Urban Science and High Performance Computing
AI/Machine Learning/Deep Learning
Big Data Analytics
TimeTuesday, June 26th11am - 11:25am
DescriptionUrban Science and High Performance Computing
This presentation will review research related to urban science, modeling energy use at a city scale, and high performance computing. Urban systems account for over 70% of energy and GHG in most countries, with a growing number of people living in urban environments. There is an urgent need to model energy use in cities, and understand how they are changing, identify opportunities to reduce energy use, integrate multiple sectors such as buildings and transportation, and prioritize investments in resilience and sustainability. The presentation will describe results from the Multiscale Coupled Urban Systems Exascale Computing Project, which is funded by the US Department of Energy. This project is a collaboration between several US DOE National Laboratories including Argonne National Laboratory, Lawrence Berkeley National Laboratory, National Renewable Energy Laboratory, Oak Ridge National Laboratory and Pacific Northwest National Laboratory. The talk will also describe urban data standards such as CityGML and the City Building Energy Saver tool.
Director Building Technology and Urban System Division