Analysis and synthesis

Analysis and synthesis 

I've always been fascinated by analysis, by the means that help explain something and the insights they produce. Especially with computers, their ability to calculate large quantities of complex data in quite short times made me believe that computer simulations are the most important contribution of digital means to designing. When it comes to synthesis, however conceptually elegant, automatic generative systems are no match to human creativity yet.

The problem is that the promise of computerised analysis has yet to be fulfilled. Technical progress seems to be limited by the lack of serious interest by those who would benefit from analyses that go beyond the capacities of rules of thumb, normative abstractions and the usual conventional stuff that serves as alibi in architectural design. I spend days in meetings on computational and data-driven approaches that are mostly about decision support but it's unclear where the support is founded on; it's all about the decisions. Well, as far as I'm concerned, analysis is the foundation of any decision, any design action, as well as most communication. Unfortunately, there seems to be an important prerequisite: some goal to be achieved, some constraint to be met, something that requires transparent, effective and reliable reasoning. If synthesis is about other matters, a self-contained exercise, then analysis is a just formality.

Things that can go wrong with a model

Things that can go wrong with a model 

Architectural models attract attention to an almost fetishist level. Students have to make them, clients want them, every museum visitor enjoys them. Few have the courage to that them as tools of the trade. I remember one teacher who used to dismantle student models, almost physically attacking them while asking interesting questions about composition and alternatives. After that, one learned not to put too much time in their models and expect the worst.

In comedy, if something goest wrong with a model, it can be funny without getting too hurtful (we're getting rather sensitive about such things, robbing physical comedy of many opportunities like pratfalls). In Monty Python's The architects sketch, a spontaneous combustion and collapse of the model momentarily embarrasses the architect and, by the strange acceptance of the design by the clients, facilitates a jump to the subject of how to recognise a Mason. The most interesting thing about the model is the association between it and the behaviour and performance of the real building: that the model catches fire suggests that the building is highly flammable, despite the architect's claims; similarly, the instability of the model suggests failure of the load-bearing structure, which the architect is quick to admit. I suppose that the association between model and building is justified by that both are three-dimensional objects. This makes us forget the scale differences and the consequent differences between a simulation and the real thing.

As for what happens to the model  in One fine day, the least said, the best for all who have seen that forgettable comedy.

I don't walk like that

I don't walk like that 

Some time ago I was testing a fire egress calculation program and was quite shocked by the routes it calculated: the lines seemed to bounce from one wall to another, generally moving in the right direction but rather blindly or perhaps drunkenly. It was comical in its deviation from what we consider normal behaviour. My immediate reaction was to think: I don't walk like that, do I?

It's undeniable that our movement in space is not as smooth and purposeful as we want to imagine. One only needs to observe how people walk in a crowded public corridor, e.g. in a train station. It's a matter we should address in architecture and allow for more fuzziness and chaos in human interaction with buildings. Textbooks are full of certainties and crisp, tight values for everything. More room for error and uncertainty would arguably make the built environment more humane.

On the other hand, computer analyses and simulations have to become more meaningful and reliable. At the moment it seems that anything goes. Much from what I see is based not on scientific knowledge but derives from basic, often outdated textbooks and easy, unsupported assumptions. With simulations of natural phenomena (light, air, temperature etc.) one requires validation but with human interaction anything plausible is just accepted.