• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.3
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• pp.267-276
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• 2001

On the basis of structural analysis of the radial gate(that is, Tainter gate), this paper focuses on the optimization of the moment distribution according to the location of the arm of the radial gate. In spite of its importance from economical view point, we could hardly find the study on the optimum design of radial gate. Accordingly, the present study identifies the optimum section modulus for a radial arm along with the optimum position for 2 of 3 radial arms with a convex cylindrical skin plate relative to a given radius of the skin plate curvature, pivot point, water depth, ice pressure, etc. These optimum measurements are then compared with previously constructed radial gates. The results indicate that the optimum section modulus vague for a radial arm was appreciably smaller than the previously constructed examples.

• Computers and Concrete
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• v.32 no.2
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• pp.149-163
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• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1666-1689
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• 2021

The red line of Permanent Basic Farmland is the most important part in the "three-line" demarcation of China's national territorial development plan. The scientific and reasonable delineation of the red line is a major strategic measure being taken by China to improve its ability to safeguard the practical interests of farmers and guarantee national food security. The delineation of Permanent Basic Farmland zoning (DPBFZ) is essentially a multi-objective optimization problem. However, the traditional method of demarcation does not take into account the synergistic development goals of conservation of cultivated land utilization, ecological conservation, or urban expansion. Therefore, this research introduces the idea of artificial immune optimization and proposes a multi-objective model of DPBFZ red line delineation based on a clone selection algorithm. This research proposes an objective functional system consisting of these three sub-objectives: optimal quality of cropland, spatially concentrated distribution, and stability of cropland. It also takes into consideration constraints such as the red line of ecological protection, topography, and space for major development projects. The mathematical formal expressions for the objectives and constraints are given in the paper, and a multi-objective optimal decision model with multiple constraints for the DPBFZ problem is constructed based on the clone selection algorithm. An antibody coding scheme was designed according to the spatial pattern of DPBFZ zoning. In addition, the antibody-antigen affinity function, the clone mechanism, and mutation strategy were constructed and improved to solve the DPBFZ problem with a spatial optimization feature. Finally, Tongxu County in Henan province was selected as the study area, and a controlled experiment was set up according to different target preferences. The results show that the model proposed in this paper is operational in the work of delineating DPBFZ. It not only avoids the adverse effects of subjective factors in the delineation process but also provides multiple scenarios DPBFZ layouts for decision makers by adjusting the weighting of the objective function.

• Journal of the Korean Geosynthetics Society
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• v.10 no.4
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• pp.113-121
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• 2011

River sand has generally used for the backfill material of underground power cables. The thermal resistivity of it has $150^{\circ}C$-cm/Watt in wet condition and more than double in dry condition. The final goal of this study is to find the backfill material which has a small change in thermal resistivity with various water contents, for example thermal resistivity is $50^{\circ}C$-cm/Watt and $100^{\circ}C$-cm/Watt in wet and dry conditions respectively. In this study it is presented that the comparison of thermal resistivity using stone powder, crush rock, weathered granite soil and Jumunjin sand as well as river sand in the needle method regarding water content, dry unit weight and particle size distribution. As a result, the thermal resistivity of a material is minimized when they have maximum dry unit weight at optimum moisture content and maximum density by appropriately mixing materials for particle size distribution. Therefore thermal resistivity characteristics should be considered two factors: one is the difference between natural dry condition and dry state after optimum moisture content, and the other is the difference between unit weight of raw material and maximum dry density.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.469-474
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• 2005

Tn this study, the noll-destructive computed X-ray tomography was adopted to observe the density distribution of the needle-punched C-C composites nozzle throat. The density distribution of the C-C was evaluated within ${\pm}0.01g/cm^3$ with 98.74% confidence when the correction of the image and high signal-to-noise ratio were achieved by the optimization of the beam hardening, the electrical noise and the scattered X-ray. The density variation of the C/C with the computed tomography was in good agreement with the results obtained by the water immersion method and the observation with scanning electron microscope.

• Progress in Medical Physics
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• v.29 no.2
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• pp.66-72
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• 2018

The proper position of a multi-leaf collimator (MLC) is essential for the quality of intensity-modulated radiation therapy (IMRT) and volumetric modulated arc radiotherapy (VMAT) dose delivery. Task Group (TG) 142 provides a quality assurance (QA) procedure for MLC position. Our study investigated the QA validation of the mechanical leaf gap measurement and the maintenance procedure. Two $VitalBeam^{TM}$ systems were evaluated to validate the acceptance of an MLC position. The dosimetric leaf gaps (DLGs) were measured for 6 MV, 6 MVFFF, 10 MV, and 15 MV photon beams. A solid water phantom was irradiated using $10{\times}10cm^2$ field size at source-to-surface distance (SSD) of 90 cm and depth of 10 cm. The portal dose image prediction (PDIP) calculation was implemented on a treatment planning system (TPS) called $Eclipse^{TM}$. A total of 20 VMAT plans were used to confirm the accuracy of dose distribution measured by an electronic portal imaging device (EPID) and those predicted by VMAT plans. The measured leaf gaps were 0.30 mm and 0.35 mm for VitalBeam 1 and 2, respectively. The DLG values decreased by an average of 6.9% and 5.9% after mechanical MLC adjustment. Although the passing rates increased slightly, by 1.5% (relative) and 1.2% (absolute) in arc 1, the average passing rates were still within the good dose delivery level (>95%). Our study shows the existence of a mechanical leaf gap error caused by a degenerated MLC motor. This can be recovered by reinitialization of MLC position on the machine control panel. Consequently, the QA procedure should be performed regularly to protect the MLC system.

• Korean Chemical Engineering Research
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• v.46 no.1
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• pp.147-155
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• 2008

The economics of most chemical plants are heavily dependent upon the management of the utilities used in the plants. The utilities are supplied by the centralized utility system of the plant. Among the various utilities the steam is by far the most important energy source and the management of the electricity and the process water are greatly affected by the steam. Therefore it is necessary to educate students and new employees the basic concepts about the effective distribution of the utilities and the fundamental strategies to apply the concepts in actual plant operations. The OOUS (Optimal Operation of Utility System) is an GUI educational system designed to educate the effective generation of the steam and the optimal steam distribution schemes within short period. The OOUS deals with various utility equipments and processes and shows how to save operation costs by displaying the optimal operation conditions based on the process models and the operational knowledgebase.

• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.311-321
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• 2009

Long-Term Hydrologic Impact Assessment (L-THIA) was modified to improve runoff and pollutant load prediction for Korean watersheds with changes in land use classification and event mean concentration produced from observed data in Korea. The L-THIA model was linked with SCE-UA, which is one of the global optimization techniques, to automatically calibrate direct runoff. Modified L-THIA model was applied to Gumho River Basins to analyze spatial distribution of nonpoint source pollution. The results of model calibration during 1991~2000 and validation during 1981~1990 for direct runoff represented high model efficiency of 0.76 for calibration and 0.86 for validation. As a results of spatial analysis of nonpoint source pollution, the BOD was mainly loaded from urban area but SS, TN, and TP from agricultural area which is mainly located along the stream. Modified L-THIA model improve its accuracy with minimum imput data and application efforts. From this study, we can find out the L-THIA model is very useful tool to predict direct runoff and pollutant loads from the watershed and spatial analysis of nonpoint source pollution.

• Journal of the Korean Institute of Gas
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• v.21 no.4
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• pp.76-83
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• 2017

Biogas, combine with ever-increasing natural gas demand, has been on the center stage in South Korea for the early part of twenty first century in an effort to reduce the emission of global warming gases. With the passage of legal system of City Gas Business Law in 2014, the biogas has its place of production and distribution to consumers. However, it has a room for its technological improvements in terms of enrichment, by separating carbon dioxide and removing impurities efficiently. For these improvements, four different methane enrichment processes were tested in this study; membrane separation, water absorption, Chemical Absorption and Adsorption. A variety of operation scenarios were applied to the processes and the best practices were drawn out. The optimum process was selected based on case study results. Methane produced in this study showed 97% purity and 98% recovery rate, which meets the requirements of the City Gas quality standards.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.2
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• pp.193-202
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• 2015

The determining the appropriate dosage of coagulant is very important, because dosage of coagulant in the coagulation process for wastewater affects removing the amount of pollutants, cost, and producing sludge amount. Accordingly, in this study, in order to determine the optimal PAC dosage in the coagulation process, CCD (Central composite design) was used to proceed experimental design, and the quadratic regression models were constructed between independent variables (pH, influent turbidity, PAC dosage) and each response variable (Total coliform, E.coli, PSD (Particle size distribution) (< $10{\mu}m$), TP, $PO_4$-P, and $COD_{cr}$) by the RSM (Response surface methodology). Also, Considering the various response variables, the optimum PAC dosage and range were derived. As a result, in order to maximize the removal rate of total coliform and E.coli, the values of independent variables are the pH 6-7, the influent turbidity 100-200 NTU, and the PAC dosage 0.07-0.09 ml/L. For maximizing the removal rate of TP, $PO_4$-P, $COD_{cr}$, and PSD(< $10{\mu}m$), it is required for the pH 9, the influent turbidity 200-250 NTU, and the PAC dosage 0.05-0.065 ml/L. In the case of multiple independent variables, when the desirable removal rate for total coliform, E.coli, TP, and $PO_4$-P is 90-100 % and that for $COD_{cr}$ and PSD(< $10{\mu}m$) is 50-100 %, the required PAC dosage is 0.05-0.07 ml/L in the pH 9 and influent turbidity 200-250 NTU. Thus, if the influent turbidity is high, adjusting pH is more effective way in terms of cost since a small amount of PAC dosage is required.