And
we’re back, Pandametrics….so onto the Do’s and Don’ts of Pandametrics a glimpse
at some most excellent shell design workflows and a hint of Ricky’s upcoming
blog.
Do’s
and Don’ts
This
is not to say that it’s better to just rely on good old fashioned know how,
what we mean by Pandametrics is that you should use parametric design to focus
on improving what you can automate to allow you more time to focus on the fun
stuff, the structure interfaces and detailing that give a building some real
finesse.
For
example, if your architect lets you know that their geometry is dictated by a
specific grid and that the values of this grid could change then you’re going
to see a massive improvement in your workflow by tying all of your follow-on
design to the grid. It would then follow that as the grid changes so your
analysis model would update loadings and then your production model would
follow suit. Clearly this is going to save you time and efficiency by not
repeating work when a grid increases by 800mm and you find you need to check
through all of your hand calculations to see if the member size is still valid.
The
images below are from a parametric process we created for taking non definable
geometry and turning it into a panelised system for analysis (you might
recognise the shape as Smiljan Radics most excellent 2014 Serpentine Pavilion);
in this instance a change in this rather unique shape can be panelised and
evaluated in a matter of hours, saving time and efficiency to spend on the
detailing and really nailing down the architectural vision.
 |
| Serpentine 2014 - Architect model, to GH, to Shell...ready for analysis |
Obviously
the gold standard is to produce a holistically optimised solution, weighting
every parameter from every discipline and optimising accordingly but if you've
ever tried to optimise a structure for every possible evaluative parameter that
can be applied in a single workflow you've no doubt found yourself staring at a
huge tangle of unmanageable workflows that at best resemble the operating board
of a NASA shuttle…too many adjustable items to ever consider a solution optimal.
Also, a
good workflow should never require astronaut levels of training to understand
it!
There
are academic studies (do find the Delft University of Technology’s excellent
paper of optimisation of parameters, it’s a good read and a look to the future
which we’ll no doubt talk about in a future blog on this year’s IASS symposium)
that are considering how the selection of parameters of a whole building can be
optimised. However, even in these studies there is not an attempt to bring all
of the building disciplines into a singular giant AI controlled workflow, rather
to evaluate the end processes of each workflow, consider the impact on the
building of each of the disciplines’ input parameters in isolation, and select
the best combination. Maybe in the future we will be seeing this kind of cross
discipline work across a single workspace, but whilst there is still a
surprising resistance to moving towards 3D modelling (I realise I’m most likely
preaching to the converted here) this could be some way off.
To
get the most from your parametric design you should be considering a simplistic
set of input parameters that will form the beginning of your workflow. The
parameters should form the key part of your workflow in which as they change,
any additional work created is minimised in the follow-on processes
So
what’s it all mean?
The
biggest tip I could offer to someone who is looking to implement parametric
design into their day-to-day processes is to start by looking at your existing
workflows and design processes. It is often argued that parametric design is
only applicable for complex geometry. Tish and pish I say. I have used parametric
design to allow me to map complex geometry for an anatomically correct stadia
roof, I have used parametric design to assign connection forces for a fully
welded truss, I have used parametric design to manage an architectural grid and
I have used parametric design to link a layout of a simple pavilion steel frame
to an architectural GRP Shell geometry (this shell analysis will look familiar,
and not just because I put some of the shell panelisation script in an image
above).
 |
| Lovely parametric shell being analysed in SCIA engineer |
Parametric
design is both underused and inappropriately used in the construction industry
and the zen art of parametric design is to take this wonderful tool and do what
we as engineers do best, use our experience and intuition to improve our
designs and workflows to make us more efficient and create better designs. A
couple of years back (before my time with the team) there was a brief that
included 6 stadia designs and 3 days with which to design them all. Suffice to
say they smashed all 6 stadia, partly through being awesome, but partly because
they used their intuition and experience with parametric design to go beyond
traditional design practices.
Pandametrics
has led to the development of our key tools for creating a series of
interconnected parametric models that simplify and improve the workflows from
geometry definition to analysis to production, without losing any of the data
links that could prove exceedingly useful in the BIM environment (more on BIM
to come in a future blog, it wouldn’t be right to have an engineering blog
without discussing BIM after all). We’ve called it (unsurprisingly) Panda and
very shortly our resident structural genius and antipodean legend Ricky will be
telling you all about it with a nice little free download for those who fancy a
go at tying Rhino/Grasshopper and SCIA engineer together and want to know the
processes so you can build one yourself.
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