Conference Paper

Performance Analysis of Optimized STARC-ABL Designs Across the Entire Mission Profile


A. Yildirim, J. S. Gray, C. A. Mader, and J. R. R. A. Martins


Proceedings of the AIAA SciTech Forum, 2021



Boundary layer ingestion (BLI) offers the potential for significant fuel burn reduction by exploiting strong aeropropulsive interactions. NASA’s STARC-ABL concept uses an electrically powered BLI tail cone thruster on what is otherwise a conventional airframe. Despite this conventional airframe, aeropropulsive integration is critical to the performance of the BLI propulsor. In particular, the aeropropulsive integration of the BLI system must account for the variation in fan performance. Because it is electrically powered, the fan pressure ratio and efficiency of the BLI tail cone thruster vary widely across the flight envelope. Thus, accurate performance prediction for this novel propulsion configuration requires using a coupled aeropropulsive model across the flight envelope. In this work, we introduce a method to quantify the benefit of BLI at off-design conditions. We analyze the off-design performance of 18 optimized designs using an aeropropulsive model that is built with the OpenMDAO framework to couple 3-D RANS CFD simulations to 1-D thermodynamic cycle analyses. The designs are generated via high-fidelity aeropropulsive design optimizations for a range of fan pressure ratio and thrust values at the cruise conditions for the STARC-ABL concept. Performance analyses are then performed at a range of off-design flight conditions that span the flight envelope, including low-speed and low-altitude flight conditions. This study provides the first set of high-fidelity data for the STARC–ABL configuration at off-design conditions. The results quantify the power savings through BLI compared to a traditional propulsion system across the entire mission profile. Finally, the results and techniques from this study will guide the extension of current aeropropulsive design capabilities to multipoint design optimizations.