Journal ArticleDOI
Comparison of MDO methods with mathematical examples
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TLDR
Multidisciplinary design optimization (MDO) is an emerging optimization method that considers a design environment with multiple disciplines and seven methods have been proposed for MDO.Abstract:
Recently, engineering systems are quite large and complicated. The design requirements are fairly complex and it is not easy to satisfy them by considering only one discipline. Therefore, a design methodology that can consider various disciplines is needed. Multidisciplinary design optimization (MDO) is an emerging optimization method that considers a design environment with multiple disciplines. Seven methods have been proposed for MDO. They are Multiple-discipline-feasible (MDF), Individual-discipline-feasible (IDF), All-at-once (AAO), Concurrent subspace optimization (CSSO), Collaborative optimization (CO), Bi-level integrated system synthesis (BLISS), and Multidisciplinary design optimization based on independent subspaces (MDOIS). Through several mathematical examples, the performances of the methods are evaluated and compared. Specific requirements are defined for comparison and new types of mathematical problems are defined based on the requirements. All the methods are coded and the performances of the methods are compared qualitatively and quantitatively.read more
Citations
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Multidisciplinary design optimization of dynamic engineering systems
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Multidisciplinary Design Optimization.
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System design of a wind turbine using a multi-level optimization approach
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Proceedings ArticleDOI
Multidisciplinary design optimization of dynamic engineering systems
TL;DR: The use of MDO for dynamic system design is reviewed, associated challenges are identified, related efforts such as optimal control are discussed, and a vision for fully integrated design approaches is presented.
References
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Proceedings ArticleDOI
Multidisciplinary aerospace design optimization: Survey of recent developments
TL;DR: A survey of recent publications in the field of aerospace where interest in multidisciplinary optimization has been particularly intense can be found in this paper, which includes sections on Mathematical Modeling, Design-oriented Analysis, Approximation Concepts, Optimization Procedures, System Sensitivity and Human Interface.
Journal ArticleDOI
Problem Formulation for Multidisciplinary Optimization
TL;DR: The “individual discipline feasible” (IDF) approaches introduced here make use of existing specialized analysis codes, and they introduce significant opportunities for coarse-grained computational parallelism particularly well suited to heterogeneous computing environments.
Journal ArticleDOI
Sensitivity of complex, internally coupled systems
TL;DR: In this paper, a method for computing sensitivity derivatives with respect to independent variables for complex, internally coupled systems, while avoiding the cost and inaccuracy of finite differencing performed on the entire system analysis, is presented.
Journal ArticleDOI
Optimization of coupled systems: a critical overview of approaches
TL;DR: A unified overview is given of problem formulation approaches for the optimization of multidisciplinary coupled systems and the approaches are compared both from a computational viewpoint and a managerial viewpoint.
Optimization by decomposition: A step from hierarchic to non-hierarchic systems
TL;DR: A new, non-hierarchic decomposition is formulated for system optimization that uses system analysis, system sensitivity analysis, temporary decoupled optimizations performed in the design subspaces corresponding to the disciplines and subsystems, and a coordination optimization concerned with the redistribution of responsibility for the constraint satisfaction and design trades.