• Proceedings of the KSME Conference
• /
• 2001.06c
• /
• pp.380-385
• /
• 2001

The paper presents a new multidisciplinary design optimization architecture using optimal sensitivity and coordination of interdisciplinary design variables. Original design problem is decomposed into a number of sub-problems that represent individual engineering analysis. The coupled effects between sub-problems are computed by interdisciplinary design variables. System level coordination is determined by optimal parameter sensitivity calculated by finite difference method. The proposed. MDO strategy is applied to a simplified model of rotorcraft blade design associated with structures and aerodynamic disciplines.

• Proceedings of the KIPE Conference
• /
• 2011.07a
• /
• pp.85-86
• /
• 2011

In this paper, the virtual power grid of Jeju in 2020 is modelled including not only VSC HVDC(Voltage Source Current-High Voltage Direct Current) but also wind power generators as 200MW for onshore and 500MW for offshore by PSCAD/EMTDC. Each active power and reactive power are able to controlled by the VSC HVDC. In addition, to verify the characteristic of the modeling VSC HVDC, those wind power generators are cut off from the grid. The result show that the modeling power grid of Jeju become stabilized after 0.1second from failure.

• 한국전산유체공학회:학술대회논문집
• /
• 2005.10a
• /
• pp.1-10
• /
• 2005

A new approach, Multi-Objective Design Exploration (MODE), is presented to address Multidisciplinary Design Optimization (MDO) problems by CFD-CSD coupling. MODE reveals the structure of the design space from the trade-off information and visualizes it as a panorama for Decision Maker. The present form of MODE consists of Kriging Model, Adaptive Range Multi Objective Genetic Algorithms, Analysis of Variance and Self-Organizing Map. The main emphasis of this approach is visual data mining. An MDO system using high fidelity simulation codes, Navier-Stokes solver and NASTRAN, has been developed and applied to a regional-jet wing design. Because the optimization system becomes very computationally expensive, only brief exploration of the design space has been performed. However, data mining result demonstrates that design knowledge can produce a good design even from the brief design exploration.

• Journal of Mechanical Science and Technology
• /
• v.18 no.5
• /
• pp.814-819
• /
• 2004

The conceptual design of a rotorcraft system involves many different analysis disciplines. The decomposition of such a system into several subsystems can make analysis and design more efficient in terms of the total computation time. Adaptive parallel decomposition makes the structure of the overall design problem suitable to apply the multidisciplinary design optimization methodologies and it can exploit parallel computing. This study proposes a decomposition method which adaptively determines the number and sequence of analyses in each sub-problem corresponding to the available number of processors in parallel. A rotorcraft design problem is solved and as a result, the adaptive parallel decomposition method shows better performance than other previous methods for the selected design problem.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.4
• /
• pp.499-506
• /
• 2003

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several sub design structure matrices (DSMs) and processing them in parallel This paper proposes a new method for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multi-objective genetic algorithm and two sample test cases are presented to show the effect of the suggested decomposition method.

• 한국전산유체공학회:학술대회논문집
• /
• 2005.04a
• /
• pp.187-190
• /
• 2005

In this study, the reliablility based design optimization is peformed for an aircraft wing. The flexiblility of the wing was assumed by considering the interaction modeled by static aeroelasticity between aerodynamic forces and the structure. For a multidisciplinary design optimization the results of aerodynamic analysis and structural analysis were included in the optimization formulation. The First Order Reliability Method(FORM) was employed to consider the uncertainty of the designed points.

• International Journal of Aeronautical and Space Sciences
• /
• v.18 no.4
• /
• pp.662-674
• /
• 2017

This paper describes the multidisciplinary design optimization (MDO) process of a tailless unmanned combat aerial vehicle (UCAV) using global variable fidelity aerodynamic analysis. The developed tailless UAV design framework combines multiple disciplines that are based on low-fidelity and empirical analysis methods. An automated high-fidelity aerodynamic analysis is efficiently integrated into the MDO framework. Global variable fidelity modeling algorithm manages the use of the high-fidelity analysis to enhance the overall accuracy of the MDO by providing the initial sampling of the design space with iterative refinement of the approximation model in the neighborhood of the optimum solution. A design formulation was established considering a specific aerodynamic, stability and control design features of a tailless aircraft configuration with a UCAV specific mission profile. Design optimization problems with low-fidelity and variable fidelity analyses were successfully solved. The objective function improvement is 14.5% and 15.9% with low and variable fidelity optimization respectively. Results also indicate that low-fidelity analysis overestimates the value of lift-to-drag ratio by 3-5%, while the variable fidelity results are equal to the high-fidelity analysis results by algorithm definition.

• Korean Journal of Computational Design and Engineering
• /
• v.8 no.4
• /
• pp.231-242
• /
• 2003

Multidisciplinary Design Optimization (MDO) is an optimization technique considering simultaneously multiple disciplines such as dynamics, mechanics, structural analysis, thermal and fluid analysis and electromagnetic analysis. A software system enabling multidisciplinary design optimization is called MDO framework. An MDO framework provides an integrated and automated design environment that increases product quality and reliability, and decreases design cycle time and cost. The MDO framework also works as a common collaborative workspace for design experts on multiple disciplines. In this paper, we present the architecture for an MDO framework along with the requirement analysis for the framework. The requirement analysis has been performed through interviews of design experts in industry and thus we claim that it reflects the real needs in industry. The requirements include integrated design environment, friendly user interface, highly extensible open architecture, distributed design environment, application program interface, and efficient data management to handle massive design data. The resultant MDO framework is datasever-oriented and designed around a centralized data server for extensible and effective data exchange in a distributed design environment among multiple design tools and software.

• Proceedings of the IEEK Conference
• /
• 2001.10a
• /
• pp.742-745
• /
• 2001

Plastics are one of difficult materials for recycling due to their characteristics in use. Recycling ratio of waste plastics was around 40% in last year in Japan, which includes energy recovery. Feed stock recycling and mechanical recycling are not easy because of additives in commercial plastics. Then, pyrolysis treatments have been done to recovery energy. Although plastics are easy to fire, complete combustion of them is not easy if anti-firing agents are added especially. Therefore, researches on pyrolysis or combustion behaviors of plastics containing additives are important from a view point recycling of plastics. Direct observation of popular plastics like polystyrene (PS), polycarbonate (PC), polyphenyle ether (PPE) and polyvinyl chloride (PVC) to investigate their pyrolysis behaviors in the present study. In case of PS, melting and gas evolution started at 9$0^{\circ}C$ and 39$0^{\circ}C$ respectively. And combustion finished at 445$^{\circ}C$. On the other hand, more than $600^{\circ}C$ and sufficient oxygen are required for complete combustion of PC and PPE.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.3 s.258
• /
• pp.355-364
• /
• 2007

Multidisciplinary design optimization based on independent subspaces (MDOIS) is a simple and practical method that can be applied to the practical engineering MDO problems. However, the current version of MDOIS does not handle the common design variables. A new version of MDOIS is proposed and named as MDOIS/2006. It is a two-level MDO method while the original MDOIS is a single-level method. At first, system analysis is performed to solve the coupling in the analysis. If the termination criteria are not satisfied, each discipline solves its own design problem. Each discipline in the lower level solves the problem with common design variables while they are constrained by equality constraints. In the upper level, the common design variables of related disciplines are determined by using the optimum sensitivity of the objective function. To validate MDOIS/2006, mathematical problem and NASA test bed problem are solved. The results are compared with those from other MDO methods. Finally, MDOIS/2006 is applied to flow patterner design and shows that it can be successfully applied to the practical engineering MDO problem.