2022/08/03 by Nafiul Nipu, Nipu, Nafiul, Carla Floricel +7
Computer Science · Engineering · #Aerospace and Aviation Technology #Aerospace engineering #Air Traffic Management and Optimization #Artificial intelligence #Cluster analysis #Computer science #Domain (mathematical analysis) #Engineering #Environmental science #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Machine Learning (cs.LG) #Meteorology #Physics #Vehicle emissions and performance #cs.HC #cs.LG
paper · pdf · doi:10.48550/arxiv.2208.02321
published in arXiv (Cornell University) (Cornell University) · 11 Pages, 7 figures, IEEE VIS 2022
openalex publication_date 2022/08/03 · arxiv created 2022/08/08 · arxiv updated 2022/08/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/08
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.