Performance Art: Analytics and the New Theatre of Design Practice


How building performance is evolving within the practice of design.

CASE. By Nathan Miller, Daniel Davis – Nov. 15, 2014

The following chapter is an excerpt from “Building Information Modeling: BIM in Current and Future Practice”, a comprehensive collection of essays that posits BIM as an advantageous opportunity to improve the process of architectural design rather a disruptive one. Using five case studies, Nathan and Daniel explore how instruments, analytics, and interactions have helped evolve design practice by harnessing BIM data overflow into meaningful information for building performance.

CASE would like to thank Douglas Noble and Karen Kensek for inviting us to contribute to this publication.

A recent example is the CASE/Autodesk comparative energy instrument. The prototype originated from the observation that while the user is able to perform quick conceptual energy analysis on models within Revit and Vasari, the presented results do not allow for effective comparative metrics, nor do they reveal the underlying mechanisms by which the results are derived. The comparative charting add-in extracts data from multiple results files and provides clear comparative charts to reveal the variations in performance among many options. Decades of research has gone into the equations powering the instrument. These equations are arguably the most significant part, but these mechanisms remain hidden behind the user interface. Like another project partner, instruments often come to embody knowledge far outside the designer’s expertise. The charting instrument is not just about making data more accessible to the designer, but also about providing visualizations that enable endow the designer with greater clarity for the decision-making process.

Comparative energy analysis prototype compares data from multiple runs of a Green Building Studio energy model. (CASE, Autodesk)

Like the CASE/Autodesk comparative energy instrument, the CASE/Snøhetta daylight instrument is about finding potentials in a range of design possibilities. The CASE/Snøhetta daylight instrument lets users set twenty-three parameters that control the rotation, spread, and depth of a series of louvered panels on a building’s facade. The instrument returns a daylight analysis, an energy analysis, and a sensitivity analysis. This focus on relative potentials rather than absolute ideals is a subtle but important shift in emphasis compared to earlier computational instruments.

Design and analysis workflow for shade and daylight optimization. (CASE, Snøhetta)

Sean Keller explains that researchers developing instruments in the 1960s were doing so because they “hoped that the application of the correct algorithms to sets of building requirements could produce architectural forms that were objectively ‘best’” (Keller 2006). The structural instrument would tell the designer the best size of beam; the walking distance instrument would tell the designer the best room adjacencies; the energy analysis instrument would tell the designer the best window size. These early tools largely failed because, according to Keller, “at best, quantitative approaches have a limited use for certain very complex problems, and must always rely on many assumptions that cannot be quantified and on inherited typologies” (Keller 2006). In other words, there will always be aspects of a building’s performance that lie outside the quantification of instruments. Turkle says that designers can become vulnerable when using digital instruments because “sometimes it can be hard to remember all that lies beyond a simulation, or even acknowledge that everything is not captured in it. An older generation fears that young scientists, engineers and designers are ‘drunk with code’” (Turkle 2009).

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