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.

While numerous architectures exist for solving multidisciplinary design optimization (MDO) problems, there is currently no standard way of describing these architectures. In particular, a standard visual representation of the solution process would be particularly useful as a communication medium among practitioners and those new to the field. This paper presents the extended design structure matrix (XDSM), a new diagram for visualizing MDO processes. The diagram is based on extending the standard design structure matrix (DSM) to simultaneously show data dependency and process flow on a single diagram. Modifications include adding special components to define iterative processes, defining different line styles to show data and process connections independently, and adding a numbering scheme to define the order in which the components are executed. This paper describes the rules for constructing XDSMs along with many examples, including diagrams of several MDO architectures. Finally, this paper discusses potential applications of the XDSM in other areas of MDO and the future development of the diagrams.

[1] Enhanced resolution Advanced Microwave Scanning Radiometer (AMSR-E) imagery is used to estimate daily sea ice area fluxes between the Canadian Arctic Archipelago and the Arctic Ocean and Baffin Bay for the period September 2002 to June 2007. Over the period, Amundsen Gulf and M'Clure Strait exported 54 Â 10 3 km 2 of sea ice area or roughly 77 km 3 of sea ice volume each year into the Arctic Ocean. Export/import into the Arctic Ocean through the Queen Elizabeth Islands is small and uncertain since no estimates for July and August could be made due to atmospheric attenuation of the microwave signal. Lancaster Sound exported 68 Â 10 3 km 2 of sea ice area or roughly 102 km 3 of ice volume into Baffin Bay. This produced a net loss of sea ice area of about 122 Â 10 3 km 2 or roughly 174 km 3 a À1 which is presumed to be generated from within the Archipelago itself mainly through the stationary and transient polynyas and leads that form each winter. Daily ice area fluxes for Amundsen Gulf (AG) and Lancaster Sound (LS) were as high as ±2500 km 2 d À1 and were event driven depending on synoptic scale atmospheric circulation and the mobility of the sea ice. Mean sea level pressure difference across each gate is moderately correlated with daily sea ice area fluxes despite the fact that free ice drift conditions are not always met in the region. Cross-gradient and daily sea ice area flux for Lancaster Sound show a large number of counter gradient ice flux occurrences suggesting that local mesoscale winds (nongeostrophic) and perhaps ocean currents play a role in transporting sea ice through this gate. Monthly ice fluxes for the AG and MS gate were positively correlated with the AO index indicating that a strong Beaufort Sea high pressure and gyre correspond to more export into the Beaufort Sea. Monthly fluxes for the LS gate were positively correlated with the NAO index indicating that strong southerly atmospheric circulation over Baffin Bay increases ice export into Baffin Bay from Lancaster Sound.

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A new method of topology optimization is introduced in which a continuous material field is combined with adaptive mesh refinement. Using a continuous material field with different analysis and design meshes allows the method to produce optimal designs that are free of numerical artifacts like checkerboard patterns and material islands. Adaptive mesh refinement is then applied to both meshes to precisely locate the optimal boundary of the final structure. A Helmholtz-type density filter is used to prevent the appearance of small topological features as the mesh refinement proceeds. Results are presented for several test problems, including problems with geometrically complex domain boundaries.