An algorithm for rapid urban building energy model generation and simulation

Project Details

The Shoeboxer is an algorithm that abstracts an arbitrarily shaped building volume into a group of simplified ‘shoebox’ b uilding energy models. It is shown that for generic perimeter and core floorplans the algorithm provides a faster but comparably accurate simulation results of annual load profiles vis-à-vis multi-zone thermal models generated according to ASHRAE90.1 Appendix G guidelines. Envisioned applications range from rapid thermal model generation for urban building energy modelling to schematic architectural design.

Following a description of the algorithm, its ability to produce load profiles for equipment electricity, heating, lighting and cooling using a diverse urban massing model containing 121 fully conditioned buildings located in a variety of climates is demonstrated. The comparison yields Energy Use Intensity RMSEs of 5 to 10% compared to ASHRAE 90.1 compliant building energy models while reducing simulation times by a factor of 296.


We investigate the intersections of architectural design, sustainability, building performance simulation and computational design. We stand for excellence in teaching and research in the area of building technology, daylight and energy modeling, passive climate control strategies and performance driven design workflows in both urban and architectural scales.


Led by: Prof. Dr. Timur Dogan
Website: Cornell AAP Profile
Email: tkdogan[at]cornell.edu


Cornell University, AAP
240B Sibley Hall
Ithaca, NY 14853,USA