• Structural Engineering and Mechanics
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• v.76 no.6
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• pp.675-685
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• 2020

As the classical response surface method (RSM), the polynomial RSM is so easy-to-apply that it is widely used in reliability analysis. However, the trade-off of accuracy and efficiency is still a challenge and the "curse of dimension" usually confines RSM to low dimension systems. In this paper, based on the univariate decomposition, the polynomial RSM is executed in a new mode, called as DPRSM. The general form of DPRSM is given and its implementation is designed referring to the classical RSM firstly. Then, in order to balance the accuracy and efficiency of DPRSM, its adaptive order revision around the most probable point (MPP) is proposed by introducing the univariate polynomial order analysis, noted as RDPRSM, which can analyze the exact nonlinearity of the limit state surface in the region around MPP. For testing the proposed techniques, several numerical examples are studied in detail, and the results indicate that DPRSM with low order can obtain similar results to the classical RSM, DPRSM with high order can obtain more precision with a large efficiency loss; RDPRSM can perform a good balance between accuracy and efficiency and preserve the good robustness property meanwhile, especially for those problems with high nonlinearity and complex problems; the proposed methods can also give a good performance in the high-dimensional cases.

• Journal of Industrial Technology
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• v.31 no.A
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• pp.27-31
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• 2011

In many industrial experiments, some practical constraints often force factors in an experiment to be much harder to change than others. Such an experiment involves randomization restrictions and it can be thought of as split-plot experiment. This paper investigates the path of steepest ascent/descent within a split-plot structure. A method is proposed for calculating the coordinates along the path.

• Bulletin of the Korean Chemical Society
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• v.18 no.7
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• pp.703-706
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• 1997

Response surface method was applied to the predicting optimum conditions of benzene synthesis for radiocarbon dating. The weight of carbon dioxide, the temperature of lithium container for producing acetylene and the activation temperature of catalyst which was used for the cyclization of acetylene to benzene were used as experimental factors. The yields of benzene synthesis were measured from twelve experiments which were carried out under various experimental conditions. The polynomial equation was obtained by using three experimental factors and yields. The validity of polynomial equation was confirmed by comparing the calculated yields with the experimental ones.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.275-282
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• 2006

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolernce of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or etimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte Carlo simulation and got the probabilistic sensitivity. The sensitivity of structural response with respect to in constant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.141-149
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• 2017

Due to the inaccuracy of micro-machining, various special processing methods have been investigated recently. Among them, pulse electrochemical machining is a promising machining method with the advantage of no residual stress and thermal deformation. Because the cross section of the wire electrode used in this study is circular, wire-pulse electrochemical machining is suitable for micro-hole machining. By applying the response surface methodology, the experimental plan was made of three factors and three levels: machining time, duty factor, and voltage. The regression equation was obtained through experiments. Then, by referring to the main effect diagram, we fixed the duty factor and machining time with little relevance, and solved the equation for the target 900 microns to obtain the voltage value. The results obtained from the response surface methodology were approximately those of the target value when the actual experiment was carried out. Therefore, it is concluded that the optimal conditions for hole processing can be obtained by the response surface methodology.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.3
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• pp.253-257
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• 2002

A new photoalignment material PNC, pole norbornene-2,3-dicarboxyolyl cholesterol, was synthesized and the electro-optical (EO) characteristics of the vortical-alignment (VA) liquid crystal display (LCD) photoaligned with UV exposure on the PNC surface were studied. EO characteristics of the photoaligned VA-LCD using a UV filter-less method was better than that of the UV filter method on the PNC surface for short UV exposure time. The response time of the photoaligned VA-LCD on the PNC surface without UV filter on the PNC surface is almost the same compared with the rubbing aligned VA-LCD.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.55-59
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• 2010

Aerodynamic design optimization of rotor airfoil has been performed with advanced design method for improved aerodynamic characteristics of ONERA airfoils as a baseline. A multiple response surface method is used to consider various consider various constraints in rotor airfoil design. Airfoil surface and mean camber line are modified using various shape functions. Numerical simulations are performed using KFLOW, a Navier-Stokes solver with shear stress transport turbulence model. The present design method provides favorable configurations for the high performance rotor airfoil. Resulting optimized air foils give better aerodynamic performance than the baseline airfoils.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.61-69
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• 2022

The function of coolant in machining is to reduce the frictional force in the contact area in between the tool and the material, and to increase the precision by cooling the work-piece and the tool, to make the machining surface uniform, and to extend the tool life. However, cutting oil is harmful to the human body because it uses chlorine-based extreme pressure additives to cause environmental pollutants. In this study, the effect of cutting temperature and surface roughness of titanium alloy for medical purpose (Ti-6Al-7Nb) in eco-friendly ADL slot shape machining was investigated using the response surface analysis method. As the design of the experiment, three levels of cutting speed, feed rate, and depth of cut were designed and the experiment was conducted using the central composite planning method. The regression expressions of cutting temperature and surface roughness were respectively obtained as quadratic functions to obtain the minimum value and optimal cutting conditions. The values from this formula and the experimental values were compared. As a result, this study makes and establishes the basis to prevent environmental pollution caused by the use of coolant and to replace it with ADL (Aerosol Dry Lubricant) machining that uses a very small amount of vegetable oil with high pressure.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.899-907
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• 2022

Purpose: Although many studies on seismic fragility analysis of general bridges have been conducted using machine learning methods, studies on curved bridge structures are insignificant. Therefore, the purpose of this study is to analyze the seismic fragility of bridges with I-shaped curved girders based on the machine learning method considering the material property and geometric uncertainties. Method: Material properties and pier height were considered as uncertainty parameters. Parameters were sampled using the Latin hypercube technique and time history analysis was performed considering the seismic uncertainty. Machine learning data was created by applying artificial neural network and response surface analysis method to the original data. Finally, earthquake fragility analysis was performed using original data and learning data. Result: Parameters were sampled using the Latin hypercube technique, and a total of 160 time history analyzes were performed considering the uncertainty of the earthquake. The analysis result and the predicted value obtained through machine learning were compared, and the coefficient of determination was compared to compare the similarity between the two values. The coefficient of determination of the response surface method was 0.737, which was relatively similar to the observed value. The seismic fragility curve also showed that the predicted value through the response surface method was similar to the observed value. Conclusion: In this study, when the observed value through the finite element analysis and the predicted value through the machine learning method were compared, it was found that the response surface method predicted a result similar to the observed value. However, both machine learning methods were found to underestimate the observed values.

• Environmental Engineering Research
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• v.15 no.2
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• pp.63-70
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• 2010

In this study, the response surface method and experimental design were applied as an alternative to conventional methods for the optimization of coagulation tests. A central composite design, with 4 axial points, 4 factorial points and 5 replicates at the center point were used to build a model for predicting and optimizing the coagulation process. Mathematical model equations were derived by computer simulation programming with a least squares method using the Minitab 15 software. In these equations, the removal efficiencies of turbidity and total organic carbon (TOC) were expressed as second-order functions of two factors, such as alum dose and coagulation pH. Statistical checks (ANOVA table, $R^2$ and $R^2_{adj}$ value, model lack of fit test, and p value) indicated that the model was adequate for representing the experimental data. The p values showed that the quadratic effects of alum dose and coagulation pH were highly significant. In other words, these two factors had an important impact on the turbidity and TOC of treated water. To gain a better understanding of the two variables for optimal coagulation performance, the model was presented as both 3-D response surface and 2-D contour graphs. As a compromise for the simultaneously removal of maximum amounts of 92.5% turbidity and 39.5% TOC, the optimum conditions were found with 44 mg/L alum at pH 7.6. The predicted response from the model showed close agreement with the experimental data ($R^2$ values of 90.63% and 91.43% for turbidity removal and TOC removal, respectively), which demonstrates the effectiveness of this approach in achieving good predictions, while minimizing the number of experiments required.