“Calculating Transmission Loss using Finite-Element Analysis,” Kevin Papiernik
Abstract: COMSOL is a finite-element analysis/solver that serves as a tool for the creation of various models. It is useful in many engineering fields as it uses multi-physics coupling to create models and run simulations. With the acoustics physics module (pressure acoustics, frequency domain), a model was created that sends sound from a single point across a window. This creates a sound pressure level and an acoustic pressure on both sides of the window that will allow for the calculation of transmission loss, the difference in the sound intensity level, as sound crosses the window. With this information, the model can be used in future simulations to detect whether certain window coatings reduce sound transmissions. In addition, different mesh sizes were applied to determine how much the mesh change would affect the results of the transmission loss calculation. The model will become the baseline model used to test whether the addition of certain materials will affect the transmission loss and whether adding layers of different materials will improve or worsen transmission loss.

Bio: Kevin Papiernik is a research aide intern working in Energy Systems. Kevin went to the College of DuPage for his freshman year and is transferring to Iowa State, where he will major in chemical engineering.

“Developing Future Weather Files for Infrastructure Modeling,” Emma Lane
Abstract: The Energy Systems Division (ES) wants to study the impacts of climate variation on the energy use of buildings. Scientists in the Environmental Science Division (EVS) have developed a weather research and forecasting (WRF) model to generate future predictions of weather conditions. EVS will use this data to study the effects of climate variation on many things, such as changes in infrastructure, crop yields, hydrological aspects, and extreme weather patterns. ES will use this data to run simulations in EnergyPlus, a building energy simulation, to study the effect of climate variation on building energy use, design, and the electric grid. First, the data is extracted from the files received from EVS. Necessary calculations are performed on each of the datum. The 3-hour data is then converted into hourly data, and finally put into the standard EnergyPlus Weather (EPW) file format. With the completion of this program, ES can create a library of fully functional future weather files to run in simulations.

Bio: Emma recently graduated from Metropolitan Community College in Kansas City, MO​.In the fall, she will attend Missouri University of Science and Technology to finish her bachelor’s in environmental engineering.

“Clustering of Smart Meter Data to Identify Electric Vehicle Chargine,” Joseph Garcia
Abstract: Electric vehicles (EVs) are becoming more practical and economic alternatives to their gas-fueled counterparts as they provide an opportunity to reduce greenhouse gas emissions. Without guidance, customers are prone to exhibit random charging behaviors that are likely to increase the peak demand load. To mitigate the risk to the utility grid, it is essential that utility companies gain insight on whether a customer owns an EV and their charging behavior. To extract these insights, machine learning has been used on household smart meter data. This research develops an unsupervised machine learning process to identify EV home charging based on anonymous smart meter data from ComEd that is separated by ZIP+4 Code. A Python module is designed to synthesize two clustering algorithms, k-means and Birch from the ​“Scikit-learn” library, which will be used to find the daily energy load curves that best represent EV home charging. The criteria for cluster selection is based on the percentage of EV ownership within a ZIP Code and that charging adds 1.5-7 kW to a household’s energy load. The initial data set includes residential single homes located in 60302, a ZIP Code belonging to Oak Park, IL.

Bio: Joseph is an undergraduate at the University of Illinois at Urbana-Champaign studying electrical engineering. He received his Associate of Science degree at Joliet Junior College.