Approach to Modeling Boundary Layer Ingestion using a Fully Coupled Propulsion-RANS Model

Airframe-propulsion integration concepts that use boundary layer ingestion have the potential to reduce aircraft fuel burn. One concept that has been recently explored is NASA's Starc-ABL aircraft configuration, which offers the potential for 12% mission fuel burn reduction by using a turbo-electric propulsion system with an aft-mounted electrically driven boundary layer ingestion propulsor. This large potential for improved performance motivates a more detailed study of the boundary layer ingestion propulsor design, but to date, analyses of boundary layer ingestion have used uncoupled methods. These methods account for only aerodynamic effects on the propulsion system or propulsion system effects on the aerodynamics, but not both simultaneously. This work presents a new approach for building fully coupled propulsive-aerodynamic models of boundary layer ingestion propulsion systems. A 1D thermodynamic cycle analysis is coupled to a RANS simulation to model the Starc-ABL aft propulsor at a cruise condition and the effects variation in propulsor design on performance are examined. The results indicates that both propulsion and aerodynamic effects contribute equally toward the overall performance and that the fully coupled model yields substantially different results compared to uncoupled. The most significant finding is that boundary layer ingestion, while offering substantial fuel burn savings, introduces throttle dependent aerodynamics effects that need to be accounted for. This work represents a first step toward the multidisciplinary design optimization of boundary layer ingestion propulsion systems.

[1]  James L. Felder,et al.  Conceptual Design of a Single-Aisle Turboelectric Commercial Transport With Fuselage Boundary Layer Ingestion , 2016 .

[2]  Joaquim R. R. A. Martins,et al.  Multimission Aircraft Fuel-Burn Minimization via Multipoint Aerostructural Optimization , 2015 .

[3]  Howard E. Roberts,et al.  The Jet Airplane Utilizing Boundary Layer Air for Propulsion , 1947 .

[4]  Joaquim R. R. A. Martins,et al.  Aerodynamic Shape Optimization of Common Research Model Wing–Body–Tail Configuration , 2016 .

[5]  Riti Singh,et al.  Thermal cycle analysis of turboelectric distributed propulsion system with boundary layer ingestion , 2013 .

[6]  Olivier Atinault,et al.  Exergy-Based Formulation for Aircraft Aeropropulsive Performance Assessment: Theoretical Development , 2015 .

[7]  Scott M. Jones An Introduction to Thermodynamic Performance Analysis of Aircraft Gas Turbine Engine Cycles Using the Numerical Propulsion System Simulation Code , 2013 .

[8]  Leroy H. Smith Wake ingestion propulsion benefit , 1993 .

[9]  Joaquim R. R. A. Martins,et al.  Multipoint High-Fidelity Aerostructural Optimization of a Transport Aircraft Configuration , 2014 .

[10]  David L. Daggett,et al.  Blended Wing Body Systems Studies: Boundary Layer Ingestion Inlets with Active Flow Control , 2013 .

[11]  Joaquim R. R. A. Martins,et al.  Aerodynamic Design Optimization Studies of a Blended-Wing-Body Aircraft , 2014 .

[12]  Cody A. Paige,et al.  Automatic Differentiation Adjoint of the Reynolds-Averaged Navier-Stokes Equations with a Turbulence Model , 2013 .

[13]  Joaquim R. R. A. Martins,et al.  Aerodynamic Shape Optimization Investigations of the Common Research Model Wing Benchmark , 2015 .

[14]  Joaquim R. R. A. Martins,et al.  Thermodynamics of gas turbine cycles with analytic derivatives in OpenMDAO , 2016 .

[15]  Pericles Pilidis,et al.  Opportunities and challenges for distributed propulsion and boundary layer ingestion , 2014 .

[16]  Joaquim R. R. A. Martins,et al.  A CAD-Free Approach to High-Fidelity Aerostructural Optimization , 2010 .

[17]  Meng-Sing Liou,et al.  Optimal Shape Design of Mail-Slot Nacelle on N3-X Hybrid Wing-Body Configuration , 2013 .

[18]  Gregory Tillman,et al.  Aircraft System Study of Boundary Layer Ingesting Propulsion , 2012 .

[19]  Joaquim R. R. A. Martins,et al.  Extensions to the design structure matrix for the description of multidisciplinary design, analysis, and optimization processes , 2012, Structural and Multidisciplinary Optimization.

[20]  George F. Wislicenus,et al.  Hydrodynamics and Propulsion of Submerged Bodies , 1960 .

[21]  Richard L. Campbell,et al.  Computational Investigation of a Boundary Layer Ingestion Propulsion System for the Common Research Model , 2016 .

[22]  Kenneth T. Moore,et al.  Optimization of Turbine Engine Cycle Analysis with Analytic Derivatives , 2016 .

[23]  M. Drela Power Balance in Aerodynamic Flows , 2009 .

[24]  Sriram K. Rallabhandi,et al.  Inlet Trade Study for a Low-Boom Aircraft Demonstrator , 2016 .

[25]  Graeme J. Kennedy,et al.  Scalable Parallel Approach for High-Fidelity Steady-State Aeroelastic Analysis and Adjoint Derivative Computations , 2014 .

[26]  Olivier Atinault,et al.  Exergy-Based Performance Assessment of a Blended Wing–Body with Boundary-Layer Ingestion , 2015 .

[27]  Gerald V. Brown,et al.  Turboelectric Distributed Propulsion Engine Cycle Analysis for Hybrid-Wing-Body Aircraft , 2009 .

[28]  B. R. Williams,et al.  Viscous-inviscid interactions in external aerodynamics , 1987 .

[29]  Joaquim R. R. A. Martins,et al.  High-Fidelity Aerostructural Design Optimization of a Supersonic Business Jet , 2002 .

[30]  A. Betz Introduction to the Theory of Flow Machines , 1966 .

[31]  Meng-Sing Liou,et al.  Optimal Inlet Shape Design of N2B Hybrid Wing Body Configuration , 2012 .

[32]  Walter S. Gearhart,et al.  Selection of a Propulsor for a Submersible System , 1966 .

[33]  Jack J. McNamara,et al.  Towards an Aero-Propulso-Servo-Elasticity Analysis of a Commercial Supersonic Transport , 2016 .

[34]  J. Alonso,et al.  A Coupled-Adjoint Sensitivity Analysis Method for High-Fidelity Aero-Structural Design , 2005 .

[35]  M. Giles,et al.  Viscous-inviscid analysis of transonic and low Reynolds number airfoils , 1986 .

[36]  Joaquim R. R. A. Martins,et al.  Automatic evaluation of multidisciplinary derivatives using a graph-based problem formulation in OpeNMDAO , 2014 .