Spatiotemporal Modeling:COVID-19

2020 ~ Present | GTRI, Perkins and Will

Goals

The built environment plays a fundamental role in hour daily life. It impacts our health, performance, stress levels, social relations, and even the contagion of COVID-19. This project explores expanding the Building Performance Analytics towards a dynamic spatiotemporal framework, studying the characteristics of spaces combined with human activities and organizational processes that influence everyone’s lives.

This semester’s specific goal is to explore the spatiotemporal dynamic of COVID-19 pandemic and its spread in built environments. The dynamic of the spread has been modeled from a virus-centric perspective, at cities and global scales. The current models do not incorporate spatial variables beyond social distance. Even though research indicates that one of the main routes of virus transmission are droplets in built environments, including airflows.

We will work on 3D modeling, spatial analytics, agent-based simulations, process simulations, CFD and airflow simulations, and mathematical models of the virus spread.

Issues Involved or Addressed

On the one hand, current spatial analytics focuses on the static aspects of a building. On the other hand, dynamic variables such as a pandemic spread, focus on the mathematical models. Spatiotemporal modeling and simulation will merge the dynamic variables inside spaces, focusing on analyzing human-centered outcomes, such as performance, health, stress levels, and social interactions.

Methods and Technologies

  • Review current research and safety practices
  • Expert Lectures
  • Modeling and Simulation Parameters
  • Modeling and Simulation Implementation
  • COVID-19 Spread Analytics
  • Building Attributes impact on Virus Spread
  • Parametric Analysis
  • Case Study / Project
  • Proposals

Academic Majors of Interest

  • IT Management
  • Computational Science and Engineering
  • Computer Science
  • OMSCS synchronous
  • Architecture
  • Geographic Information Science and Technology
  • Aerospace Engineering
  • Health Systems
  • Industrial Engineering
  • Psychology
  • Statistics

Preferred Interests and Preparation

Areas: Computational Design, Architecture, Computer Science, Industrial Engineering, Systems Engineering, Business Analytics, Psychology, Statistics.

Background/interest: Experience or willingness to learn modeling and simulation.

Meeting Schedule & Location

Time 
12:30-1:20
Meeting Location 
Klaus 1440
Meeting Day 
Tuesday

Team Advisors

Dr. Paula Gómez
  • Georgia Tech Research Institute
Dr. Matthew Swarts
  • Georgia Tech Research Institute

Partner(s) and Sponsor(s)

GTRI, Perkins and Will