Fig. 1 Parameter controlled fractal branching structure without any random script components (DL 2006).
It is not an easy task to make architecture students become acquainted with the concepts and techniques of parametric modelling. One reason is the harsh beginning and a relative long phase, before the approach plays off its full potential (Fig. 2). Sufficient motivation can only be achieved by projects not too large for beginners but already too complex to be managed by traditional means. Thus, several courses previous to Bridging the Gap focussed on digital production (Fig. 3, left) or geometrically challenging tasks (Fig. 3, right).
Fig. 2 Diagram according to Neil Katz, SOM, as seen at the Design Modelling Symposium Berlin 2011.
Fig. 3 Left: non-rationalized surface model from a laser-cutter in a file-to-factory manner (Silke Maret, TU Dresden, 2009). Right: pre-rationalized surface discretized by interlocking elements (Robin Bongers, TU Dresden, 2010).
3 Objectives
Before starting Bridging the Gap, we analysed the results of the previous courses and decided to gear the course strictly to the accessible and affordable means of production. Given the equipment of TU Berlin laser cutting for the scale models and three-axis CNC milling for components of the bridge seemed to be the suitable tools. Thus we envisioned the bridge to be constructed modular with custom parts and joints from plywood. Through the restriction to a certain technical outcome we ensured that the students were able to track the workflow from the early design stage to the file-to-fabrication phase by one coherent digital model.
The approach involves a culture of thinking that accentuates the definition of the geometrical structure instead of the actual form (cf. Valena et al. 2011, Nake et al. 2007, p. 220). A parametric model in essence is only meaningful, provided it is wisely structured, allows the creation of substantially different variations from a relatively small number of parameters, and at the same time can easily adapt to changing constraints. Thus we wanted to review not only the outcome of the Grasshopper definitions but particularly the way they were conceived.
Pedestrian bridges in the Großer Tiergarten stand for the integration of artefacts into a natural environment (Fig. 4). We wanted to refer to this topic by looking at nature at a micro scale instead of mimicking its phenomena. Conceptually, there is an interesting coherence between the growth of plants from genome information and the creation of parametric models from bits of code (cf. the term digital morphogenesis, e.g. Hensel, Menges 2008). Although a species as well as a parametric model is essentially described by its code (genotype), there is still a great variety of forms possible by slightly changing the variables and by inherent adaptability (phenotypes).
Fig. 4 Detail of a historic pedestrian bridge in the Tiergarten with a floral motif.
One pitfall of parametric modelling is that the students forget about their ability to design and instead clone code solutions found in the Internet – with the effect of a worldwide homogeneous menu of inchoate parametric compositions at any digital design lab (van Berkel 2013). One reason for this apparent defect may be that the students are simply not able to take advantage of the programming tools because of a lack of deeper understanding. Thus, the programming environment again – as any other CAAD software – acts as a black box with predefined tool sets and outcome. The second reason might be found in the software itself: Only design decisions that can easily be quantified find their way into the digital model. Last but not least the students are often overwhelmed by the efficiency of parametric models in handling large quantities, which may suggest complexity. It takes a little experience to realize that apparent complexity is not added value.
The challenge in conducting Bridging the Gap was to avoid these tendencies by two strategies. First, in order not to be narrowed by the software the students evolved the seedlings of the designs with analogue techniques. Second, the students had to build up Grasshopper definitions from scratch. In a set of consecutive tutorials, each starting from a plain canvas the students became familiar with the essential concepts of the software and the underlying geometric knowledge. Altogether the aim of the course was to unleash the students’ potential to handle complex design tasks skilfully and to make them create unique concepts within a short period of time.
4 Method
In respect to the location in the park and with the conceptual orientation towards a modular structure we started our course with the analysis of the formation and structure of elements and joints from biological examples (Fig. 5). Each student had to work on sketches and physical models to document personal observations and speculations (Fig. 6). The students investigated in several directions: Is an example promising from the structural point of view? Does it reveal geometrical principles that qualify it for a module? Could it be an inspiration for materialization in a larger scale?
Fig. 5 Some found objects serving as examples at the beginning of Bridging the Gap.
The reflection on biological artefacts has numerous famous precursors like Karl Blossfeldt and Ernst Haeckel (Sachsse 1996, Haeckel 1998). We especially emphasized the morphological perspective that D’Arcy Wentworth Thompson unfolded (Thompson 1917). Though, the focus was not to generate engineering solutions like in bionics, but to start a voyage of discovery as for example artist Amely Spötzl undertakes in disassembling and cutting parts of plants (Hupasch; Lordick 2008, pp. 24/25, 70/71). During this first step, each student unveiled a pattern and principle to refer to during the following tasks. Then groups of two students each were formed to combine related motives. In cooperation the students formulated a spectrum of forms that transcended the biological example, and they tested and extracted options of parameterization for the digital model (Fig. 7). Next the concepts were transferred into code and the resulting digital models were refined. In a phase of exploration and inspection the students created variants gauging the design space of their concepts (Fig. 8).
Fig. 6 Selection of students’ sketches and models inspired by biological examples.
Fig. 7 Formal explorations to extract relevant parameters.
Fig. 8 Variations derived from a parametric model.
Obviously, we established a procedure where we did not start with the instruction „Design a footbridge!”, but in a bottom-up strategy tried to develop and agglomerate building parts, which eventually are able to span a stream. This is a generative method, which among other aspects helped to prevent unfounded copy and paste tactics during the scripting phase: Any new inspiration appearing on the screens had to be related to previous steps of the evolution.
Generative design is not an invention of the digital era. It is a highly process-based approach that opens the space of possible solutions for the unexpected. In a systematic sequence of actions that are partly carried out by technical means. Step by step the design emerges. The idea is not to draw from a source of predefined forms but to get involved into an algorithm for form-finding (Kraft; Taraz-Breinholt 2002, p. 20). As an early predecessor for generative strategies may apply Sonia