Multi-modality in augmented Lagrangian coordination for distributed optimal design

Tosserams, S.; Etman, L.F.P.; Rooda, J.E.

doi:10.1007/s00158-009-0371-7

Cited by 17 publications

(16 citation statements)

References 37 publications

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“…Another benchmarking problem that possesses some scalability is the microaccelerometer problem of Tosserams et al [207]. Test problems with lower dimensionality but with multiple local minima are presented by Tosserams et al [208]. We also feel that a test suite of MDO problems similar to the now-defunct NASA MDO suite [209] would be a great resource for researchers and practitioners.…”

Section: Architecture Benchmarking Issuesmentioning

confidence: 99%

Multidisciplinary Design Optimization: A Survey of Architectures

2013

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Multidisciplinary design optimization (MDO) is a field of research that studies the application of numerical optimization techniques to the design of engineering systems involving multiple disciplines or components. Since the inception of MDO, various methods (architectures) have been developed and applied to solve MDO problems. This paper provides a survey of all the architectures that have been presented in the literature so far. All architectures are explained in detail using a unified description that includes optimization problem statements, diagrams, and detailed algorithms. The diagrams show both data and process flow through the multidisciplinary system and computational elements, which facilitates the understanding of the various architectures, and how they relate to each other.A classification of the MDO architectures based on their problem formulations and decomposition strategies is also provided, and the benefits and drawbacks of the architectures are discussed from both a theoretical and experimental perspective. For each architecture, several applications to the solution of engineering design problems are cited. The result is a comprehensive but straightforward introduction to MDO for non-specialists, and a reference detailing all current MDO architectures for specialists.

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Section: Architecture Benchmarking Issuesmentioning

confidence: 99%

Multidisciplinary Design Optimization: A Survey of Architectures

2013

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“…MLHO and MSLO are demonstrated on multi-modal test problems which are taken from [132]. Computational efficiency of the schemes and their progress in finding the global optimum are evaluated based on the obtained results.…”

Section: Numerical Results and Discussionmentioning

confidence: 99%

“…This is demonstrated in the following examples. 3 and x * 4 as 0.5 and 2, respectively, by setting x 2 as either 0 or 2 and leaving x 1 free to take any value as long as the inequality constraint is satisfied [132].…”

Section: Numerical Results and Discussionmentioning

confidence: 99%

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Optimizing the dynamic behavior of structures using substructuring and surrogate modeling

Akcay-Perdahcioglu¹

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“…Among these we can find [201], where ATC and Augmented Lagrangian Coordination (ALC) are compared; the study of ALC in [202]; the same way that MDF, CO, and Individual Discipline Feasible (IDF) methods are compared in [203];…”

Section: Multidisciplinary Design Optimizationmentioning

confidence: 99%

RPAS Design : an MDO Approach

Aliaga-Aguilar¹

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Unmanned aircraft and, particularly, RPAS (Remotely Piloted Aircraft Systems) are nowadays experiencing great growth both in the military and civil industries. This is due to the fact that removing the need to be manned has enabled the improvement of their endurance, range, and overall performance while, at the same time, reducing the risk to which human lives were exposed. In addition, RPAS can be made much smaller. This decrease of mass and size increases the variety of missions they can perform. However, the design process to manufacture such aircraft is often long and costly, which prevents small companies from undertaking it. Multidisciplinary Design Optimization (MDO) is an engineering field whose focus is to solve highly complex problems by the means of optimization techniques. It has been used in the design of commercial aircraft for a long time, but integrating the various engineering disciplines that take part in designing an RPAS within an MDO to simplify the design process is a challenge. In addition, there is an ample variety of architectures for MDO projects and, the reasons to choose a particular one, have to be discussed on a case by case basis. During the last years, distributed architectures have become widespread, given that they can take advantage of parallel computing (even with graphical platforms) and reduce computing time. Adapting the formulation of a problem to a particular vii Dissertation Overview Chapter 1: This is the introduction to the thesis. It presents the evolution of RPAS and the current state of the art both in MDO and in RPAS design methodologies. Chapter 2 introduces the Generic Parameter Penalty Architecture (GPPA): a new, flexible MDO architecture, oriented towards the solution of engineering problems that present different levels of complexity. Chapter 3 introduces the RPAS Advanced MDO Platform (RAMP). A new MDO environment aimed at the design of small RPAS. Chapters 4-7 present RAMP's main analysis models: aerodynamics, structure, economy and pricing, propulsion, and performance. Chapter 8 presents an application case of RAMP to a real-world mission. Chapter 8 does so by limiting RAMP's configuration availability to just classical. This provides the opportunity to compare its results to most commercially available RPAS, while Chapter 9 unleashes RAMP's full capabilities to also consider Blended Wing Body (BWB) and Canard configurations. Chapter 9 presents results for the various tests and hypothesis that are presented in the thesis, while Chapter 10 serves to give shape to the conclusions of the thesis and the future lines of research.

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Multi-modality in augmented Lagrangian coordination for distributed optimal design

Cited by 17 publications

References 37 publications

Multidisciplinary Design Optimization: A Survey of Architectures

Multidisciplinary Design Optimization: A Survey of Architectures

Optimizing the dynamic behavior of structures using substructuring and surrogate modeling

RPAS Design : an MDO Approach

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