• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.7 no.3
• /
• pp.17-24
• /
• 2008

Rail clamps are mechanical components installed to fix the container crane to its lower members against wind blast or slip. According to rail clamps should be designed to survive harsh wind loading conditions. In this study, a jaw structure, which is a part of a wedge-typed rail clamp, is optimized with respect to its strength under a severe wind loading condition. According to the classification of structural optimization, the structural optimization of a jaw is included in the category of shape optimization. Conventional structural optimization methods have difficulties in defining complex shape design variables and preventing mesh distortions. To overcome the difficulties, the metamodel using Kriging interpolation method is introduced to replace the true response by an approximate one. This research presents the shape optimization of a jaw using iterative Kriging interpolation models and a simulated annealing algorithm. The new Kriging models are iteratively constructed by refining the former Kriging models. This process is continued until the convergence criteria are satisfied. The optimum results obtained by the suggested method are compared with those obtained by the DOE (design of experiments) and VT (variation technology) methods built in ANSYS WORKBENCH.

• Bulletin of the Korean Chemical Society
• /
• v.33 no.3
• /
• pp.770-774
• /
• 2012

Protein loops are often involved in diverse biological functions, and some functional loops show conformational changes upon ligand binding. Since this conformational change is directly related to ligand binding pose and protein function, there have been numerous attempts to predict this change accurately. In this study, we show that it is plausible to obtain meaningful ensembles of loop conformations for flexible, ligand-binding protein loops efficiently by applying a loop modeling method. The loop modeling method employs triaxial loop closure algorithm for trial conformation generation and conformational space annealing for global energy optimization. When loop modeling was performed on the framework of ligand-free structure, loop structures within $3\AA$ RMSD from the crystal loop structure for the ligand-bound state were sampled in 4 out of 6 cases. This result is encouraging considering that no information on the ligand-bound state was used during the loop modeling process. We therefore expect that the present loop modeling method will be useful for future developments of flexible protein-ligand docking methods.

• Journal of the Society of Naval Architects of Korea
• /
• v.54 no.3
• /
• pp.187-195
• /
• 2017

The operation planning of transports used to move blocks is the one of key factors. Furthermore, reducing the running time through the effective plan contributes to pulling forward the whole logistic process of the shipyard and substantially saving the fuel consumption of itself as well. The past researches of the transporter focused on finding only the shortest distances, so called, Manhattan distance. However, these searching approaches cannot help having the significant difference in the real operational time and distance with the minimum cost approach which considers the speed retardation for turns or safety at the intersection. This study suggests the noble transporter's operational model which could take account of the consuming operational time around the crossroads on the shipyard. Concretely, the proposed method guarantees the minimization of transporters' turns and passage number which are huge burdensome to the operation time and the whole planning of transports with the given period. Resultantly, this paper is willing to explain the appropriateness of our approach, compared with the previous ones.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.30 no.4 s.247
• /
• pp.465-472
• /
• 2006

Recently, the regulations of the government and the concerns of people have rise to the interest in noise pollution levels as compared to other vehicles. In this area, many researchers have studied to reduce this noise in the field of automotive engineering. This paper proposes an optimal design scheme to reduce the noise of the intake system by adapting Kriging with two meta-heuristic techniques. For this, as a measuring tool for the performance of the intake system, the performance prediction software, was used. Then, the length and radius of each component of the current intake system are selected as input variables and the orthogonal arrays is adapted as a space-filling design. With these simulated data, we can estimate a correlation parameter in Kriging by solving the nonlinear problem with a genetic algorithm and find an optimal level for the intake system by optimizing Kriging estimated with simulated annealing. We notice that this optimal design scheme gives noticeable results and is a preferable way to analyze the intake system. Therefore, an optimal design for the intake system is proposed by reducing the noise of its system.

• Korean Journal of Optics and Photonics
• /
• v.14 no.4
• /
• pp.377-382
• /
• 2003

We propose a new optical watermarking method, which can protect the copyright of digital data, using a binary phase hologram and a Mach-Zehnder interferometer. Using a simulated annealing algorithm, the binary phase hologram of the mark image to be hidden is designed. We obtained a watermarked image by linearly superposing the hologram, which is the watermark, in the original image. The extraction processing of the mark image from the watermarked image is achieved by placing the phase-modulated watermarked image on a LCD in one path and the phase-modulated original image on another LCD in the other path in the Mach-Zehnder interferometer. The mark image was obtained by inverse Fourier transforming the phase modulated interference intensity. We confirmed that the proposed method is robust for the cropped images through computer simulation, and we implemented it optically using LCDs which are phase modulation devices.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.19 no.5
• /
• pp.509-515
• /
• 2009

This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the optimal design for noise reduction of the engine cooling fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.1307-1312
• /
• 2007

This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the Optimal Design for Noise Reduction of the Engine Cooling Fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

• IE interfaces
• /
• v.24 no.4
• /
• pp.281-294
• /
• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.6
• /
• pp.2166-2176
• /
• 2017

Electricity price prediction plays a crucial part in making the schedule and managing the risk to the competitive electricity market participants. However, it is a difficult and challenging task owing to the characteristics of the nonlinearity, non-stationarity and uncertainty of the price series. This study proposes a hybrid improved strategy which incorporates data preprocessor components and a forecasting engine component to enhance the forecasting accuracy of the electricity price. In the developed forecasting procedure, the Seasonal Adjustment (SA) method and the Ensemble Empirical Mode Decomposition (EEMD) technique are synthesized as the data preprocessing component; the Coupled Simulated Annealing (CSA) optimization method and the Least Square Support Vector Regression (LSSVR) algorithm construct the prediction engine. The proposed hybrid approach is verified with electricity price data sampled from the power market of New South Wales in Australia. The simulation outcome manifests that the proposed hybrid approach obtains the observable improvement in the forecasting accuracy compared with other approaches, which suggests that the proposed combinational approach occupies preferable predication ability and enough precision.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.20 no.6
• /
• pp.133-149
• /
• 2017

As cities face increasing problems such as aging, environmental pollution and growth limits, we have been trying to incorporate sustainability into urban planning and related policies. However, it is very difficult to generate a 'sustainable spatial plans' because there are trade-offs among environmental, society, and economic values. This is a kind of non-linear problem, and has limitations to be solved by existing qualitative expert knowledge. Many researches from abroad have used the meta heuristic optimization algorithms such as Genetic Algorithms(GAs), Simulated Annealing(SA), Ant Colony Optimization(ACO) and so on to synthesize competing values in spaces. GAs is the most frequently applied theory and have been known to produce 'good-enough plans' in a reasonable time. Therefore we collected the research on 'spatial optimization model based GAs' and analyzed in terms of 'study area', 'optimization objective', 'fitness function', and 'effectiveness/efficiency'. We expect the results of this study can suggest that 'what problems the spatial optimization model can be applied to' and 'linkage possibility with existing planning methodology'.