Visual Analysis and Detection of Contrails in Aircraft Engine Simulations
This work addresses the challenge of interpreting contrail formation in simulations for climate science and aviation researchers, but it is incremental as it builds on existing simulation and clustering methods.
The authors tackled the problem of analyzing computationally intensive aircraft engine simulations to define and characterize contrails, proposing a visual computing system that assists in detecting contrail shapes and analyzing parameters across simulation runs, with evaluation showing it successfully aids domain experts in contrail data investigation.
Contrails are condensation trails generated from emitted particles by aircraft engines, which perturb Earth's radiation budget. Simulation modeling is used to interpret the formation and development of contrails. These simulations are computationally intensive and rely on high-performance computing solutions, and the contrail structures are not well defined. We propose a visual computing system to assist in defining contrails and their characteristics, as well as in the analysis of parameters for computer-generated aircraft engine simulations. The back-end of our system leverages a contrail-formation criterion and clustering methods to detect contrails' shape and evolution and identify similar simulation runs. The front-end system helps analyze contrails and their parameters across multiple simulation runs. The evaluation with domain experts shows this approach successfully aids in contrail data investigation.