StiffenedPanel

class StiffenedPanel

Data class for the stiffened panel model.

Examples

>>> from openturns.usecases import stiffened_panel
>>> # Load the stiffened panel model
>>> panel = stiffened_panel.StiffenedPanel()
>>> print("Inputs:", panel.model.getInputDescription())
Inputs: [F,L,a,De,di,E]
>>> print("Outputs:", panel.model.getOutputDescription())
[Deflection,Left angle,Right angle]
Attributes:
dimConstant, the dimension of the problem.

dim=10

modelSymbolicFunction

Model of the critical shearing load. The model has input dimension 10 and output dimension 1. More precisely, we have \vect{X} = (E, \nu, h_c, \ell, f_1, f_2, t, a, b_0, p) and Y = (N_{xy})_{cr}.

EYoung modulus (Pa), TruncatedNormal distribution

ot.TruncatedNormal(110.0e9, 55.0e9, 99.0e9, 121.0e9)

nuPoisson coefficient (-), Uniform distribution

ot.Uniform(0.3675, 0.3825)

h_cDistance between the mean surface of the hat and the foot of the Stiffener (m), Uniform distribution

ot.Uniform(0.0285, 0.0315)

ellLength of the stiffener flank (m), Uniform distribution

ot.Uniform(0.04655, 0.05145)

f_1Width of the stiffener foot (m), Uniform distribution

ot.Uniform(0.0266, 0.0294)

f_2Width of the stiffener hat (m), Uniform distribution

ot.Uniform(0.00627, 0.00693)

tThickness of the panel and the stiffener (m), Uniform distribution

ot.Uniform(8.02e-5, 8.181e-5)

aWidth of the panel (m), Uniform distribution

ot.Uniform(0.6039, 0.6161)

b_0Distance between two stiffeners (m), Uniform distribution

ot.Uniform(0.04455, 0.04545)

pHalf-width of the stiffener (m), Uniform distribution

ot.Uniform(0.03762, 0.03838)

distributionJointDistribution

The joint distribution of the input parameters.

__init__()

Examples using the class

Estimate a buckling probability

Estimate a buckling probability