Many factors can be a source for variations in design parameters changing the nature
of a design problem from deterministic to probabilistic.
These factors can be due to various types of uncertainty.
Physical uncertainty:
Loads
Boundary and initial conditions
Material properties
Geometry
Numerical simulation uncertainty:
Conceptual modeling
Mathematical modeling
Manufacturing:
Sheet metal thickness
Welds
Random design (controlled) variables
Loads:
Direction
Magnitude
Random noise (uncontrolled) variables
Material data:
Elastic properties
Failure
Random noise or input variables
Uncertainties can affect input variables, also called controlled parameters, such as
thickness or stiffness. They can also affect design parameters, also called uncontrolled
or noise parameters, such as temperature or humidity. The resulting variations in these
parameters are usually modeled by one of the many probability distribution functions
based on their nature. In HyperStudy, normal, uniform,
weibull, triangular, and exponential distributions are available.
Corresponding to the variations in controlled or uncontrolled parameters, the design
performance will also have variations. In Figure 1
probabilistic characteristics of both the parameter types and output response are shown
with a typical probability density function, PDF, curve. PDF curve is a plot of variable
values and corresponding probabilities. PDF describes the range of values that a
probabilistic variable can attain along with the occurrence probability of each
value.Figure 1. Uncertainty in Design