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

  • Reinhold MaierlEmail author
  • Alessandro Gastaldi
  • Jan-Niclas Walther
  • Aidan Jungo
Conference paper
  • 22 Downloads
Part of the Lecture Notes in Applied and Computational Mechanics book series (LNACM, volume 92)

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).

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

Notes

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.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Reinhold Maierl
    • 1
    Email author
  • Alessandro Gastaldi
    • 1
  • Jan-Niclas Walther
    • 2
  • Aidan Jungo
    • 3
  1. 1.Airbus Defence and SpaceManchingGermany
  2. 2.German Aerospace CenterHamburgGermany
  3. 3.CFS Engineering, EPFL Innovation ParkLausanneSwitzerland

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