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"""This example illustrates the usage of creator, evaluator and generator.
All the steps of airfoil creation & evaluation are detailed here;
furthermore, the generator.py module contains certain presets
(default airfoils).
Create an airfoil;
Evaluate an airfoil;
Generate a population of airfoils & optimize.
"""
import resources.materials as mt
import creator
import evaluator.evaluator as evaluator
import generator
# from generator import
import time
start_time = time.time()
# Airfoil dimensions (in)
NACA_NUM = 2412
# Thicknesses
SPAR_THICKNESS = 0.4
SKIN_THICKNESS = 0.1
# Component masses (lbs)
AIRFOIL_MASS = 10
SPAR_MASS = 10
STRINGER_MASS = 5
# Area (sqin)
SPAR_CAP_AREA = 0.3
STRINGER_AREA = 0.1
# Amount of stringers
TOP_STRINGERS = 6
BOTTOM_STRINGERS = 4
NOSE_TOP_STRINGERS = 3
NOSE_BOTTOM_STRINGERS = 5
SAVE_PATH = '/home/blendux/Projects/Aircraft_Studio/save'
eval = evaluator.Evaluator()
ac = creator.base.Aircraft(eval, "ac")
af = creator.wing.Airfoil(ac, 'af')
af.add_naca(NACA_NUM)
# af.info_print(2)
af.info_save()
spar1 = creator.wing.Spar(af, 'spar1')
spar2 = creator.wing.Spar(af, 'spar2', 0.57)
# af.spar1.info_print(2)
# af.spar2.info_print(2)
spar1.info_save()
spar2.info_save()
ac2 = creator.base.Aircraft(eval, "ac2")
af2 = creator.wing.Airfoil(ac2, 'af2')
af2.add_naca(3412)
spar3 = creator.wing.Spar(af2, 'spar3', 0.23)
spar4 = creator.wing.Spar(af2, 'spar4', 0.67)
eval.update()
# eval.info_print(2)
# # Create stringer instance
# af.stringer = wing.Stringer()
# # Compute the stringer coordinates from their quantity in each zone
# af.stringer.add_coord(af, [af.spar1, af.spar2], NOSE_TOP_STRINGERS, TOP_STRINGERS,
# NOSE_BOTTOM_STRINGERS, BOTTOM_STRINGERS)
# af.stringer.add_area(STRINGER_AREA)
# af.stringer.add_webs(SKIN_THICKNESS)
# af.stringer.info_print(2)
# af.stringer.info_save(SAVE_PATH, 'foo_name')
# Plot components with matplotlib
# creator.wing.plot_geom(af, [af.spar1, af.spar2], None)
# Evaluator object contains airfoil analysis results.
# The analysis is performed in the evaluator.py module.
# eval.analysis(1, 1)
# eval.info_print(2)
# eval.info_save(SAVE_PATH, 'foo_name')
# evaluator.plot_geom(eval)
# evaluator.plot_lift(eval)
# Final execution time
final_time = time.time() - start_time
print(f"--- {round(final_time, 4)}s seconds ---")
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