minor typos fixed
@@ -35,7 +35,7 @@ class ControlSurfaceDeflector(object):
self.tsaero0 = None
self.tsstruct0 = None
- self.under_delopment = True
+ self.under_development = True
def initialise(self, data, linuvlm):
# Tasks:
@@ -71,6 +71,8 @@ class ControlSurfaceDeflector(object):
The parsing of arguments is temporary since this state space element will include a full actuator model.
+ The parsing of arguments is optional if the class has been previously initialised.
+
Args:
linuvlm:
tsaero0:
@@ -89,13 +91,12 @@ class ControlSurfaceDeflector(object):
tsaero0 = self.tsaero0
tsstruct0 = self.tsstruct0
-
# Find the vertices corresponding to a control surface from beam coordinates to aerogrid
aero_dict = aero.aero_dict
n_surf = aero.timestep_info[0].n_surf
n_control_surfaces = len(aero_dict['control_surface_chord'])
- if self.under_delopment:
+ if self.under_development:
import matplotlib.pyplot as plt # Part of the testing process
Kdisp = np.zeros((3 * linuvlm.Kzeta, n_control_surfaces))
Kdisp_n = Kdisp.copy()
@@ -123,7 +124,7 @@ class ControlSurfaceDeflector(object):
Cgb = Cbg.T
# print(global_node)
- if self.under_delopment:
+ if self.under_development:
print('Node -- ' + str(global_node))
# Map onto aerodynamic coordinates. Some nodes may be part of two aerodynamic surfaces. This will happen
# at the surface boundary
@@ -191,7 +192,7 @@ class ControlSurfaceDeflector(object):
0,
-for_delta * Cbg.dot(chord_vec)))
# Testing progress
- if self.under_delopment:
+ if self.under_development:
plt.scatter(zeta_hingeB[1], zeta_hingeB[2], color='k')
plt.scatter(zeta_nodeB[1], zeta_nodeB[2], color='b')
# plt.scatter(zeta_hinge[1], zeta_hinge[2], color='k')
@@ -208,7 +209,7 @@ class ControlSurfaceDeflector(object):
angle = np.arccos(new_vector.dot(old_vector) / (np.linalg.norm(new_vector) * np.linalg.norm(old_vector)))
print(angle)
- if self.under_delopment:
+ if self.under_development:
plt.axis('equal')
plt.show()
else:
