Multidisciplinary design optimization 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 multidisciplinary design optimization, various methods (architectures) have been developed and applied to solve multidisciplinary design-optimization 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 facilitate the understanding of the various architectures, and how they relate to each other. A classification of the multidisciplinary design-optimization architectures based on their problem formulations and decomposition strategies is also provided, a...

Multidisciplinary design optimization: A survey of architectures

Dynamic engineering systems are playing an increasingly important role in society, especially as active and autonomous dynamic systems become more mature and prevalent across a variety of domains. Successful design of complex dynamic systems requires multidisciplinary analysis and design techniques. While multidisciplinary design optimization has been used successfully for the development of many dynamic systems, the established multidisciplinary design optimization formulations were developed around fundamentally static system models. General multidisciplinary design optimization approaches that address the specific needs of dynamic system design are still lacking. In this article, the use of multidisciplinary design optimization 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. Finally, a set of exciting new directions that provide an opportunity for fundame...

Multidisciplinary design optimization of dynamic engineering systems

A first metal surface of a first article of metal, such as the metalization layer on a silicon semiconductor device, is bonded to an opposing or second metal surface of a second article of metal, such as a "structured copper" strain buffer, using an improved method of thermo-compression diffusion bonding that involves temperature control independent of compressional force control, whereby a superior bond is obtained.

Multidisciplinary Design Optimization.

System design of a wind turbine using a multi-level optimization approach

Dynamic engineering systems are playing an increasingly important role in society, especially as active and autonomous dynamic systems become more mature and prevalent across a variety of domains. Successful design of complex dynamic systems requires multidisciplinary analysis and design techniques. While multidisciplinary design optimization (MDO) has been used successfully for the development of many dynamic systems, the established MDO formulations were developed around fundamentally static system models. We still lack general MDO approaches that address the specific needs of dynamic system design. In this article we review the use of MDO for dynamic system design, identify associated challenges, discuss related efforts such as optimal control, and present a vision for fully integrated design approaches. Finally, we lay out a set of exciting new directions that provide an opportunity for fundamental work in MDO.

/pdf/multidisciplinary-design-optimization-of-dynamic-engineering-2txecw2f2c.pdf

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.

J. K. Shin

Papers

Comparison of MDO methods with mathematical examples