Live Webinar on Thursday
MIT Developer Led
Urban Heat Island Modeling with Dragonfly
Register to receive a recording or to attend live
https://attendee.gototraining.com/42b11/register/5727370740465560322
Global warming; urban heat island; weather variations from large water bodies and high altitude. All of these factors can affect a given climate and yet they operate on a scale so large that we don?t know their relative magnitude or even think of them as measurable phenomena. This session will introduce the Dragonfly plugin, which was built to help understand these large-scale climate variations. Specifically, this session will show how to warp epw weather files to account for urban heat island - the condition where an urban area is a few degrees warmer than the surrounding rural area. Using city geometry in Rhino, the Dragonfly plugin, and the Urban Weather Generator engine, we will alter an existing rural epw to account for the heat island of the city. The resulting files can be used for more accurate energy simulations and outdoor comfort analysis. They can also help test strategies to optimize the heat island for greater outdoor comfort in developing cities.
About the Presenter
Chris Mackey is a building scientist and designer at Payette Architects as well as a recent graduate of MIT?s Masters of Architecture and Masters of Science in Building Technology
programs. His completed thesis involved the development of software to produce high-resolution thermal comfort maps of buildings off of EnergyPlus results as well as a new suite of spatial thermal comfort metrics that mirror those currently used to quantify daylight.
SKILLS & TOPICS: Chris has intimate knowledge of the following languages / software: Python, Grasshopper, Rhino (incl. RhinoCommon), EnergyPlus, OpenStudio. In his free time,
Chris is an avid contributor to the Ladybug + Honeybee environmental analysis plugins for grasshopper and is currently in the process of building a new ?insect? to link these two plugins and the Rhino/Grasshopper interface to macro-scale climate modeling engines and data sets.
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