Project Overview
Over the past three decades, urban planners have attempted to make cities more sustainable by espousing higher density urban design concepts such as Compact Cities, Walkable Communities, and New Urbanist developments. It has been argued by some urban planners that the per capita energy use and air pollution emissions in densely built cities are less than in their more sprawling less dense counterparts. Green infrastructure projects, in the form of parks, alteration of building rooftops, and the use of novel asphalt and concrete materials for streets and parking lots, have also been introduced to help reduce energy usage, mitigate pollution emissions, and improving the urban microclimate. Unfortunately, the complex effects of these interactions is not well understood on large urban scales.
Our interdiscplinary efforts aim at increasing knowledge for how the natural environment and urban form interact. Our hypothesis is that urban structures and well placed green infrastructure exist which can minimize energy use, while also minimizing air pollution exposure. We have been investigating the complex interactions between urban form, green infrastructure, and the environment across a variety of scales to better understand these relationships. The results from our efforts are designed to guide future urban projects, development, and policy.
Large-scale science simulation can assist in the optimization of urban form, green infrastructure, and energy conservation by exploring large problem domains. Our chief tool in performing these optimizations is an extremely fast and inexpensive energy use and dispersion modeling system that runs on the GPU. We utilize a suite of computationally based strategies to bridge different scales of the urban environment to improve our understanding for how green infrastructure interacts with the urban environment at local (neighborhood), city, and meso-scales (regional). Our GPU-based simulation codes are used within a genetic algorithm optimization structure to explore large problem domains narrowing down on sets of choices that satisfy many of our constraints and goals for energy use and pollution mitigation. We will also utilize an interactive and immersive virtual environment to provide unprecedented understanding and refinement of the complex physical processes associated with the energy balance and pollutant dispersion in an urban setting.
Additional Links
- GEnUSiS Project - Environmental Simulation within the Urban Environment
- GPU Environmental Simulation Software
Funding Source
GEnUSiS stands for Green Environmental Urban Simulations for Sustainability. This project uses large-scale simulation science to investigate the impact of green infrastructure projects on urban energy use and microclimate. This material is based upon work supported by the National Science Foundation under Grants No. CBET-1133590 (UMD), CBET-1134580 (Utah), and CBET-0828206 (UMD). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
- NSF Award: 1133590. 10/01/2011-09/30/2014. IDR-Collaborative Research: The impact of green infrastructure on urban microclimate and energy use.
- NSF Award: 0828206. Ended 01/31/2012. Collaborative Research: Optimization of Urban Designs for Air Quality and Energy Efficiency.
Related Thesis Documents
- Vegesna, A. Optimizing Urban Environmental Simulations using BOINC. M.S. Thesis, University of Minnesota Duluth. August 2013. PDF
- Halverson, S. Energy Transfer Ray Tracing with OptiX. M.S. Thesis, University of Minnesota Duluth. June 2012. PDF
- Clark, J. A Fast and Efficient Simulation Framework for Modeling Heat Transport. M.S. Thesis, University of Minnesota Duluth. January 2012. PDF
Collaborators
The project is supported by the National Science Foundation and is a highly collaborative project including colleagues from the University of Utah’s Mechanical Engineering and Atmospheric Sciences Departments and the University of Minnesota Duluth’s Department of Computer Science.