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A survey of multidisciplinary design optimization methods in launch vehicle design

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Abstract

Optimal design of launch vehicles is a complex problem which requires the use of specific techniques called Multidisciplinary Design Optimization (MDO) methods. MDO methodologies are applied in various domains and are an interesting strategy to solve such an optimization problem. This paper surveys the different MDO methods and their applications to launch vehicle design. The paper is focused on the analysis of the launch vehicle design problem and brings out the advantages and the drawbacks of the main MDO methods in this specific problem. Some characteristics such as the robustness, the calculation costs, the flexibility, the convergence speed or the implementation difficulty are considered in order to determine the methods which are the most appropriate in the launch vehicle design framework. From this analysis, several ways of improvement of the MDO methods are proposed to take into account the specificities of the launch vehicle design problem in order to improve the efficiency of the optimization process.

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Abbreviations

AAO:

All At Once

ATC:

Analytical Target Cascading

BLISS:

Bi-Level System Synthesis

CO:

Collaborative Optimization

CSSO:

Concurrent SubSpace Optimization

DIVE:

Discipline Interaction Variable Elimination

DyLeaf:

Dynamic Leader Follower

ELV:

Expendable Launch Vehicle

FPI:

Fixed Point Iteration

GA:

Genetic Algorithm

GAGGS:

Genetic Algorithm Guided Gradient Search

GLOW:

Gross Lift-Off Weight

GSE:

Global Sensitivity Equation

IDF:

Individual Discipline Feasible

LDC:

Local Distributed Criteria

MCO:

Modified Collaborative Optimization

MDA:

Muldisciplinary Design Analysis

MDF:

Multi Discipline Feasible

MDO:

Multidisciplinary Design Optimization

MOPCSSO:

Multi-Objective Pareto CSSO

MSTO:

Multi-Stage To Orbit

NAND:

Nested Analysis and Design

OBD:

Optimization Based Decomposition

RLV:

Reusable Launch Vehicle

RSM:

Response Surface Method

SAND:

Simultaneous Analysis and Design

SQP:

Sequential Quadratic Programming

SNN:

Single NAND NAND

SSA:

System Sensitivity Analysis

SSN:

Single SAND NAND

SSS:

Single SAND SAND

SSTO:

Single Stage To Orbit

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Authors and Affiliations

  1. Onera – The French Aerospace Lab, Palaiseau, France

    Mathieu Balesdent & Nicolas Bérend

  2. CNES, Launchers Directorate, Evry, France

    Mathieu Balesdent

  3. Ecole Centrale de Nantes, IRCCyN, Nantes, France

    Mathieu Balesdent, Philippe Dépincé & Abdelhamid Chriette

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  1. Mathieu Balesdent
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  2. Nicolas Bérend
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  3. Philippe Dépincé
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  4. Abdelhamid Chriette
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Correspondence to Mathieu Balesdent.

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The work presented in this paper is part of a CNES/ONERA PhD thesis attached to CNES’s HADES project (Help on Advanced launchers DESign).

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Balesdent, M., Bérend, N., Dépincé, P. et al. A survey of multidisciplinary design optimization methods in launch vehicle design. Struct Multidisc Optim 45, 619–642 (2012). https://doi.org/10.1007/s00158-011-0701-4

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