• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.4
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• pp.215-226
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• 2022

Significant efforts have been devoted to developing high-performance composite materials by emulating the structure of biological creatures with superior mechanical characteristics. Nacre has been one of the most sought-after natural structures due to its exceptional fracture toughness compared with the constituent materials. However, the effect of manipulating the nacre-like geometry on the impact performance has not been fully investigated thus far. In this study, composites of randomly manipulated nacreous geometry are numerically developed and the impact performance is analyzed. We develop an algorithm by which the planar area of platelets in the nacre-like design is randomly resized. Thereafter, the numerical models of nonuniform nacre-patterned multi-layer structures are developed and the drop-weight impact simulation is performed. The impact behaviors of the model are evaluated by using the ratio of absorbed energy, the von Mises stress distribution, and the impact force-time curve. Therefore, the effect of the geometric irregularity on the nacre-patterned design is elucidated. This insight can be efficiently utilized in establishing the optimum design of the nacre-patterned structure.

• Journal of Marine Life Science
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• v.8 no.1
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• pp.68-77
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• 2023

In this study, we investigated the quantitative distribution of microplastics in the surface seawater at 8 points near the Taean Peninsula using fluorescence staining. The study revealed a detection range of microplastics from 0 to 360.5 particles/l, with an average of 149.7 ± 46.0 particles/l. When classifying the microplastics by size, it was found that particles smaller than 50 ㎛ were dominant, although there were differences at Site 3. Moreover, it was not possible to identify clear correlations when comparing the number of microplastics based on collection area and particle size. Various physical and chemical factors, including plastic material, dynamic ocean conditions (such as currents, wind, waves, tides), geological characteristics (topography, slope), sediment materials including coastal organisms, human activities (fishing, development, tourism), and weather conditions (floods, rainfall), affect the behavior of microplastics. Therefore, future efforts should focus on standardizing quantitative analysis methods and conducting fundamental research on microplastic monitoring, including the analysis of environmental factors.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.7 no.1
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• pp.1-7
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• 2009

This study has been focused on determining the chemical composition of $^{14}C$ - in terms of both organic and inorganic $^{14}C$ contents - in reactor coolant from 3 different PWR's reactor type. The purpose was to evaluate the characteristic of $^{14}C$ that can serve as a basis for reliable estimation of the environmental release at domestic PWR sites. $^{14}C$ is the most important nuclide in the inventory, since it contributes one of the main dose contributors in future release scenarios. The reason for this is its high mobility in the environment, biological availability and long half-life(5730yr). More recent studies - where a more detailed investigation of organic $^{14}C$ species believed to be formed in the coolant under reducing conditions have been made - show that the organic compounds not only are limited to hydrocarbons and CO. Possible organic compounds formed including formaldehyde, formic acid and acetic acid, etc. Under oxidizing conditions shows the oxidized carbon forms, possibly mainly carbon dioxide and bicarbonate forms. Measurements of organic and inorganic $^{14}C$ in various water systems were also performed. The $^{14}C$ inventory in the reactor water was found to be 3.1 GBq/kg in PWR of which less than 10% was in inorganic form. Generally, the $^{14}C$ activity in the water was divided equally between the gas- and water- phase. Even though organic $^{14}C$ compound shows that dominant species during the reactor operation, But during the releasing of $^{14}C$ from the plant stack, chemical forms of $^{14}C$ shows the different composition due to the operation conditions such as temperature, pH, volume control tank venting and shut down chemistry.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.1
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• pp.25-31
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• 2011

In this study, model-based $NH_4-N$ predictive control algorithm by using influent pattern was developed and evaluated for effective control application in $A^2/O$ process. A pilot-scale $A^2/O$process at S wastewater treatment plant in B city was selected. The behaviors of organic, nitrogen and phosphorous in the biological reactors were described by using the modified ASM3+Bio-P model. A one-dimensional double exponential function model was selected for modeling of the secondary settlers. The effluent $NH_4-N$ concentration on the next day was predicted according to model-based simulation by using influent pattern. After the objective effluent quality and simulation result were compared, the optimal operational condition which able to meet the objective effluent quality was deduced through repetitive simulation. Next the effluent $NH_4-N$ control schedule was generated by using the optimal operational condition and this control schedule on the next day was applied in pilot-scale $A^2/O$ process. DO concentration in aerobic reactor in predictive control algorithm was selected as the manipulated variable. Without control case and with control case were compared to confirm the control applicability and the study of the applied $NH_4-N$control schedule in summer and winter was performed to confirm the seasonal effect. In this result, the effluent $NH_4-N$concentration without control case was exceeded the objective effluent quality. However the effluent $NH_4-N$ concentration with control case was not exceeded the objective effluent quality both summer and winter season. As compared in case of without predictive control algorithm, in case of application of predictive control algorithm, the RPM of air blower was increased about 9.1%, however the effluent $NH_4-N$ concentration was decreased about 45.2%. Therefore it was concluded that the developed predictive control algorithm to the effluent $NH_4-N$ in this study was properly applied in a full-scale wastewater treatment process and was more efficient in aspect to stable effluent.