Download - Autosim Autosim

THE AUTOSIM PROJECT
4.5.5 Robust Design and Complexity Management
With the advance of automated optimization methods it became clear that
optimization “alone” applied to real world engineering tasks will not solve
“the whole problem”. Optimization algorithms will drive the design to the
constraint limits where scatter in the input parameters may cause a violation
of these constraints and consequently a product to fail.
Fig. 4.5.5.1: Complexity Management
One means to avoid this and to get more insight into the design behaviour is
to utilise the tools which have been developed which are mostly based on
stochastic techniques. They have emerged in the past couple of years and
have been improved continuously by academia and software vendors.
These methods were conceived to be uncertainty management tools and
their goal was to evaluate the effects of tolerances on scatter, quality of
performance, most likely behaviour and the identification of dominant design
variables (Ref. [12], [17], [24]).
The underlying algorithms of these tools became mature. At the same time
also the expressiveness of these methods was improved in terms of
graphical results interpretation.
Post-processing evaluation can now be used to detect and visualize the
most dominant design variables using a correlation map showing the
correlation between input and output parameters (Fig. 4.5.5.1). The intensity
of correlation can be highlighted by various means e.g. by different colours,
different line characteristics and the distinction between direct and indirect
correlation etc.
SIXTH FRAMEWORK PROGRAMME PRIORITY [6.2] [SUSTAINABLE SURFACE TRANSPORT]
012497 AUTOSIM
53 |