Visualization of Parameters from Multiple Numerical Simulations

Visualization of a contrail’s lifecycle that forms due to water vapor condensing around small dust particles.

About

This research project awarded me the University of Illinois Chancellor’s Undergraduate Research Award in 2020 and was featured on the university’s Computer Science news site. Under supervision from professor G. Elisabeta Marai, because the engines on aircrafts emit particles and very hot gases, I wanted to visualize how they may contribute towards climate change. One of the main goals for the project is to predict and understand the lifecycle of a contrail that forms due to water vapor condensing around small dust particles.

Below you can see a two-dimensional heatmap visualization of the points being cooled after being heated due to the engine, and then interacting with the low pressure at higher altitudes.

To get a better understanding of the temperature’s state, I elected for brighter colors to indicate hot matter and a dark blue for more colder positions. When highlighting your mouse cursor on a point, an info box will appear above detailing information on that point’s position and temperature. The radius of each point can also be adjusted with a slider that can make the points on the graph smaller or bigger from a range of one to four, with the default being two.

To see more about the data (such as CSV), click the “Observable” button at the bottom of this page, and if you would like to see a more technical detail of my research, please check out my page by clicking the button below labeled “My Research Page”.

2D Heatmap Visualization of Lagrangian Field Temperature

Details

Using the contrail data provided from the team, I chose the Lagrangian Field and exported to a CSV file every point’s temperature data and position. I thought that since airplanes travel in a linear fashion from point A to point B, a 2D representation of the temperature data would suffice. The heatmap is hosted on an observable notebook that I created using the d3 library, and using d3 helps make visualizing data easier and importing the time-step CSV files a breeze. Porting this visualization to consumer computing devices helps later reference this data much easier. Opening and viewing the contrails data requires a minimum of 128GB of RAM and a lot of computational power to render. Now, using JavaScript, it’s much more bearable to reference!

Observable My Research Page