• Journal of Korean Association for Spatial Structures
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• v.24 no.3
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• pp.43-51
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• 2024

Dynamic responses of nuclear power plant structure subjected to earthquake loads should be carefully investigated for safety. Because nuclear power plant structure are usually constructed by material of reinforced concrete, the aging deterioration of R.C. have no small effect on structural behavior of nuclear power plant structure. Therefore, aging deterioration of R.C. nuclear power plant structure should be considered for exact prediction of seismic responses of the structure. In this study, a machine learning model for seismic response prediction of nuclear power plant structure was developed by considering aging deterioration. The OPR-1000 was selected as an example structure for numerical simulation. The OPR-1000 was originally designated as the Korean Standard Nuclear Power Plant (KSNP), and was re-designated as the OPR-1000 in 2005 for foreign sales. 500 artificial ground motions were generated based on site characteristics of Korea. Elastic modulus, damping ratio, poisson's ratio and density were selected to consider material property variation due to aging deterioration. Six machine learning algorithms such as, Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost), were used t o construct seispic response prediction model. 13 intensity measures and 4 material properties were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks present good prediction performance considering aging deterioration.

• Journal of Korean Society of Water and Wastewater
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• v.38 no.4
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• pp.233-242
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• 2024

This study evaluates the potential of various coagulants to enhance the efficiency of total phosphorus removal facilities in a sewage treatment plant. After analyzing the existing water quality conditions of the sewage treatment plant, the coagulant of poly aluminium chloride was experimentally applied to measure its effectiveness. In this process, the use of poly aluminium chloride and polymers in various ratios was explored to identify the optimal combination of coagulants. The experimental results showed that the a coagulants combination demonstrated higher treatment efficiency compared to exclusive use of large amounts of poly aluminium chloride methods. Particularly, the appropriate combination of poly aluminium chloride and polymers played a significant role. The optimal coagulant combination derived from the experiments was applied in a micro flotation method of real sewage treatment plant to evaluate its effectiveness. This study presents a new methodology that can contribute to enhancing the efficiency of sewage treatment processes and reducing environmental pollution. This research is expected to make an important contribution to improving to phosphorus remove efficiency of similar wastewater treatment plant and reducing the ecological impact from using coagulants in the future.

• Computers and Concrete
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• v.34 no.3
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• pp.279-296
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• 2024

In this study, ensemble machine learning (ML) models are employed to estimate the hardened properties of Self-Compacting Geopolymer Concrete (SCGC). The input variables affecting model development include the content of the SCGC such as the binder material, the age of the specimen, and the ratio of alkaline solution. On the other hand, the output parameters examined includes compressive strength, flexural strength, and split tensile strength. The ensemble machine learning models are trained and validated using a database comprising 396 records compiled from 132 unique mix trials performed in the laboratory. Diverse machine learning techniques, notably K-nearest neighbours (KNN), Random Forest, and Extreme Gradient Boosting (XGBoost), have been employed to construct the models coupled with Bayesian optimisation (BO) for the purpose of hyperparameter tuning. Furthermore, the application of nested cross-validation has been employed in order to mitigate the risk of overfitting. The findings of this study reveal that the BO-XGBoost hybrid model confirms better predictive accuracy in comparison to other models. The R² values for compressive strength, flexural strength, and split tensile strength are 0.9974, 0.9978, and 0.9937, respectively. Additionally, the BO-XGBoost hybrid model exhibits the lowest RMSE values of 0.8712, 0.0773, and 0.0799 for compressive strength, flexural strength, and split tensile strength, respectively. Furthermore, a SHAP dependency analysis was conducted to ascertain the significance of each parameter. It is observed from this study that GGBS, Flyash, and the age of specimens exhibit a substantial level of influence when predicting the strengths of geopolymers.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.2
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• pp.165-174
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• 2010

The numerical modeling of a coal gasification reaction occurring in an entrained flow coal gasifier is presented in this study. The purposes of this study are to develop a reliable evaluation method of coal gasifier not only for the basic design but also further system operation optimization using a CFD(Computational Fluid Dynamics) method. The coal gasification reaction consists of a series of reaction processes such as water evaporation, coal devolatilization, heterogeneous char reactions, and coal-off gaseous reaction in two-phase, turbulent and radiation participating media. Both numerical and experimental studies are made for the 1.0 ton/day entrained flow coal gasifier installed in the Korea Institute of Energy Research (KIER). The comprehensive computer program in this study is made basically using commercial CFD program by implementing several subroutines necessary for gasification process, which include Eddy-Breakup model together with the harmonic mean approach for turbulent reaction. Further Lagrangian approach in particle trajectory is adopted with the consideration of turbulent effect caused by the non-linearity of drag force, etc. The program developed is successfully evaluated against experimental data such as profiles of temperature and gaseous species concentration together with the cold gas efficiency. Further intensive investigation has been made in terms of the size distribution of pulverized coal particle, the slurry concentration, and the design parameters of gasifier. These parameters considered in this study are compared and evaluated each other through the calculated syngas production rate and cold gas efficiency, appearing to directly affect gasification performance. Considering the complexity of entrained coal gasification, even if the results of this study looks physically reasonable and consistent in parametric study, more efforts of elaborating modeling together with the systematic evaluation against experimental data are necessary for the development of an reliable design tool using CFD method.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.9
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• pp.917-925
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• 2006

The aim of our research was to apply experimental design methodology in the optimization of photocatalytic degradation of azo dye(Reactive orange 16). The reactions were mathematically described as a function of parameters amount of $TiO_2(x_1)$, and dye concentration($x_2$) being modeled by the use of the Box-Behnken method. The results show that the responses of color removal(%)($Y_1$) in photocatalysis of dyes were significantly affected by the synergistic effect of linear term of $TiO_2(x_1)$ and dye concentration($x_2$). Significant factors and synergistic effects for the $COD_{Cr}$, removal(%)($Y_2$) were the linear term of $TiO_2(x_1)$ and dye concentration($x_2$). However, the quadratic term of $TiO_2(x_1^2)$ and dye concentration($x_2^2$) had an antagonistic effect on $Y_1$ and $Y_2$ responses. Canonical analysis indicates that the stationary point was a saddle point for $Y_1$ and $Y_2$, respectively. The estimated ridge of maximum responses and optimal conditions for $Y_1:(X_1,\;X_2)$=(1.11 g/L, 51.2 mg/L) and $Y_2:(X_1,\;X_2)$=(1.42 g/L, 72.83 mg/L) using canonical analysis was 93% and 73%, respectively.

• Journal of the Korean Applied Science and Technology
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• v.34 no.3
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• pp.683-693
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• 2017

Transport biofuels have been recognized as a promising means to resolve the following issues like global warming, oil depletion and environmental pollutions. Among various biofuels, biodiesel has several advantages such as less emission of air pollutants and higher cetane values compared to diesel oil. Demand for biodiesel in Korea is increasing that leads to higher dependence on the imported feedstocks. Therefore, it is important to utilize the waste materials collected domestically for biodiesel production. Food waste oil collected in waste treatment facility has not been used for biodiesel production due to high free fatty contents in the oil. In this work, biodiesel conversion of food waste oil by Amberlyst 15 was studied. Synthetic and actual food waste oils have been used in the study. First, the effects of the major operating parameters including reaction temperature, methanol to oil molar ratio and catalyst loading on the conversion rates and yields were determined with synthetic waste oil. Kinetic modelling work was also done to determine the activation energy of the reaction. From the work, optimization reaction conditions were determined to be 383K, 1: 26.1 for methanol molar ratio to oil, 10 wt.% for catalyst loading and 360 min for reaction time. Activation energy of the reaction is determined to be 29.75 kJ/mol, lower than those reported in the previous works. So the solid catalyst, Amberlyst 15, was more efficient for esterification than the solid catalysts employed in the other works. Agitation rates have the negligible effects on the conversion rates and yields. With the identified optimization conditions, conversion of the actual food waste oil was also carried out. The esterification yield of actual food waste oil in 60 min was 13% lower than that of synthetic waste oil but the final yields in 240 min were similar each other, 98.12% for synthetic oil and 97.62% for actual waste oil.

• Korea journal of population studies
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• v.28 no.2
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• pp.1-32
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• 2005

The optimum population of a society or country can be defined as 'the population growth path that maximizes the welfare level of the society over the whole generations of both the present and the future, under the paths allowed by its endowments of production factors such as technology, capital and labor'. Thus, the optimum size or growth rate of population depends on: (i) the social welfare function, (ii) the production function, and (iii)demographic economic interrelationship which defines how the national income is disposed into consumption(birth and education of children included) and savings on the one hand and how the demographic and economic change induced thereby, in turn, affect production capacities on the other. The optimum population growth path can, then, be derived in the process of dynamic optimization of (i) under the constraints of (ii) and (iii), which will give us the optimum population growth rate defined as a function of parameters thereof. This paper estimates the optimum population growth rate of Korea by: specifying (i), (ii), and (iii) based on the recent development of economic theories, solving the dynamic optimization problem and inserting empirical estimates in Korea as the parametric values. The result shows that the optimum path of population growth in Korea is around TFR=1.81, which is affected most sensitively, in terms of the size of the partial elasticity around the optimum path, by the cost of children, share of capital income, consumption rate, time preference, population elasticity of utility function, etc. According to a survey implemented as a follow up study, there are quite a significant variations in the perceived cost of children, time preference rate, population elasticity of utility across different socio-economic classes in Korea, which implied that, compared to their counterparts, older generation and more highly educated classes prefer higher growth path for the population of Korea.

• Food Science and Preservation
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• v.16 no.4
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• pp.472-481
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• 2009

Response surface methodology (RSM) is frequently used for optimization studies. In the present work, RSM was used to determine the antimicrobial activitiesof grapefruit seed extract (GFSE) and a lactic acid mixture (LA) against Staphylococcus aureus, Bacillus cereus, Escherichia coli, Salmonella typhimurium, Pseudomonas fluorescens, and Vibrio parahaemolyticus. A central composite design was used to investigate the effects of independent variables on dependent parameters. One set of antimicrobial preparations included mixtures of 1% (w/w) GFSE and 10% (w/w) LA, in which the relative proportions of component antimicrobials varied between 0 and 100%. In further experiments, the relative proportions were between 20% and 100%. Antimicrobial effects against various microorganisms were mathematically encoded for analysis. The codes are given in parentheses after the bacterial names, and were S. aureus ($Y_1$), B. cereus ($Y_2$), E. coli ($Y_3$), S. typhimurium ($Y_4$), P. fluorescens ($Y_5$), and V. parahaemolyticus ($Y_6$). The optimum antimicrobial activity of the 1% (w/w) GFSE:10% (w/w) LA mixture against each microorganism was obtained by superimposing contour plots ofantimicrobial activities on measures of response obtained under various conditions. The optimum rangesfor maximum antimicrobial activity of a mixture with a ratio of 1:10 (by weight) GFSE and LA were 35.73:64.27 and 56.58:43.42 (v/v), and the optimum mixture ratio was 51.70-100%. Under the tested conditions (a ratio of 1% [w/w] GFSE to 10% [w/w] LA of 40:60, and a concentration of 1% [w/w] GFSE and 10% [w/w] LA, 70% of the highest value tested), and within optimum antimicrobial activity ranges, the antimicrobial activities of the 1% (w/w) GFSE:10% (w/w) LA mixture against S. aureus ($Y_1$), B. cereus ($Y_2$), E. coli ($Y_3$), S. typhimurium ($Y_4$), P. fluorescens ($Y_5$), and V. parahaemolyticus ($Y_6$) were 24.55, 25.22, 20.20, 22.49, 23.89, and 28.04 mm, respectively. The predicted values at optimum conditions were similar to experimental values.

• Progress in Medical Physics
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• v.22 no.4
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• pp.163-171
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• 2011

The purpose of this study was to investigate the effect of various technical parameters for the dose optimization in pediatric chest radiological examinations by evaluating effective dose and effective detective quantum efficiency (eDQE) including the scatter radiation from the object, the blur caused by the focal spot, geometric magnification and detector characteristics. For the tube voltages ranging from 40 to 90 kVp in 10 kVp increments at the FDD of 100, 110, 120, 150, 180 cm, the eDQE was evaluated at the same effective dose. The results showed that the eDQE was largest at 60 kVp when compares the eDQE at different tube voltage. Especially, the eDQE was considerably higher without the use of an anti-scatter grid on equivalent effective dose. This indicates that the reducing the scatter radiation did not compensate for the loss of absorbed effective photons in the grid. When the grid is not used the eDQE increased with increasing FDD because of the greater effective modulation transfer function (eMTF). However, most of major hospitals in Korea employed a short FDD of 100 cm with an anti-scatter grid for the chest radiological examination of a 15 month old infant. As a result, the entrance surface air kerma (ESAK) values for the hospitals of this survey exceeded the Korean DRL (diagnostic reference level) of $100{\mu}Gy$. Therefore, appropriate technical parameters should be established to perform pediatric chest examinations on children of different ages. The results of this study may serve as a baseline to establish detailed reference level of pediatric dose for different ages.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.6
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• pp.642-652
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• 2008

The aim of our research was to apply experimental design methodology in the optimization condition of Photo-Fenton oxidation of the residual livestock wastewater after the coagulation process. The reactions of Photo-Fenton oxidation were mathematically described as a function of parameters amount of Fe(II)($x_1$), $H_2O_2(x_2)$ and pH($x_3$) being modeled by the use of the Box-Behnken method, which was used for fitting 2nd order response surface models and was alternative to central composite designs. The application of RSM using the Box-Behnken method yielded the following regression equation, which is an empirical relationship between the removal(%) of livestock wastewater and test variables in coded unit: Y = 79.3 + 15.61x$_1$ - 7.31x$_2$ - 4.26x$_3$ - 18x$_1{^2}$ - 10x$_2{^2}$ - 11.9x$_3{^2}$ + 2.49x$_1$x$_2$ - 4.4x$_2$x$_3$ - 1.65x$_1$x$_3$. The model predicted also agreed with the experimentally observed result(R$^2$ = 0.96) The results show that the response of treatment removal(%) in Photo-Fenton oxidation of livestock wastewater were significantly affected by the synergistic effect of linear terms(Fe(II)($x_1$), $H_2O_2(x_2)$, pH(x$_3$)), whereas Fe(II) $\times$ Fe(II)(x$_1{^2}$), $H_2O_2$ $\times$ $H_2O_2$(x$_2{^2}$) and pH $\times$ pH(x$_3{^2}$) on the quadratic terms were significantly affected by the antagonistic effect. $H_2O_2$ $\times$ pH(x$_2$x$_3$) had also a antagonistic effect in the cross-product term. The estimated ridge of the expected maximum response and optimal conditions for Y using canonical analysis were 84 $\pm$ 0.95% and (Fe(II)(X$_1$) = 0.0146 mM, $H_2O_2$(X$_2$) = 0.0867 mM and pH(X$_3$) = 4.704, respectively. The optimal ratio of Fe/H$_2O_2$ was also 0.17 at the pH 4.7.