GEMS, a Generic Engine for MDO Scenarios : Key Features in Application

Gallard, François; Barjhoux, Pierre-Jean; Olivanti, Romain; Gazaix, Anne

doi:10.2514/6.2019-2991

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…They found that monolithic architectures were better than distributed. Other examples are openMDAO [38,39], developed by NASA, and GEMS [40,41], developed at IRT Saint Exupery.…”

Section: Choice Of Architecturementioning

confidence: 99%

Multidisciplinary Optimisation of Aircraft Structures with Critical Non-Regular Areas: Current Practice and Challenges

et al. 2021

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The design optimisation of aerostructures is largely based on Multidisciplinary Design Optimisation (MDO), which is a set of tools used by the aircraft industry to size primary structures: wings, large portions of the fuselage or even an entire aircraft. The procedure is computationally expensive, as it must account for several thousands of loadcases, multiple analyses with hundreds of thousands of degrees of freedom, thousands of design variables and millions of constraints. Because of this, the coarse Global Finite Element Model (GFEM), on which the procedure is based, cannot be further refined. The structures represented in the GFEM contain many components and non-regular areas, which require a detailed modelling to capture their complex mechanical behaviour. Instead, in the GFEM, these components are represented by simplified models with approximated stiffness, whose main role is to contribute to the identification of the load paths over the whole structure. Therefore, these parts are kept fixed and are not constrained during the optimisation, as the description of their internal deformation is not sufficiently accurate. In this paper, we show that it would nevertheless be desirable to size the non-regular areas and the overall structures at once. Firstly, we introduce the concept of non-regular areas in the context of a structural airframe MDO. Secondly, we present a literature survey on MDO with a critical review of several architectures and their current applications to aircraft design optimisation. Then, we analyse and demonstrate with examples the possible consequences of neglecting non-regular areas when MDO is applied. In the conclusion, we analyse the requirements for alternative approaches and why the current ones are not viable solutions. Lastly, we discuss which characteristics of the problem could be exploited to contain the computational cost.

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“…They found that monolithic architectures were better than distributed. Other examples are openMDAO [38,39], developed by NASA, and GEMS [40,41], developed at IRT Saint Exupery.…”

Section: Choice Of Architecturementioning

confidence: 99%

Multidisciplinary Optimisation of Aircraft Structures with Critical Non-Regular Areas: Current Practice and Challenges

et al. 2021

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“…Algorithm 1 was implemented using the Generic Engine for MDO Scenarios (GEMS) (Gallard et al, 2018) in Python. The tool offers an efficient way to test multilevel formulations, with built-in classes that facilitate optimization problems manipulations (Gallard et al, 2019). The continuous optimization problems (i.e., evaluations of Ψ ) are solved with the Method of Moving Asymptotes (MMA) (Svanberg, 2002) as implemented in the nonlinear-optimization (NLOPT) package (Johnson, 2008).…”

Section: Implementation Details and Comparison Solversmentioning

confidence: 99%

A bi-level methodology for solving large-scale mixed categorical structural optimization

Barjhoux

Diouane

Grihon

et al. 2020

Struct Multidisc Optim

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In this paper, large scale structural optimization problems involving both non-ordinal categorical and continuous design variables are investigated. The aim is to minimize the weight of a truss structure with respect to the cross-section areas, with optimal materials and cross-section type selection. The targeted structure counts more than one hundred elements. The proposed methodology consists of using a bi-level decomposition involving two problems, named master and slave. For given categorical choices, the slave addresses the continuous variables of our optimization problem. The master consists of minimizing a first order like approximation of the slave problem with respect to the categorical design variables. Such approximation helps to drastically reduce the combinatorial raised by the

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“…Step 5 is handled by the MDO library GEMS [7], [8], which usage along with MARILib is briefly introduced in the present paper.…”

Section: Fig 2 Optimization Loopmentioning

confidence: 99%

“…GEMS is a MDO framework, which offers many possibilities to build, run and post process complex multidisciplinary design problems based on a catalog of MDO formulations [7] [8].…”

Section: Interfacing With the Gems Mdo Librarymentioning

confidence: 99%

A Multidisciplinary Airplane Research Integrated Library With Applications To Partial Turboelectric Propulsion

Druot

Belleville

Roches

et al. 2019

AIAA Aviation 2019 Forum

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The aim of this paper is to present a new model library developped as a new test case to benchmark optimization algorithms and Multidisciplinary Design Optimization (MDO) formulations. It introduces the MARILib software (Multidisciplinary Airplane Research Integrated Library). MARILib's first objective is to provide models for research on a wide range of aircraft concepts, from business jets to super jumbos, and also some unconventional configurations, through an Overall Aircraft Design (OAD) approach. The second objective is to share a new benchmark test case for MDO strategies, which does not raise intellectual property issues. The third objective is to describe a case study for educational and training purposes. MARILib will be available as Open Source.

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GEMS, a Generic Engine for MDO Scenarios : Key Features in Application

Cited by 5 publications

References 13 publications

Multidisciplinary Optimisation of Aircraft Structures with Critical Non-Regular Areas: Current Practice and Challenges

Multidisciplinary Optimisation of Aircraft Structures with Critical Non-Regular Areas: Current Practice and Challenges

A bi-level methodology for solving large-scale mixed categorical structural optimization

A Multidisciplinary Airplane Research Integrated Library With Applications To Partial Turboelectric Propulsion

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