Towards the Industrialization of New MDO Methodologies and Tools for Aircraft Design

An overall summary of the Institute of Technology IRT Saint Exupery MDA-MDO project (Multi-Disciplinary Analysis - Multidisciplinary Design Optimization) is presented. The aim of the project is to develop efficient capabilities (methods, tools and a software platform) to enable industrial deployment of MDO methods in industry. At IRT Saint Exupery, industrial and academic partners collaborate in a single place to the development of MDO methodologies; the advantage provided by this mixed organization is to directly benefit from both advanced methods at the cutting edge of research and deep knowledge of industrial needs and constraints. This paper presents the three main goals of the project: the elaboration of innovative MDO methodologies and formulations (also referred to as architectures in the literature 1) adapted to the resolution of industrial aircraft optimization design problems, the development of a MDO platform featuring scalable MDO capabilities for transfer to industry and the achievement of a simulation-based optimization of an aircraft engine pylon with industrial Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) tools.

[1]  François Gallard,et al.  An Adaptive Multipoint Formulation for Robust Parametric Optimization , 2015, J. Optim. Theory Appl..

[2]  Sebastien Defoort,et al.  Multidisciplinary Aerospace System Design: Principles, Issues and Onera Experience , 2012 .

[3]  Peter Schmollgruber,et al.  Investigation of Multi-Disciplinary Optimisation for Aircraft Preliminary Design , 2011 .

[4]  Joaquim R. R. A. Martins,et al.  Multidisciplinary design optimization: A survey of architectures , 2013 .

[5]  Kroo Ilan,et al.  Multidisciplinary Optimization Methods for Aircraft Preliminary Design , 1994 .

[6]  Kenneth T. Moore,et al.  OpenMDAO: An Open Source Framework for Multidisciplinary Analysis and Optimization , 2010 .

[7]  François Gallard.  Aircraft shape optimization for mission performance , 2014 .

[8]  Sobieszczanski Jaroslaw,et al.  Bi-Level Integrated System Synthesis (BLISS) , 1998 .

[9]  Ilan Kroo,et al.  Use of the Collaborative Optimization Architecture for Launch Vehicle Design , 1996 .

[10]  M. Powell.  A Direct Search Optimization Method That Models the Objective and Constraint Functions by Linear Interpolation , 1994 .

[11]  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.

[12]  M. Meaux,et al.  VISCOUS AERODYNAMIC SHAPE OPTIMIZATION BASED ON THE DISCRETE ADJOINT STATE FOR 3D INDUSTRIAL CONFIGURATIONS , 2004 .