High-performance computing and data-driven modeling of aircraft contrails


Researchers: G. Elisabeta Marai, (co-PI), Roberto Paoli (PI, UIC MIE)

Funding: CBET-1854815: High-performance computing and data-driven modeling of aircraft contrails

In this project, we will develop a novel computational method to model the evolution of aircraft contrail (ice particles forming in aircraft engine’s exhaust) using high-performance computing. The specific goals of the research are: (1) to carry out the first fully three-dimensional spatial large-eddy simulations of contrail formation that include the aircraft geometry and to develop accurate data-set of contrail evolution in the early phases of the aircraft wake; (2) to identify the 3D contrail features and fit parameters by journaling the simulation workflow using advanced visualization techniques; and (3): to apply reduced-order modeling, such as Polynomial Chaos reconstructions, and machine-learning techniques, such as Artificial Neural Networks, to estimate model parameters and to reduce the large dimensionality of the problem to ease integration into global atmospheric models.



Date: July 1, 2019 - June 30, 2022

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