Andrew Sang’s research while affiliated with Massachusetts Institute of Technology and other places

One widely recognized opportunity to reduce global carbon emissions is to make urban neighborhoods more resource efficient. Significant effort has hence gone into developing computer-based design tools to ensure that individual buildings use less energy. While these tools are increasingly used in practice, they currently do not allow design teams to model groups of dozens or hundreds of buildings effectively, which is why a growing number of research teams are working on dedicated urban modeling tools. Many of these teams concentrate on isolated sustainable performance aspects such as operational building energy use or transportation; however, limited progress has been made on integrating multiple performance aspects into one tool and/or on penetrating urban design education and practice. In this paper a new Rhinoceros-based urban modeling design tool called umi is presented which allows users to carry out operational energy, daylighting and walkability evaluations of complete neighborhoods. The underlying simulation engines are EnergyPlus, Radiance/Daysim as well as a series of Grasshopper and Python scripts. Technical details of umi along with a case study of a mixed use development in Boston are documented.