If you’ve arrived at this blog, you will probably have had some exposure to the concept of ‘computational design’. You may also have heard some of the related terms that fall under this heading – ‘parametric design’, ‘algorithmic design’, ‘generative design’ and so on. As computational design is still a relatively young and evolving field the meanings of these terms can be a little vague and are used by different practitioners in different ways. This article presents the vision of computational design that we have in Ramboll and the role that we see it having in the future of the industry. This is what *we* mean by computational design.
But, before we can answer the title question we need to first answer another – what is design?
Wikipedia describes design as “the creation of a plan or convention for the construction of an object, system or measurable human interaction“, which seems like a reasonable definition, but one that doesn’t give much insight into the process involved, or rather processes. In Ramboll, we are mainly concerned with designing aspects of the built environment – buildings, bridges, infrastructure and so on – very large, very complex projects that require whole teams of experts in different subject areas to work together in parallel.
Even within a single discipline, we might divide the process of delivering a project into two – the mental and the physical. In the former category we have the cerebral work that goes into a design – generating ideas, understanding requirements, thinking (and talking) through problems and deciding on the fundamental principles that go into forming ‘the design’. But this cannot stay a purely ephemeral undertaking – we as designers also need to test our ideas and communicate them to our clients and colleagues and for this we must engage in a range of more tangible activities – performing calculations, writing documents, producing drawings and models and so on. These are not merely end-products, however – they are integral to producing a better understanding of the problem we are trying to solve and the implications of our assumptions in solving it. There is thus an interplay between the mental and physical sides of design. The process as a whole is highly iterative, with many embryonic design options dreamt up, examined and refined or discarded on the way to the ultimate solution.
Recently, computers have been increasingly used as a method of production, to the extent that the second half of the above equation might often be termed ‘virtual’ rather than ‘physical’. Whereas previously we would have produced drawings by hand, we now more commonly draw on the computer using CAD (Computer-Aided-Design) packages such as AutoCAD and Rhino. Whereas in the past we would have had to physically construct an architectural model to see what a project looked like in 3D, we can now build and view a virtual 3D model, perhaps with additional detailed information embedded into it. Whereas we would have had to perform engineering calculations by hand we now have a plethora of software packages available to perform analysis and run through standard calculations on our behalf.
These are some of the ways in which computers are now used in design, but is this what we mean by computational design?
These technologies augment the process of design to make it more efficient, but they do not represent any fundamental change to the process itself. The first generation of CAD software set out to replicate as closely as possible the previously existing paradigms – they swapped out the mechanical pencil for the mouse and the eraser for the delete key but otherwise the experience was maintained. To draw a line, you press down and move your hand from start to end. This was deliberate and, to an extent, necessary during the first transition into the virtual world, but in treating a computer as merely a replacement for a sheet of paper the true power of computation was overlooked.
Computers are not inanimate objects. They are machines of logic and process. They can think; not quite in the same way we do but in a way which is certainly compatible. That means that they can be integrated not only with the physical aspects of the design process but with the mental ones as well.
A (good) design is a fundamentally logical construct. Every aspect will have some reason to be the way it is, whether that is structural, functional, aesthetic or some combination of the above. Walk into the office tower of your choice, for example, and you are likely to find that the columns which support the building are not arranged randomly – they will be evenly-spaced and follow a regular grid. This is done to make the structure more efficient, easier to build and to allow for standardisation of components. Where columns deviate from this grid there will likewise be good reasons for that to be the case – perhaps to keep an auditorium space column-free, perhaps to allow enough clear space for access to be provided for large vehicles, perhaps to better support large loads from above. Each column will have an underlying logical process determining its placement.
Traditionally, it would be for humans to both decide upon this logic and then work through it to determine the arrangement it suggested, drawing or modelling the result. But this second stage is well within the capabilities of the computer, which is after all nothing more or less than a machine for the evaluation of logical processes. If the human can describe the principles driving the design in a form that the computer can understand – i.e. as an algorithm – then the computer can begin to take on a much larger role in the design process, becoming not just a recipient of data but also a generator of it, creating the design representation from the rules the designer has set. This shift is what demarks Computational Design as distinct from simply using computers in a more traditional design exercise.
In brief; Computational Design is a change in the medium of design expression from geometry to logic.
There are a number of advantages to this approach; firstly being that the geometry of the design tends to be changed far more often than the logic. As a structural engineer, I may want to try out several different arrangements of the column grid in order to find the frame that best fits the geometry and construction type of the project. I am unlikely, however, to discard the principle of using a regular grid altogether. If changing the grid means having to redraw every single column position, or perhaps even having to fully recreate from scratch whatever analysis model I am using to make my assessment, that is going to limit the number of options I can feasibly examine (and make me far more likely to stick with whatever I first came up with). If changing that grid merely means adjusting a few input parameters of my generative model and having everything else done for me by the computer then I have far more freedom to explore the design space, find a more optimal arrangement and to adapt to external changes and new information introduced later in the design process. I can, in short, come up with a better design.
Leaving the resolution of the design logic to the computer also removes the restriction that said logic must be resolvable by humans. When rules begin to combine with one another their effects can sometimes be hard for the human brain to visualise. A fractal image, for example, is typically generated by very simple operations repeated over and over and over again, but while the rules may be easy to understand it can be very difficult to anticipate the geometric result without prior experience. So too with buildings, the many competing design drivers of which are often dealt with through simplification and convention far more than they are by optimisation. Computational design allows us to break through these barriers and produce responsive virtual models to do what brainpower alone cannot.
Computational design is an excellent means of dealing with complexity, whether that complexity is caused by the interaction of the factors we have control over or the uncertainty surrounding the factors we don’t. Traditionally this approach has been applied mainly to niche projects whose obvious visual complexity demanded it – buildings with highly sculptural forms, intricate facades and so on that would be next to impossible to design through any other means. However, all projects are complex in their own way, and can benefit from automation to handle that complexity. At Ramboll we recognise this, and so are working to make computational design technology and expertise a more deeply embedded and mainstream part of our design process across all types of project.