Skip to main content Accessibility help

Coupled aeropropulsive design optimisation of a boundary-layer ingestion propulsor

  • Justin S. Gray (a1) (a2) and Joaquim R. R. A. Martins (a3)


Airframe–propulsion integration concepts that use boundary-layer ingestion (BLI) 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 fuel burn reduction by using a turboelectric propulsion system with an aft-mounted electrically driven BLI propulsor. So far, attempts to quantify this potential fuel burn reduction have not considered the full coupling between the aerodynamic and propulsive performance. To address the need for a more careful quantification of the aeropropulsive benefit of the STARC-ABL concept, we run a series of design optimisations based on a fully coupled aeropropulsive model. A 1D thermodynamic cycle analysis is coupled to a Reynolds-averaged Navier–Stokes simulation to model the aft propulsor at a cruise condition and the effects variation in propulsor design on overall performance. A series of design optimisation studies are performed to minimise the required cruise power, assuming different relative sizes of the BLI propulsor. The design variables consist of the fan pressure ratio, static pressure at the fan face, and 311 variables that control the shape of both the nacelle and the fuselage. The power required by the BLI propulsor is compared with a podded configuration. The results show that the BLI configuration offers 6–9% reduction in required power at cruise, depending on assumptions made about the efficiency of power transmission system between the under-wing engines and the aft propulsor. Additionally, the results indicate that the power transmission efficiency directly affects the relative size of the under-wing engines and the aft propulsor. This design optimisation, based on computational fluid dynamics, is shown to be essential to evaluate current BLI concepts and provides a powerful tool for the design of future concepts.


Corresponding author


Hide All
1. Smith, A.M.O. and Roberts, H.E. The jet airplane utilizing boundary layer ingestion for propulsion, J Aeronautical Sciences, 1947, 14, (2), pp 97109.
2. Wislicenus, G.F. Hydrodynamics and propulsion of submerged bodies, J American Rocket Society, 1960, 30, pp 11401148.
3. Betz, A. Introduction to the Theory of Flow Machines . Pergamon Press, 1966. London.
4. Gearhart, W.S. and Henderson, R.E. Selection of a propulsor for a submersible system, J Aircraft, 1966, 3, (1), pp 8490.
5. Smith, L.H. Wake ingestion propulsion benefit, J Propulsion and Power, 1993, 9, (1), pp 7482.
6. Drela, M. Power balance in aerodynamic flows, AIAA J, 2009, 47, (7), pp 17611771, doi: 10.2514/1.42409.
7. Felder, J.L., Kim, H.D. and Brown, G.V. Turboelectric distributed propulsion engine cycle analysis for hybrid-wing-body aircraft, 47th AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition, AIAA 2009-1132, 2009, doi: 10.2514/6.2009-1132.
8. Drela, M. Development of the D8 transport configuration, 9th AIAA applied aerodynamics conference, AIAA 2011-3970, 2011, doi: 10.2514/6.2011-3970.
9. Liu, C., Doulgeris, G., Laskaridis, P. and Singh, R. Thermal cycle analysis of turboelectric distributed propulsion system with boundary layer ingestion, Aerospace Science and Technology, 2013, 27, (1), pp 163170.
10. Laskaridis, P., Pachidis, V. and Pilidis, P. Opportunities and challenges for distributed propulsion and boundary layer ingestion, Aircr Engineering and Aerospace Technology, 2014, 86, (6), pp 451458.
11. Welstead, J.R. and Felder, J.L. Conceptual design of a single-aisle turboelectric commercial transport with fuselage boundary layer ingestion, 54th AIAA aerospace sciences meeting, AIAA 2016-1027, 2016, doi: 10.2514/6.2016-1027.
12. Hardin, L., Tillman, G., Sharma, O., Berton, J. and Arend, D. Aircraft system study of boundary layer ingesting propulsion, 48th AIAA/ASME/SAE/ASEE joint propulsion conference and exhibit, AIAA-2012-2993, 2012, doi: 10.2514/6.2012-3993.
13. Uranga, A., Drela, M., Greitzer, E.M., Hall, D.K., Titchener, N.A., Lieu, M.K., Siu, N.M., Casses, C., Huang, A.C., Gatlin, G.M. and Hannon, J.A. Boundary layer ingestion benefit of the D8 transport aircraft, AIAA J, 2017, 55, (11), pp 36933708.
14. Gray, S., Mader, J., Kenway, C.A., , G.K.W. and Martins, J.R.R.A. Modeling boundary layer ingestion using a coupled aeropropulsive analysis, AIAA J Aircr, 2018, 55, pp 11911199.
15. Gray, J.S., Hearn, T.A., Moore, K.T., Hwang, J.T., Martins, J.R.R.A. and Ning, A. “Automatic Evaluation of multidisciplinary derivatives using a graph-based problem formulation in OpenMDAO, 15th AIAA/ISSMO multidisciplinary analysis and optimization conference, American Institute of Aeronautics and Astronautics, August 2014, doi: 10.2514/6.2014-2042.
16. Hwang, J.T. and Martins, J.R.R.A. A computational architecture for coupling heterogeneous numerical models and computing coupled derivatives. ACM Transactions on Mathematical Software, 2018, 44, (4), Article 37.
17. Lyu, Z., Kenway, G.K.W. and Martins, J.R.R.A. Aerodynamic shape optimization investigations of the common research model wing benchmark, AIAA J, 2015, 53, (4), pp 968985.
18. Lyu, Z., Kenway, G.K., Paige, C. and Martins, J.R.R.A. Automatic differentiation adjoint of the Reynolds-averaged Navier–Stokes equations with a turbulence model, 21st AIAA computational fluid dynamics conference, San Diego, CA, July 2013, doi: 10.2514/6.2013-2581.
19. Martins, J.R.R.A. and Hwang, J.T. Review and unification of methods for computing derivatives of multidisciplinary computational models, AIAA J, 2013, 51, (11), pp 25822599.
20. Coder, J.G., Pulliam, T.H., Hue, D., Kenway, G.K. and Sclafani, A.J. Contributions to the 6th AIAA CFD drag prediction workshop using structured grid methods, AIAA SciTech Forum, American Institute of Aeronautics and Astronautics, January 2017. doi: 10.2514/6.2017-0960.
21. Kenway, G.K.W., Secco, N.R., Martins, J.R.R.A., Mishra, A. and Duraisamy, K. An efficient parallel overset method for aerodynamic shape optimization, Proceedings of the 58th AIAA/ASCE/AHS/ASC structures, structural dynamics, and materials conference, AIAA SciTech Forum, January 2017, doi: 10.2514/6.2017-0357.
22. Kenway, G.K., Kennedy, G.J. and Martins, J.R.R.A. A CAD-free approach to high-fidelity aerostructural optimization, Proceedings of the 13th AIAA/ISSMO multidisciplinary analysis optimization conference, No. AIAA 2010-9231, Fort Worth, TX, September 2010, doi: 10.2514/6.2010-9231.
23. Luke, E., Collins, E. and Blades, E. A fast mesh deformation method using explicit interpolation, J Computational Physics, 2012, 231, (2), pp 586601.
24. Gray, J., Chin, J., Hearn, T., Hendricks, E., Lavelle, T. and Martins, J.R.R.A. Chemical equilibrium analysis with adjoint derivatives for propulsion cycle analysis, J Propulsion and Power, 2017, 33, (5), pp 10411052.
25. Hearn, D.T., Hendricks, E., Chin, J., Gray, J. and Moore, D.K.T. Optimization of turbine engine cycle analysis with analytic derivatives, 17th AIAA/ISSMO multidisciplinary analysis and optimization conference, Part of AIAA Aviation 2016 (Washington, DC), 2016, doi: 10.2514/6.2016-4297.
26. Jones, S. An introduction to thermodynamic performance analysis of aircraft gas turbine engine cycles using the numerical propulsion system simulation code, 2007, NASA TM-2007-214690.
27. Lambe, A.B. and Martins, J.R.R.A. Extensions to the design structure matrix for the description of multidisciplinary design, analysis, and optimization processes, Structural and Multidisciplinary Optimization, 2012, 46, pp 273284.
28. Greitzer, E., Bonnefoy, P., la Rosa Blanco, E.D., Dorbian, C., Drela, M., Hall, D., Hansman, R., Hileman, J., Liebeck, R., Lovegren, J., Mody, P., Pertuze, J., Sato, S., Spakovszky, Z., Tan, C., Hollman, J., Duda, J., Fitzgerald, N., Houghton, J., Kerrebrock, J., Kiwada, G., Kordonowy, D., Parrish, J., Tylko, J., Wen, E. and Lord, W. N+3 aircraft concept designs and trade studies, final report, NASA CR 2010-216794, National Aeronautics and Space Administration, 2010.
29. Bradley, M.K. and Droney, C.K. Subsonic ultra green aircraft research: Phase I final report, NASA CR 2011-216847, National Aeronautics and Space Administration, 2011.
30. Gray, J.S., Kenway, G.K.W. and Martins, J.R.R.A. Aero-propulsive design optimization of a turboelectric boundary layer ingestion propulsion system, 2018 AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Atlanta, GA, AIAA 2018-3976, June 2018.
31. Gill, P.E., Murray, W. and Saunders, M.A. SNOPT: an SQP algorithm for large-scale constrained optimization, SIAM Review, 2005, 47, (1), pp 99131.
32. Perez, R.E., Jansen, P.W. and Martins, J.R.R.A. pyOpt: a Python-based object-oriented framework for nonlinear constrained optimization, Structural and Multidisciplinary Optimization, 2012, 45, 101118.
33. Martins, J.R.R.A. and Lambe, A.B. Multidisciplinary design optimization: a survey of architectures, AIAA J, 2013, 51, pp 20492075.
34. McCullers, L.A. Aircraft configuration optimization including optimized flight profiles, NASA CR CP-2327, National Aeronautics and Space Administration, 1984.


Related content

Powered by UNSILO

Coupled aeropropulsive design optimisation of a boundary-layer ingestion propulsor

  • Justin S. Gray (a1) (a2) and Joaquim R. R. A. Martins (a3)


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.