Rethinking Prototyping. Группа авторов

      Foreword

      Prototypical Models of Design

      At this Symposium, we look forward to discussing the relationship between prototypes and models of design. The term prototype stands for an implemented design step rather than a trial run for mass production, as an extension to the thought and computational constructs that make up the model of design. The term models of design stands for the idea and all underlying abstractions and assumptions that define the design process.

      The relation between model of design and prototype gains importance as our understanding and relating of material systems to their simulated abstract models improves and computation increasingly becomes embodied in physical constructs replacing complex mechanical assemblies with computational feedback and control.

      In architecture, the mechanical complexity has usually been lower than in other engineering fields; but obviously much of architecture’s complexity lies in its cultural context and the human occupation due to its scale and the social density of the built environment. Buildings need to evolve due to their potential long lifespan and are essentially evolving prototypes of the initial design intent reflected in the design model. Bridging the gap between design abstraction during the design development and the operation of the built structure is an ongoing challenge. Inherent to the use of digital tools for design is a tension between using simulation and computational processes to develop robust physical constructs that work as physical assemblies but independent of their computational simulations, or whether to move the computational processes into the built form and further sophisticate the feedback and control cycles and adaptability of physical constructs. In other words, computational processes may be found at many levels whether implicitly as computationally crafted material behaviour and/or explicitly in the computational capabilities of construction elements.

      In other engineering disciplines, one can see a fascinating trend where complex and large scale mechanical assemblies for mechanical control are replaced by simpler mechanics empowered by computational controls such as for instance in the case of the development of helicopters to quadcopters or windmills to autonomously flying power kites.

      Architecture and engineering structures are obviously different from aerospace constructs in terms of development costs and impact on the physical environment, but similar effects may be achievable in enabling existing infrastructure and structure to operate beyond their initial design intent and capabilities. Already actuated structures responding computationally to live loads thus simpler or lighter than conventional ones are being developed and constructed. Even the average eco-building corresponds to the definition of a robot with complex control algorithms linking sensors to actuators. Imagining coordination and collaboration on a building-to-building scale as well as at the scale of cities, think of smart grids, is not inconceivable.

      However fascinating, such developments implicitly entail further vulnerability to system failure. Structures losing their control capabilities may collapse; automatically-shaded Passivehaus buildings overheat and become non-liveable. Directly embedding complex computational processes in the architecture calls for a careful balance between system performance and robustness.

      Actually, long-going efforts in autonomous robotics suggest achieving robustness through embedding non-digital computational capabilities in physical constructs by exploiting system dynamics and non-linearities. Control only then provides the additional performance delta that makes the system reach the prescribed efficiency. Models, meaning our abstract understanding and invention of such processes play a crucial role in the development of new ideas and increasingly so as we rely more and more on their implementations in digital form.

      We