Creation of a Model to Predict Indoor Air Quality Using BEopt, EnergyPlus, and Python
Session Number
J14
Advisor(s)
Brent Stephens, Illinois Institute of Technology
Location
A-131
Start Date
28-4-2016 8:25 AM
End Date
28-4-2016 8:50 AM
Abstract
Indoor air quality and energy consumption are factors that constantly impact our lives, but they have a negative health impact. My SIR involved writing a program to model these two factors using Python, BEopt (Building Energy Optimization), and EnergyPlus and was part of a 3 year project to model indoor air quality and building energy consumption, predict how this will change by 2050 and 2080, and determine the health impacts of these factors. I wrote 3 programs to do this. They calculate the indoor air quality from input values and graph the results, modify IDF files, the type of files that EnergyPlus uses, and run lists of files through EnergyPlus. Together, these programs can use an IDF file to find the indoor air concentration of PM2.5 (particles smaller than 2.5 micrometers) and UFP (ultrafine particles smaller than 0.1 micrometers). They do not deal with energy consumption since I was unable to work on this aspect. In addition, a few outlying data points throw the graphs off. The work I did will help the 3 year project and this will help the scientific community by providing the health impact of these pollutants and a projection for how this will change.
Creation of a Model to Predict Indoor Air Quality Using BEopt, EnergyPlus, and Python
A-131
Indoor air quality and energy consumption are factors that constantly impact our lives, but they have a negative health impact. My SIR involved writing a program to model these two factors using Python, BEopt (Building Energy Optimization), and EnergyPlus and was part of a 3 year project to model indoor air quality and building energy consumption, predict how this will change by 2050 and 2080, and determine the health impacts of these factors. I wrote 3 programs to do this. They calculate the indoor air quality from input values and graph the results, modify IDF files, the type of files that EnergyPlus uses, and run lists of files through EnergyPlus. Together, these programs can use an IDF file to find the indoor air concentration of PM2.5 (particles smaller than 2.5 micrometers) and UFP (ultrafine particles smaller than 0.1 micrometers). They do not deal with energy consumption since I was unable to work on this aspect. In addition, a few outlying data points throw the graphs off. The work I did will help the 3 year project and this will help the scientific community by providing the health impact of these pollutants and a projection for how this will change.