Almost by definition, the early part of the conceptual design process is the only part of the product development where we do not yet have a geometry model to refer to. Thus, some of the all-important aerodynamic figures have to be guessed at this point, largely on the basis of high level geometrical parameters like the aspect ratio.

In [30]: AspectRatio_ = 9

In [31]: CDmin = 0.0418

In [32]: WSmax_kgm2 = 20

In [33]: TWmax = 0.6

In [34]: Pmax_kW = 4

Estimated take-off parameters

In [35]: CLTO = 0.97

CDTO = 0.0898 muTO = 0.17

Preamble

Some of the computations and visualizations performed in this document may require additional Python modules; these need to be loaded first as follows:

In [36]: %matplotlib inline

In [37]: from __future_ import division

import math

from aerocalc import std_atm as ISA import numpy as np

In [38]: import matplotlib

import matplotlib.pylab as pylab import matplotlib.pyplot as plt

In the interest of conciseness and modularity, it is often useful to define repeated operations as functions. Let us first define a function for coloring in the unfeasible area underneath a constraint boundary:

In [39]: def ConstraintPoly(WSl,TWl,Col,al):

WSl.append(WSl[-1])

TWl.append(0)

WSl.append(WSl[0])

TWl.append(0)

WSl.append(0)

TWl.append(TWl[-2 ]) zp = zip (WSl,TWl)

pa = matplotlib.patches.Polygon(zp,closed = True

, color=Col, alpha = al)

return pa

Next, we define a method for setting the appropriate bounds on each constraint diagram: