• Journal of the Korea Society for Simulation
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• v.3 no.2
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• pp.57-67
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• 1994

For many practical and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computer simulation is one of the most effective means of studying such complex systems. In this paper, with discussion of simulation optimization techniques, a case study in machining process for application of simulation optimization is presented. Most of optimization techniques can be classified as single-or multiple-response techniques. The optimization of single-response category, these strategies are gradient based search methods, stochastic approximate method, response surface method, and heuristic search methods. In the multiple-response category, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphical method, direct search method, constrained optimization, unconstrained optimization, and goal programming methods. The choice of the procedure to employ in simulation optimization depends on the analyst and the problem to be solved.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.106-118
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• 1998

The study concerns a design procedure of rule-based systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient from of "IF..., THEN..." statements, and exploits the theory of system optimization and fuzzy implication rules. The method for rule-based fuzzy modeling concerns the from of the conclusion part of the the rules that can be constant. Both triangular and Gaussian-like membership function are studied. The optimization hinges on an autotuning algorithm that covers as a modified constrained optimization method known as a complex method. The study introduces a weighted performance index (objective function) that helps achieve a sound balance between the quality of results produced for the training and testing set. This methodology sheds light on the role and impact of different parameters of the model on its performance. The study is illustrated with the aid of two representative numerical examples.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.408-417
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• 2005

Increasing numbers of value added chemicals are being produced using microbial fermentation strategies. Computational modeling and simulation of microbial metabolism is rapidly becoming an enabling technology that is driving a new paradigm to accelerate the bioprocess development cycle. In particular, constraint-based modeling and the development of genome-scale models of industrial microbes are finding increasing utility across many phases of the bioprocess development workflow. Herein, we review and discuss the requirements and trends in the industrial application of this technology as we build toward integrated computational/experimental platforms for bioprocess engineering. Specifically we cover the following topics: (1) genome-scale models as genetically and biochemically consistent representations of metabolic networks; (2) the ability of these models to predict, assess, and interpret metabolic physiology and flux states of metabolism; (3) the model-guided integrative analysis of high throughput 'omics' data; (4) the reconciliation and analysis of on- and off-line fermentation data as well as flux tracing data; (5) model-aided strain design strategies and the integration of calculated biotransformation routes; and (6) control and optimization of the fermentation processes. Collectively, constraint-based modeling strategies are impacting the iterative characterization of metabolic flux states throughout the bioprocess development cycle, while also driving metabolic engineering strategies and fermentation optimization.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.317-324
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• 2004

Shape design optimization of shell structure is implemented on a basis of integrated framework of geometric modeling and finite element analysis which is constructed on the geometrically exact shell theory. This shell theory enables more accurate and robust analysis for complicated shell structures, and it fits for the nature of B-spline function which Is popular modeling scheme in CAD field. Shape of laminated composite shells is optimized through genetic algorithm and sequential linear programming, because there ire numerous optima for various configurations, constraints, and searching paths. Sequential adaptation of global and local optimization makes the process more efficient. Two different optimized results of laminated composite shell structures to minimize strain energy are shown for different layup sequence.

• Transactions of the Korean Society of Automotive Engineers
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• v.1 no.3
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• pp.95-108
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• 1993

The needs for smooth curves and surfaces are increasing in modeling cars, ships, airplanes, and other consumer products either for aesthetic or functional purpose. However, the curves and surfaces generated by conventional modeling methods usually exhibit an unwanted behavior due to digitizing errors or inadequate generation method, and thus much time and extra effort is spent afterwards to get the faired results. The objective of this work is to develop a fairing scheme by which well refined shape of a surface can be acquired with detecting and removing the shape imperfections of the given surface represented by NURBS. The fairing scheme is based on an optimization process in which the control points of the given surface are repositioned to minimize the integration of the jumps(perturbations) of the unit normal vectors at all surface points.

• Smart Structures and Systems
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• v.16 no.1
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• pp.1-26
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• 2015

Minimizing construction cost and reducing seismic damage are two conflicting objectives in the design of any new structure. In the present work, we try to develop a framework in order to solve the optimum performance-based design problem considering the construction cost and the seismic damage of steel moment-frame structures. The Park-Ang damage index is selected as the seismic damage measure because it is one of the most realistic measures of structural damage. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. To improve the time efficiency of the proposed framework, three simplifying strategies are adopted: first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication; second, fitness approximation decreasing the number of fitness function evaluations; third, wavelet decomposition of earthquake record decreasing the number of acceleration points involved in time-history loading. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency's (FEMA) recommended seismic design specifications. The results from numerical application of the proposed framework demonstrate the efficiency of the framework in solving the present multi-objective optimization problem.

• 한국신재생에너지학회:학술대회논문집
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• 2005.11a
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• pp.541-544
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• 2005

This study presents the integrated modeling approach to simulate the proton exchange membrane (PEM) fuel cell system for vehicle application. The fuel cell system consisting of stack and balance of plant (BOP) was simulated with MATLAB/Simulink environment to estimate the maximum system power and investigate the effect of BOP component sizing on system performance and efficiency. The PEM fuel cell stack model was established by using a semi-empirical modeling. To maximize the net efficiency of fuel cel1 system, multi-variable optimization code was adopted. Using this method the optimized operating values were obtained according to various system net power levels. The fuel cell model established was co-linked to AVL CRUISE, a vehicle simulation package. Through the vehicle simulation software, the fuel economy of fuel cell powered electric vehicle for two types of driving cycles was presented and compared. It is expected that this study tan be effectively employed in the basic BOP component sizing and in establishing system operation map with respect to net power level of fuel cell system.

• New & Renewable Energy
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• v.1 no.4 s.4
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• pp.43-48
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• 2005

This study presents the integrated modeling approach to simulate the proton exchange membrane [PEM] fuel cell system for vehicle application. The fuel cell system consisting of stack and balance of plant (BOP) was simulated with MATLAB/Simulink environment to estimate the maximum system power and investigate the effect of BOP component sizing on system performance and efficiency. The PEM fuel cell stack model was established by using a semi-empirical modeling. To maximize the net efficiency of fuel cell system, multi-variable optimization code was adopted. Using this method, the optimized operating values were obtained according to various system net power levels. The fuel cell model established was co-linked to AVL CRUISE, a vehicle simulation package. Through the vehicle simulation software, the fuel economy of fuel cell powered electric vehicle for two types of driving cycles was presented and compared. It is expected that this study can be effectively employed in the basic BOP component sizing and in establishing system operation map with respect to net power level of fuel cell system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.3
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• pp.229-237
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• 2008

In this research, a MDO(multi-disciplinary design optimization) framework, which integrates aerodynamic and structural analysis to design an aircraft wing, is constructed. Whole optimization process is automated by a parametric-modeling approach. A CFD mesh is generated automatically from parametric modeling of CATIA and Gridgen followed by automatic flow analysis using Fluent. Finite element mesh is generated automatically by parametric method of MSC.Patran PCL. Aerodynamic load is transferred to Finite element model by the volume spline method. RSM(Response Surface Method) is applied for optimization, which helps to achieve global optimum. As the design problem to test the current MDO framework, a wing weight minimization with constraints of lift-drag ratio and deflection of the wing is selected. Aspect ratio, taper ratio and sweepback angle are defined as design variables. The optimization result demonstrates the successful construction of the MDO framework.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.341-345
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• 2003

This study develops modeling processes for alignment optimization considering characteristics of intersections using genetic algorithms and GIS for road alignment optimization. Since existing highway alignment optimization models have neglected the characteristics of intersections, they have shown serious weaknesses for real applications. In this paper, intersection costs include earthwork, right-of-way, pavement, accident, delay and fuel consumption costs that are sensitive and dominating to alignments. Also, local optimization of intersections for saving good alignment alternatives is developed and embedded. A highway alignment is described by parametric representation in space and vector manipulation is used to find the coordinates of intersections and other interesting points. The developed intersection cost estimation model is sufficiently precise for estimating intersection costs and eventually enhancing the performance of highway alignment optimization models. Also, local optimization of intersections can be used for improving search flexibility, thus allowing more effective intersections. It also provides a basis for extending the alignment optimization from single highways to networks. The presented two artificial examples show that the total intersection costs are substantial and sensitive to highway alignments.