• Steel and Composite Structures
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• v.27 no.1
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• pp.27-33
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• 2018

In this study, a mixed-interpolated tensorial component 4 nodes method (MITC4) is treated as a numerical analysis model for topology optimization using multiple materials assigned within Reissner-Mindlin plates. Multi-material optimal topology and shape are produced as alternative plate retrofit designs to provide reasonable material assignments based on stress distributions. Element density distribution contours of mixing multiple material densities are linked to Solid Isotropic Material with Penalization (SIMP) as a design model. Mathematical formulation of multi-material topology optimization problem solving minimum compliance is an alternating active-phase algorithm with the Gauss-Seidel version as an optimization model of optimality criteria. Numerical examples illustrate the reliability and accuracy of the present design method for multi-material topology optimization with Reissner-Mindlin plates using MITC4 elements and steel materials.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.2
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• pp.114-126
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• 2009

In this paper, a versatile multi-criteria optimization concept for fatigue life prediction is introduced. Multi-criteria decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1187-1192
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• 2008

In this paper, a versatile multi-objective optimization concept for fatigue life prediction is introduced. Multi-objective decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.528-530
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• 1999

This paper addresses the analysis and design of fuzzy control systems for a class of complex single input single output nonlinear systems. Firstly, the nonlinear system is represented by well-known Takagai-Sugeno (TS) fuzzy model and the global controller is constructed by compensating each linear model in the rule of TS fuzzy model. The design of conventional TS fuzzy-model-based controller usually is composed of two processes. One is to determine static state feedback gain of each local model and the other is to validate the stability of the designed fuzzy controller. In this paper, we propose an alternative of the design of TS fuzzy-model-based controller. The design scheme is based on the extension of conventional optimal control theory to the design of TS fuzzy-model-based controller. By using the proposed method the design and stability analysis of the TS fuzzy model-based controller is reduced to the problem of finding the solution of a set of algebraic Riccati equations. And we use the recently developed interior point method to find the solution of AREs, where AREs are recast as the LMI formulation. One simulation example is given to show the effectiveness and feasibility of the proposed fuzzy controller design method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.1
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• pp.1-9
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• 2010

Quality design methodologies have received constituent attention from a number of researchers and practitioners for more than twenty years. Specially, the quality design for drug products must be carefully considered because of the hazards involved in the pharmaceutical industry. Conventional pharmaceutical formulation design problems with mixture experiments have been typically studied under the assumption of an unconstrained experimental region with a single quality characteristic. However, real-world pharmaceutical industrial situations have many physical limitations. We are often faced with multiple quality characteristics with constrained experimental regions. ln order to address these issues, the main objective of this paper is to propose a robust desirability function (RDF) model using a desirability function (DF) and mean square error (MSE) to simultaneously consider a number of multiple quality characteristics. This paper then present L-pseudocomponents and U-pseudocomponents to handle physical constraints. Finally, a numerical example shows that the proposed RDF can efficiently be applied to a pharmaceutical process design.

• Journal of Korean Society of societal Security
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• v.4 no.1
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• pp.49-55
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• 2011

The primary objective of this paper is to develop optimal algorithms of reinforced concrete frame structural systems by the limit state design(CP 1110) and to look into the possibility of detailed design of these structural systems. The structural formulation is derived on the finite element method. The objective of optimization of a reinforced structure for a specified geometry is mainly to determine the optimum cross-sectional dimensions of concrete and the area of the various sizes of the reinforcement required for each member. In addition to the detail s such as the amount of web reinforcement, cutoff points of longitudinal reinforcedments etc. are also considered as design variables. In this study, the method of "Generalized Reduced Gradient, Rounding and with Neighborhood search" and "the Sequential Linear Programming" are employed as an analytical method of nonlinear optimization.

• Journal of the Korean Society of Food Culture
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• v.27 no.2
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• pp.202-210
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• 2012

The purpose of this study was to bake sweet rice muffins with oak mushroom ($Lentinus$ $edodes$) powder. The process included substituting sweet rice flour for cake flour and adding oak mushroom powder. This study determined the optimal mixing conditions of oak mushroom muffins by adjusting the amounts of oak mushroom powder, whole eggs, and soybean oil. The mixing conditions for the oak mushroom muffins included 3 categories: oak mushroom powder (X1), whole eggs (X2), and soybean oil (X3) by Central Composite Design (CCD) which was optimized by Response Surface Methodology (RSM). Oak mushroom muffin formulation was optimized using rheology. Yellowness (p<0.001) and redness (p<0.05) displayed a linear model pattern, whereas lightness (p<0.05) was represented by a quadratic model. Among the sensory properties, variables that appeared to show significant values such as appearance (p<0.5), texture (p<0.5), and overall quality (p<0.5) were used to identify optimums. The result of mechanical properties showed significant values in gumminess (p<0.5) and chewiness (p<0.5). The numerical and graphical methods used in this study determined that the optimum formulation for oak mushroom powder sweet rice muffins was 8.75 g of oak mushroom powder, 235.95 g of whole eggs, and 19.93 g of soybean oil.

• Structural Engineering and Mechanics
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• v.49 no.1
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• pp.65-80
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• 2014

This paper reports on the development of a minimum cost design model and its application for obtaining economic designs for reinforced High Strength Concrete (HSC) T-sections in bending under ultimate limit state conditions. Cost objective functions, behavior constraint including material nonlinearities of steel and HSC, conditions on strain compatibility in steel and concrete and geometric design variable constraints are derived and implemented within the Conjugate Gradient optimization algorithm. Particular attention is paid to problem formulation, solution behavior and economic considerations. A typical example problem is considered to illustrate the applicability of the minimum cost design model and solution methodology. Results are confronted to design solutions derived from conventional design office methods to evaluate the performance of the cost model and its sensitivity to a wide range of unit cost ratios of construction materials and various classes of HSC described in Eurocode2. It is shown, among others that optimal solutions achieved using the present approach can lead to substantial savings in the amount of construction materials to be used. In addition, the proposed approach is practically simple, reliable and computationally effective compared to standard design procedures used in current engineering practice.

• Journal of Environmental Science International
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• v.29 no.8
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• pp.793-800
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• 2020

The conventional development of multi-component electrodes is based on the researcher's experience and is based on trial and error. Therefore, there is a need for a scientific method to reduce the time and economic losses thereof and systematize the mixing of electrode components. In this study, we use design of mixture experiments (DOME)- in particular a simplex lattice design with Design Expert^Ⓡ program- to attempt to find an optimum mixing ratio for a three-component electrode for the high RNO degradation; RNO is an indictor of OH radical formation. The experiment included 12 experimental points with 2 center replicates for 3 different independent variables (with the molar ratio of Ru, Ti, Ir). As the Prob > F value of the 'Quadratic' model is 0.0026, the secondary model was found to be suitable. Applying the molar ratio of the electrode components to the corrected response model results is an RNO removal efficiency (%) = 59.89 × [Ru] + 9.78 × [Ti] + 67.03 × [Ir] + 66.38 × [Ru] × [Ir] + 132.86 × [Ti] × [Ir]. The R² value of the equation is 0.9374 after the error term is excluded. The optimized formulation of the ternary electrode for an high RNO degradation was acquired when the molar ratio of Ru 0.100, Ti 0.200, Ir 0.700 (desirability d value, 1).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.5 no.4
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• pp.9-14
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• 1985

In this research mass of a plane strain two dimensional elastic concrete dam under gravitational and hydrostatic loads is minimized, through shape optimization of the dam cross section. Cross sectional area of the dam is taken as cost function of the optimization problem while constraints on the principal stress distribution and dam thickness are imposed. Shape of the boundary of the model is chosen as design variable. Variational formulation of the optimization problem, the material derivative idea of continuum mechanics, and an adjoint variable method are employed for the shape design sensitivity calculation. Then the gradient projection algorithm is utilized to obtain an optimum design iteratively. Research results fully demonstrate that the theory and procedure adopted are quite efficient and can be applicable to a wide class of practical elastic structural design problems.