The simulation of physical reality is a necessary preoccupation of the architect, engineer, builder and systems specialist. For centuries, simulations have existed in the form of heuristic techniques used in establishing rules of thumb for architecture and design. These drawings, physical mock-ups, models, and other forms of mediated representations were surely satisfactory, but rarely optimal. In the twenty-first century, architecture benefits from the availability of near-immediate performance simulations executed during the design process and enabled by advanced computation software and rapid prototyping. In this context, prescriptive codes and standardization give way to hybrid models that integrate design goals, site and climate conditions, available resources, and building systems. Whether used for construction sequencing, parametric design comparisons, or structural, lighting, air flow and energy analysis, these simulations generate large amounts of complex performance data requiring a rigorous interpretation of results.

All good simulation models however, —whether made of sticks or bits—necessarily simplify in order to isolate and test relationships. Increasingly, digital simulation platforms operate as scripted add-ons, linking simulation engines to design software and embedding default values for building-based parameters. So doing, they rapidly generate performance data albeit with less user specified information. Feedback is immediate, results are plentiful, and queries are customizable, even when user expertise is limited. And while it appears the integration of data and performance in design has never been more accessible, the process is also more susceptible to false results from incorrect parameters and the blind acceptance of black box output. As we embrace the role of simulations in supporting generative design, we invite a critical evaluation of their assumptions, fidelity, limits, and potentials. 

Designing increasingly smarter, integrated, and efficient systems requires a nuanced understanding of the benefits and constraints of simulations. How might we assess whether they truly result in better performing buildings? Rarely studied post construction and almost never evaluated from the perspective of end-users, how do we know if completed works of architecture actually perform to their simulated measures? What are the standards by which we might validate and establish consensus for parameters needed to construct increasingly elaborate models? How might methodologies in collateral fields inform our approaches to architectural simulations? And most critically, in what way are designers expanding the objectives of a practice historically driven by engineering economy? Beyond measuring “efficiencies”, how can simulations disrupt the process of design itself by transforming the very way in which we communicate, collaborate and legislate? And how might simulations help us define and generate improved architectural outcomes? 

TAD (TECHNOLOGY | ARCHITECTURE + DESIGN) Issue 2, seeks empirical research, creative design, and critical theory manuscripts that investigate the role of simulations in the built environment. The issue aims to question the full spectrum of methodologies, models and measurement paradigms attendant to simulations of the built environment. It is equally committed to investigating the potential of this 21st century technology to disrupt the very practice of design.