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

Gazaix, Anne; Gallard, François; Gachelin, Vincent; Druot, Thierry; Grihon, Stéphane; Ambert, Vincent; Guénot, Damien; Lafage, Rémi; Vanaret, Charlie; Pauwels, B.; Bartoli, Nathalie; Lefèbvre, Thierry; Sarouille, Patrick; Desfachelles, Nicolas; Brézillon, Joël; Hamadi, Maxime; Gürol, Selime

doi:10.2514/6.2017-3149

Cited by 16 publications

(14 citation statements)

References 6 publications

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“…In this section, the results of the visualization enhancements will be presented with regard to a tool repository containing a collection of DUT aircraft design tools. 9 This use case concerns the aerostructural optimization of an aircraft wing. The starting point of this case is a tool repository containing over 28,000 variables and over 37,000 data connections based on 29 function nodes.…”

Section: Resultsmentioning

confidence: 99%

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Graph-based algorithms and data-driven documents for formulation and visualization of large MDO systems

et al. 2018

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A new system is presented that enables the visualization of large multidisciplinary design optimization (MDO) problems and their solution strategy. It was developed within the scope of the European project AGILE. In AGILE, collaborative MDO is performed in large, heterogeneous teams of experts by solving MDO problems using a collection of design and analysis tools. This paper focuses on the visualizations required to support the formulation phase of an MDO project. The Knowledge and graph-based AGILE Design for Multidisciplinary Optimization System (KADMOS), an open-source MDO support system developed by Delft University of Technology, uses graph-based analysis to formulate an MDO problem and its solution strategy, based on the disciplinary analyses available in a repository. The results of KADMOS are stored in the standardized format CMDOWS (Common MDO Workflow Schema), which comprises the entire information on an MDO system. Although, based on Extensible Markup Language, the readability of the CMDOWS file is quite poor also for MDO experts, especially for large MDO systems involving thousands of variables. Providing visualization capabilities to thoroughly inspect the outcome of the different MDO formulation steps becomes a key factor to enable the specification of large MDO systems in a heterogeneous team. Therefore, VISTOMS (VISualization TOol for MDO Systems), a dynamic visualization package, was developed by RWTH Aachen University to enable the visualization and inspection of the different MDO system specification steps, thereby removing one of the main hurdles for using MDO as a development process. The developed visualization capabilities are demonstrated by means of an aerostructural wing design optimization project. Keywords MDO · Visualization · KADMOS · CMDOWS · VISTOMS Abbreviations

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Section: Resultsmentioning

confidence: 99%

“…XDSM The enhanced XDSM visualization developed in this research is based on the open-source XDSMjs package, which was released by Lafage in 2016 [9,18]. The main structure is the same as the conventional XDSM (see Fig.…”

Section: Visualization Techniques For Cmdows Filesmentioning

confidence: 99%

Graph-based algorithms and data-driven documents for formulation and visualization of large MDO systems

et al. 2018

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“…Methods compatible with the industrial settings are more likely to be accepted and applied in industry because they will have lower risks to implementation. One recent example is a version of the Bi-Level Integrated System Synthesis currently under development at IRT Saint Exupery [6]. A top level optimiser controls the shared design variables and domain level optimisers set the values for the local variables.…”

Section: Introductionmentioning

confidence: 99%

“…A top level optimiser controls the shared design variables and domain level optimisers set the values for the local variables. Over successive iterations between the two levels, Gazaix et al [6] showed that the process is able to converge to a feasible optimal result when applied to academic and industrial test cases. One of the main disadvantages of this method however is that the shared variables are exclusively controlled at a system level.…”

Section: Introductionmentioning

confidence: 99%

Pattern Search Algorithm for Blackboard-Based Multidisciplinary Design Optimization Frameworks

Jelev

Keane

Holden

2019

Journal of Aircraft

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Preliminary aircraft design necessitates the use of a range of analysis tools, which are often scattered among many departments in an organisation and require regular tuning from skilled operators. For this reason, a distributed Multidisciplinary Design Optimisation approach that permits individual organisational domains to use their preferred analysis and optimisation tools would be most suitable. This paper revisits a Blackboard framework, which uses simple heuristics to automatically guide organisational design domains to a single optimum by narrowing the bounds on the shared design variables. The authors present a newly developed rule base for this legacy framework, which has been given the title "Multidisciplinary Pattern Search". Two examples, one of which is for conceptual transonic wing design, demonstrate the merit of the newly developed rule base, database and visualisation modules. They also serve as a means for comparisons with two established Multidisciplinary Design Optimisation architectures. The results indicate that the Blackboard performs better than the distributed Collaborative Optimisation approach, albeit worse than the monolithic Simultaneous Analysis and Design method that tends to be organisationally disruptive to implement.

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“…11 In particular, GEMS (Generic Engine for MDO Scenarios), an in-house Python framework, is used to generate the optimization processes and host the present methodology.…”

Section: Implementation Of the Architecturesmentioning

confidence: 99%

On the Consequences of the "No Free Lunch" Theorem for Optimization on the Choice of an Appropriate MDO Architecture

Vanaret¹,

Gallard²,

Martins

2017

18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 18241To link to this article: DOI : 10.2514/6.2017-3148 URL : https://doi.org/10. 2514/6.2017-3148 Any correspondence concerning this service should be sent to the repository administrator: staff-oatao@listes-diff.inp-toulouse.fr Multidisciplinary Design Optimization (MDO) based on high-fidelity models is challenging due to the high computational cost of evaluating the objective and constraints. To choose the best MDO architecture, a trial-and-error approach is not possible due to the high cost of the overall optimization and the complexity of each implementation. We propose to address this issue by developing a generic methodology that applies to any (potentially expensive) design optimization problem. The methodology consists in generating a scalable analytic replacement function that can be quickly computed, yet captures the structure and behavior of the original high-fidelity problem. One crucial characteristic of this replacement model is that the number of inputs and outputs can be set independently, making the problem scalable. This facilitates the evaluation of MDO architectures for the original MDO problem. The methodology is applied to two academic MDO test cases: a supersonic business jet design problem and a propane combustion problem. Well-known architectures (Multidisciplinary Feasible (MDF) and Individual Disciplinary Feasible (IDF)) are benchmarked on various instances to demonstrate the dependency between the performance of the architecture and the dimensions of the problem. The results show that the "no free lunch" theorem of optimization, which states that no particular optimization algorithm holds an advantage over another when considering all possible problems, also applies to the choice of the best suited MDO architecture for an MDO problem with scalable dimensions.

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

Cited by 16 publications

References 6 publications

Graph-based algorithms and data-driven documents for formulation and visualization of large MDO systems

Graph-based algorithms and data-driven documents for formulation and visualization of large MDO systems

Pattern Search Algorithm for Blackboard-Based Multidisciplinary Design Optimization Frameworks

On the Consequences of the "No Free Lunch" Theorem for Optimization on the Choice of an Appropriate MDO Architecture

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