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.

Featured on NVIDIA's CUDA Spotlight

GPUs for Green Urban Planning - This week’s Spotlight is on Pete Willemsen of the University of Minnesota Duluth. Article is posted on NVIDIA's Spotlight Webpages

Sky View Factor for the 2.36km X 2.36km Salt Lake City Dataset - 2m resolution

slc temp data

This image represents the Salt Lake City 2.36km x 2.36km database at 2m resolution. The scene is made up of 2,312,300 patches and 2151 buildings. The Sky View Factor is calculated on the GPU using 256 rays per patch.

Video of QUIC Energy Application

Temperature Data for the Salt Lake City Dataset

slc temp data

Sky View Factor Data for the Salt Lake City Dataset

slc svf data