Page 108 - Using ANSYS for Finite Element Analysis Dynamic, Probabilistic, Design and Heat Transfer Analysis

probabilistic Design analysis • 95
questions: If we have 1,000 components that are operated under
real-life conditions, what would the lowest load value be that only
one of these 1,000 components is subjected to and all others have
a higher load? What would the most likely load value be, that is,
the value that most of these 1,000 components have (or are very
close to)? What would the highest load value be that only one of the
1,000 components is subjected to and all others have a lower load?
To be safe you should ask these questions not only of the person
who provided the nominal value, but also to one or more experts
who are familiar with how your products are operated under real-
life conditions. From all the answers you get, you can then consol-
idate what the minimum, the most likely, and the maximum value
probably is. As verification you can compare this picture with the
nominal value that you would use for a deterministic analysis. If the
nominal value does not have a conservative bias to it then it should
be close to the most likely value. If the nominal value includes a
conservative assumption (is biased), then its value is probably close
to the maximum value. Finally, you can use a triangular distribution
using the minimum, most likely, and maximum values obtained.
• If the load parameter is generated by a computer program then
the more accurate procedure is to consider a probabilistic analysis
using this computer program as the solver mechanism. Use a prob-
abilistic design technique on that computer program to assess what
the scatter of the output parameters are, and apply that data as input
to a subsequent analysis. In other words, first run a probabilistic
analysis to generate an output range, and then use that output range
as input for a subsequent probabilistic analysis.

3.3.4 ChooSing RAnDoM oUTPUT PARAMeTeRS

Output parameters are usually parameters such as length, thickness, diam-
eter, or model coordinates. The ANSYS PDS does not restrict you with
regard to the number of RPs, provided that the total number of probabi-
listic design variables (i.e., RVs and RPs together) does not exceed 5,000.
ANSYS recommends that you include all output parameters that you
can think of and that might be useful to you. The additional computing
time required to handle more RPs is marginal when compared to the time
required to solve the problem. It is better to define RPs that you might not
consider important before you start the analysis. If you forgot to include
a random output parameter that later turns out to be important, you must
redo the entire analysis.