0.5 * rho * S B = K * W ** 2 / 0.5 / rho / S # Flight speed vector Vs = np.linspace(Vstall[0], 340, 1000) # Define drags Dind = B * Vs**-2 Dprof = A * Vs**2 D = Dind + Dprof # Get minimum drag Vmd = (B/A)**.25 md = A * Vmd**2 + B * Vmd**-2 fig.add_trace(go.Scatter(x=Vs, y=D, name=f"Total Drag: {alt/1e3:1.0f}km")) fig.add_trace(go.Scatter(x=Vmd, y=md, mode="markers+text",\ text=f"{Vmd[0]:1.0f} m/s ",\ textposition="bottom center", name="Annotation")) fig.update_layout( title=f"Total drag variation with altitude - CD0 = {CD0}, K={K}, S={S}m^2, W={W/1e3}", xaxis_title="TAS / (m/s)", yaxis_title="Drag / N", legend_title="Altitude", ) fig.add_trace(go.Scatter(x=np.linspace(0, 300, 1000), y=md*np.ones(1000), name="Constant Minimum Drag", connectgaps=True)) for trace in fig['data']: if(trace['name'] == "Annotation"): trace['showlegend'] = False fig.show()
Variation of drag with aircraft weight¶
By contrast to the density, the aircraft weight only appears in the induced drag term, \(B=\frac{K\,W^2}{\frac{1}{2}\rho S}\), and hence the profile drag stays constant whilst the induced drag increases with aircraft weight.
This makes sense as the wetted area of the aircraft is unchanged, hence the viscous drag would be constant. The dimensional value of lift is increased, therefore the cruise \(C_L\) is also increased, and the circulation must be increased hence the trailing vortex system is given more energy - more drag.
fig = go.Figure()fig.update_xaxes(range=[0, 300])fig.update_yaxes(range=[0, 20e3])alt = 0for W in [160e3, 200e3, 300e3]: mosphere = Atmosphere(alt) rho = mosphere.density # Determine stall speed Vstall = np.sqrt(W / (0.5 * rho * S * Clmax)) # Determine A and B A = CD0 * 0.5 * rho * S B = K * W ** 2 / 0.5 / rho / S # Flight speed vector Vs = np.linspace(Vstall[0], 340, 1000) # Define drags Dind = B * Vs**-2 Dprof = A * Vs**2 D = Dind + Dprof # Get minimum drag Vmd = (B/A)**.25 md = A * Vmd**2 + B * Vmd**-2 fig.add_trace(go.Scatter(x=Vs, y=D, name=f"Total Drag: W={W/1e3:1.0f}kN")) fig.add_trace(go.Scatter(x=Vmd, y=md, mode="markers+text",\ text=f"{Vmd[0]:1.0f} m/s ",\ textposition="bottom center", name="Annotation")) fig.update_layout( title=f"Total drag variation with aircraft weight - CD0 = {CD0}, K={K}, S={S}m^2, Sea Level", xaxis_title="TAS / (m/s)", yaxis_title="Drag / N", legend_title="Altitude", ) # fig.add_trace(go.Scatter(x=np.linspace(0, 300, 1000), y=md*np.ones(1000), name="Constant Minimum Drag", connectgaps=True)) for trace in fig['data']: if(trace['name'] == "Annotation"): trace['showlegend'] = False fig.show()
Variation of aircraft drag in cruise: summary¶
In the drag equation, the combination of \(V^2\) and \(V^{-2}\) terms gives a minima in the total drag curve at the minimum drag speed, \(V_{md}\) which can be determined directly from \(V_{md}=\left[\frac{B}{A}\right]^{\frac{1}{4}}\).
At low speed, the induced drag term \(B=\frac{K\,W}{\frac{1}{2}\rho\,S}\) dominates.
Think: where in a flight regime is this important?
Take-off, landing, and air combat.
At high speed, the profile drag term \(A=\frac{1}{2}\rho C_{D0}S\) dominates.
Think: where in a flight regime is this important?
At cruise conditions.
This gives an indication of which parameters are relevant for different aircraft if drag reduction is desired.
Answer the following questions:
Describe the effect of altitude on drag curves.
An increase in altitude causes a decrease in density. This causes the induced drag to increase, and the profile drag to decrease. The minimum drag speed increases with altitude, but the minimum drag stays constant.
The visual effect is that total drag curves are shifted to the right, but the minima remains at the same position.
Describe the effect of aircraft weight on drag curves.
An increase in aircraft weight affects only the induced drag, which is increased.
The visual effect is that total drag curves are shifted to the right, and up - the minimum drag and the minimum drag speed are increased.
Describe the effect of wing area on drag curves.
This wasn’t covered above, but you should be able to answer using the same logic. Think about what you expect the answer to be, then try and plot it.
Discuss the answer on Slack.
Removing the Altitude Dependency - EAS¶
The drag equation as presented, in dimensional form is
\[D = C_{D0}\frac{1}{2}\rho\,V^2S + \frac{K\,W^2}{\frac{1}{2}\rho\,V^2S}\]
where the velocity in question is TAS. We can use the relationship
\[\frac{V_E}{V}=\sqrt{\frac{\rho}{\rho_{SL}}}\]
to express the drag equation in terms of EAS:
\[D = C_{D0}\frac{1}{2}\rho_{SL}\,V_E^2S + \frac{K\,W^2}{\frac{1}{2}\rho_{SL}\,V_E^2S}\]
or
\[D = A_E\cdot V_E^2 + B_E\cdot V_E^{-2}\]
where \(A_E\) and \(B_E\) are defined as before, but with the sea-level density in place of density at whatever altitude is in question.
This has the effect of collapsing the drag curves together, as \(\rho_{SL}\) is a constant.
fig = go.Figure()fig.update_xaxes(range=[0, 300])fig.update_yaxes(range=[0, 20e3])rho_sl = 1.225for alt in [0, 5000, 15000]: mosphere = Atmosphere(alt) rho = mosphere.density # Determine stall speed Vstall = np.sqrt(W / (0.5 * rho_sl * S * Clmax)) # Determine A and B AE = CD0 * 0.5 * rho_sl * S BE = K * W ** 2 / 0.5 / rho_sl / S # Flight speed vector VE = np.linspace(Vstall, 340, 1000) # Define drags Dind = BE * VE**-2 Dprof = AE * VE**2 D = Dind + Dprof # Get minimum drag Vmd = (BE/AE)**.25 md = AE * Vmd**2 + BE * Vmd**-2 fig.add_trace(go.Scatter(x=Vs, y=D, name=f"Total Drag: {alt/1e3:1.0f}km")) fig.update_layout( title=f"Total drag variation with altitude - CD0 = {CD0}, K={K}, S={S}m^2, W={W/1e3}", xaxis_title="EAS / (m/s)", yaxis_title="Drag / N", legend_title="Altitude", ) # fig.add_trace(go.Scatter(x=np.linspace(0, 300, 1000), y=md*np.ones(1000), name="Constant Minimum Drag", connectgaps=True)) for trace in fig['data']: if(trace['name'] == "Annotation"): trace['showlegend'] = False fig.show()
Hence the minimum drag speed in EAS is a function of the constants \(K\) and \(C_{Dmin}\), and \(\rho_{SL}\). \(V_{E_{MD}}\) and increases with aircraft weight and remains constant with aircraft altitude.
Range vs Endurance¶
The aircraft drag can be considered as the force required to propel the aircraft forward. For this reason, it is useful to determine the condition of minimum drag, as this means the aircraft is flying with the greatest aerodynamic efficiency - when flying at this condition, the aircraft can go the farthest. This defines the maximum range (see the note below). Hence, if a pilot wishes to fly the longest distance (in a glider or propeller-drive aircraft) for a certain amount of fuel, they should fly at \(V_{md} = \left[\frac{B}{A}\right]^{-\frac{1}{4}}\).
Actually…
The maximum range is found at \(V_{md}\) for a glider or a propeller-driven aircraft, for reasons that we’ll get to.
The maximum range for a turbojet is found at the minimum power speed - so this is another reason why we need to look at power.
However, they will not be able to fly for the longest period of time at this speed. For certain aircraft missions, it is desirable to seek endurance as opposed to range.
For consideration of endurance, the problem is not one of minimising the force required, but instead to minimise the amount of energy required in a given amount of time, Hence, the problem is not one of minimising the force required (the drag), but minimising the amount of work done per time - flying with minimum power.
Power required¶
Power is the rate of doing work - so the power required to overcome drag is:
\[\text{required power } = \text{ drag} \times \text{flight speed}\]
\[P_R=D\cdot V\]
\[P = T\cdot V = D\cdot V\]
\[= \left[AV^2 + \frac{B}{V^2}\right]\cdot V\]
\[= AV^3 + \frac{B}{V}\]
the minimum power required is found
\[\frac{\text{d}P}{\text{d}V} = 3AV^2 - \frac{B}{V^2} (= 0 \text{ at }P_{min}\text{)})\]
\[V_{MP}^4 = \frac{B}{3A}\]
\[V_{MP} = \left[\frac{B}{3A}\right]^{\frac{1}{4}}\]
\[= \left[\frac{2W}{\rho S}\right]^\frac{1}{2}\left[\frac{K}{3\cdot C_{D0}}\right]^{\frac{1}{4}}\]
It is easy to compare the minimum drag speed and the minimum power speeds, now:
\[\frac{V_{MP}}{V_{MD}} = \frac{\left[\frac{B}{3A}\right]^{\frac{1}{4}}}{\left[\frac{B}{A}\right]^{\frac{1}{4}}}=\left[\frac{1}{3}\right]^\frac{1}{4}\simeq 75.98\%\]
So flying at the minimum power speed, which is slower than the minimum drag speed, will not get the best range but will enable a pilot to stay in the air for the longest period of time.
As was performed for Drag, the Power required can now be plotted vs TAS:
import plotly.io as pioimport plotly.express as pximport plotly.offline as pyimport plotly.graph_objects as gofrom ambiance import Atmosphereimport numpy as np# Define constantsCD0=0.016 # Zero incidence dragK=0.045 # Induced drag factorS=50 # Wing area, m^2W=160e3 # Aircarft weight, NewtonsClmax = 1.5alt=0; # Altitudemosphere = Atmosphere(alt*1000)rho = mosphere.density# Determine stall speedVstall = np.sqrt(W / (0.5 * rho * S * Clmax))# Determine A and BA = CD0 * 0.5 * rho * SB = K * W ** 2 / 0.5 / rho / S# Flight speed vectorVs = np.linspace(Vstall[0], 200, 1000)# Define dragsPind = B * Vs**-1Pprof = A * Vs**3P = Pind + Pprof# Get minimum drag speed and associated powerVmd = (B/A)**.25mdp = A * Vmd**3 + B * Vmd**-1# Get minimum powerVmp = (B/3/A)**.25mp = A * Vmp**3 + B * Vmp**-1fig = go.Figure()fig.add_trace(go.Scatter(x=Vs, y=Pind, name="Induced Power"))fig.add_trace(go.Scatter(x=Vs, y=Pprof, name="Profile Power"))fig.add_trace(go.Scatter(x=Vs, y=P, name="Total Power"))fig.add_trace(go.Scatter(x=Vmd, y=mdp, mode="markers+text", text=f"$V_{{md}}={Vmd[0]:1.2f}$", textposition="top center", name="Annotation"))fig.add_trace(go.Scatter(x=Vmp, y=mp, mode="markers+text", text=f"$V_{{mp}}={Vmp[0]:1.2f}$", textposition="top center", name="Annotation"))fig.update_layout( title=f"Variation of Profile, Induced, and Total Power - CD0 = {CD0}, K={K}, altitude={alt}km, S={S}m^2, W={W/1e3}", xaxis_title="TAS / (m/s)", yaxis_title="Drag / N", legend_title="Drag Breakdown",)for trace in fig['data']: if(trace['name'] == "Annotation"): trace['showlegend'] = Falsefig.update_xaxes(range=[0, 200])fig.update_yaxes(range=[0, 4e6])
Effect of altitude on minimum power¶
Recall that an increase in altitude caused the total drag curve to shift to the right - increasing the minimum drag speed but keeping the same value of dimensional minimum drag.
A similar plot can be made to show the variation of minimum power with altitude - it can be seen that the minimum power increases linearly, with a line that passes through the origin.
If you really wish to, you can show analytically that the gradient is a constant by differentiating the expression for \(V_{MP}\) with respect to \(\rho\). It will yield a constant - but this will be a bit of a laborious exercise in algebra and calculus.
import plotly.io as pioimport plotly.express as pximport plotly.offline as pyimport plotly.graph_objects as gofrom ambiance import Atmosphereimport numpy as np# Define constantsCD0=0.016 # Zero incidence dragK=0.045 # Induced drag factorS=50 # Wing area, m^2W=160e3 # Aircarft weight, NewtonsClmax = 1.5fig = go.Figure()for alt in [0, 5, 10]: # Altitude mosphere = Atmosphere(alt*1000) rho = mosphere.density # Determine stall speed Vstall = np.sqrt(W / (0.5 * rho * S * Clmax)) # Determine A and B A = CD0 * 0.5 * rho * S B = K * W ** 2 / 0.5 / rho / S # Flight speed vector Vs = np.linspace(Vstall[0], 200, 1000) # Define power Pind = B * Vs**-1 Pprof = A * Vs**3 P = Pind + Pprof # Get minimum drag speed and associated power Vmd = (B/A)**.25 mdp = A * Vmd**3 + B * Vmd**-1 # Get minimum power Vmp = (B/3/A)**.25 mp = A * Vmp**3 + B * Vmp**-1# fig.add_trace(go.Scatter(x=Vs, y=Dind, name="Induced Power"))# fig.add_trace(go.Scatter(x=Vs, y=Dprof, name="Profile Power")) fig.add_trace(go.Scatter(x=Vs, y=P, name=f"Total Power - {alt}km")) fig.add_trace(go.Scatter(x=Vmp, y=mp, mode="markers+text", text=f"$V_{{mp}}={Vmp[0]:1.2f}$", textposition="top center", name="Annotation"))fig.add_trace(go.Scatter(x=[0, Vmp[0]], y=[0, mp[0]], name="Annotation", mode='lines')) fig.update_xaxes(range=[0, 200])fig.update_yaxes(range=[0, 4e6])for trace in fig['data']: if(trace['name'] == "Annotation"): trace['showlegend'] = Falsefig.update_layout( title=f"Variation of Total Power with Altitude - CD0 = {CD0}, K={K}, S={S}m^2, W={W/1e3}", xaxis_title="TAS / (m/s)", yaxis_title="Drag / N", legend_title="Drag Breakdown",)
import plotly.io as pioimport plotly.express as pximport plotly.offline as pyimport plotly.graph_objects as gofrom ambiance import Atmosphereimport numpy as np# Define constantsCD0=0.016 # Zero incidence dragK=0.045 # Induced drag factorS=50 # Wing area, m^2W=160e3 # Aircarft weight, NewtonsClmax = 1.5fig = go.Figure()alt = 0for W in [160e3, 200e3, 240e3]: # Weight mosphere = Atmosphere(alt*1000) rho = mosphere.density # Determine stall speed Vstall = np.sqrt(W / (0.5 * rho * S * Clmax)) # Determine A and B A = CD0 * 0.5 * rho * S B = K * W ** 2 / 0.5 / rho / S # Flight speed vector Vs = np.linspace(Vstall[0], 200, 1000) # Define power Pind = B * Vs**-1 Pprof = A * Vs**3 P = Pind + Pprof # Get minimum drag speed and associated power Vmd = (B/A)**.25 mdp = A * Vmd**3 + B * Vmd**-1 # Get minimum power Vmp = (B/3/A)**.25 mp = A * Vmp**3 + B * Vmp**-1# fig.add_trace(go.Scatter(x=Vs, y=Dind, name="Induced Power"))# fig.add_trace(go.Scatter(x=Vs, y=Dprof, name="Profile Power")) fig.add_trace(go.Scatter(x=Vs, y=P, name=f"Total Power - {W}kN")) fig.add_trace(go.Scatter(x=Vmp, y=mp, mode="markers+text", text=f"$V_{{mp}}={Vmp[0]:1.2f}$", textposition="top center", name="Annotation")) fig.update_xaxes(range=[0, 200])fig.update_yaxes(range=[0, 4e6])for trace in fig['data']: if(trace['name'] == "Annotation"): trace['showlegend'] = Falsefig.update_layout( title=f"Variation of Total Power with Aircraft Weight - CD0 = {CD0}, K={K}, sea level, S={S}m^2", xaxis_title="TAS / (m/s)", yaxis_title="Drag / N", legend_title="Drag Breakdown",)
Variation of aircraft power in cruise: summary¶
In the power equation, the combination of \(V^3\) and \(V^{-1}\) terms gives a minima in the total drag curve that is lower than minimum drag speed. This is the minimum power speed, \(V_{mp}\) which can be determined directly from \(V_{mp}=\left[\frac{B}{3\,A}\right]^{\frac{1}{4}}\).
Answer the following questions:
Describe the effect of altitude on power curves.
An increase in altitude causes a decrease in density. This causes the induced power to increase, and the profile drag to decrease - but the profile power rises with the cube of speed, whilst induced power falls with the inverse of forward speed. The minimum power speed increases with altitude, but and the minimum power rises linearly.
The visual effect is that total drag curves are shifted to the right and up.
Describe the effect of aircraft weight on drag curves.
Similarly to drag, an increase in aircraft weight affects only the induced power, which is increased.
The visual effect is that total drag curves are shifted to the right, and up - the minimum power and the minimum power speed are increased.
Removing the Altitude Dependency - EAS¶
To plot power vs equivalent airspeed as performed before for drag, one has to be careful with definitions. If you take the power equation, and simply replace \(V\) with \(V_E\), and plot against \(V_E\), then we are not representing true power vs. EAS due to the velocity term outside the brackets. What we are actually showing is a parameter that can be considered density-scaled power:
\[\begin{split}\begin{aligned} P\sqrt{\sigma}&=\left[A_EV_E^2 + \frac{B_E}{V_E^2}\right]\cdot V_E\\ \text{since}\\ P&=\left[A_EV_E^2 + \frac{B_E}{V_E^2}\right]\cdot V\\ &=\left[A_EV_E^2 + \frac{B_E}{V_E^2}\right]\cdot \frac{V_E}{\sqrt{\sigma}}\end{aligned}\end{split}\]
Similar to plotting drag vs. EAS, plotting \(P\sqrt{\sigma}\) vs EAS collapses the curves for different altitudes onto one another, creating a single power curve vs. EAS. However, caution must be taken as the ordinate is not actual power, unlike for the drag plot, where the ordinate is dimensional true drag.
It is left as an exercise for the reader to show this plot based upon those already given.
Thrust Available vs. Thrust Required¶
As stated previously, the aircraft total drag is analogous to the total thrust force required to maintain a condition. The total power is analogous to the total propulsive power required to maintain the condition.
The aircraft powerplant creates thrust and power (more on the distinction, shortly), and this sets the range of possible flight speeds.
Consider an aircraft engine capable of producing a thrust that is constant with forward speed (which isn’t realistic, as we will see), this can be overlaid on the thrust OR power required curve.
Fig. 19 Thrust Available and Thrust Required¶
Denoting the thrust produced by the powerplant as \(T_A\), meaning thrust available and the total drag as \(T_R\), meaning thrust required, the intersection between the \(T_A\) and \(T_R\) curves gives the possible flight speeds.
\(T_A\) is simply a number, whilst the \(T_R\) curve is a polynomial so the intersection can be determined from:
\[T_R=A\cdot V^2 + B\cdot V^{-2}\]
Which is equal to the thrust available:
\[T_R=A\cdot V^2 + B\cdot V^{-2}=T_A\]
\[A\cdot V^4 + B - T_A\cdot V^2=0\]
hence a quadratic in \(V^2\) or
\[a\cdot (V^2)^2 + b\cdot (V^2) + c=0\]
with \(a=A\), \(b=-T_A\) and \(c=B\)
\[V=\sqrt{\frac{T_A\pm\sqrt{T_A^2-4\cdot A\cdot B}}{2\cdot A}}\]
which yields the two velocities from the graph, \(V_1\) and \(V_2\).
Example¶
For an aircraft with a drag equation described by:
\[C_D = 0.016 + 0.045\cdot C_L^2\]
with a wing area of 50m\(^2\), a weight of 160kN, a \(C_{L,max}=1.5\), flying at sea-level determine the maximum and minimum flight speeds for a constant thrust of 10kN
Solution procedure - attempt the question before looking at the answer.
The drag equation gives you the constants \(C_{D0}=0.016\) and \(K=0.045\), and the remaining constants are provided in the question.
This enables you to determine the profile drag factor A=0.49000001 and the induced drag factor B=37616325.974.
With \(T_A=10,000N\), you now have everything to solve the quadratic equation to yield \(v_1=70.53m/s\) and \(v_2=124.43m/s\).
Look at the plot below, and see if you could reproduce is without looking at the source code.
import plotly.io as pioimport plotly.express as pximport plotly.offline as pyimport plotly.graph_objects as gofrom ambiance import Atmosphereimport numpy as npimport cmath# Define constantsCD0=0.016 # Zero incidence dragK=0.045 # Induced drag factorS=50 # Wing area, m^2W=160e3 # Aircarft weight, NewtonsClmax = 1.5alt=0; # Altitudemosphere = Atmosphere(alt*1000)rho = mosphere.density# Determine stall speedVstall = np.sqrt(W / (0.5 * rho * S * Clmax))# Determine A and BA = CD0 * 0.5 * rho * SB = K * W ** 2 / 0.5 / rho / S# Flight speed vectorVs = np.linspace(Vstall[0], 200, 1000)# Define dragsDind = B * Vs**-2Dprof = A * Vs**2D = Dind + Dprof# Get minimum dragVmd = (B/A)**.25md = A * Vmd**2 + B * Vmd**-2fig = go.Figure()# Thrust availableTA = 10e3fig.add_trace(go.Scatter(x=[min(Vs), max(Vs)], y=[TA, TA], name="$T_A$", mode="lines"))# Get the intersectiona = Ab = -TAc = Bflight_limit_speeds = np.sort(np.sqrt(np.roots([a, b, c])))fig.add_trace(go.Scatter(x=Vs, y=D, name="$T_R$"))fig.add_trace(go.Scatter(x=Vmd, y=md, mode="markers+text", text="$V_{md}$", textposition="top center", name="Annotation"))fig.add_trace(go.Scatter(x=flight_limit_speeds, y=[TA, TA], mode="markers+text", text=[f"V1={flight_limit_speeds[0]:1.2f}", f"V2={flight_limit_speeds[1]:1.2f}"], textposition="bottom center", name="Annotation"))fig.update_layout( title=f"Graphical Solution", xaxis_title="TAS / (m/s)", yaxis_title="Drag / N", legend_title="Drag Breakdown",)for trace in fig['data']: if(trace['name'] == "Annotation"): trace['showlegend'] = Falsefig.update_xaxes(range=[0, 200])fig.update_yaxes(range=[0, 20e3])
/Users/harrysmith/opt/anaconda3/lib/python3.8/site-packages/numpy/core/_asarray.py:171: VisibleDeprecationWarning:Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
Speed stability in cruise¶
In the figure above, for a fixed throttle setting of 10kN, steady flight is possible at \(V_1\) or \(V_2\). At speeds \(V_1\) or \(V_2\) only \(T_A=T_R\) and there is no excess thrust.
At speeds \(V_1 < v < V_2\), there is positive excess thrust and at speeds \(v<V_1\) or \(v>V_1\) there is negative excess thrust (sometimes called excess drag). With positive excess thrust, the aircraft accelerates. With negative excess thrust the aircraft decellerates.
Flight at v1¶
Consider flight at \(V_1\) - any velocity perturbation (e.g., due to a gust) will move the aircraft into a condition of excess thrust.
For the case with no pilot input, if the aircraft speeds up, there will be positive excess thrust leading to acceleration all the way to \(V_2\). If the aircraft slows down, there will be negative excess thrust leading to decelleration all the way to \(V_{stall}\).
This is speed instability, and leads to increased pilot workload (requires continual throttle adjustments)
Flight at v2¶
Consider flight at \(V_2\) - any velocity perturbation (e.g., due to a gust) will move the aircraft into a condition of excess thrust.
For the case with no pilot input, if the aircraft speeds up, there will be negative excess thrust leading to decelleration back to \(V_2\). If the aircraft slows down, there will be postitive excess thrust leading to acceleration back to \(V_{2}\).
This is a stable system, with reduced pilot workload (no required throttle adjustments)
Stability boundary¶
Consider that the pilot may adjust the throttle to increase or decrease the thrust. Accordingly, if in the example given above the \(T_A\) line represents the maximum thrust, then the throttle could be adjusted to allow cruise to be possible at all speeds \(V_1\le v\le V_2\).
Using the reasoning above, though, it can be seen that cruise at any velocity \(V\leq V_{md}\) will be subject to a speed instability.
Caution - the above is a simplification.
The description of what happens with excess thrust as described above is a simplification (you’ll read this phrase a lot in Flight Mechanics).
In reality, whenever there is positive excess thrust, the resulting acceleration will result in a speed increase which, for a given attitude will result in an increase in lift and hence climb.
If the pilot wishes to maintain constant speed, they may intuitively adjust attitude via the stick/yoke which will take the aircraft out of equilibrium.
Aircraft Propulsion - thrust or power available¶
In the question above, it was assumed that the thrust was constant with forward speed. This is only the case for a pure turbojet or a high bypass-ratio turbofan. Before we can go further with the methodology, a broad comparison between aircraft powerplant types needs to be made.
With infinite thrust/power available, our aircraft could fly anywhere on the D vs. TAS curve, but this is not the case in reality. Thrust and power are provided by the aircraft powerplant, so some understanding of what it means to produce thrust is required.
Newton’s second law states that “force is equal to the rate of change of momentum”. The momentum change in question is that of the fluid before and the effect of the propulsor.
A revision of aircraft propulsion.
Recall that the fluid accelerates before and after the propulsor, and reaches the ultimate velocity at some downstream distance.
All generalised jets, meaning any propulsor that works by accelerating a fluid provide a \textsl{streamwise pressure discontinuity} which creates a continuous streamwise velocity variation. You may resolve the force as \(F=\Delta P\cdot A\) or \(F=\dot{m}\Delta V\), and these are equal to each other - they are not summative.
Defining a jet efflux velocity, \(v_j\), as the velocity of the air when it is fully accelerated by the propulsor. Newton’s second law is then:
\[\begin{split}\begin{aligned} T &= \frac{\text{d}}{\text{d}t}\left({m}\cdot\Delta v\right)\\ \text{in steady flight, }\Delta v=0\\ &= \dot{m}\cdot\Delta v \\ &= \dot{m}\Delta v\\ &= \dot{m}\left(v_j - V\right)\end{aligned}\end{split}\]
Considering work done; the work that the propulsor performs on the airframe is useful work, whilst any work done in providing the streamtube with velocity is waste work.
Work is force \(\times\) displacement in the direction of the force, and power is the rate of doing work, so:
Useful power
\[\begin{split}\begin{aligned} P &= T\cdot V\\ &= \dot{m}\cdot\left(v_j - V\right)\cdot V \end{aligned}\end{split}\]
Waste power is the rate of change of kinetic energy of the air:
\[\begin{aligned} P_{waste}=\frac{1}{2}\dot{m}\left(v_j-V\right)^2 \end{aligned}\]
Which allows the definition of propulsive efficiency as a measure of the propulsive power to the total power required.
\[\begin{split}\begin{aligned} \eta&=\frac{\text{Useful (Propulsive) Power}}{\text{Total Power Output}}\\ &= \frac{T\cdot V}{T\cdot V + \frac{1}{2}\dot{m}\left(v_j-V\right)^2 }\\ &= \frac{\dot{m}\cdot\left(v_j - V\right)\cdot V}{\dot{m}\cdot\left(v_j - V\right)\cdot V + \frac{1}{2}\dot{m}\left(v_j-V\right)^2 }\end{aligned}\end{split}\]
Noting that propulsive power is a function of the aerodynamics of the propulsor and does not include any effects such as losses in the powerplant itself.
Propellers and High Bypass-Ratio Turbofans have a high \(\dot{m}\) due to a large disc area, but a small \(v_j\). This means:
Lower fuel consumption due to small KE increase
Rapid loss of thrust with forward speed due to small \(v_j-V\)
These engines may be defined as power engines as their fuel consumption is generally linear with the power they produce. They have an associated specific fuel consumption (SFC) which has units of kg/s/W or lb/h/hP or equivalents.
Turbojets and Low Bypass-Ratio Turbofans have a small \(\dot{m}\) due to a small disc area, but a large \(v_j\). This means:
High fuel consumption due to large KE increase
Little loss of thrust with forward speed due to small \(v_j>>V\)
These engines are defined as thrust engines as their fuel consumption is generally linear with the thrust they produce. They have an associated thrust specific fuel consumption (TSFC) which has units of kg/s/N or lb/h/lbf or equivalents.
Thrust and Power Model¶
Since all aircraft propulsors accelerate a mass of air, it follows that their output is a function of air density/altitude - but also of many, many other factors.
Validity of this model
In reality, the relationships for thrust and power for different types of engines are functions of forward speed, Mach number, density, temperature, and engine-specific factors relating to efficiency.
For a detailed discussion of these effects, see Chapter 3 in “Aircraft Performance and Design” [And99]. The summary on page 186 results in the altitude model used in
There are a myriad of different thrust and power models used for aircraft performance, but for this course, the simplest one will be used.
For thrust engines, the altitude variation is described by:
\[\begin{split}\begin{aligned} \frac{T}{T_{SL}} &= k\cdot\sigma^n\label{eq:thrustmodel}\\\text{where}\\ k &: \text{Throttle setting = 0 to 1}\\ T_{SL} &: \text{Thrust produced at ISA SL}\\ \sigma &: \text{Density ratio} - \frac{\rho}{\rho_{SL}}\\ n &: \text{1 if not indicated otherwise} \end{aligned}\end{split}\]
For power engines, the altitude variation is described by:
\[\begin{split}\begin{aligned} \frac{P}{P_{SL}} &= k\cdot\sigma^n\\\text{where}\\ k &: \text{Throttle setting = 0 to 1}\\ P_{SL} &: \text{Power produced at ISA SL}\\ \sigma &: \text{Density ratio} - \frac{\rho}{\rho_{SL}}\\ n &: \text{1 if not indicated otherwise} \end{aligned}\end{split}\]
Some sources list \(n\) as an altitude dependent parameter that accounts for the change of lapse rate at the tropopause, whilst other list it as an engine-specific parameter. In this course, it will be used as a parameter that encompasses both - you will be able to assume \(n=1.0\) unless otherwise directed.
v1 and v2 with altitude¶
With the thrust or power model now giving the variation of available thrust with altitude (with the change in density), the range of possible speeds can be determined for different altitudes.
It can be appreciated that it is easier to perform this exercise in EAS rather than TAS, as there is a single \(T_R\) curve in EAS.
import plotly.io as pioimport plotly.express as pximport plotly.offline as pyimport plotly.graph_objects as gofrom ambiance import Atmosphereimport numpy as npimport cmathfrom myst_nb import glue# Define constantsCD0=0.016 # Zero incidence dragK=0.045 # Induced drag factorS=50 # Wing area, m^2W=160e3 # Aircarft weight, NewtonsClmax = 1.5rho_sl = 1.225TSL = 25e3fig = go.Figure()# Determine A and B - EASAE = CD0 * 0.5 * rho_sl * SBE = K * W ** 2 / 0.5 / rho_sl / S# Find mimimum drag as this sets the ceilingVemd = (BE/AE)**.25Dmin = AE * Vemd**2 + BE * Vemd**-2sig_dmin = Dmin/TSLrho_dmin = sig_dmin * rho_sl# Need to find the altitude for this - this isn't an efficient way to calculate it. But it'll workceiling_found = Falsealt = 0iteration = 0dH = 1while not ceiling_found: mosphere = Atmosphere(alt*1000) rho = mosphere.density drho = rho - rho_dmin dH = drho alt = alt + drho if abs(drho) < 1e-5: ceiling_found = True ceiling = altaltvec = np.arange(0, ceiling, 2)altvec = np.concatenate((altvec, ceiling))# Get minimum dragVemd = (BE/AE)**.25md = AE * Vemd**2 + BE * Vemd**-2# Turn this into TASVmd = Vemd * sig_dmin**-.5# Save these values for laterglue("Vemd", Vemd, display=False);glue("Vmd", Vmd, display=False);# Flight speed vector# Determine stall speedVstall = np.sqrt(W / (0.5 * rho_sl * S * Clmax))Vs = np.linspace(Vstall, 300, 1000)# Define dragsDind = BE * Vs**-2Dprof = AE * Vs**2D = Dind + Dproffig.add_trace(go.Scatter(x=Vs, y=D, name="$T_R$")) for alt in altvec: mosphere = Atmosphere(alt*1000) rho = mosphere.density # Thrust available at this altitude sigma = rho/rho_sl TA = TSL * sigma[0] # Plot available thrust fig.add_trace(go.Scatter(x=[0, 250], y=[TA, TA], name="Annotation", mode="lines")) fig.add_trace(go.Scatter(x=[250], y=[TA], mode="text", text=f"h={alt}km", textposition="middle right", name="Annotation")) # Get the intersection a = AE b = -TA c = BE flight_limit_speeds = np.sort(np.sqrt(np.roots([a, b, c]))) # Is this in the envelope (this code is redundant now, but might be handy for later) in_envelope = not (isinstance(flight_limit_speeds[0], complex)) # Add v1 and v2 annotations if in_envelope and not (alt == ceiling): fig.add_trace(go.Scatter(x=flight_limit_speeds, y=[TA, TA], mode="markers+text", text=[f"v1={flight_limit_speeds[0]:1.2f}", f"v2={flight_limit_speeds[1]:1.2f}"], textposition="bottom center", name="Annotation")) elif in_envelope: fig.add_trace(go.Scatter(x=[flight_limit_speeds[0]], y=[TA], mode="markers+text", text=[f"v1=v2={flight_limit_speeds[0]:1.2f}"], textposition="bottom center", name="Annotation"))# Add the stall speedfig.add_trace(go.Scatter(x=[Vstall, Vstall], y=[0, 30e3], mode="lines", name="Annotation")) fig.add_trace(go.Scatter(x=[Vstall], y=[27e3], mode="text", text="Stall Speed", textposition="middle right", name="Annotation"))fig.update_layout( title=f"$T_R \\text{{ and }} T_A \\text{{ for different altitudes}}$", xaxis_title="EAS / (m/s)", yaxis_title="Drag / N", legend_title="Drag Breakdown",)for trace in fig['data']: if(trace['name'] == "Annotation"): trace['showlegend'] = Falsefig.update_xaxes(range=[0, 260])fig.update_yaxes(range=[0, 30e3])fig.show()
Look at the graph above, observe the following:
There is a single \(T_R\) curve since the graph has been plotted in EAS
At sea-level the \(T_A\) curve is highest as the air density is lowest, hence there is the greatest available thrust
As altitude increases, the available thrust decreases, and hence the minimum flight speed \(v_1\) increases whilst the maximum flight speed \(v_2\) increases
For many altitudes, the minimum flight speed is lower than the stall speed hence the value has no physical significance - since flight would not be possible at these speeds
Altitudes have been plotted in 2km intervals, which is an arbitrary interval.
As \(v_1\) and \(v_2\) get closer together, they finally meet at the minimum drag speed - the physical significance here is that at this altitude the engine can only produce sufficient thrust (i.e., at maximum throttle) to enable cruise at a single speed (that which requires the minimum thrust, \(V_{md}\)) - 93.604m/s EAS or 159.719m/s TAS
Plotting flight speeds¶
From the above, it is possible to plot the maximum and minimum flight speeds with altitude
# Make a vector for the altitude in 100m intervalsalt_vector = np.arange(0, ceiling, 0.1)alt_vector = np.concatenate((alt_vector, ceiling))# AE and BE are already available from before - we'll introduce two new arrays to store V1 and V2#EASVE1 = np.zeros(alt_vector.shape)VE2 = np.zeros(alt_vector.shape)#TASV1 = np.zeros(alt_vector.shape)V2 = np.zeros(alt_vector.shape)# iterate over the altitudesfor i, altitude in enumerate(alt_vector): mosphere = Atmosphere(altitude*1000) rho = mosphere.density # Thrust available at this altitude sigma = rho/rho_sl TA = TSL * sigma[0] # Get the intersection a = AE b = -TA c = BE flight_limit_speeds = np.sort(np.sqrt(np.roots([a, b, c]))) # Store these in the array VE1[i] = flight_limit_speeds[0] VE2[i] = flight_limit_speeds[1] # And for EAS V1[i] = VE1[i] * sigma ** -.5 V2[i] = VE2[i] * sigma ** -.5 # Sort these into an array for plottingVEs = np.concatenate((VE1, np.flip(VE2)))Vs = np.concatenate((V1, np.flip(V2)))alt_vector = np.concatenate((alt_vector, np.flip(alt_vector)))# fig = go.Figure()fig.add_trace(go.Scatter(x=VEs, y=alt_vector, mode="lines", name="EAS"))fig.add_trace(go.Scatter(x=Vs, y=alt_vector, mode="lines", name="TAS"))fig.update_layout( title=f"Possible airspeeds for different altitudes in EAS and TAS", xaxis_title="Airspeed / (m/s)", yaxis_title="Altitude / km",)
Now - the plot above show the possible flight speeds from the solution of the quadratic, but it was shown in the previous plot that for lower altitudes, \(v_1\) was below the stall speed.
If this is taken into consideration, then the plot is modified to:
The source code for the plot above is not included on the website - though you could download it if you look at the source .ipynb file.
You are advised to try and reproduce the plot above based on the source code from the previous plot. This will be a good test of your ability to understand the equations and the logic flow of these codes.
Aircraft Absolute Ceiling¶
This introduces the concept of aircraft absolute ceiling, which is defined as the altitude at which the only possible flightspeed is \(V_{md}\).
A consideration of this concept should ring alarm bells in your aircraft performance engineer’s brain.
What alarm bells?
Think back to the concept of speed stability - where the idea of velocity perturbations were introduced.
If an aircraft is flying at the absolute ceiling, then any velocity perturbation will push the aircraft to a speed where there is negative excess thrust and thus the aircraft will begin to sink.
As a consequence, sustained cruise at the absolute ceiling is not feasible.
For the above reasons, the aircraft absolute ceiling is rarely used or listed by a manufacturer. In reality, the aircraft service ceiling is defined, where a small rate of climb is still possible - the rate is usually dictated by the manufacturer.
To explore this concept, a model for climbing/sinking/gliding flight will be required. This ends the section of Steady Level Flight.
FAQs
What is the difference between steady flight and level flight? ›
A: Steady flight is what pilots call a flight with no acceleration. Lift, Weight, Drag and Thrust are balanced, and the plane is neither acceleraing nor deceleraing. This can happen during a climb, a dive, or level flight.
What is a steady level flight in an aircraft? ›Steady flight, unaccelerated flight, or equilibrium flight is a special case in flight dynamics where the aircraft's linear and angular velocity are constant in a body-fixed reference frame.
What are the 4 principles of flight? ›The four forces are lift, thrust, drag, and weight.
Which is the minimum speed at which aircraft can be considered in steady level flight? ›Find the velocity for minimum thrust required at steady level flight if wing loading is 75N/m2 and induced drag factor K is 0.0025. Consider CD0 as 0.02 and density as sea level. Explanation: Given, CDO = 0.02, k = 0.0025. By solving these we get answer as 6.45m/s.
What is the thrust required for steady level flight? ›For a vehicle in steady, level flight, the thrust force is equal to the drag force, and lift is equal to weight. Any thrust available in excess of that required to overcome the drag can be applied to accelerate the vehicle (increasing kinetic energy) or to cause the vehicle to climb (increasing potential energy).
What are the 3 classes of flight? ›Traditionally, an airliner is divided into, from the fore to aft, first, business, and economy classes, sometimes referred to as cabins. In recent years, some airlines have added a premium economy class as an intermediate class between economy and business classes.
Why do pilots say Flight Level? ›Flight Level (FL)
Strictly speaking a flight level is an indication of pressure, not of altitude. Only above the transition level (which depends on the local QNH but is typically 4000 feet above sea level) are flight levels used to indicate altitude; below the transition level feet are used.
(b) Airplane certification levels are: (1) Level 1 - for airplanes with a maximum seating configuration of 0 to 1 passengers. (2) Level 2 - for airplanes with a maximum seating configuration of 2 to 6 passengers. (3) Level 3 - for airplanes with a maximum seating configuration of 7 to 9 passengers.
What is the golden rule in aviation? ›Golden rules are: Basic principles of flying modern commercial aircraft. Part of good airmanship and maintaining situational awareness. Available for normal, abnormal and emergency situations.
What is the rule of 3 pilots? ›In aviation, the rule of three or "3:1 rule of descent" is a rule of thumb that 3 nautical miles (5.6 km) of travel should be allowed for every 1,000 feet (300 m) of descent. For example, a descent from flight level 350 would require approximately 35x3=105 nautical miles.
What are the 3 6 rules in aviation? ›
For larger aircraft, typically people use some form of the 3/6 Rule: 3 times the altitude (in thousands of feet) you have to lose is the distance back to start the descent; 6 times your groundspeed is your descent rate.
What's the slowest a plane can fly? ›Slowest aircraft
The MacCready Gossamer Condor is a human-powered aircraft capable of flight as slow as 8 miles per hour (13 km/h). Its successor, the MacCready Gossamer Albatross can fly as slow as 9.23 miles per hour (14.85 km/h).
§ 91.117 Aircraft speed.
(a) Unless otherwise authorized by the Administrator, no person may operate an aircraft below 10,000 feet MSL at an indicated airspeed of more than 250 knots (288 m.p.h.).
The minimum safe altitude of a route is 19,000 feet MSL and the altimeter setting is reported between 29.92 and 29.43 “Hg, the lowest usable flight level will be 195, which is the flight level equivalent of 19,500 feet MSL (minimum altitude (TBL ENR 1.7-1) plus 500 feet).
What altitude must I be stabilized by? ›All flights must be stabilized by 1,000 feet above airport elevation in instrument meteorological conditions (IMC) and by 500 feet above airport elevation in visual meteorological conditions (VMC).
What is the limit for takeoff thrust? ›Maximum takeoff (MTO) thrust is the highest amount of thrust an aricraft is allowed to give in the first 5 minutes of takeoff and flight. It is used when an aircraft has a heavy payload and only a small runway for takeoff.
What is the FAA glide ratio? ›The glide ratio (absolute value) is the ratio of speed divided by descent rate. It is the slope of a line (tangent) drawn to the polar curve. L/D Max is the optimum, but there are variation that can occur, both at higher and lower airspeeds.
Do you prefer window or aisle seat? ›Window seats are better for resting
Whether you're in economy or business class, window seats are consistently better if you're trying to rest. In economy, you can rest your head against the wall, which you can't do in the aisle seat.
Domestic first class is the top cabin on domestic flights and some short-haul international flights. On most airlines and aircraft, this means you'll sit in a recliner-style seat that offers more space and legroom than economy.
What rank do pilots stop flying? ›Over 90% of the pilots within a flying squadron who make it to 20 years will retire as an O-5. For those who wish to continue their career, they may be eligible for promotion to O-6 after four years as an O-5.
Why do pilots say v1? ›
V1 is the maximum speed at which a rejected takeoff can be initiated in the event of an emergency. V1 is also the minimum speed at which a pilot can continue takeoff following an engine failure.
Why do pilots say heavy? ›Wake turbulence poses a major risk to other aircraft, so pilots and ATC use the term “heavy” in radio transmissions as a reminder that the aircraft's wake may be dangerous to others passing behind or below the flightpath of these larger-mass aircraft.
What are the 7 categories of aircraft? ›There are seven main categories under the FAA's class rating system. These classes are airplane, rotorcraft, powered lift, gliders, lighter than air, powered parachute and weight-shift-control aircraft.
What is golden Flight Level? ›Golden Flight Level (GFL) is the annual international winter sports championship of air traffic controllers with participants from all across Europe, as well as from overseas (Canada, USA, Carribbean, Russia, Dubai and Australia).
What are the 4 types of flight classes? ›These days most modern airlines offer travellers a choice of three or four service levels: Economy, Premium Economy, Business, and First Class. This basic structure is usually based on the cost of the flight and the services included during the journey.
What are flight levels in USA? ›In the United States and Canada, Flight Levels are classified as Class A airspace and begin at FL180, (18,000 ft) and extend to FL600. The transition level between altitudes and Flight Levels differs by country, depending on the terrain and highest obstacles in that country.
What does Level 2 mean in airport? ›If delays can be managed with some guidance on the number and timing of flights through schedule facilitation, then an airport may be designated Level 2 by the FAA based primarily on performance metrics and runway capacity.
What does flight level 60 mean? ›FL is measured in increments of 100 feet. So FL60 is 6,000 feet (above mean sea level when the pressure at sea level is 1013.2hpa). FL61 is 6,100 feet according to a standard atmosphere. A graphic that visualizes the difference between altitude, flight level, and where the transition altitude comes into play.
What is Rule 57 in aviation? ›PURPOSE: Rule 57 of Aircraft Rules, 1937 requires that every aircraft shall be fitted and equipped with instruments and equipment, including radio apparatus and special equipment as may be specified according to the use and circumstances under which the flight is to be conducted.
What is the 12 5 rule in aviation? ›The current Twelve-Five Standard Security Program (TFSSP) rules require aircraft operators of aircraft with a maximum certificated takeoff weight (MTOW) of more than 12,500 pounds conduct criminal background checks on their flight crew members, and restrict access to the flight deck.
What is rule 13 in aviation? ›
—No person shall take, or cause or permit to be taken, at a Government aerodrome or from an aircraft in flight, any photograph except in accordance with and subject to the terms and conditions of a permission in writing granted by the Director-General, a Deputy Director-General, the Director of Regulations and ...
What is the 50 70 rule in aviation? ›unobstructed runways, establish a landmark at 50% of your calculated takeoff distance. When reaching that landmark, you should be at 70% of your rotation speed. If not, abort the takeoff and reduce weight or wait for more favorable wind and temperature conditions.
What is the rule of thumbs in aviation? ›There's a pretty easy rule-of-thumb to figure that descent rate out. Divide your ground speed by 2, then add a 0 to the end. So if you take 90 knots / 2, you get 45. Add a zero to the end, and you get 450 FPM.
What is the 321 rule flying? ›Each passenger may carry liquids, gels and aerosols in travel-size containers that are 3.4 ounces or100 milliliters. Each passenger is limited to one quart-size bag of liquids, gels and aerosols.
What is the 90 10 rule in aviation? ›90 percent of the time, the pilot's attention should be outside the flight deck. No more than 10 percent of the pilot's attention should be inside the flight deck. smoothly, and accurately applied with reference to the natural horizon.
What is the 10 21 rule in aviation? ›The takeoff distance varies with the square of the gross weight. A 10 percent increase in gross weight equals 21 percent increase in takeoff distance.
What is Rule 90 in aviation? ›(1) No person shall enter or be in the terminal building of any Government aerodrome or public aerodrome or part of such building or any other area in such - aerodrome notified in this behalf by the Central Government unless he holds an admission ticket issued by the aerodrome operator or an entry pass issued by the ...
What is the easiest plane to drive? ›- The Cessna 172. The Cessna 172 didn't become the top-selling airplane of all time for out of the blue. ...
- The Piper PA-28. The Piper was built to compete with the Cessna 170. ...
- The Diamond DA40. The Diamond DA40 is a newer plane. ...
- Ready to Learn to Fly?
Most pilots learning to fly solo start on either Cessna 150/152 or Diamond DA-40/42. Both are two-seat aircraft and are extremely popular for flight training. As a beginner private pilot, the types of planes that you can fly depend on the country in which you are located and the type of license you hold.
What is the longest plane flight without stopping? ›Undefeated record: The world record for the world's longest continuous flight was set in 1959 by Robert Timm (pictured) and his co-pilot John Cook. Months in the air: The men flew in this four-seater aircraft for 64 days, 22 hours and 19 minutes.
What is the FAA drone speed limit? ›
The maximum allowable altitude is 400 feet above the ground, and higher if your drone remains within 400 feet of a structure. The maximum speed is 100 mph (87 knots).
What is the max hold speed FAA? ›2.1a or the charted maximum holding speed. All fixed wing aircraft conducting holding should fly at speeds at or above 90 KIAS to minimize the influence of wind drift.
Why is there a 250 knot speed limit? ›Multiple Deadly Mid-Air Collisions Resulted In This Speed Restriction. On December 16th, 1960, a United Airlines Douglas DC-8 collided with a TWA Lockheed L-1049 Super Constellation over the skies of Brooklyn, New York.
What is the lowest a helicopter can fly legally? ›An altitude of 500 feet above the surface, except over open water or sparsely populated areas. In those cases, the aircraft may not be operated closer than 500 feet to any person, vessel, vehicle, or structure.
What is the most restricted airspace class? ›Controlled and uncontrolled airspaces are the ones you will spend most of your time flying within as a pilot. Controlled airspace consists of five tiers beginning with most restrictive to least restrictive: Class Alpha (A), Class Bravo (B), Class Charlie (C), Class Delta (D), and Class Echo (E).
Why would two planes fly close together? ›When an airplane is departing, Air Traffic Controllers can place aircraft much closer together than they do at cruise altitude. This allows controllers to maximize their rate of departures for efficiency.
What is the meaning of level flight? ›Straight and level flight is flight in which a constant heading and altitude are maintained. Used during cross-countries when flying from point A to point B. Accomplished by making immediate and measured corrections for deviations.
What is the difference between level and flight level? ›Flight Level (FL)
Only above the transition level (which depends on the local QNH but is typically 4000 feet above sea level) are flight levels used to indicate altitude; below the transition level feet are used. e.g. FL250 = 25,000 feet above mean sea level when the pressure at sea level is 1013.2 mb.
Flight level means a level of constant atmospheric pressure related to a reference datum of 29.92 inches of mercury. Each is stated in three digits that represent hundreds of feet. For example, flight level 250 represents a barometric altimeter indication of 25,000 feet; flight level 255, an indication of 25,500 feet.
What does Flight Level 60 mean? ›FL is measured in increments of 100 feet. So FL60 is 6,000 feet (above mean sea level when the pressure at sea level is 1013.2hpa). FL61 is 6,100 feet according to a standard atmosphere. A graphic that visualizes the difference between altitude, flight level, and where the transition altitude comes into play.
What is the highest Flight Level? ›
A: The highest commercial airliner ceilings are 45,000 feet. It is not uncommon to fly at the certified ceiling of the airplane.
What is the minimum safe flight level? ›In aviation (particularly in air navigation), lowest safe altitude (LSALT) is an altitude that is at least 500 feet above any obstacle or terrain within a defined safety buffer region around a particular route that a pilot might fly.
What does flight level 100 mean? ›The Flight Level is written using the two letters FL with the altitude (at standard QNH) in feet, without the two digits at the end: 10000 feet becomes Flight Level 100 = FL100. 6500 feet becomes Flight Level 65 = FL65.
What are the 5 stages of flight? ›“'Critical phases of flight' in the case of aeroplanes means the take-off run, the take-off flight path, the final approach, the missed approach, the landing, including the landing roll, and any other phases of flight as determined by the pilot-in-command or commander.
What are the 6 stages of flight? ›3.1.
The general flight phases are divided into: planning phase, takeoff phase, climb phase, cruise phase, descent phase, approach phase, and taxi phase.
Golden Flight Level (GFL) is the annual international winter sports championship of air traffic controllers with participants from all across Europe, as well as from overseas (Canada, USA, Carribbean, Russia, Dubai and Australia).
What does flight level 600 mean? ›Class A airspace is generally the airspace from 18,000 feet mean sea level (MSL) up to and including flight level (FL) 600, including the airspace overlying the waters within 12 nautical miles (NM) of the coast of the 48 contiguous states and Alaska.