• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.5
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• pp.77-86
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• 2010

Hydrologic Simulation Program-Fortran (HSPF) coupled with PEST which is optimization program was calibrated and validated at Bochung watershed by using monitoring data of water quantities and nutrient loading. Although the calibrated data were limited, model parameters of each land use type were optimized and coefficient of determinations were ranged from 0.94 to 0.99 for runoff, from 0.89 to 1.00 for TN loading, and from 0.92 to 1.00 for TP loading. The optimized hydrological parameters indicated that the forested land could retain rainfall within soil layer with high soil layer depth and infiltration rate compared with other land use type. Hydrological characteristics of paddy rice field are low infiltration rate and coefficient of roughness. The calibrated parameters related to nutrient loading indicated generation of nutrient pollution from agricultural area including upland and paddy rice field higher than other land use type resulting from fertilizer application. Overall PEST program is useful tool to calibrate HSPF automatically without consuming time and efforts.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.116-122
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• 2006

Most of the multimedia applications require strict quality of service (QoS) guarantee during the communication between a single source and multiple destinations. This gives rise to the need for an efficient QoS multicast routing strategy. Determination of such QoS-based optimal multicast routes basically leads to a multi-objective optimization problem, which is computationally intractable in polynomial time due to the uncertainty of resources in Internet. This paper describes a network model for researching the routing problem and proposes a new multicast tree selection algorithm based on genetic algorithms to simultaneously optimize multiple QoS parameters. The paper mainly presents a QoS multicast routing algorithm based on genetic algorithm (QMRGA). The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or near-optimal solution within few iterations, even for the networks environment with uncertain parameters. The incremental rate of computational cost can close to polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated using simulations. The simulation results show that this approach has fast convergence speed and high reliability. It can meet the real-time requirement in multimedia communication networks.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.789-799
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• 1999

In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.210-214
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• 2003

This paper presents a residence time distribution (RTD) measurement method using a radioisotope tracer and the estimation method of RTD model parameters to analyze a submerged bio-reactor. The mathematical RTD models have been investigated to represent the flow behavior and the existence of stagnant regions in the reactor. Knowing the parameters of the RTD model is important for understanding the mixing characteristics of a reactor The radioisotope tracer experiment was carried out by injecting a radioisotope tracer as a pulse into the inlet of the reactor and recording the change of its concentration at the outlet of the reactor to obtain the experimental RTD response. The parameter estimation was performed by the Levenberg-Marquardt optimization algorithm. The proposed scheme allowed the parameter estimation of RTD model suggested by Adler-Hovorka with very low deviations. The estimation procedure is shown to lead to accurate estimation of the RTD parameters and to a good agreement between experimental and simulated response.

• Computers and Concrete
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• v.21 no.4
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• pp.441-449
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• 2018

FE models for complex or large-scaled structures that need detailed modeling of structural components are usually constructed using commercial analysis softwares. Updating of such FE model by conventional sensitivity-based methods is difficult since repeated computation for perturbed parameters and manual calculations are needed to obtain sensitivity matrix in each iteration. In this study, an FE model updating procedure avoiding such difficulties by using response surface (RS) method and a Pareto-based multiobjective optimization (MOO) was formulated and applied to FE models constructed with a commercial analysis package. The test building is a low-rise reinforced concrete building that has been seismically retrofitted. Dynamic properties of the building were extracted from vibration tests performed before and after the seismic retrofits, respectively. The elastic modulus of concrete and masonry, and spring constants for the expansion joint were updated. Two RS functions representing the errors in the natural frequencies and mode shape, respectively, were obtained and used as the objective functions for MOO. Among the Pareto solutions, the best compromise solution was determined using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) procedure. A similar task was performed for retrofitted building by taking the updating parameters as the stiffness of modified or added members. Obtained parameters of the existing building were reasonably comparable with the current code provisions. However, the stiffness of added concrete shear walls and steel section jacketed members were considerably lower than expectation. Such low values are seemingly because the bond between new and existing concrete was not as good as the monolithically casted members, even though they were connected by the anchoring bars.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.4
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• pp.417-430
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• 2009

A BNR comprehensive performance evaluation (BNR CPE) system was established employing system-oriented evaluation methodology for biological nutrient removal (BNR) processes based on the CPE techniques developed by U.S. EPA for evaluation of conventional biological processes. The BNR CPE system applied to five domestic BNR plants adopting $A^2/O$ process confirmed that all target plants except the smallest one had not any serious defective performance and process stability was enhanced with increasing plant size. The system also clearly verified relatively poor performances in anoxic reactors without exception mainly due to influent carbon limit rather than functional defect. Consistent good performances were confirmed even during both winter season and wet weather generally known to be difficult to achieve satisfactory removals. Presentation of evaluation results by modified radar chart system simplified and clarified the evaluation and analysis procedures. The BNR CPE system could not only discover readily the causes of present and prospective poor performances but also facilitate the suggestion of their optimization options. Mutual effect and cause-and-effect among operation parameters and unit processes were also found easily using the evaluation system. The system justified that the adverse effect of defective operating parameters could be compensated by other favorable parameters, especially in anaerobic and anoxic reactors as well as during the winter season.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.150-152
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• 1994

In this paper, the optimum shape design of stator slot of induction motors for iron loss reduction is proposed. To obtain the flux distribution in induction motors, 2-D finite element method with voltage source is employed. The iron loss is calculated from the iron loss data given by the iron manufacturer. To calculate the sensitivity of iron loss to shape variation, the sensitivity analysis of discrete approach is used. The proposed algorithm is applied to a 3-phase squirrel cage induction motor. The nodes at stator slot boundary of the induction motor are defined as design parameters. By controlling these parameters under the constant volume of iron, we can minimize the iron loss. Furthermore, the stator copper loss is reduced by increasing the slot area. So the stator slot area is determined at the point that the summation of iron loss and copper loss of stator is minimized. Since the constraint of constant volume of iron is nonlinear to the design parameters, the Gradient Projection method is used as an optimization algorithm.

• Bulletin of the Korean Chemical Society
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• v.34 no.1
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• pp.79-88
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• 2013

$LiFePO_4$ is a promising active material (AM) suitable for use in high performance lithium-ion batteries used in automotive applications that require high current capabilities and a high degree of safety and reliability. In this study, an optimization of the electrode design parameters was performed to produce high capacity lithium-ion batteries based on $LiFePO_4$/graphite electrodes. The electrode thickness and porosity (AM density) are the two most important design parameters influencing the cell capacity. We quantified the effects of cathode thickness and porosity ($LiFePO_4$ electrode) on cell performance using a detailed one-dimensional electrochemical model. In addition, the effects of those parameters were experimentally studied through various coin cell tests. Based on the numerical and experimental results, the optimal ranges for the electrode thickness and porosity were determined to maximize the cell capacity of the $LiFePO_4$/graphite lithium-ion batteries.

• Structural Engineering and Mechanics
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• v.59 no.2
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• pp.313-326
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• 2016

In this study the three-dimensional nonlinear finite element method was used to analyze the stresses distribution in the adhesive layer used to joint two Aluminum 2024-T3 adherends. We consider in this study the effect of different parameters witch directly affect the values of different stresses. The experimental design method is used to investigate the effects of geometrical parameters of the single lap joint in order to achieve an optimization of the assembly with simple lap joint. As a result, it can be said that both the geometrical modifications of the adhesive and adherends edge have presented a significant effect at the overlap edge thereby causing a decrease in peel and shear stresses. In addition, an analytical model is also given to predict in a simple but effective way the joint strength and its dependence on the geometrical parameters. This approach can help the designers to improve the quality and the durability of the structural adhesive joints.

• Journal of Wetlands Research
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• v.11 no.2
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• pp.107-121
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• 2009

Many rainfall-runoff models have been used for the flood forecasting. However, the determination of rainfall-runoff model parameters is very difficult. In this study, we investigated the efficiency of flood forecasting models by studying the optimization techniques for parameter calibration of SFM, Tank, and SSARR models. We analyzed the correlations between parameters in optimization techniques, then classified the parameters into parameter groups. For this we applied the sequential calibration method through the sensitivity analysis. As the results of the analysis, the parameter groups clibration method showed better result for peak flow and clibtation time.