Pandametrics (The Zen Art of Parametrics) Episode II

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.