In the domain of simulation-based design of high-performance buildings, emerging techniques using parametric design platforms such as Rhino/Grasshopper are enabling architects to algorithmically relate building design decisions to physics-based evaluations of daylight quality, energy demand, and thermal comfort. By making use of additional tools, such as parametric ‘optimisation’ plug-ins for Grasshopper, architects can seek out the designs appear to ‘best’ balance energy, environmental, and cost performance criteria. However, as one uses these tools, one must often make assumptions regarding exogenous environmental and economic parameters affecting a building’s development and life-cycle. These assumptions are often addressed ‘deterministically’, meaning that it’s not uncommon that one assigns only a single scenario for building development costs, site climate, and urban form in any given design investigation. This is set to change as we become more aware of the risks posed by ‘uncertainties’ in the high-performance building design process, such as the future impact of climate change on a building’s lifecycle and uncertain trends in building construction costs and construction quality. This long-term project represents a body of work examining the integration of uncertainty theory in simulation-based building design. As an interdisciplinary study, it engages design pedagogies along with techniques and practises developed in the fields of engineering and economics. It seeks to inform whether introducing the concept of ‘resiliency’ and ‘robustness’ into the parametric design process may yield new insights for the design of future buildings and communities. The work is funded by UBC and the Pacific Institute for Climate Solutions, via the Data-driven Building Retrofits project. Images above and below feature the work of Haobo Liu (M.Arch candidate) and Prof. Adam Rysanek.

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