def plot_runwayv():
M = Mission(sp=False)
M.substitutions.update({
"R": 400,
"W_{pay}": 195 * 6,
"g_{loading}": 0.3,
"C_{L_{TO}}": 4.0,
"C_{L_{land}}": 3.5
})
del M.substitutions["R"]
clrs = ["#084081", "#0868ac", "#2b8cbe", "#4eb3d3", "#7bccc4"] * 5
fig, ax = plt.subplots()
i = 0
for vmin in [100, 125, 150]:
M.substitutions.update({"V_{min}": vmin})
M.cost = 1 / M["R"]
sol = M.solve("mosek")
M.cost = M[M.aircraft.topvar("W")]
Rmax = sol("R").magnitude - 5
Rmin = 5
bst = autosweep_1d(M, 0.01, M["R"], [Rmin, Rmax])
_x = np.linspace(Rmin, Rmax, 100)
mtow = bst.sample_at(_x)(M.aircraft.topvar("W"))
ax.plot(_x, mtow, c=clrs[i], lw=2)
i += 1
ax.grid()
ax.set_ylim([0, 10000])
ax.set_xlabel("Range [nmi]")
ax.set_ylabel("Max Takeoff Weight [lbf]")
fig.savefig("rangev.pdf", bbox_inches="tight")
def plot_gl():
M = Mission(sp=False)
M.substitutions.update({
"R": 100,
"V_{min}": 100,
"C_{L_{land}}": 3.5,
"C_{L_{TO}}": 4.0,
"W_{pay}": 5. * 195
})
clrs = ["#084081", "#0868ac", "#2b8cbe", "#4eb3d3", "#7bccc4"] * 5
fig, ax = plt.subplots()
fig2, ax2 = plt.subplots()
i = 0
for gl in [0.3, 0.4, 0.5]:
M.substitutions.update({"g_{loading}": gl})
M.cost = M["S_{runway}"]
sol = M.solve("mosek")
M.cost = M.aircraft.topvar("W")
Smin = sol("S_{runway}").magnitude + 5
Smax = 800
bst = autosweep_1d(M, 0.01, M["S_{runway}"], [Smin, Smax])
_x = np.linspace(Smin, Smax, 100)
pay = bst.sample_at(_x)(M.aircraft.topvar("W"))
ax.plot(_x, pay, c=clrs[i], lw=2)
i += 1
ax.grid()
ax.set_ylim([0, 8000])
ax.set_xlim([0, 800])
ax.set_xlabel("Runway Length [ft]")
ax.set_ylabel("Max Take Off Weight [lbs]")
fig.savefig("smtow_gl.pdf", bbox_inches="tight")
def plot_vminWp():
M = Mission(sp=False)
M.substitutions.update({
"S_{runway}": 600,
"R": 100,
"g_{loading}": 0.3,
"C_{L_{TO}}": 4.0,
"C_{L_{land}}": 4.0
})
del M.substitutions["V_{min}"]
clrs = ["#084081", "#0868ac", "#2b8cbe", "#4eb3d3", "#7bccc4"] * 5
fig, ax = plt.subplots()
i = 0
for wpay in [2, 4, 6, 8]:
M.substitutions.update({"W_{pay}": 195. * wpay})
M.cost = 1 / M["V_{min}"]
sol = M.solve("mosek")
M.cost = M[M.aircraft.topvar("W")]
Vmin = 50
Vmax = sol("V_{min}").magnitude - 1
bst = autosweep_1d(M, 0.1, M["V_{min}"], [Vmin, Vmax])
_x = np.linspace(Vmin, Vmax, 100)
mtow = bst.sample_at(_x)(M.aircraft.topvar("W"))
ax.plot(_x, mtow, c=clrs[i], lw=2)
i += 1
ax.grid()
ax.set_ylim([0, 10000])
ax.set_xlabel("Minimum Cruise Speed [kts]")
ax.set_ylabel("Max Takeoff Weight [lbf]")
fig.savefig("vweightWp.pdf", bbox_inches="tight")
def plot_sw_mtowtech():
M = Mission(sp=False)
M.substitutions.update({
"R": 100,
"V_{min}": 100,
"h_{batt}": 300,
"m_{fac}_Mission/GLanding": 1.2,
"m_{fac}_Mission/TakeOff": 1.2,
"sp_{motor}": 7. / 9.81 * 0.8,
"f_{ref}": 1.1,
"g_{loading}": 0.5,
"C_{L_{TO}}": 5.0,
"C_{L_{land}}": 4.5
})
clrs = ["#084081", "#0868ac", "#2b8cbe", "#4eb3d3", "#7bccc4"] * 5
fig, ax = plt.subplots()
fig2, ax2 = plt.subplots()
i = 0
for npax in range(2, 9):
M.substitutions.update({"W_{pay}": npax * 195.})
M.cost = M["S_{runway}"]
sol = M.solve("mosek")
M.cost = M.aircraft.topvar("W")
Smin = sol("S_{runway}").magnitude + 5
Smax = 800
bst = autosweep_1d(M, 0.1, M["S_{runway}"], [Smin, Smax])
_x = np.linspace(Smin, Smax, 100)
sensland = bst.solarray["sensitivities"]["constants"]["C_{L_{land}}"]
xp = bst.solarray("S_{runway}").magnitude
f = interp1d(xp, sensland)
sensland = f(_x)
ax2.plot(_x, sensland, c=clrs[i])
pay = bst.sample_at(_x)(M.aircraft.topvar("W"))
ax.plot(_x, pay, c=clrs[i], lw=2)
i += 1
ax.grid()
ax.set_ylim([0, 8000])
ax.set_xlim([0, 800])
ax.set_xlabel("Runway Length [ft]")
ax.set_ylabel("Max Take Off Weight [lbs]")
fig.savefig("sw_mtowt.pdf", bbox_inches="tight")
ax2.set_ylabel("Sensitivity to landing constraints")
ax2.grid()
ax2.set_xlabel("Runway Length [ft]")
fig2.savefig("sw_mtowtsens.pdf", bbox_inches="tight")
if s[1] > 0:
pss.append(s[1])
ngs.append(0)
else:
ngs.append(abs(s[1]))
pss.append(0)
ind = np.arange(0.5, i + 0.5, 1)
ax.bar(ind, pss, 0.5, color="#4D606E")
ax.bar(ind, ngs, 0.5, color="#3FBAC2")
ax.set_xlim([0.0, ind[-1] + 1.0])
ax.set_xticks(ind)
ax.set_xticklabels(labels, rotation=-45, ha="left")
ax.legend(["Positive", "Negative"])
ax.set_ylabel("sensitivities")
return fig, ax
if __name__ == "__main__":
M = Mission()
M.cost = M["W"]
sol = M.solve("mosek")
varns = [
"W_{pay}", "R", "S_{TO}", "h_{batt}", "(W/S)", "sp_{motor}", "AR",
"\\eta_{prop}"
]
Fig, _ = plot_sens(M, sol, varns)
Fig.savefig("sensbar.pdf", bbox_inches="tight")