Airfoil database illinois3/19/2024 ![]() Return _Tcol_dim_1(li, TColgp_Array1OfPnt2d)įunction factory for 1-dimensional TCol* typesįrom import init_displayĭisplay, start_display, add_menu, add_function_to_menu = init_display()ĭisplay.DisplayShape(airfoil.shape, update=True)įirst, we create a UiucAirfoil object with 4 attributes: Return BRepPrimAPI_MakePrism(face.Face(),ĭef point2d_list_to_TColgp_Array1OfPnt2d(li): # the trailing edge segment could not be created, probably because the points are too closeįace = BRepBuilderAPI_MakeFace(make_wire(make_edge(spline))) Gp_Pnt(section_pts_2d.X(), section_pts_2d.Y(),0.0))įace = BRepBuilderAPI_MakeFace(make_wire()) #first and last point of spline -> trailing edge # 5 - figure out if the trailing edge has a thickness or not, and create a Face Spline = GeomAPI_To3d(spline_2d.Curve(),plan) ![]() ![]() # 4 - use the array to create a spline describing the airfoil section Section_pts_2d.append(gp_Pnt2d(float(data)*self.chord, If len(data)=2: # two coordinates for each point # 2 - do some cleanup on the data (mostly dealing with spaces) Plan = gp_Pln(gp_Pnt(0,0,0), gp_Dir(0,0,1)) # Z=0 plan / XY planįor line in f.readlines(): # The first line contains info only # 1 - retrieve the data from the UIUC airfoil data page Just replace the profile name with another valid profile name(see ) in the UiucAirfoil constructor call to construct a wing with a different profile.įrom OCC.BRepBuilderAPI import BRepBuilderAPI_MakeFaceįrom OCC.BRepPrimAPI import BRepPrimAPI_MakePrismįrom OCC.Geom2dAPI import Geom2dAPI_PointsToBSplineįrom OCC.gp import gp_Pnt, gp_Vec, gp_Pnt2d, gp_Pln, gp_Dirįrom OCC.TColgp import TColgp_Array1OfPnt2dįrom import make_wire, make_edge, make_vertexĪirfoil with a section from the UIUC database The list of available profile data is visible at. In this post, we will tap into the airfoil data from the UIUC (University of Illinois at Urbana-Champaign) to create a wing profile. With PythonOCC, you can read data from other websites and use it to create geometry: we could call that a geometrical mashup. Furthermore, it enables the cruise performance and drag divergence Mach number to be predicted with only one simulation of the cruise point, which will greatly save the computational cost of optimizations.Being a former user of OpenSCAD, a programmatic modeller that uses its own language, I really like the fact that PythonOCC relies on a mainstream language and all the ‘batteries included’ that come with it. It indicates that the drag divergence Mach number can be increased by obtaining a shock wave that is further upstream in the detailed design. Compared with Korn's equation, the discovered correlation reduces the maximum prediction error by approximately 40%. A new linear correlation is discovered and validated by existed airfoil databases. Correlation screening and multivariate regression are carried out to discover knowledge about the airfoil drag divergence Mach number and pressure distribution features. This paper designs a supercritical airfoil database that covers the typical free stream Mach number, angle of attack, lift coefficient, and geometry of modern transonic commercial aircraft. However, it neither reveals the key factors of fluid features on the drag divergence nor contributes to the detailed design. It is very helpful in the aircraft initial design. For example, Korn's equation predicts the airfoil drag divergence Mach number using the airfoil maximum thickness and the lift coefficient. ![]() Aerodynamic rules and knowledge are often obtained through theoretical research and experiments, which have contributed greatly to aircraft design.
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