The aviation industry has recognized the challenges of its contribution to greenhouse gas emissions while being a critical component of the global economic infrastructure. One of the key strategies to significantly reduce the environmental footprint of the aviation industry is to radically change the propulsion system architecture to minimize energy utilization required for future aircraft, and primarily for the dominant aircraft market segment. As the trend of increasing bypass ratio for ducted turbofans is asymptoting, an architecture change to open fan propulsion is needed to attain nearly optimal propulsive efficiency. To realize the fuel burn and emissions improvement potential of the open fan, the integration of the engine on the wing and aircraft must be optimized. In this project, NASA, Boeing, and GE Aerospace are engaging in a collaboration to investigate the challenge of integrating an open fan on an aircraft in a wing-mounted configuration, for which installation effects are a key risk to realizing the efficiency gains associated with this propulsion architecture. This project focuses on developing a deep understanding of flow physics of the aircraft-installed open fan propulsor through high-fidelity simulations. The simulation data generated will be used to benchmark and improve computational design models through machine learning and physics-based methods. The use of these models would allow for more efficient and practical design optimization for the open fan aircraft installation. Predictive capabilities of the improved models will be assessed on integrated propulsion and aircraft in various configurations and flow conditions. High-fidelity simulations of such configurations require tens of billions of cell volumes to fully resolve the turbulence and highly varying flow velocities in the propulsion system and the airplane components. Exascale computing capacity available under the INCITE program is critically required for the success of this project.