• Journal of Korean Association for Spatial Structures
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• v.20 no.4
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• pp.177-184
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• 2020

This study evaluates safety assessment before and after repair of Seonamsa temple seungseon bridge, which refer to the representative Hongye bridge in Korea. In this approach natural frequency of the structure were considered in the modeling procedure. Trial & error method is applied to obtain the approximate natural frequency before and after retrofit construction. Stiffness of the actual structure was examined to account for the dynamic characteristics of Hongye bridge measured in the field and adjusting parameters in computer modeling. The safety and usability of the stone structure in terms of load bearing capacity and displacement were examined.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.253-254
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• 2012

The purpose of this study is to suggest and verify high-strength concrete mix design model applying neural network theory, in order to minimize effort and time wasted by using trial and error method utill now. There are 7 input and 2 output to predict mix design. 40 data of mix design were learned with back-propagation algorithm. Then they are repeatedly learned back-propagation in neural network theory. Also, to verify predicted model, we analyzed and compared value predicted from 60MPa mix design with value measured by actual compressive strength test.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.4
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• pp.450-456
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• 2002

Die desig for manufacturing hooks from steel wires has been depended on empirical procedures based on trial and error method. To design die, at first the curvature and bending angle of hook are computed by using AutoCAD and developed program which is composed of Visual Basic. Then spring back should be considered because the elastic recovery of material is very important in bending process. In this study, bending analysis of elastic-plastic materials is applied to predict curvature of hook and spring back. Therefore, systematic procedure of die design for bending hook is achieved to consider elastic recovery in terms of hook shapes. Experimental results are good agreement with calculated results.

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.544-551
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• 2020

Reactor control is a standout amongst the most vital issues in the nuclear power plant. In this paper, the optimal design of variable structure controller (VSC) based on the lightning search algorithm (LSA) is proposed for a nuclear reactor power system. The LSA is a new optimization algorithm. It is used to find the optimal parameters of the VSC instead of the trial and error method or experts of the designer. The proposed algorithm is used for the tuning of the feedback gains and the sliding equation gains of the VSC to prove a good performance. Furthermore, the parameters of the VSC are tuned by the genetic algorithm (GA). Simulation tests are carried out to verify the performance and robustness of the proposed LSA-based VSC compared with GA-based VSC. The results prove the high performance and the superiority of VSC based on LSA compared with VSC based on GA.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.1047-1050
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• 1997

Rapid Prototyping(RP) is an efficient method for rapid design verification and trial manufacturing. In order to improve their unique characteristics according to the working principles. Variable Lamination Manufacturing process and corresponding CAD/CAM system is developed. The objective of this study is to improve dimensional accuracy of VLM-ST process, and it can be done by offset for cutting error correction, cutting path correction for sharp edge and reference shape generation. To verify the proposed algorithms, they applied to three-dimensional shapes, such as spanner and mechanical part.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.413-418
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• 1996

Alternate pirn winding is more difficult to control than others because starting points of its traverse strokes are changed alternately through the winding operations. However, the alternate pirn winding is ye useful method because the yarn can be hardly broken when it is unwinded from full packaged bobbin. This paper presents kinematic control algorithm for the alternate pirn. The proposed algorithm can decide the values of control variables such as bobbin speed and traverse speed from the given input parameters and constraints by using the kinematic relations of the winding mechanism. The compute simulations and experimental verifications of the developed winding control algorithm are carried out It is concluded that the proposed algorithm is an efficient and reliable alternative to traditional trial and error control methods.

• Journal of Welding and Joining
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• v.15 no.6
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• pp.116-123
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• 1997

In GMA welding processes, bead contour and penetration patterns are criterion to estimate weld quality. Bead geometry is commonly defined with width, height and depth. When weaving is taken into account, selection of welding conditions is known to be difficult. Thus, empirical or trial-and-error method are usually introduced. This study examined the correlation of welding process variables including weaving parameters with bead geometry using srtificial neural networks(ANN). The main task of the Ann estimator is to realize the mapping characteristics from the sampled welding process variables to the actual bead geometry through training. After the neural network model is constructed, welding process variables for desired bead geometry is selected by inverse model. Experimental varification of the inverse model is conducted through actual welding.

• Journal of the Semiconductor & Display Technology
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• v.11 no.2
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• pp.63-69
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• 2012

As decreasing size of chips, the need of wafer level packaging is increased in semi-conductor and display industries. Temperature uniformity is a crucial factor in vacuum soldering process to guarantee quality of bonding between chips and wafer. In this paper, a stepwise iterative algorithm has been suggested to obtain output profile of each heat source. Since this algorithm is based on open-loop stepwise iterative experimental technique, it is easier to implement and cost effective than real time feedback controls. Along with some experiments, it was shown that the suggested algorithm can remarkably improve temperature uniformity of wafer during whole heating process compared with the ordinary manual trial-and error method.

• Journal of Environmental Science International
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• v.11 no.3
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• pp.201-207
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• 2002

This study was carried out to evaluate the artificial neural network algorithm for water quality forecasting in Chungju lake, north Chungcheong province. Multi-layer perceptron(MLP) was used to train artificial neural networks. MLP was composed of one input layer, two hidden layers and one output layer. Transfer functions of the hidden layer were sigmoid and linear function. The number of node in the hidden layer was decided by trial and error method. It showed that appropriate node number in the hidden layer is 10 for pH training, 15 for DO and BOD, respectively. Reliability index was used to verify for the forecasting power. Considering some outlying data, artificial neural network fitted well between actual water quality data and computed data by artificial neural networks.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.6
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• pp.590-597
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• 2009

This paper propose a PI controller that maximizes the degree of stability using a stability in a simplified motor model the applies decoupling control. The PI controller gains are directly from the motor parameters, thereby reducing the element of trial and error, and, the Kharitonov equation was used to evaluate the robustness of the gains to changes in the motor parameters. In addition, the system poles are located in the same position, the proposed method can provide a fast response. The effectiveness of the proposed controller is verified by simulation results.