• Journal of Mechanical Science and Technology
• /
• v.20 no.1
• /
• pp.133-146
• /
• 2006

Collaborative optimization (CO) is a multi-level decomposed methodology for a large-scale multidisciplinary design optimization (MDO). CO is known to have computational and organizational advantages. Its decomposed architecture removes a necessity of direct communication among disciplines, guaranteeing their autonomy. However, CO has several problems at convergence characteristics and computation time. In this study, such features are discussed and some suggestions are made to improve the performance of CO. Only for the system level optimization, genetic algorithm is used and gradient-based method is used for subspace optimizers. Moreover, response surface models are replaced as analyses in subspaces. In this manner, CO is applied to aero-structural design problems of the aircraft wing and its results are compared with the multidisciplinary feasible (MDF) method and the original CO. Through these results, it is verified that the suggested approach improves convergence characteristics and offers a proper solution.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.35 no.12
• /
• pp.1121-1128
• /
• 2007

MDO(Multidisciplinary Design and Optimization) can be applied for design of complex systems such as aircraft and SLV(Space Launch Vehicle). MDO System can be an integrated environment or a system, which is for synthetic and instantaneous analysis and design optimization in various design fields. MDO System has to efficiently use and integrate distributed resources such as various analysis codes, optimization codes, CAD, DBMS, GUI, and etc. in heterogeneous environments. In this paper, we present Web Services-based MDO System that integrates resources for MDO using Globus Toolkit and provides organic autonomous execution using automation technique such as Workflow system and agent. And also, it provides collaborative design environment through web user interfaces.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1999.10a
• /
• pp.359-369
• /
• 1999

The paper describes the study of concurrent subspace optimization(CSSO) for coupled multidisciplinary design optimization (MDO) techniques in mechanical systems. This method is a solution to large scale coupled multidisciplinary system, wherein the original problem is decomposed into a set of smaller, more tractable subproblems. Key elements in CSSO are consisted of global sensitivity equation(GSE), subspace optimization (SSO), optimum sensitivity analysis(OSA), and coordination optimization problem(COP) so as to inquiry valanced design solutions finally, Automatic differentiation has an ability to provide a robust sensitivity solution, and have shown the numerical numerical effectiveness over finite difference schemes wherein the perturbed step size in design variable is required. The present paper will develop the automatic differentiation based concurrent subspace optimization(AD-CSSO) in MDO. An automatic differentiation tool in FORTRAN(ADIFOR) will be employed to evaluate sensitivities. The use of exact function derivatives in GSE, OSA and COP makes Possible to enhance the numerical accuracy during the iterative design process. The paper discusses how much influence on final optimal design compared with traditional all-in-one approach, finite difference based CSSO and AD-CSSO applying coupled design variables.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2007.04a
• /
• pp.38-42
• /
• 2007

In this study, cruise missile configuration is optimal designed by using multidisciplinary analysis. Aerodynamic, weight, performance and mission analysis modules are developed by FORTRAN and integrated with framework. Darwin algorithm, a global optimization tool, is used for optimization. In the result of optimal design, gross weight of designed configuration is reduced about 17% than baseline configuration while satisfying design constraint conditions.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.28 no.2
• /
• pp.109-117
• /
• 2004

Optimization has been successfully applied to systems with a single discipline. As many disciplines are involved in coupled fashion, MDO (multidisciplinary design optimization) technology has been developed. MDO algorithms are trying to solve the coupled aspects generated from interdisciplinary relationship. In a general MDO algorithms, a large design problem is decomposed into small ones which can be easily solved. Although various methods have been proposed for MDO, the research is still in the early stage. This research proposes a new MDO method which is named as MDOIS (Multidisciplinary Design Optimization Based on Independent Subspaces). Many real engineering problems consist of physically separate components and they can be independently designed. The inter-relationship occurs through coupled physics. MDOIS is developed for such problems. In MDOIS, a large system is decomposed into small subsystems. The coupled aspects are solved via system analysis which solves the coupled physics. The algorithm is mathematically validated by showing that the solution satisfies the Karush-Kuhn-Tucker condition.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• v.y2005m4
• /
• pp.11-15
• /
• 2005

Compared with the conventional ground rocket launching, air-launching has many advantages. However, comprehensive and integrated system design approach is required because the physical geometry of air launch vehicle is quite dependent on the installation limitation of the mother plane. The system design has been performed using two different approaches: the sequential optimization and the multidisciplinary feasible(MDF) optimization method. Analysis modules include mission analysis, staging, propulsion analysis, configuration, weight analysis, aerodynamics analysis and trajectory analysis. MDF optimization shows better result than sequential optimization. As a result of system optimization, a supersonic air launching rocket with total mass of 1244.91 kg, total length of 6.18 m, outer diameter of 0.60 m and the payload mass of 7.5 kg has been successfully designed.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.33 no.12
• /
• pp.26-32
• /
• 2005

Compared with the conventional ground rocket launching, air-launching has many advantages. However, a comprehensive and integrated system design approach is required because the physical geometry of air launch vehicle is quite dependent on the installation limitation of the mother plane. The system design has been performed using two different approaches: the sequential optimization and the multidisciplinary feasible(MDF) optimization method. Analysis modules include mission analysis, staging, propulsion analysis, configuration, weight analysis, aerodynamics analysis and trajectory analysis. MDF optimization shows better results than the sequential optimization. As a result of system optimization, a supersonic air launching rocket with total mass of 1244.91kg, total length of 6.36m, outer diameter of 0.60m and the payload mass of 7.5kg has been successfully designed.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.20 no.6
• /
• pp.1-8
• /
• 2012

Multidisciplinary design optimization (MDO) for a suspension component of the vehicle front suspension was performed in this research. Shapes and thicknesses of the subframe were optimized to satisfy multi-disciplinary design requirements; weight, fatigue, crash, noise, vibration, and harshness (NVH), and kinematic and compliance (K&C). Analyses procedures of the performance disciplines were integrated and automated by using the process integration and design optimization (PIDO) technique, and the integrated and automated analyses environments enabled various types of analytic design methodologies for solving the MDO problem. We applied an approximate optimization technique which involves sequential sampling and metamodeling. Since the design variables for thicknesses should be dealt as discrete variables. the evolutionary algorithm is selected as optimization technique. The MDO problem was formulated three types of problems according to the order of priorities among the performance disciplines, and the results of MDO provided design alternatives for various design situations.

• 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
• /
• 2004.10a
• /
• pp.173-176
• /
• 2004

In this study, the multidisciplinary aerodynamic-structural optimal design is carried out for the supersonic fighter wing. Through the aeroelastic analyses of the various candidate wings, the aerodynamic and structural performances are calculated such as the lift coefficient, the drag coefficient and the deformation of the wing. In general, the supersonic fighter is maneuvered under the various flight conditions and those conditions must be considered all together during the design process. The multi-point design, therefore, is deemed essential. For this purpose, supersonic dash, long cruise range and high angle of attack maneuver are selected as representative design points. Based on the calculated performances of the candidate wings, the response surfaces for the objectives and constraints are generated and the supersonic fighter wing is designed for better aerodynamic performances and less weights than the baseline. At each design point, the single-point design is performed to obtain better performances. Finally, the multi-point design is performed to improve the aerodynamic and structural performances for all design points. The optimization results of the multi-point design are compared with those of the single-point designs and analyzed in detail.