Document
Approach to Modeling Boundary Layer Ingestion using a
Fully Coupled Propulsion-RANS Model
Justin Gray, Charles A. Mader, Gaetan K.W. Kenway, Joaquim R. R. A. Martins th January 12 , 2017
Boundary Layer Ingestion (BLI) offers
between 5% and 12% fuel burn savings
Aft-mounted BLI propulsor Mail-slot inlet BLI propulsors Aft-mounted BLI engines Motivation Fully Coupled Propulsion-Aerodynamic Modeling
NASA’s Starc-ABL configuration applies
BLI to a traditional airframe
Tube-with-wings configuration Under-wing engines and generator Electric BLI propulsor Motivation Fully Coupled Propulsion-Aerodynamic Modeling
The BLI propulsor is powered by an
electric motor delivering a constant 3500 hp
3500 hp motor 2x 1925 hp generators (90% transmission efficiency) Turboelectric propulsion system has an electric BLI propulsor powered by generators mounted on the under-wing turbofans Motivation Fully Coupled Propulsion-Aerodynamic Modeling
We simplified the configuration to focus on
the coupled performance of the BLI propulsor
Loosely based on 737 fuselage dimensions Removed wing, tail, and under-wing engines to simplify the analysis Modeling Fully Coupled Propulsion-Aerodynamic Modeling
BLI propulsor performance was
compared to a podded configuration
Exact same propulsor geometry, including inlet, was used for both BLI and podded configurations Modeling Fully Coupled Propulsion-Aerodynamic Modeling
The propulsion analysis was a
1D thermodynamic cycle model
modeled with pyCycle, a modular propulsion cycle tool built in the OpenMDAO framework Modeling Fully Coupled Propulsion-Aerodynamic Modeling
The aerodynamic analysis was a
2D axisymmetric RANS model
Mach contours ˜170,000 cell mesh a single solve takes ˜2 minutes Modeling Fully Coupled Propulsion-Aerodynamic Modeling
The analyses were coupled via a Gauss-Seidel iteration
pyCycle → ADflow : fan-exit P and T t t and required ˙ m for 3500 hp ADflow → pyCycle : mass-averaged fan-face P and T t t GS and Broyden iterations implemented with OpenMDAO solvers Modeling Fully Coupled Propulsion-Aerodynamic Modeling
For any given FPR the propulsor is resized
and the mass-flow across the propulsor is balanced
FPR = 1.2 FPR = 1.35 baseline Modeling Fully Coupled Propulsion-Aerodynamic Modeling
Performance is examined via net force coefficient
2 f C = F - x 2 ρ V A ∞ ref ∞ C C F -fuse F -prop C should be negative, a decelerating force (i.e. drag) F -fuse C should be positive, an accelerating force (i.e. thrust) F -prop C can be positive or negative F - x Fan Pressure Ratio Trade Study Fully Coupled Propulsion-Aerodynamic Modeling
BLI offers 5 to 6 more force counts
for the same 3500 hp to the propulsor
Fan Pressure Ratio Trade Study Fully Coupled Propulsion-Aerodynamic Modeling
Propulsion-aerodynamic interactions cause the
boundary layer height to vary with FPR
FPR = 1.2 FPR = 1.35 baseline Fan Pressure Ratio Trade Study Fully Coupled Propulsion-Aerodynamic Modeling
Propulsion-aerodynamic interactions cause the
boundary layer height to vary with FPR
Fan Pressure Ratio Trade Study Fully Coupled Propulsion-Aerodynamic Modeling
Improved propulsor performance accounts
for 50-60% of the BLI performance gain
Of the 5 to 6 total counts of improvement C , F - x 3 counts come from increased C F -prop Fan Pressure Ratio Trade Study Fully Coupled Propulsion-Aerodynamic Modeling
Fuselage drag reduction contributed
40-50% of the BLI performance gain
Of the 5 to 6 total counts of improvement C , F - x 2 to 3 counts come from smaller C F -fuse Fan Pressure Ratio Trade Study Fully Coupled Propulsion-Aerodynamic Modeling
Reduction in C comes from an increased
F -fuse
surface static pressure on the aft-fuselage
the change in surface static pressure profile is a strong function of FPR Fan Pressure Ratio Trade Study Fully Coupled Propulsion-Aerodynamic Modeling
The performance gains from BLI come from a
combination of propulsion and aerodynamic effects
Capturing BLI effects requires a coupled simulation Aerodynamic effects are strongly influenced by inlet design and throttle setting Conclusions and Future Work Fully Coupled Propulsion-Aerodynamic Modeling
The performance gains from BLI come from a
combination of propulsion and aerodynamic effects
Capturing BLI effects requires a coupled simulation Aerodynamic effects are strongly influenced by inlet design and throttle setting Conclusions and Future Work Fully Coupled Propulsion-Aerodynamic Modeling
Next step is to perform optimization of this configuration
with propulsion and shape design variables
Thank you to: Transformational Tools and Technologies Project (TTT) for funding the OpenMDAO framework and pyCycle development Advanced Aviation Transportation Technologies (AATT) for funding my PhD research Jim Felder for his guidance and advice Conclusions and Future Work Fully Coupled Propulsion-Aerodynamic Modeling