• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.622-629
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• 2022

The study aim was to derive a stem taper equation for Phyllostachys pubescens, a type of bamboo in South Korea, and to develop a stem volume table. To derive the stem taper equation, three stem taper models (Max & Burkhart, Kozak, and Lee) were used. Since bamboo stalks are hollow because of its woody characteristics, the outer and inner diameters of the tree were calculated, and connecting them enabled estimating the tree curves. The results of the three equations for estimating the outer and inner diameters led to selection of the Kozak model for determining the optimal stem taper because it had the highest fitness index and lowest error and bias. We used the Kozak model to estimate the diameter of Phyllostachys pubescens by stem height, which proved optimal, and drew the stem curve. After checking the residual degree in the stem taper equation, all residuals were distributed around "0", which proved the suitability of the equation. To calculate the stem volume of Phyllostachys pubescens, a rotating cube was created by rotating the stem curve with the outer diameter at 360°, and the volume was calculated by applying Smalian's method. The volume of Phyllostachys pubescens was calculated by deducting the inner diameter calculated volume from the outer diameter calculated volume. The volume of Phyllostachys pubescens was only 20~30% of the volume of Larix kaempferi, which is a general species. However, considering the current trees/ha of Phyllostachys pubescens and the amount of bamboo shoots generated every year, the individual tree volume was predicted to be small, but the volume/ha was not very different or perhaps more. The significance of this study is the stem taper equation and stem volume table for Phyllostachys pubescens developed for the first time in South Korea. The results are expected to be used as basic data for bamboo trading that is in increasing public and industrial demand and carbon absorption estimation.

• Journal of Wetlands Research
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• v.24 no.2
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• pp.83-92
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• 2022

The amount of the plastic waste has been increasing according to global demand for plastic. Microplastics are the most hazardous among all plastic pollutants due to their toxicity and unknown physicochemical properties. This study investigates the optimal methodology that can be applied to sewage samples for detecting microplastics before discussing reducing microplastics in MWTPs. In this study, the effect of different pretreatment methods while detecting microplastic analysis of MWTP influent samples was investigated; the samples were collected from the J sewage treatment plant. There are many pretreatment methods but two of them are widely used: Fenton digestion and hydrogen peroxide oxidation. Although there are many pretreatment methods that can be applied to investigate microplastics, the most widely used methods for sewage treatment plant samples are Fenton digestion and H₂O₂ oxidation. For each pretreatment method, there were factors that could cause an error in the measurement. To overcome this, in the case of the Fenton digestion pretreatment, it is recommended to proceed with the analysis by filtration instead of the density separation method. In the case of the H₂O₂ oxidation method, the process of washing with distilled water after the reaction is recommended. As a result of the analysis, the concentration of microplastics was measured to be 2.75ea/L for the sample using the H₂O₂ oxidation method and 3.2ea/L for the sample using the Fenton oxidation method, and most of them were present in the form of fibers. In addition, it is difficult to guarantee the reliability of measurement results from quantitative analysis performed via microscope with eyes. A calibration curve was created for prove the reliability. A total of three calibration curves were drawn, and as a result of analysis of the calibration curves, all R² values were more than 0.9. This ensures high reliability for quantitative analysis. The qualitative analysis could determine the series of microplastics flowing into the MWTP, but could not confirm the chemical composition of each microplastic. This study can be used to confirm the chemical composition of microplastics introduced into MWTP in the future research.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.83-92
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• 2023

This study was established to investigate the site environment of mixed forests in Korea and to estimate the growth and yield of stands using national forest resources inventory data. The growth of mixed forests was derived by applying the Chapman-Richards model with diameter at breast height (DBH), height, and cross-sectional area at breast height (BA), and the yield of mixed forests was derived by applying stepwise regression analysis with factors such as cross-sectional area at breast height, site index (SI), age, and standing tree density per ha. Mixed forests were found to be growing in various locations. By climate zone, more than half of them were distributed in the temperate central region. By altitude, about 62% were distributed at 101-400 m. The fitness indexes (FI) for the growth model of mixed forests, which is the independent variable of stand age, were 0.32 for the DBH estimation, 0.22 for the height estimation, and 0.18 for the basal area at breast height estimation, which were somewhat low. However, considering the graph and residual between the estimated and measured values of the estimation equation, the use of this estimation model is not expected to cause any particular problems. The yield prediction model of mixed forests was derived as follows: Stand volume =-162.6859+6.3434 ∙ BA+9.9214 ∙ SI+0.7271 ∙ Age, which is a step- by-step input of basal area at breast height (BA), site index (SI), and age among several growth factors, and the determination coefficient (R²) of the equation was about 96%. Using our optimal growth and yield prediction model, a makeshift stand yield table was created. This table of mixed forests was also used to derive the rotation of the highest production in volume.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.197-206
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• 2023

Recently, the international community, including the International Maritime Organization (IMO), has strengthened regulations on air pollution emissions of ships, and eco-friendly ships are actively being developed to reduce exhaust gas emissions. Among them, rotor sail (RS), a wind-assisted ship propulsion system, is attracting attention again. RS is a cylindrical device installed on the ship deck, that generates hydrodynamic lift using a magnus effect. This is a next generation eco-friendly auxiliary propulsion technology, and Enercon company, which developed RS-applied ships, announced that fuel savings of more than 30% are possible. In this study, optimal installation conditions such as RS spacing and arrangement type were selected when multiple RSs were installed on ships. AR=5.1, SR=1.0, and D_e/D was fixed at 2.0 according to the RS arrangement, and the wind direction was considered only for the unidirectional +y-axis. Regarding arrangement conditions, five conditions were set at 3D intervals in the +x-axis direction from 3D to 15D and five conditions in the +y-axis direction from 5D to 25D. C_L, C_D and aerodynamic efficiency (C_L/C_D) were compared according to the square(□) and diamond(◇) shape arrangements. Consequently, the effect of RS on the longitudinal distance was not significantly different. However, in the case of RS flow characteristics according to the transverse distance, the interaction effect of RS was the greatest when the two RSs almost matched the wind direction. In the case of the RS flow characteristics according to the arrangement, notably, when the wind blew in the forward (0°) direction, the diamond (◇) arrangement was least affected by the backward flow between RSs.

• Korean Chemical Engineering Research
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• v.61 no.3
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• pp.378-387
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• 2023

Petrochemical is an energy consuming industry that consumes about 30% of total industrial energy consumption and is a representative carbon dioxide (CO₂) emission source. Among them, the Naphtha Cracking Center (NCC), which produces ethylene, propylene, propane and mixed C4, consumes large amounts of energy and emits significant amounts of CO₂. For this reason, an integrated techno economic- environmental impact assessment aimed at reducing energy consumption and environmental impact factors is necessary to ensure efficiency in terms of economics and environment. This study aims to analyze the efficiency of the heat exchanger network used in the existing NCC base on the pinch analysis and select an improvement plan that can reduced energy consumption. In order to reduces the utility consumption in the process, an optimal heat exchanger network considering the high-temperature and low-temperature stream was derived, and the economic evaluation was conducted by considering the trade-off between the reduction in utility consumption and the increase in heat exchanger installation cost. In addition, an environmental impact assessment was conducted on the reduced CO₂ emission in consideration of the environmental aspect, and the economic environmental impact assessment used the payback period to recover the invested funds to come up with an energy saving plan that can be applied based on the actual process. As a result of considering the economic-environmental impact assessment, when the environmental impact assessment was not considered, it was 4.29 months, 3.21 months, and 3.39 months for each case, and when considering the environmental impact assessment, it was 4.24 months, 3.17 months, and 3.35 months for each case. These results appeared equally both when the environmental impact assessment was not include and when it was include. In addition, a sensitivity analysis was conducted for each case to determine how important factors affect the payback period. As a result of the sensitivity analysis, the cost of the heat exchanger was identified as a major factor influencing the overall cost.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Korean Journal of Poultry Science
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• v.50 no.4
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• pp.203-212
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• 2023

This study conducted a diallel-crossbreeding test using four Korean native chicken parent stock lines (YC, YD, CK, and CF) to develop a native commercial layer with high egg-laying performance. A total of 312 chickens in six combinations were examined for various traits, including livability, body weight, age at first egg-laying, hen-day, and hen-housed egg production, egg weight, and egg quality, from hatching to 60 weeks of age. The results showed that the average survival rate was 77.1±18.8% with the YDYC combination having the highest survival rate along with excellent specific combining ability. The YDYC combination exhibited significantly higher body weight compared to the other combinations (P<0.01). The average age at first egg-laying was 121.3±2.5 days, with no significant difference between the combinations. The average hen-day egg production was 74.0±6.4%, and the hen-housed egg production was 181.4±33.8 eggs with the YDCF and YCCK combinations demonstrating the highest laying performance, while the YDYC and CKCF combinations had the lowest (P<0.05). Laying performance was more influenced by specific combining ability than general combining ability. The eggs from the YDYC combination were significantly lighter and had the darkest shell color (P<0.01), whereas the YDCF combination exhibited the thickest eggshells. There was no difference in internal egg quality among combinations, except the YDCF combination had the darkest yolk color. Overall, we concluded that the YCCK combination, characterized by high laying performance and livability, and the YDCF combination with high laying performance and good egg quality are the most desirable combinations for Korean native commercial layers.

• Food Science and Preservation
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• v.30 no.1
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• pp.155-169
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• 2023

Jerusalem artichoke (JA, Helianthus tuberosus L.) has a great potential to enhance the quality of yakju due to the plentiful inulin content which is functional and indigestible carbohydrate in human. In this study, the optimal preparation conditions such as the added amount and steam treatment of JA were investigated to improve the quality of yakju. As the amount of JA added to yakju increased, alcohol production decreased, whereas fermentation was performed well when the steam-cooked JA was added to yakju. The pH and total acidity of yakju decreased and increased, respectively, when the amount of JA added to yakju increased, whereas pH and total acidity of yakju increased and decreased, respectively, when the steam-cooked JA was added to yakju. The free sugar and organic acid contents of yakju increased and decreased, respectively, when the amount of JA added to yakju increased, whereas those of yakju decreased when the steam-cooked JA was added to Yakju. Amino acid content of JA decreased as the amount of JA added to yakju increased and that of JA significantly decreased when the steam-cooked JA was added to yakju. In the sensory evaluation analysis, the addition of 10% unsteam-cooked JA to yakju was the best when considering sweetness, flavor, sourness, and overall preference of yakju supplemented with JA. Consequently, utilizing JA to yakju may contribute to the improvement of the quality of yakju.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

• Journal of Korean Society of Forest Science
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• v.56 no.1
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• pp.66-76
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• 1982

Soil harness represents such physical properties as porosity, amount of water, bulk density and soil texture. It is very important to know the mechanical properties of soil as well as the chemical in order to research the fundamental phenomena in the growth and the distribution of tree roots. The writer intended to grip soil hardness by soil layer and also to grasp the root distribution and the correlation between soil hardness and the root distribution of Pinus riguda Mill. planted on the denuded hillside with sooding works by soil layer on soil profile. The site investigated is situated at Peongchang-ri 13, Kocksung county, Chon-nam Province. The area is consisted of 3.63 ha having on elevation of 167.5-207.5 m. Soil texture is sandy loam and parant rock in granite. Average slope of the area is $17^{\circ}-30^{\circ}$. Soil moisture condition is dry. Main exposure of the area is NW or SW. The total number of plots investigated was 24 plots. It divided into two groups by direction each 12 plots in NW and SW and divided into three groups by the position of mountain plots in foot of mountain, in hillside, and in summit of mountain, respectively. Each sampling tree was selected as specimen by purposive sampling and soil profile was made at the downward distance of 50cm form the sampling tree at each plot. Soil hardness, soil layer surveying, root distribution of the tree and vegetation were measured and investigated at the each plot. The soil hardness measured by the Yamanaka Soil Hardness Tester in mm unit. the results are as follows: 1) Soil hardness increases gradually in conformity with the increment of soil depth. The average soil indicator hardness by soil layer are as follows: 14.6mm in I - soil layer (0-10cm in depth from soil surface), 16.2mm in II - soil layer (10-20cm), 17.2 in III - soil layer (20-30cm), 18.3mm in IV - soil layer(30-40cm), 19.8mm in V - soil layer (4.50mm). 2) The tree roots (less than 20mm in diameter) distribute more in the surface layer than in the subsoil layer and decrease gradually according to the increment of soil depth. The ratio of the root distribution can be illustrated by comparing with each of five soil layers from surface to subsoil layer as follows: I - soil layer; 31%, II - soil layer; 26%, III - soil layer; 18%, IV - soil layer; 12%, V - soil layer; 13%, 3) Soil hardness and tree root distribution (less than 20mm in diameter) of Pinus rigida Mill. correlate negatively each other; the more soil hardness increases, the most root distribution decreases. The correlation coefficients between soil hardness and distribution of tree roots by soil layer are as follows: I - soil layer; -0.3675 (at the 10% significance level), II - soil layer; -0.5299 (at the 1% significance level), III - soil layer; -0.5573 (at the 2% significance level), IV - soil layer; -0.6922 (at the 5% significance level), V - soil layer; -0.7325 (at the 2% significance level). 4) the most suitable range of soil hardness for the growth of Pinus rigida Mill is the range of 12-14.9mm in soil indicator hardness. In this range of soil indicator hardness, the root distribution of this tree amounts to 41.8% in spite of 33% in soil harness and under the 20.9mm of soil indicator hardness, the distribution amounts to 93.2% in spite of 82% in soil hardness. Judging from above facts, the roots of Pinus rigida can easily grow within the soil condition of 20.9mm in soil indicator hardness. 5) The soil layers are classified by their depths from the surface soil.