Skip to main content

Aero-structural Optimization of a MALE Configuration in the AGILE MDO Framework

  • Conference paper
  • First Online:
Flexible Engineering Toward Green Aircraft

Part of the book series: Lecture Notes in Applied and Computational Mechanics ((LNACM,volume 92))

  • 450 Accesses

Abstract

Aircraft, and in particular military aircraft, are complex systems and the demand for high-performance flying platforms is constantly growing both for civil and  military purposes.  The development of aircraft is inherently  multidisciplinary and the exploitation of the interaction between the disciplines driving the design opens the door for new (unconventional) aircraft designs, and consequently, for novel aircraft having increased performance. In modern aircraft development processes and procedures, it is crucial to enable the engineers accessing complex design spaces, especially in the conceptual design phase where key configuration decisions are made and frozen for later development phases. Pushing more MDO and numerical analysis capabilities into the early design phase will support the decision-making process through reliable physical information for very large design spaces which can hardly be grasped and explored by humans without the support of automated numerical analysis capabilities. Therefore, from the start of the aircraft development, process computer simulations play a major role in the prediction of the physical properties and behavior of the aircraft. Recent advances in computational performance and simulation capabilities provide sophisticated physics based models, which can deliver disciplinary analysis data in a time effective manner, even for unconventional configurations. However, a major challenge arises in aircraft design as the properties from different disciplines (aerodynamics, structures, stability and control, etc.) are in constant interaction with each other. This challenge is even greater when specialized competences are provided by several multidisciplinary teams distributed among different organizations. It is therefore important to connect not only the simulation models between organizations, but also the corresponding experts to combine all competences and accelerate the design process to find the best possible solution. A multi-disciplinary study of an unmanned aerial vehicle (UAV), presented in this article, was performed by eight different partners all over Europe to show the advances during the Horizon 2020 project Aircraft 3rd Generation  MDO for Innovative Collaboration of Heterogeneous Teams of Experts (AGILE).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

AGILE:

Aircraft 3rd Generation MDO for Innovative Collaboration of Heterogeneous Teams of Experts

AVL:

Athena Vortex Lattice

CFD:

Computational Fluid Dynamics

CPACS:

Common Parametric Aircraft Configuration Scheme

CSV:

Comma Separated Value

DLR:

German Aerospace Center

DoE:

Design of Experiments

FSI:

Fluid Structure Interaction

ICAS:

International Council of the Aeronautical Sciences

MALE:

Medium Altitude Long Endurance

MDO:

Multidisciplinary Design Optimization

MLS:

Moving Least Squares

MTOW:

Maximum Take-Off Weight

MZFW:

Maximum Zero Fuel Weight

RBF:

Radial Basis Function

RCE:

Remote Component Environment

SEP:

Specific Excess Power

SU2:

Stanford University Unstructured

TSFC:

Thrust Specific Fuel Consumption

UAV:

Unmanned Aerial Vehicle

References

  1. AGILE Project. url: www.agile-project.eu.

  2. Ciampa, P. D., & Nagel, B. (2018). Streamlining cross-organizational aircraft development processes: An overview of the AGILE project. In 31th Congress of the International Council of the Aeronautical Sciences, Belo-Horizonte.

    Google Scholar 

  3. Ciampa, P. D., & Nagel, B. (2017). AGILE Paradigm: Developing the next generation collaborative MDO. In 18th AIAA ISSMO Multidisciplinary Analysis and Optimization Conference, Denver.

    Google Scholar 

  4. Van Gent, I., Ciampa, P. D., Aigner, B., Jepsen, J., La Rocca, G., & Schut, J., Knowledge architecture supporting collaborative MDO in the AGILE Paradigm. In AIAA Paper 2017-4139.

    Google Scholar 

  5. Lefebvre, T., Bartoli, N., Dubreuil, S., Panzeri, M., Lombardi, R., D’ Ippolito, R., et al. (2017). Methodological enhancements in MDO process investigated in the AGILE European project. In 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Denver.

    Google Scholar 

  6. Elssel, K., Petersson, Ö. (2016). AeroStruct - Schlussbericht, Airbus Defence and Space.

    Google Scholar 

  7. Fioriti, M., Boggero, L., Corpino, S., Prakasha, P. S., Ciampa, P. D., & Nagel, B. (2018). The effect of sub-systems design parameters on preliminary aircraft design in a multidisciplinary design environment. Elsevier Transportation Research Procedia, 29, 135–145.

    Article  Google Scholar 

  8. Fioriti, M., Boggero, L., Corpino, S., Isyanov, A., Mirzoyan, A., Lombardi, R., & D’Ippolito, R. (2017). Automated selection of the optimal on-board systems architecture. In 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Denver (US-CO).

    Google Scholar 

  9. Voskuijl, M., La Rocca, G., & Dircken, F., (2008). Controllability of blended wing body aircraft. In 26th Congress of International Council of the Aeronautical Sciences, Anchorage, Alaska, 14–19 September 2008.

    Google Scholar 

  10. Liersch, C., & Hepperle, M. (2011). A distributed toolbox for multidisciplinary preliminary aircraft design. CEAS Aeronautical Journal, 2, 57–68.

    Article  Google Scholar 

  11. Zhang, M., Jungo, A., Gastaldi, A. A., & Melin, T. (2018). Aircraft geometry and meshing with common language schema CPACS for variable-fidelity MDO applications. Aerospace, 5, 47.

    Article  Google Scholar 

  12. Tomac, M., & Eller, D. (2011). From geometry to CFD grids. An automated approach for conceptual design. Progress in Aerospace Sciences, 47(No. 11), 589–596.

    Google Scholar 

  13. Si, H. (2013). TetGen: A quality tetrahedral mesh generator and 3D delaunay triangulator. WIAS technical Report, No. 13.

    Google Scholar 

  14. Maierl, R., Petersson, Ö., & Daoud, F. (2013). Automated creation of aeroelastic optimization models from a parameterized geometry. In 15th International Forum on Aeroelasticity and Structural Dynamics, Bristol.

    Google Scholar 

  15. Maierl, R., Petersson, Ö., Daoud, F., & Bletzinger, K. U. (2015). Automatic generation of aeroelastic simulation models combined with a knowledge based mass prediction. 5th CEAS Air & Space Conference, Delft.

    Google Scholar 

  16. Beckert, A., & Wendland, H. (2001). Multivariate interpolation for fluid-structure interaction problems using radial basis functions. Aerospace Science and Technology, 5(2), 125–134.

    Article  Google Scholar 

  17. Rendall, T. C. S., & Allen, C. B. (2007). Unified fluid-structure interpolation and mesh motion using radial basis functions. International Journal for Numerical Methods in Engineering, 74, 1519–1559.

    Article  ADS  MathSciNet  Google Scholar 

  18. Schuhmacher, G., Daoud, F., Petersson, Ö, & Wagner, M. (2012). Multidisciplinary airframe design optimization. In 28th International Congress of the Aeronautical Sciences, Brisbane.

    Google Scholar 

  19. Anderson, J. D. (2000). Introduction to flight (4th ed). McGraw-Hill.

    Google Scholar 

  20. Baalbergen, E., Kos, J., Louriou, C., Campguilhem, C., & Barron, J. (2016). Streamlining cross-organisation product design in aeronautics. Proceedings of the Institution of Mechanical Engineers, Part G.

    Google Scholar 

  21. Seider D., Fischer P., Litz M., Schreiber A., & Gerndt A. (2012). Open source software framework for applications in aeronautics and space. In IEEE Aerospace Conference, Big Sky, MT, USA.

    Google Scholar 

  22. Palacios, F., Colonno, M. R., Aranake, A. C., Campos, A., Copeland, S. R., Economon, T. D., et al. (2013). Stanford University Unstructured (SU2): An open-source integrated computational environment for multi-Physics simulation and design, 51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, AIAA 2013–0287. Texas, USA: Grapevine.

    Google Scholar 

  23. Mason, W. (2002). FRICTION v3 url: http://www.dept.aoe.vt.edu/~mason/Mason_f/MRsoft.html#SkinFriction.

  24. ICAS—International Council of the Aeronautical Sciences url: https://www.icas.org/.

Download references

Acknowledgements

The research presented in this paper has been performed in the framework of the AGILE project (Aircraft 3rd Generation MDO for Innovative Collaboration of Heterogeneous Teams of Experts) and has received funding from the European Union Horizon 2020 Programme (H2020-MG-2014-2015) under grant agreement n\(^\circ \) 636202. The Swiss participation in the AGILE project was supported by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 15.0162. The authors are grateful to the partners of the AGILE consortium for their contributions and feedback.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Reinhold Maierl .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Maierl, R., Gastaldi, A., Walther, JN., Jungo, A. (2020). Aero-structural Optimization of a MALE Configuration in the AGILE MDO Framework. In: Biancolini, M., Cella, U. (eds) Flexible Engineering Toward Green Aircraft. Lecture Notes in Applied and Computational Mechanics, vol 92. Springer, Cham. https://doi.org/10.1007/978-3-030-36514-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-36514-1_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36513-4

  • Online ISBN: 978-3-030-36514-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics