Page 85 - Using ANSYS for Finite Element Analysis Dynamic, Probabilistic, Design and Heat Transfer Analysis

72 • using ansys for finite eLement anaLysis
demand safety factors in certain procedural codes. If you are not faced with
such restrictions or demands, then using conservative assumptions and
safety factors can lead to inefficient and costly overdesign. You can avoid
overdesign by using probabilistic methods while still ensuring the safety of
the component. Probabilistic methods even enable you to quantify the safety
of the component by providing a probability that the component will survive
operating conditions. Quantifying a goal is the necessary first step toward
achieving it. Probabilistic methods can tell you how to achieve your goal.

3.1.2 ReLiAbiLiTy AnD QUALiTy iSSUeS

Use probabilistic design when issues of reliability and quality are para-
mount. Reliability is usually always a concern because product or com-
ponent failures have significant financial consequences (costs of repair,
replacement, warranty, or penalties); worse, a failure can result in injury
or loss of life. Although perfection is neither physically possible nor
financially feasible, probabilistic design helps you to design safe and reli-
able products while avoiding costly overdesign and conserve manufac-
turing resources (machining accuracy, efforts in quality control, and so
on). Quality is the perception by a customer that the product performs as
expected or better. In a quality product, the customer rarely receives unex-
pected and unpleasant events where the product or one of its components
fails to perform as expected. By nature, those rare “failure” events are
driven by uncertainties in the design. Here, probabilistic design methods
help you to assess how often “failure” events may happen. In turn, you can
improve the design for those cases where the “failure” event rate is above
your customers’ tolerance limit.

3.1.3 PRobAbiLiSTiC DeSign TeRMinoLogy

PDS term Description
Quantities that influence the result of an analysis.
In probabilistic design, RVs are often called
Random input “drivers” because they drive the result of an
variables (RVs) analysis. You must specify the type of statistical
distribution the RVs follow and the parameter
values of their distribution functions.
Two (or more) RVs that are statistically dependent
Correlation
on each other.