MIT Sustainable Design Lab
Decision Support Tools


Over the years our lab has developed a series of software tools to support, architects, engineeering consultants, urban planners, municipalties and homeowners to make more informed design/buying decisions. A collection of those inititatives, some of which have evolved into commercial products, are shown below.

Daysim (since 2001) is a validated, RADIANCE-based daylight simulation engine that models the annual amount of daylight in and around buildings. DAYSIM allows users to model dynamic facades systems ranging from standard venetian blinds to state-of-the-art light redirecting elements, switchable glazings and combinations thereof.

DAYSIM web site | Source code on GitHub

DIVA-for-Rhino (since 2009) is a highly optimized daylighting and energy modeling plug-in for Rhinoceros 3D, a NURBS modeling software. DIVA was originally developed by members of our lab when we were at Harvard's Graduate School of Design. Nowadays, DIVA is actively expanded and distributed by Solemma LLC.

Download DIVA

mapdwell: In 2012 we developed a solar mapping technique that reliably predicts the annual electricity yield from photovoltaic arrays located across urban rooftops. This project grew into a spinoff called mapdwell LLC that provides urban mapping services to multiple cities including Boston, New York City and Santiago de Chile.

Download on itunes

Urban Modeling Interface (umi) (since 2012) is an effort by the Sustainable Design Lab to develop an urban modeling platform to evaluate the environmental performance of neighborhoods and cities with respect to operational and embodied energy use, walkability and daylighting potential.

Go to umi web site

ACCELERAD (2014 - 2017) is a free suite of programs for lighting and daylighting analysis and visualization. The suite uses physically-based backward ray tracing algorithms inspired by RADIANCE. These algorithms are accelerated up to twenty times faster using OptiX™, a ray tracing engine built for the graphics processor unit (GPU).

GitHub web site | SDL project web site