A digital workflow to quantify regenerative urban design in the context of a changing climate.

The regenerative approach to design goes beyond limiting the environmental impact of the built environment and towards the enrichment of the ecosystem, adaptation to climate change, and the improvement of human health. This concept is being applied to buildings through new standards such as the Living Building Challenge, yet examples of implementation of regenerative design at the urban scale are rare. While this is a promising direction for sustainable design, in theory new metrics, design tools and workflows need to be developed to translate regenerative design concepts into practice effectively. Among other factors, barriers to implementation remain rooted in the shortcomings of existing urban simulation tools to evaluate a wide range of performance metrics simultaneously. This paper thus proposes a prototype workflow to evaluate regenerative performance using existing evaluation tools in a single digital workflow. A series of existing and customised plugins, most of which are already in use and open source, were integrated into a multi-parametric workflow based on the Grasshopper visual programming tool. The workflow was tested on Malaga as a case study and incorporated key performance indicators related to outdoor human thermal comfort, biophilia, daylight performance, and energy use and production, based on data exchange and synergies across the different tools. These indicators were evaluated for present and future climate scenarios obtained from a weather generator. This paper demonstrates the potential of this workflow to receive visual feedback on various aspects of regenerative urban design, thus enabling designers to more effectively pursue an evidence-based urban design process. • Key Performance Indicators for Regenerative Design defined for an urban context. • Multi-layered parametric workflow based on data exchange defined in Grasshopper. • Importance of connecting algorithms to evaluate performance highlighted. • Modelling of future climates, urban energy, and environmental quality discussed. • Findings may improve adoption of evidence-based urban design. [ABSTRACT FROM AUTHOR]