• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.396-396
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• 2000

Multiperiod optimization is the key step to tackle the supply chain optimization problems. Taking supply and demand uncertainty or prediction into consideration during the process synthesis phase leads to the maximization of the profit for the long range time horizon. In this study, new algorithm based on the Genetic Algorithms is proposed for multiperiod optimization formulated in MINLP, GDP and hybrid MINLP/GDP. In this study, the focus is given especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is tried. and many heuristics are adopted for this purpose.

• Microbiology and Biotechnology Letters
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• v.19 no.3
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• pp.281-289
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• 1991

Neurospora crassa (KCTC 6079) produces tyrosinase (EC 1.14.18.1) during sexual differentiation under derepressed conditions in the presence of inducers such as amino acid analogues, antimetabolites or protein synthesis inhibitors. The selection of inducer concentration and induction time as well as inducer type are critical for the optimization of the enzyme production. The best inducer was found to be cycloheximide. Since cycloheximide was toxic to the cells, an optimal inducer concentration and an optimal induction time were determined to maximize the enzyme production from batch cultures. Mathematical models for the cell growth and the enzyme production were proposed and used for process optimization. By optimizing the induction conditions, maximum tyrosinase productivity was increased significantly.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.877-885
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• 2018

Various controllers such as proportional-integral-derivative (PID) controllers have been designed and optimized for load-following issues in nuclear reactors. To achieve high performance, gain tuning is of great importance in PID controllers. In this work, gains of a PID controller are optimized for power-level control of a typical pressurized water reactor using particle swarm optimization (PSO) algorithm. The point kinetic is used as a reactor power model. In PSO, the objective (cost) function defined by decision variables including overshoot, settling time, and stabilization time (stability condition) must be minimized (optimized). Stability condition is guaranteed by Lyapunov synthesis. The simulation results demonstrated good stability and high performance of the closed-loop PSO-PID controller to response power demand.

• Korean Journal of Optics and Photonics
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• v.20 no.6
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• pp.319-327
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• 2009

We introduce a new design technique by treating a two-group zoom lens system with a wide angle of view. First, the concept of the global optimization is introduced in the initial design stage, and from this, the global design technique is completed by analyzing and summarizing large quantities of modern design data. That is, we define the global structure function to achieve a new conceptual design technique for global optimization. And the function is put in a simple form by referring lots of patent data, manipulated with other algebraic equations, and solved finally such that we obtain the global solution region. The global solution region corresponds to the global optimization and suggests insightful systematized directions for the design of two-group zoom lens systems. These directions are attractive compared to global optimization.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.940-947
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• 2022

Meta-heuristic algorithms have found their place in optimization problems. Henry gas solubility optimization (HGSO) is one of the newest population-based algorithms. This algorithm is inspired by Henry's law of physics. To evaluate the performance of a new algorithm, it must be used in various problems. On the other hand, the optimization of the proportional-integral-derivative (PID) gains for load-following of a nuclear power plant (NPP) is a good challenge to assess the performance of HGSO. Accordingly, the power control of a pressurized water reactor (PWR) is targeted, based on the point kinetics model with six groups of delayed-neutron precursors. In any optimization problem based on meta-heuristic algorithms, an efficient objective function is required. Therefore, the integral of the time-weighted square error (ITSE) performance index is utilized as the objective (cost) function of HGSO, which is constrained by a stability criterion in steady-state operations. A Lyapunov approach guarantees this stability. The results show that this method provides superior results compared to an empirically tuned PID controller with the least error. It also achieves good accuracy compared to an established GA-tuned PID controller.

• Journal of Mechanical Science and Technology
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• v.19 no.5
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• pp.1072-1079
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• 2005

Conceptual design is the first step in the overall process of product design. Its intrinsic uncertainty, imprecision, and lack of information lead to the fact that current conceptual design activities in engineering have not been computerized and very few CAD systems are available to support conceptual design. In most of the current intelligent design systems, approach of principle synthesis, such as morphology matrix, bond graphic, or design catalogues, is usually adopted to deal with the concept generation, in which optional concepts are generally combined and enumerated through function analysis. However, as a large number of concepts are generated, it is difficult to evaluate and optimize these design candidates using regular algorithm. It is necessary to develop a new approach or a tool to solve the concept generation. Generally speaking, concept generation is a problem of concept synthesis. In substance, this process of developing design candidate is a combinatorial optimization process, viz., the process of concept generation can be regarded as a solution for a state-place composed of multi-concepts. In this paper, genetic algorithm is utilized as a feasible tool to solve the problem of combinatorial optimization in concept generation, in which the encoding method of morphology matrix based on function analysis is applied, and a sequence of optimal concepts are generated through the search and iterative process which is controlled by genetic operators, including selection, crossover, mutation, and reproduction in GA. Several crucial problems on GA are discussed in this paper, such as the calculation of fitness value and the criteria for heredity termination, which have a heavy effect on selection of better concepts. The feasibility and intellectualization of the proposed approach are demonstrated with an engineering case. In this work concept generation is implemented using GA, which can facilitate not only generating several better concepts, but also selecting the best concept. Thus optimal concepts can be conveniently developed and design efficiency can be greatly improved.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.8
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• pp.695-702
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• 2012

In this study, Multi-fidelity analysis is performed to improve the accuracy of analysis result during conceptual design stage. Multidisciplinary Design Optimization(MDO) method is also considered to satisfy the total system requirements. Low-fidelity analysis codes which are based on empirical equations are developed and validated for analyzing the Unmanned Aerial Vehicle(UAV) which have unconventional configurations. Analysis codes consist of initial sizing, aerodynamics, propulsion, mission, weight, performance, and stability modules. Design synthesis program which is composed of those modules is developed. To improve the accuracy of the design method for UAV, Vortex Lattice Method is used for the strategy of MFA. Multi-Disciplinary Feasible(MDF) method is used for MDO technique. To demonstrate the validity of presented method, the optimization results of both methods are compared. According to those results, the presented method is demonstrated to be applicable to improve the accuracy of the analyses during conceptual design stage.

• Environmental Engineering Research
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• v.19 no.4
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• pp.339-344
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• 2014

Different types of polyethersulfone (PES) support layer for a thin film composite (TFC) membrane were synthesized under various synthesis conditions using the phase inversion method to study the combined effects of substrate, adhesive, and pore former. The permeability, selectivity, pore structure, and morphology of the prepared membranes were analyzed to evaluate the membrane performance. The combined use of substrate, adhesive, and pore former produced a thinner dense top layer, with more straight finger-like pores. The pure water permeation (PWP) of the optimized PES membrane was $27.42L/m^2hr$ (LMH), whereas that of bare PES membrane was 3.24 LMH. Moreover, membrane selectivity, represented as divalent ion ($CaSO_4$) rejection, was not sacrificed under the synthesis conditions, which produced the dramatically enhanced PWP. The high permeability and selectivity of the PES membrane produced under the optimized synthesis conditions suggest that it can be utilized as a potential support layer for TFC membranes.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.6
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• pp.1330-1341
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• 1993

The kinematic synthesis deals with the systematic design of mechanisms for a given performance. The area of synthesis may be grouped into two categories to determine the type and to size the dimensions of a mechanism for a specified task. In this paper, using a database of mechanisms a designer can determine the type of mechanism conveniently and design equations are automatically generated for a given input performance. The solving method of design equations utilizes an optimization routine to obtain roots effectively. The linkages of 4, 6, and 8bars with revolute joints are considered in this study but may be extended to linkages of more bars.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.322-327
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• 2023

A design of experiments was evaluated in optimizing MOF-5 synthesis for acetylene adsorption. At first, mixture design was used to optimize precursor concentration, terephthalic acid, zinc acetate dihydrate and N,N-dimethylformamide. More specifically, 13 conditions with various molar ratios were designed by extreme vertices design method. After preparing the samples, XRD, N₂ physisorption and SEM analysis were performed for their characterization. Moreover, acetylene adsorption experiments were carried out over the samples under identical conditions. The optimal precursor composition for MOF-5 synthesis was predicted on a molar basis as follows: terephthalic acid : acetate dihydrate : dimethylformamide = 0.1 : 0.4 : 0.5. Thereafter, multi-level factorial design was designated to investigate the effect of synthesis reaction conditions such as temperature, time and stirring speed. By the statistical analysis of 18 samples designed, 4 reaction parameters were determined for additional adsorption experiments. Therefore, MOF-5 prepared under the synthesis time and temperature of 100 ℃ and 12 h, respectively, showed the maximum adsorption capacity of 15.1 mmol/g.