• Structural Engineering and Mechanics
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• v.77 no.6
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• pp.779-795
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• 2021

In the recent decades, various optimization algorithms have been considered for the optimization of structures. In this research, a new enhanced algorithm is used for the size and topology optimization of truss structures. This algorithm, which is obtained from the combination of Crow Search Algorithm (CSA) and the Cellular Automata (CA) method, is called CA-CSA method. In the first iteration of the CA-CSA method, some of the best designs of the crow's memory are first selected and then located in the cells of CA. Then, a random cell is selected from CA, and the best design is chosen from the selected cell and its neighborhood; it is considered as a "local superior design" (LSD). In the optimization process, the LSD design is used to modify the CSA method. Numerical examples show that the CA-CSA method is more effective than CSA in the size and topology optimization of the truss structures.

• Advances in Computational Design
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• v.9 no.2
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• pp.115-136
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• 2024

Stochastic optimization methods have been extensively studied for structural optimization in recent decades. In this study, a novel algorithm named the CA-SA method, is proposed for topology optimization of steel double-layer grid structures. The CA-SA method is a hybridized algorithm combining the Simulated Annealing (SA) algorithm and the Cellular Automata (CA) method. In the CA-SA method, during the initial iterations of the SA algorithm, some of the preliminary designs obtained by SA are placed in the cells of the CA. In each successive iteration, a cell is randomly chosen from the CA. Then, the "local leader" (LL) is determined by selecting the best design from the chosen cell and its neighboring ones. This LL then serves as the leader for modifying the SA algorithm. To evaluate the performance of the proposed CA-SA algorithm, two square-on-square steel double-layer grid structures are considered, with discrete cross-sectional areas. These numerical examples demonstrate the superiority of the CA-SA method over SA, and other meta-heuristic algorithms reported in the literature in the topology optimization of large-scale skeletal structures.

• Journal of Educational Research in Mathematics
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• v.20 no.2
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• pp.185-202
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• 2010

This study was designed to investigate the possibility that the optimization problem solving activities based on the instrumented CAS can have an influence on the sequence of mathematics curriculum in secondary mathematics education. Some optimization problem solving activities based on CAS were constructed and executed to eleventh grade(the penultimate year of Korean high school) 7 students for nine class hours. They have experienced using CAS in mathematics class for three months, but never learned calculus. The data which consists of classroom observations(audio and video taped) and post-unit interviews with students were analyzed. In the analysis, with CAS, students can highly deal with the applied optimization problems made up of calculus, cubic equation, solution of radical equation, and graph analysis which never learned. This result shows CAS may have an influence on the sequence of mathematics curriculum in secondary mathematics education.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.2
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• pp.107-114
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• 2007

This paper focuses on the performance evaluation of various control allocation methods applied on DURUMI-II UAV system. In order to implement control allocation scheme to aircraft control system, control system can be designed through two step design procedure. The first step is to design a baseline control system for an aircraft without consideration of control surface failure. The second step is to design a control allocator that maps the total control command on the individual control surfaces. In this paper, several control allocation methods such as Psuedo-Inverse CA method, Direct CA method, and Optimization CA method are implemented and integrated to the baseline flight control system of DURUMI-II UAV. The performance of these control allocation methods is evaluated by nonlinear simulation under the flight scenario of control surface failure.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.695-700
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• 2008

Artificial neural network (ANN) has been extensively used in areas of nonlinear system modeling, analysis and design applications. Basically, ANN has its distinct capabilities of implementing system identification and/or function approximation using a number of input/output patterns that can be obtained via numerical and/or experimental manners. The paper describes a role of ANN, especially a back-propagation neural network (BPN) in the context of engineering analysis, design and optimization. Fundamental mechanism of BPN is briefly summarized in terms of training procedure and function approximation. The BPN based causality analysis (CA) is further discussed to realize the problem decomposition in the context of multidisciplinary design optimization. Such CA is also applied to quantitatively evaluate the uncoupled or decoupled design matrix in the context of axiomatic design with the independence axiom.

• KSBB Journal
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• v.26 no.1
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• pp.13-18
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• 2011

In this study, precipitation process was developed for the recovery of the lactic acid from calcium lactate fermentation broth. Calcium lactate yield was improved by decreasing the solubility of calcium lactate through the addition of ethanol (25%, v/v) as a co-precipitant. The optimal lime type, lime concentration, stirrer speed, precipitation time, temperature, and solvent amount for $Ca(LA)_2$ precipitation were CaO, 0.0175 g/mL, 220 rpm, 24 h, $5^{\circ}C$, ethanol 25% (v/v), respectively. Lactic acid was easily and efficiently recovered from precipitated $Ca(LA)_2$ by adding sulfuric acid ($Ca(LA)_2/H_2SO_4$ molar ratio=1:1). In the model solution of organic acids and fermentation broth, the overall yields of recovered lactic acid were 62% and 55%, respectively, under the aforementioned optimal conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4799-4818
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• 2015

In this paper, we investigate the problem of achieving global optimization for distributed carrier aggregation (CA) in small cell networks, using a game theoretic solution. To cope with the local interference and the distinct cost of intra-band and inter-band CA, we propose a non-cooperation game which is proved as an exact potential game. Furthermore, we propose a spatial adaptive play learning algorithm with heterogeneous learning parameters to converge towards NE of the game. In this algorithm, heterogeneous learning parameters are introduced to accelerate the convergence speed. It is shown that with the proposed game-theoretic approach, global optimization is achieved with local information exchange. Simulation results validate the effectivity of the proposed game-theoretic CA approach.

• Korean Chemical Engineering Research
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• v.56 no.4
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• pp.435-440
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• 2018

Nyamplung (Calophyllum inophyllum Linn) is one of the most widely grown plants in Indonesia. In addition, nyamplung oil has a future competitive advantage in that it can be processed into biodiesel. However, conventional methods for transesterification of nyamplung oil have been less effective. Therefore, in this study biodiesel was produced using microwaves as one of the alternative methods that can improve the shortcomings of conventional methods. In addition, optimization of parameters such as microwave power, catalyst concentration and transesterification time was done using Box-Behnken design. The combination of microwave with CaO catalyst and treated with Box-Behnken design are considered as a new and modern method for production of biodiesel from nyamplung oil and optimizing the factors that affected the transesterification process. The results showed that factors such as microwave power of 449.29 W, concentration of catalyst of 4.86% and transesterification time of 10.07 min can produce optimal yield of biodiesel of 92.73% with reliability of 93.22%.

• Food Science of Animal Resources
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• v.30 no.3
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• pp.359-364
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• 2010

Lactobacillus acidophilus A12 was isolated from chicken feces for use as an immunostimulating livestock probiotic. The purpose of this study was to optimize the production of L. acidophilus A12 using response surface methodology (RSM). Initially, the influence of growth medium was studied in terms of carbon sources (glucose, fructose, lactose, glycerol, sucrose, ethanol, and mannitol), nitrogen sources (beef extract, yeast extract, malt extract, and tryptone), and inorganic salts ($CaCl_2$, $MgSO_4$, $KH_2PO_4$, $(NH_4)_2SO_4$, $FeSO_4$, and NaCl). Through one factor-at-a time experiment, lactose, yeast extract, and $CaCl_2$ were determined to be the best sources of carbon, nitrogen, and inorganic salt, respectively. The optimum composition was found to be 17.7 g/L lactose, 18.6 g/L yeast extract, and 0.9 g/L $CaCl_2$. Under these conditions, a maximum cell density of 9.33 Log CFU/mL was produced, similar to the predicted value.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.11
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• pp.1809-1814
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• 2003

Differential evolution (DE) algorithm is presented and applied to global optimization in this research. DE suggested initially fur the solution to Chebychev polynomial fitting problem is similar to genetic algorithm(GA) including crossover, mutation and selection process. However, differential evolution algorithm is simpler than GA because it uses a vector concept in populating process. And DE turns out to be converged faster than CA, since it employs the difference information as pseudo-sensitivity In this paper, a trial vector and its control parameters of DE are examined and unconstrained optimization problems of highly nonlinear multimodal functions are demonstrated. To illustrate the efficiency of DE, convergence rates and robustness of global optimization algorithms are compared with those of simple GA.